The Blog Pros

25 video lessons (8h). Updated yearly.
Also available as a UX Bundle with 2 video courses.

The Backstory

In many companies, designers are perceived as disruptors, rather than enablers. Designers challenge established ways of working. They ask a lot of questions — much needed ones but also uncomfortable ones. They focus “too much” on user needs, pushing revenue projections back, often with long-winded commitment to testing and research and planning and scoping.

Almost every department in almost every company has their own clearly defined objectives, metrics and KPIs. In fact, most departments — from finance to marketing to HR to sales — are remarkably good at visualizing their impact and making it visible throughout the entire organization.

Designing a KPI tree, an example of how to connect business objectives with design initiatives through the lens of design KPIs. (Large preview)

But as designers, we rarely have a set of established Design KPIs that we regularly report to senior management. We don’t have a clear definition of design success. And we rarely measure the impact of our work once it’s launched. So it’s not surprising that moste parts of the business barely know what we actually do all day long.

Business wants results. It also wants to do more of what has worked in the past. But it doesn’t want to be disrupted — it wants to disrupt. It wants to reduce time to market and minimize expenses; increase revenue and existing business, find new markets. This requires fast delivery and good execution.

And that’s what we are often supposed to be — good “executors”. Or to put differently, “pixel pushers”.

Over years, I’ve been searching for a way to change that. This brought me to Design KPIs and UX scorecards, and a workflow to translate business goals into actionable and measurable design initiatives. I had to find a way to explain, visualize and track that incredible impact that designers have on all parts of business — from revenue to loyalty to support to delivery.

The results of that journey are now public in our new video course: “How To Measure UX and Design Impact” — a practical guide for designers, researchers and UX leads to measure and visualize UX impact on business.

About The Course

The course dives deep into establishing team-specific design KPIs, how to track them effectively, how to set up ownership and integrate metrics in design process. You’ll discover how to translate ambiguous objectives into practical design goals, and how to measure design systems and UX research.

Also, we’ll make sense of OKRs, Top Task Analysis, SUS, UMUX-Lite, UEQ, TPI, KPI trees, feedback scoring, gap analysis, and Kano model — and what UX research methods to choose to get better results. Jump to the table of contents or get your early-bird.

The setup for the video recordings. Once all content is in place, it’s about time to set up the recording.

<a class="btn btn--large btn--green btn--text-shadow" href=https://measure-ux.com>Jump to the video course →

A practical guide to UX metrics and Design KPIs
8h-video course + live UX training. Free preview.

25 chapters (8h), with videos added/updated yearly
Free preview, examples, templates, workflows
No subscription: get once, access forever
Life-time access to all videos, slides, checklists.
Add-on: live UX training, running 2× a year
Use the code SMASHING to get 20% off today
Jump to the details →

Table of Contents

25 chapters, 8 hours, with practical examples, exercises, and everything you need to master the art of measuring UX and design impact. Don’t worry, even if it might seem overwhelming at first, we’ll explore things slowly and thoroughly. Taking 1–2 sessions per week is a perfectly good goal to aim for.

We can’t improve without measuring. That’s why our new video course gives you the tools you need to make sense of it all: user needs, just like business needs. (View large version)

1. Welcome

So, how do we measure UX? Well, let’s find out! Meet a friendly welcome message to the video course, outlining all the fine details we’ll be going through: design impact, business metrics, design metrics, surveys, target times and states, measuring UX in B2B and enterprises, design KPI trees, Kano model, event storming, choosing metrics, reporting design success — and how to measure design systems and UX research efforts.

Keywords:
Design impact, UX metrics, business goals, articulating design value, real-world examples, showcasing impact, evidence-driven design.

2. Design Impact

In this segment, we’ll explore how and where we, as UX designers, make an impact within organizations. We’ll explore where we fit in the company structure, how to build strong relationships with colleagues, and how to communicate design value in business terms.

Keywords:
Design impact, design ROI, orgcharts, stakeholder engagement, business language vs. UX language, Double Diamond vs. Reverse Double Diamond, risk mitigation.

3. OKRs and Business Metrics

We’ll explore the key business terms and concepts related to measuring business performance. We’ll dive into business strategy and tactics, and unpack the components of OKRs (Objectives and Key Results), KPIs, SMART goals, and metrics.

Keywords:
OKRs, objectives, key results, initiatives, SMART goals, measurable goals, time-bound metrics, goal-setting framework, business objectives.

4. Leading And Lagging Indicators

Businesses often speak of leading and lagging indicators — predictive and retrospective measures of success. Let’s explore what they are and how they are different — and how we can use them to understand the immediate and long-term impact of our UX work.

Keywords:
Leading vs. lagging indicators, cause-and-effect relationship, backwards-looking and forward-looking indicators, signals for future success.

5. Business Metrics, NPS

We dive into the world of business metrics, from Monthly Active Users (MAU) to Monthly Recurring Revenue (MRR) to Customer Lifetime Value (CLV), and many other metrics that often find their way to dashboards of senior management.

Also, almost every business measures NPS. Yet NPS has many limitations, requires a large sample size to be statistically reliable, and what people say and what people do are often very different things. Let’s see what we as designers can do with NPS, and how it relates to our UX work.

Keywords:
Business metrics, MAU, MRR, ARR, CLV, ACV, Net Promoter Score, customer loyalty.

6. Business Metrics, CSAT, CES

We’ll explore the broader context of business metrics, including revenue-related measures like Monthly Recurring Revenue (MRR) and Annual Recurring Revenue (ARR), Customer Lifetime Value (CLV), and churn rate.

We’ll also dive into Customer Satisfaction Score (CSAT) and Customer Effort Score (CES). We’ll discuss how these metrics are calculated, their importance in measuring customer experience, and how they complement other well-known (but not necessarily helpful) business metrics like NPS.

Keywords:
Customer Lifetime Value (CLV), churn rate, Customer Satisfaction Score (CSAT), Customer Effort Score (CES), Net Promoter Score (NPS), Monthly Recurring Revenue (MRR), Annual Recurring Revenue (ARR).

7. Feedback Scoring and Gap Analysis

If you are looking for a simple alternative to NPS, feedback scoring and gap analysis might be a neat little helper. It transforms qualitative user feedback into quantifiable data, allowing us to track UX improvements over time. Unlike NPS, which focuses on future behavior, feedback scoring looks at past actions and current perceptions.

Keywords:
Feedback scoring, gap analysis, qualitative feedback, quantitative data.

8. Design Metrics (TPI, SUS, SUPR-Q)

We’ll explore the landscape of established and reliable design metrics for tracking and capturing UX in digital products. From task success rate and time on task to System Usability Scale (SUS) to Standardized User Experience Percentile Rank Questionnaire (SUPR-Q) to Accessible Usability Scale (AUS), with an overview of when and how to use each, the drawbacks, and things to keep in mind.

Keywords:
UX metrics, KPIs, task success rate, time on task, error rates, error recovery, SUS, SUPR-Q.

9. Design Metrics (UMUX-Lite, SEQ, UEQ)

We’ll continue with slightly shorter alternatives to SUS and SUPR-Q that could be used in a quick email survey or an in-app prompt — UMUX-Lite and Single Ease Question (SEQ). We’ll also explore the “big behemoths” of UX measurements — User Experience Questionnaire (UEQ), Google’s HEART framework, and custom UX measurement surveys — and how to bring key metrics together in one simple UX scorecard tailored to your product’s unique needs.

Keywords:
UX metrics, UMUX-Lite, Single Ease Question (SEQ), User Experience Questionnaire (UEQ), HEART framework, UEQ, UX scorecards.

10. Top Tasks Analysis

The most impactful way to measure UX is to study how successful users are in completing their tasks in their common customer journeys. With top tasks analysis, we focus on what matters, and explore task success rates and time on task. We need to identify representative tasks and bring 15–18 users in for testing. Let’s dive into how it all works and some of the important gotchas and takeaways to consider.

Keywords:
Top task analysis, UX metrics, task success rate, time on task, qualitative testing, 80% success, statistical reliability, baseline testing.

11. Surveys and Sample Sizes

Designing good surveys is hard! We need to be careful on how we shape our questions to avoid biases, how to find the right segment of audience and large enough sample size, how to provide high confidence levels and low margins of errors. In this chapter, we review best practices and a cheat sheet for better survey design — along with do’s and don’ts on question types, rating scales, and survey pre-testing.

Keywords:
Survey design, question types, rating scales, survey length, pre-testing, response rates, statistical significance, sample quality, mean vs. median scores.

12. Measuring UX in B2B and Enterprise

Best measurements come from testing with actual users. But what if you don’t have access to any users? Perhaps because of NDA, IP concerns, lack of clearance, poor availability, and high costs of customers and just lack of users? Let’s explore how we can find a way around such restrictive environments, how to engage with stakeholders, and how we can measure efficiency, failures — and set up UX KPI programs.

Keywords:
B2B, enterprise UX, limited access to users, compliance, legacy systems, compliance, desk research, stakeholder engagement, testing proxies, employee’s UX.

13. Design KPI Trees

To visualize design impact, we need to connect high-level business objectives with specific design initiatives. To do that, we can build up and present Design KPI trees. From the bottom up, the tree captures user needs, pain points, and insights from research, which inform design initiatives. For each, we define UX metrics to track the impact of these initiatives, and they roll up to higher-level design and business KPIs. Let’s explore how it all works in action and how you can use it in your work.

Keywords:
User needs, UX metrics, KPI trees, sub-trees, design initiatives, setting up metrics, measuring and reporting design impact, design workflow, UX metrics graphs, UX planes.

14. Event Storming

How do we choose the right metrics? Well, we don’t start with metrics. We start by identifying most critical user needs and assess the impact of meeting user needs well. To do that, we apply event storming by mapping critical user’s success moments as they interact with a digital product. Our job, then, is to maximize success, remove frustrations, and pave a clear path towards a successful outcome — with event storming.

Keywords:
UX mapping, customer journey maps, service blueprints, event storming, stakeholder alignment, collaborative mapping, UX lanes, critical events, user needs vs. business goals.

15. Kano Model and Survey

Once we have a business objective in front of us, we need to choose design initiatives that are most likely to drive the impact that we need to enable with our UX work. To test how effective our design ideas are, we can map them against a Kano model und run a concept testing survey. It gives us a user’s sentiment that we then need to weigh against business priorities. Let’s see how to do just that.

Keywords:
Feature prioritization, threshold attributes, performance attributes, excitement attributes, user’s sentiment, mapping design ideas, boosting user’s satisfaction.

16. Design Process

How do we design a KPI tree from scratch? We start by running a collaborative event storming to identify key success moments. Then we prioritize key events and explore how we can amplify and streamline them. Then we ideate and come up with design initiatives. These initiatives are stress tested in an impact-effort matrix for viability and impact. Eventually, we define and assign metrics and KPIs, and pull them together in a KPI tree. Here’s how it works from start till the end.

Keywords:
Uncovering user needs, impact-effort matrix, concept testing, event storming, stakeholder collaboration, traversing the KPI tree.

17. Choosing The Right Metrics

Should we rely on established UX metrics such as SUS, UMUX-Lite, and SUPR-Q, or should we define custom metrics tailored to product and user needs? We need to find a balance between the two. It depends on what we want to measure, what we actually can measure, and whether we want to track local impact for a specific change or global impact for the entire customer journey. Let’s figure out how to define and establish metrics that actually will help us track our UX success.

Keywords:
Local vs. global KPIs, time spans, percentage vs. absolute values, A/B testing, mapping between metrics and KPIs, task breakdown, UX lanes, naming design KPIs.

18. Design KPIs Examples

Different contexts will require different design KPIs. In this chapter, we explore a diverse set of UX metrics related to search quality (quality of search for top 100 search queries), form design (error frequency, accuracy), e-commerce (time to final price), subscription-based services (time to tier boundaries), customer support (service desk inquiries) and many others. This should give you a good starting point to build upon for your own product and user needs.

Keywords:
Time to first success, search results quality, form error recovery, password recovery rate, accessibility coverage, time to tier boundaries, service desk inquiries, fake email frequency, early drop-off rate, carbon emissions per page view, presets and templates usage, default settings adoption, design system health.

19. UX Strategy

Establishing UX metrics doesn’t happen over night. You need to discuss and decide what you want to measure and how often it should happen. But also how to integrate metrics, evaluate data, and report findings. And how to embed them into an existing design workflow. For that, you will need time — and green lights from your stakeholders and managers. To achieve that, we need to tap into the uncharted waters of UX strategy. Let’s see what it involves for us and how to make progress there.

Keywords:
Stakeholder engagement, UX maturity, governance, risk mitigation, integration, ownership, accountability, viability.

20. Reporting Design Success

Once you’ve established UX metrics, you will need to report them repeatedly to the senior management. How exactly would you do that? In this chapter, we explore the process of selecting representative tasks, recruiting participants, facilitating testing sessions, and analyzing the resulting data to create a compelling report and presentation that will highlight the value of your UX efforts to stakeholders.

Keywords:
Data analysis, reporting, facilitation, observation notes, video clips, guidelines and recommendations, definition of design success, targets, alignment, and stakeholder’s buy-in.

21. Target Times and States

To show the impact of our design work, we need to track UX snapshots. Basically, it’s four states, mapped against touch points in a customer journey: baseline (threshold not to cross), current state (how we are currently doing), target state (objective we are aiming for), and industry benchmark (to stay competitive). Let’s see how it would work in an actual project.

Keywords:
Competitive benchmarking, baseline measurement, local and global design KPIs, cross-teams metrics, setting realistic goals.

22. Measuring Design Systems

How do we measure the health of a design system? Surely it’s not just a roll-out speed for newly designed UI components or flows. Most teams track productivity and coverage, but we can also go beyond that by measuring relative adoption, efficiency gains (time saved, faster time-to-market, satisfaction score, and product quality). But the best metric is how early designers involve the design system in a conversation during their design work.

Keywords:
Component coverage, decision trees, adoption, efficiency, time to market, user satisfaction, usage analytics, design system ROI, relative adoption.

23. Measuring UX Research

Research insights often end up gaining dust in PDF reports stored on remote fringes of Sharepoint. To track the impact of UX research, we need to track outcomes and research-specific metrics. The way to do that is to track UX research impact for UX and business, through organisational learning and engagement, through make-up of research efforts and their reach. And most importantly: amplifying research where we expect the most significant impact. Let’s see what it involves.

Keywords:
Outcome metrics, organizational influence, research-specific metrics, research references, study observers, research formalization, tracking research-initiated product changes.

24. Getting Started

So you’ve made it so far! Now, how do you get your UX metrics initiative off the ground? By following small steps heading in the right direction. Small commitments, pilot projects, and design guilds will support and enable your efforts. We just need to define realistic goals and turn UX metrics in a culture of measurement, or simply a way of working. Let’s see how we can do just that.

Keywords:
Pilot projects, UX integration, resource assessment, evidence-driven design, establishing a baseline, culture of measurement.

25. Next Steps

Let’s wrap up our journey into UX metrics and Design KPIs and reflect what we have learned. What remains is the first next step: and that would be starting where you are and growing incrementally, by continuously visualizing and explaining your UX impact — however limited it might be — to your stakeholders. This is the last chapter of the course, but the first chapter of your incredible journey that’s ahead of you.

Keywords:
Stakeholder engagement, incremental growth, risk mitigation, user satisfaction, business success.

Who Is The Course For?

This course is tailored for advanced UX practitioners, design leaders, product managers, and UX researchers who are looking for a practical guide to define, establish and track design KPIs, translate business goals into actionable design tasks, and connect business needs with user needs.

What You’ll Learn

By the end of the video course, you’ll have a packed toolbox of practical techniques and strategies on how to define, establish, sell, and measure design KPIs from start to finish — and how to make sure that your design work is always on the right trajectory. You’ll learn:

How to translate business goals to UX initiatives,
The difference between OKRs, KPIs, and metrics,
How to define design success for your company,
Metrics and KPIs that businesses typically measure,
How to choose the right set of metrics and KPIs,
How to establish design KPIs focused on user needs,
How to build a comprehensive design KPI tree,
How to combine qualitative and quantitative insights,
How to choose and prioritize design work,
How to track the impact of design work on business goals,
How to explain, visualize, and defend design work,
How companies define and track design KPIs,
How to make a strong case for UX metrics.

Community Matters ❤️

Producing a video course takes quite a bit of time, and we couldn’t pull it off without the support of our wonderful community. So thank you from the bottom of our hearts! We hope you’ll find the course useful for your work. Happy watching, everyone! 🎉🥳

Video + UX Training

$ 495.00 $ 799.00 Get Video + UX Training

25 video lessons (8h) + Live UX Training.
100 days money-back-guarantee.

Video only

$ 250.00$ 395.00

25 video lessons (8h). Updated yearly.
Also available as a UX Bundle with 2 video courses.

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October 15, 2024

It’s Here! How To Measure UX & Design Impact, With Vitaly Friedman

Finally! After so many years, we’re very happy to launch “How To Measure UX and Design Impact”, our new practical guide for designers and managers on how to set up and track design success in your company — with UX scorecards, UX metrics, the entire workflow and Design KPI trees. Neatly put together by yours truly, Vitaly Friedman. Jump to details.

Video + UX Training

$ 495.00 $ 799.00 Get Video + UX Training

25 video lessons (8h) + Live UX Training.
100 days money-back-guarantee.

Video only

$ 250.00$ 395.00

25 video lessons (8h). Updated yearly.
Also available as a UX Bundle with 2 video courses.

The Backstory

Designing a KPI tree, an example of how to connect business objectives with design initiatives through the lens of design KPIs. (Large preview)

And that’s what we are often supposed to be — good “executors”. Or to put differently, “pixel pushers”.

About The Course

The setup for the video recordings. Once all content is in place, it’s about time to set up the recording.

<a class="btn btn--large btn--green btn--text-shadow" href=https://measure-ux.com>Jump to the video course →

A practical guide to UX metrics and Design KPIs
8h-video course + live UX training. Free preview.

25 chapters (8h), with videos added/updated yearly
Free preview, examples, templates, workflows
No subscription: get once, access forever
Life-time access to all videos, slides, checklists.
Add-on: live UX training, running 2× a year
Use the code SMASHING to get 20% off today
Jump to the details →

Table of Contents

We can’t improve without measuring. That’s why our new video course gives you the tools you need to make sense of it all: user needs, just like business needs. (View large version)

1. Welcome

2. Design Impact

3. OKRs and Business Metrics

4. Leading And Lagging Indicators

5. Business Metrics, NPS

6. Business Metrics, CSAT, CES

7. Feedback Scoring and Gap Analysis

8. Design Metrics (TPI, SUS, SUPR-Q)

9. Design Metrics (UMUX-Lite, SEQ, UEQ)

10. Top Tasks Analysis

11. Surveys and Sample Sizes

12. Measuring UX in B2B and Enterprise

13. Design KPI Trees

14. Event Storming

15. Kano Model and Survey

16. Design Process

17. Choosing The Right Metrics

18. Design KPIs Examples

19. UX Strategy

20. Reporting Design Success

21. Target Times and States

22. Measuring Design Systems

23. Measuring UX Research

24. Getting Started

25. Next Steps

Who Is The Course For?

What You’ll Learn

How to translate business goals to UX initiatives,
The difference between OKRs, KPIs, and metrics,
How to define design success for your company,
Metrics and KPIs that businesses typically measure,
How to choose the right set of metrics and KPIs,
How to establish design KPIs focused on user needs,
How to build a comprehensive design KPI tree,
How to combine qualitative and quantitative insights,
How to choose and prioritize design work,
How to track the impact of design work on business goals,
How to explain, visualize, and defend design work,
How companies define and track design KPIs,
How to make a strong case for UX metrics.

Community Matters ❤️

Video + UX Training

$ 495.00 $ 799.00 Get Video + UX Training

25 video lessons (8h) + Live UX Training.
100 days money-back-guarantee.

Video only

$ 250.00$ 395.00

25 video lessons (8h). Updated yearly.
Also available as a UX Bundle with 2 video courses.

October 14, 2024

Thanksgiving Design Ideas: Flyers, Posters, Graphics & More

With Thanksgiving just around the corner, it’s the perfect time to start planning your festive designs for events, promotions, or community gatherings.

Whether you’re creating flyers for a local Thanksgiving dinner, posters for seasonal sales, or social media graphics to spread holiday cheer, having the right design elements can make all the difference.

In this post, we’ve put together a collection of Thanksgiving design templates, including flyers, posters, graphics, and more, to help you capture the warmth and joy of the holiday season.

Thanksgiving is all about togetherness, gratitude, and celebration, and your designs should reflect that spirit. From rich autumnal color palettes to cozy, welcoming imagery, these templates and graphics are designed to evoke the essence of the holiday. Have a look.

Creative Thanksgiving Flyer Template

This is a thoughtfully designed, fully editable Thanksgiving flyer in PSD format. Sized at A4 with a 3mm bleed, it’s prepared for professional printing, supporting CMYK colors at a high resolution of 300 dpi. It’s especially perfect for promoting various events and celebrations.

Stylish Thanksgiving Flyer Template

This a versatile Thanksgiving flyer template for promoting your special event. Designed with meticulous attention to detail, this fully editable template offers well-organized layers and top-quality resolution (CMYK 300 DPI). Spanning 21 x 29.7 cm with bleed, the template is compatible with Adobe Illustrator and Photoshop (CS5).

Simple Thanksgiving Flyer Template

A minimalist Thanksgiving flyer template with customization options to fit your needs. Its specifications include a Photoshop file (CS5), 8.27 x 11.69 inch dimensions including bleeds, 300 dpi CMYK resolution for print-ready convenience, editable fonts and text, and an easy color-change option.

Modern Thanksgiving Flyer & Poster Template

This is a contemporary, easy-to-use Thanksgiving flyer template for business promotions. It comes packaged as a print-ready PSD file neatly organized into layers for straightforward editing. All elements including colors, images, and text can be tailored to suit your needs. An A4 size with extra bleed ensures a professional finish.

2 Thanksgiving Flyer Templates

A perfect pair of flyer templates ideal for Thanksgiving-themed projects. They’re fully layered PSDs, making them easy to edit and customize. Designed in 300 DPI and CMYK colors, they’re print-ready in a 4×6 size.

Red Thanksgiving Flyer Template

This is a customizable Thanksgiving flyer template for your special November event planning. With its appealing red theme, and well-organized, fully editable layers, this A4 size PSD file is easy to use. Everything you need is included, even the free font, which can be found in the readme file.

Colorful Thanksgiving Flyer & Poster Template

Add a splash of color to your Thanksgiving promotions with this vibrant flyer and poster template. It’s simple to customize, with editable text and an easy color change system. The template, which is available in Ai CS 6, CS 3, and Eps files, also boasts organized layers for straightforward editing.

Thanksgiving Festival Flyer Template

An easily customizable Thanksgiving flyer template suitable for seasonal promotions. It includes files in AI, PSD, PDF, PNG, EPS formats and features 300 dpi CMYK resolution. The template is a vector at Ai, ideal for print, and allows for editable fonts/text and color changes.

Thanksgiving Event Flyer Template

This is an ideal flyer template for any Thanksgiving-related event, party, or festival. It offers a customizable, editable, and well-organized PSD and Ai file, conveniently sized to A4 and ready to print. Fonts used in this tastefully designed template are outlined in the readme file and are free for commercial use.

Thanksgiving Celebration Flyer Template

An easily customizable PSD flyer designed for your Thanksgiving festivities. Sized at 8.27 x 11.69 inches (A4) with bleed, its 100% print-ready format includes well-organized layers for straightforward changes to color, image, text, and other elements. It also provides a readme file detailing used fonts.

Thanksgiving Party Flyer Template

This flyer template is perfect for any fall gathering or Thanksgiving dinner. This Photoshop file is remarkably easy to customize, organized in well-labeled layers and folders. Adjust colors, pictures, elements and text in just a few clicks. It’s print-ready, featuring a 300DPI resolution and multiple color variations.

Happy Thanksgiving Flyer Template

Another Thanksgiving flyer template creatively designed for any project. It’s easy to customize with editable fonts/text, adjustable colors, and well-organized layers. The package includes Ai, PSD, PDF, PNG, and EPS files, all in 8.27×11.69 inch dimensions with 300 dpi CMYK resolution, ready for print.

Cute Thanksgiving Poster Template

Check out this adorable Thanksgiving poster template! It comes well-organized in 3 PSD files, all 100% editable and print-ready. Its size is 8.27 x 11.69 inch, designed in full CMYK 300 DPI. The charming design is entirely vector-based for high-quality results.

Thanksgiving Dinner Party Flyer Template

An easily editable Thanksgiving flyer template ideal for your festive gatherings. Provided in both Ai CS6 and Psd formats, it’s fully vectorized and print-ready with sharp 300 DPI CMYK color format, perfectly adaptable to A4 size.

Elegant Thanksgiving Poster Template

This Thanksgiving poster template pack offers a modern and sophisticated aesthetic, perfect for promoting any kind of event. This pack includes various flyer and poster sizes, professionally designed in Illustrator and Photoshop. Its customizability and clean design present your work in a visually appealing manner.

Thanksgiving Social Media Template Kit

A creative Thanksgiving-themed social media template pack, perfect for amplifying your festive posts. It includes 10 templates, tailored to fit the dimensions of Facebook, Instagram, and Twitter posts. The kit provides a fully layered PSD file that’s customizable and editable, along with JPG files for reference.

Thanksgiving Party Social Media Template Pack

Another Thanksgiving social media template pack that offers versatile and professional-grade design templates to help businesses enhance their social media presence. This pack covers 24 different sizes suitable for popular platforms like Facebook, Instagram, Twitter, and more.

Thanksgiving Instagram Story Templates

This Thanksgiving Instagram story template pack is an excellent tool for enhancing your business’s social media presence. Ideal for eCommerce, fashion, or design blogs, the templates are easy to use and adjust- just replace text and images to reflect your brand. Customizable aspects include color, text, images, and overall design.

Thanksgiving Day Social Media Banner Templates

If you’re looking to spruce up your social media presence this Thanksgiving, consider using this Thanksgiving social media template kit. These easy-to-use, editable templates are perfect for any business or blog, offering high resolution, vector-based designs in multiple sizes appropriate for Instagram, Facebook, Pinterest, Twitter and LinkedIn.

Thanksgiving Social Media Templates Pack

This Thanksgiving social media template kit provides six professionally designed, customizable banner post templates for several social platforms (including Instagram, Facebook, Twitter, Pinterest, and LinkedIn). With editable text and colors and easy image placement, these templates allow your holiday social media ads to shine.

Two-Side Thanksgiving Greeting Card Template

A professionally designed Thanksgiving greeting card template offering a two-sided card design. This versatile kit includes an AI (Adobe Illustrator) file, a PSD (Adobe Photoshop) file, and an EPS file for customization. With a size of 7×5 inches plus bleed, it’s 100% ready to print and neatly arranged in layers.

Thanksgiving Greetings Card Templates

This is a set of elegantly rustic Thanksgiving greeting card templates that enrich your holiday wishes. Featuring line art borders of autumnal elements and a variety of layouts, it’s perfect for Thanksgiving flyers and invitations. They are provided in Photoshop PSD and Illustrator AI files, these 5×7″ printed size templates.

Free Thanksgiving Flyer Templates

Free Thanksgiving Flyer & Poster Template

This is a free flyer template you can use to promote all kinds of Thanksgiving events, dinner parties, and more. The template comes in PSD format with easily editable elements.

Free Happy Thanksgiving Flyer

Another free Thanksgiving flyer template with a colorful design. It has lots of decorative elements with creative typography and image placeholders to help you craft a more attractive flyer for your event.

Free Simple Thanksgiving Flyer Template

This free PSD template is perfect for your modern Thanksgiving flyer designs. It features a simple layout with minimal decorations and plenty of space to include details about your event.

Free Dark Thanksgiving Flyer Template

If you prefer darker designs, this free Thanksgiving flyer template is perfect for your event. It comes with a bold and dark design that effectively highlights you content above all else.

Free Creative Thanksgiving Flyer Template

Another free Thanksgiving flyer template for various events and celebrations. This template also comes in PSD format and it features beautiful hand-drawn illustrations that give the design a hand-crafted look and feel.

October 13, 2024

WordPress vs Angular: Choosing the Right Platform for Your Website

Building a website can be exciting, but choosing the right platform can be overwhelming. Two popular options are WordPress and Angular, each catering to different needs. So, which one is right for you? Let’s dive into the strengths and weaknesses of each platform. WordPress WordPress is a powerful content management system (CMS) used by millions […]

The post WordPress vs Angular: Choosing the Right Platform for Your Website first appeared on WPArena and is written by Dilip Kumar.

October 13, 2024

Database Design – Timestamps

This week I'm working on the data warehousing capabilities of my application. Now most people here who have built more than a couple of applications can tell you how useful it is to include a datestamp on records or requests as they come in. The advantages are numerous.

So much so that I'm now fighting the temptation to include a datestamp on every table. Won't that bloat my database?

I suppose what I'm looking for is guidance on making a per table decision to include or exclude the datestamp. Because if space were free I'd put one on every darn table! But space isn't free and my app is likely to generate a factor of five to ten times the amount of metadata per data and so datestamps would put me in danger of doubling that again, or trebling it. That's fine up to a point but will impact load times.

October 13, 2024

How AI is Changing the Future of Remote Hiring and Virtual Recruitment

The second half of the pandemic has entrenched remote hiring, while AI attempts to improve the virtual hiring experience by removing any inefficiencies. Virtual recruitment automation tools, such as Pitch N Hire, are arming the arms of a recruiter, so over the process of hiring employees remotely, one would move from virtual interviews to evaluation.

Some of the advantages of remote hiring with the help of AI include:

Video Interview Enhancement through AI: Recorded or live video interviews use AI to give more than just a convenient way to discuss which candidates are better. Video interviews can also help analyze how the person behaves in front of the camera. It allows understanding of the nuances if interviewing persons on OTT.
Virtual Niche Recruitment: The assessment takes the form of a well-structured, engaging mini-game with hints that test the candidates abilities avocation and sense competently without superfluities that waste both HR & candidates time.
Seamless Candidate Communication: AI-powered chatbots will keep the candidates warm and in the loop throughout the remote hiring process, providing relevant updates, answering questions, and avoiding communication bottlenecks.

Consequently, AI uses data in the recruitment process hence it enhances effectiveness of remote recruitment saving on the time taken and enabling faster recruitment of talent without compromising on quality hire.

CSS Tricks That Use Only One Gradient

CSS gradients have been so long that there’s no need to rehash what they are and how to use them. You have surely encountered them at some point in your front-end journey, and if you follow me, you also know that I use them all the time. I use them for CSS patterns, nice CSS decorations, and even CSS loaders. But even so, gradients have a tough syntax that can get very complicated very quickly if you’re not paying attention.

In this article, we are not going to make complex stuff with CSS gradients. Instead, we’re keeping things simple and I am going to walk through all of the incredible things we can do with just one gradient.

Only one gradient? In this case, reading the doc should be enough, no?

No, not really. Follow along and you will see that gradients are easy at their most basic, but are super powerful if we push them — or in this case, just one — to their limits.

CSS patterns

One of the first things you learn with gradients is that we can establish repeatable patterns with them. You’ve probably seen some examples of checkerboard patterns in the wild. That’s something we can quickly pull off with a single CSS gradient. In this case, we can reach for the repeating-conic-gradient() function:

background: 
  repeating-conic-gradient(#000 0 25%, #fff 0 50%) 
  0 / 100px 100px;

A more verbose version of that without the background shorthand:

background-image: repeating-conic-gradient(#000 0 25%, #fff 0 50%);
background-size: 100px 100px;

Either way, the result is the same:

Pretty simple so far, right? You have two colors that you can easily swap out for other colors, plus the background-size property to control the square shapes.

If we change the color stops — where one color stops and another starts — we get another cool pattern based on triangles:

background: 
  repeating-conic-gradient(#000 0 12.5%, #fff 0 25%) 
  0 / 100px 100px;

If you compare the CSS for the two demos we’ve seen so far, you’ll see that all I did was divide the color stops in half, 25% to 12.5% and 50% to 25%.

Another one? Let’s go!

This time I’m working with CSS variables. I like this because variables make it infinitely easier to configure the gradients by updating a few values without actually touching the syntax. The calculation is a little more complex this time around, as it relies on trigonometric functions to get accurate values.

I know what you are thinking: Trigonometry? That sounds hard. That is certainly true, particularly if you’re new to CSS gradients. A good way to visualize the pattern is to disable the repetition using the no-repeat value. This isolates the pattern to one instance so that you clearly see what’s getting repeated. The following example declares background-image without a background-size so you can see the tile that repeats and better understand each gradient:

I want to avoid a step-by-step tutorial for each and every example we’re covering so that I can share lots more examples without getting lost in the weeds. Instead, I’ll point you to three articles you can refer to that get into those weeds and allow you to pick apart our examples.

How to create background patterns using CSS & conic-gradient (Verpex blog)
Learn CSS radial-gradient by Building Background Patterns (freeCodeCamp)
Background Patterns, Simplified by Conic Gradients (Ana Tudor)

I’ll also encourage you to open my online collection of patterns for even more examples. Most of the examples are made with multiple gradients, but there are plenty that use only one. The goal of this article is to learn a few “single gradient” tricks — but the ultimate goal is to be able to combine as many gradients as possible to create cool stuff!

Grid lines

Let’s start with the following example:

You might claim that this belongs under “Patterns” — and you are right! But let’s make it more flexible by adding variables for controlling the thickness and the total number of cells. In other words, let’s create a grid!

.grid-lines {
  --n: 3; /* number of rows */
  --m: 5; /* number of columns */
  --s: 80px; /* control the size of the grid */
  --t: 2px; /* the thickness */

  width: calc(var(--m)*var(--s) + var(--t));
  height: calc(var(--n)*var(--s) + var(--t));
  background:  
    conic-gradient(from 90deg at var(--t) var(--t), #0000 25%, #000 0)
      0 0/var(--s) var(--s);
}

First of all, let’s isolate the gradient to better understand the repetition (like we did in the previous section).

One repetition will give us a horizontal and a vertical line. The size of the gradient is controlled by the variable --s, so we define the width and height as a multiplier to get as many lines as we want to establish the grid pattern.

What’s with “+ var(--t)” in the equation?

The grid winds up like this without it:

We are missing lines at the right and the bottom which is logical considering the gradient we are using. To fix this, the gradient needs to be repeated one more time, but not at full size. For this reason, we are adding the thickness to the equation to have enough space for the extra repetition and the get the missing lines.

And what about a responsive configuration where the number of columns depends on the available space? We remove the --m variable and define the width like this:

width: calc(round(down, 100%, var(--s)) + var(--t));

Instead of multiplying things, we use the round() function to tell the browser to make the element full width and round the value to be a multiple of --s. In other words, the browser will find the multiplier for us!

Resize the below and see how the grid behaves:

In the future, we will also be able to do this with the calc-size() function:

width: calc-size(auto, round(down, size, var(--s)) + var(--t));

Using calc-size() is essentially the same as the last example, but instead of using 100% we consider auto to be the width value. It’s still early to adopt such syntax. You can test the result in the latest version of Chrome at the time of this writing:

Dashed lines

Let’s try something different: vertical (or horizontal) dashed lines where we can control everything.

.dashed-lines {
  --t: 2px;  /* thickness of the lines */
  --g: 50px; /* gap between lines */
  --s: 12px; /* size of the dashes */
  
  background:
    conic-gradient(at var(--t) 50%, #0000 75%, #000 0)
    var(--g)/calc(var(--g) + var(--t)) var(--s);
}

Can you figure out how it works? Here is a figure with hints:

Outline of a rectangle with dashed green borders. Variables for t, g, and s are labeled.

Try creating the horizontal version on your own. Here’s a demo that shows how I tackled it, but give it a try before peeking at it.

What about a grid with dashed lines — is that possible?

Yes, but using two gradients instead of one. The code is published over at my collection of CSS shapes. And yes, the responsive behavior is there as well!

Rainbow gradient

How would you create the following gradient in CSS?

You might start by picking as many color values along the rainbow as you can, then chaining them in a linear-gradient:

linear-gradient(90deg, red, yellow, green, /* etc. */, red);

Good idea, but it won’t get you all the way there. Plus, it requires you to juggle color stops and fuss with them until you get things just right.

There is a simpler solution. We can accomplish this with just one color!

background: linear-gradient(90deg in hsl longer hue, red 0 0);

I know, the syntax looks strange if you’re seeing the new color interpolation for the first time.

If I only declare this:

background: linear-gradient(90deg, red, red); /* or (90deg, red 0 0) */

…the browser creates a gradient that goes from red to red… red everywhere! When we set this “in hsl“, we’re changing the color space used for the interpolation between the colors:

background: linear-gradient(90deg in hsl, red, red);

Now, the browser will create a gradient that goes from red to red… this time using the HSL color space rather than the default RGB color space. Nothing changes visually… still see red everywhere.

The longer hue bit is what’s interesting. When we’re in the HSL color space, the hue channel’s value is an angle unit (e.g., 25deg). You can see the HSL color space as a circle where the angle defines the position of the color within that circle.

3D models of the RGB and HSL color spaces.

Since it’s a circle, we can move between two points using a “short” path or “long” path.

Showing the long and short ends of the hue in a color circle.

If we consider the same point (red in our case) it means that the “short” path contains only red and the “long” path runs into all the colors as it traverses the color space.

Adam Argyle published a very detailed guide on high-definition colors in CSS. I recommend reading it because you will find all the features we’re covering (this section in particular) to get more context on how everything comes together.

We can use the same technique to create a color wheel using a conic-gradient:

background: conic-gradient(in hsl longer hue,red 0 0);

And while we are on the topic of CSS colors, I shared another fun trick that allows you to define an array of color values… yes, in CSS! And it only uses a single gradient as well.

Hover effects

Let’s do another exercise, this time working with hover effects. We tend to rely on pseudo-elements and extra elements when it comes to things like applying underlines and overlays on hover, and we tend to forget that gradients are equally, if not more, effective for getting the job done.

Case in point. Let’s use a single gradient to form an underline that slides on hover:

h3 {
  background: 
    linear-gradient(#1095c1 0 0) no-repeat
    var(--p,0) 100%/var(--p, 0) .1em;
  transition: 0.4s, background-position 0s;
}

h3:hover {
  --p: 100%;
}

You likely would have used a pseudo-element for this, right? I think that’s probably how most people would approach it. It’s a viable solution but I find that using a gradient instead results in cleaner, more concise CSS.

You might be interested in another article I wrote for CSS-Tricks where I use the same technique to create a wide variety of cool hover effects.

CSS shapes

Creating shapes with gradients is my favorite thing to do in CSS. I’ve been doing it for what feels like forever and love it so much that I published a “Modern Guide for Making CSS Shapes” over at Smashing Magazine earlier this year. I hope you check it out not only to learn more tricks but to see just how many shapes we can create with such a small amount of code — many that rely only on a single CSS gradient.

Some of my favorites include zig-zag borders:

…and “scooped” corners:

…as well as sparkles:

…and common icons like the plus sign:

I won’t get into the details of creating these shapes to avoid making this article long and boring. R ead the guide and visit my CSS Shape collection and you’ll have everything you need to make these, and more!

Border image tricks

Let’s do one more before we put a cap on this. Earlier this year, I discovered how awesome the CSS border-image property is for creating different kinds of decorations and shapes. And guess what? border-image limits us to using just one gradient, so we are obliged to follow that restriction.

Again, just one gradient and we get a bunch of fun results. I’ll drop in my favorites like I did in the last section. Starting with a gradient overlay:

We can use this technique for a full-width background:

…as well as heading dividers:

…and even ribbons:

All of these have traditionally required hacks, magic numbers, and other workarounds. It’s awesome to see modern CSS making things more effortless. Go read my article on this topic to find all the interesting stuff you can make using border-image.

Wrapping up

I hope you enjoyed this collection of “single-gradient” tricks. Most folks I know tend to use gradients to create, well, gradients. But as we’ve seen, they are more powerful and can be used for lots of other things, like drawing shapes.

I like to add a reminder at the end of an article like this that the goal is not to restrict yourself to using one gradient. You can use more! The goal is to get a better handle on how gradients work and push them in interesting ways — that, in turn, makes us better at writing CSS. So, go forth and experiment — I’d love to see what you make!

CSS Tricks That Use Only One Gradient originally published on CSS-Tricks, which is part of the DigitalOcean family. You should get the newsletter.

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Qwen vs Llama – Who is winning the Open Source LLM Race

Open-source LLMS, owing to their comparable performance with advanced proprietary LLMs, have been gaining immense popularity lately. Open-source LLMs are free to use, and you can easily modify their source code or fine-tune them on your systems.

Alibaba's Qwen and Meta's Llama series of models are two major players in the open source LLM arena. In this article, we will compare the performance of Qwen 2.5-72b and Llama 3.1-70b models for zero-shot text classification and summarization.

By the end of this article, you will have a rough idea of which model to use for your NLP tasks.

So, lets begin without ado.

Installing and Importing Required Libraries

We will call the Hugging Face inference API to access the Qwen and LLama models. In addition, we will need the rouge-score library to calculate ROUGE scores for text summarization tasks. The script below installs the required libraries for this article.


!pip install huggingface_hub==0.24.7
!pip install rouge-score
!pip install --upgrade openpyxl
!pip install pandas openpyxl

The script below installs the required libraries.


from huggingface_hub import InferenceClient
import os
import pandas as pd
from rouge_score import rouge_scorer
from sklearn.metrics import accuracy_score
from collections import defaultdict

Calling Qwen 2.5 and Llama 3.1 Using Hugging Face Inference API

To access models via the Hugging Face inference API, you will need your Hugging Face User Access tokens.

Next, create a client object for the corresponding model using the InferenceClient class from the huggingface_hub library.
You must pass the Hugging Face model path and the access token to the InferenceClientclass constructor.

The script below creates model clients for Qwen 2.5-72b and Llama 3.1-70b models.


hf_token = os.environ.get('HF_TOKEN')

#qwen 2.5 endpoint
#https://huggingface.co/Qwen/Qwen2.5-72B-Instruct
qwen_model_client = InferenceClient(
    "Qwen/Qwen2.5-72B-Instruct",
    token=hf_token
)

#Llama 3.1 endpoint
#https://huggingface.co/meta-llama/Llama-3.1-70B-Instruct
llama_model_client = InferenceClient(
    "meta-llama/Llama-3.1-70B-Instruct",
    token=hf_token
)

To get a response from the model, you can call the chat_completion() method and pass a list of system and user messages to the messages attribute of the method.

The script below defines the make_prediction() method, which accepts the model client, the system role prompt, and the user query and generates a response using the model client.


def make_prediction(model, system_role, user_query):

    response = model.chat_completion(
    messages=[{"role": "system", "content": system_role},
        {"role": "user", "content": user_query}],
    max_tokens=10,
    )

    return response.choices[0].message.content

Let's first generate a dummy response using the Qwen 2.5-72b.


system_role = "Assign positive, negative, or neutral sentiment to the movie review. Return only a single word in your response"
user_query = "I like this movie a lot"
make_prediction(qwen_model_client,
               system_role,
               user_query)

Output:

'positive'

The above output shows that the Qwen model generates the expected response.

Let's try the Llama 3.1-70b model now.

system_role = "Assign positive, negative, or neutral sentiment to the movie review. Return only a single word in your response"
user_query = "I hate this movie a lot"
make_prediction(llama_model_client,
               system_role,
               user_query)

Output:

'negative'

And voila, the Llama also makes correct predictions.

In the following two sections, we will compare the performance of the two models on custom datasets. We see how the two models fare for zero-shot text classification and summarization.

Qwen 2.5-72b vs Llama 3.1-70b For Text Classification

For text classification, we will use the Twitter US Airline Sentiment, which consists of positive, negative, and neutral tweets for various US airlines.

The following script imports the dataset into a Pandas DataFrame.


## Dataset download link
## https://www.kaggle.com/datasets/crowdflower/twitter-airline-sentiment?select=Tweets.csv

dataset = pd.read_csv(r"D:\Datasets\Tweets.csv")
dataset.head()

Output:

We will preprocess our dataset and select 100 tweets (34 neutral and 33 each for positive and negative sentiments).


# Remove rows where 'airline_sentiment' or 'text' are NaN
dataset = dataset.dropna(subset=['airline_sentiment', 'text'])

# Remove rows where 'airline_sentiment' or 'text' are empty strings
dataset = dataset[(dataset['airline_sentiment'].str.strip() != '') & (dataset['text'].str.strip() != '')]

# Filter the DataFrame for each sentiment
neutral_df = dataset[dataset['airline_sentiment'] == 'neutral']
positive_df = dataset[dataset['airline_sentiment'] == 'positive']
negative_df = dataset[dataset['airline_sentiment'] == 'negative']

# Randomly sample records from each sentiment
neutral_sample = neutral_df.sample(n=34)
positive_sample = positive_df.sample(n=33)
negative_sample = negative_df.sample(n=33)

# Concatenate the samples into one DataFrame
dataset = pd.concat([neutral_sample, positive_sample, negative_sample])

# Reset index if needed
dataset.reset_index(drop=True, inplace=True)

# print value counts
print(dataset["airline_sentiment"].value_counts())

Output:


airline_sentiment
neutral     34
positive    33
negative    33
Name: count, dtype: int64

Next, we will define the predict_sentiment() function, which accepts the model client, the system prompt, and the user query and generates a model response.


def predict_sentiment(model, system_role, user_query):

    response = model.chat_completion(
    messages=[{"role": "system", "content": system_role},
        {"role": "user", "content": user_query}],
    max_tokens=10,
    )

    return response.choices[0].message.content

In the next step, we will iterate through the 100 tweets in our dataset and predict sentiment for each tweet using the Qwen 2.5-72b and Llama 3.1-70b models, as shown in the following script.


models = {
    "qwen2.5-72b": qwen_model_client,
    "llama3.1-70b": llama_model_client
}

tweets_list = dataset["text"].tolist()
all_sentiments = []
exceptions = 0

for i, tweet in enumerate(tweets_list, 1):
    for model_name, model_client in models.items():
        try:
            print(f"Processing tweet {i} with model {model_name}")

            system_role = "You are an expert in annotating tweets with positive, negative, and neutral emotions"

            user_query = (
                f"What is the sentiment expressed in the following tweet about an airline? "
                f"Select sentiment value from positive, negative, or neutral. "
                f"Return only the sentiment value in small letters.\n\n"
                f"tweet: {tweet}"
            )

            sentiment_value = predict_sentiment(model_client, system_role, user_query)
            all_sentiments.append({
                'tweet_id': i,
                'model': model_name,
                'sentiment': sentiment_value
            })
            print(i, model_name, sentiment_value)

        except Exception as e:
            print("===================")
            print("Exception occurred with model:", model_name, "| Tweet:", i, "| Error:", e)
            exceptions += 1

print("Total exception count:", exceptions)

Output:

Finally, we will convert the predictions for both models into a Pandas Dataframe. We will then fetch the predictions for the individual models and compare them with the actual sentiment values in the datasets to calculate accuracy.

# Convert results to DataFrame and calculate accuracy for each model
results_df = pd.DataFrame(all_sentiments)

for model_name in models.keys():
    model_results = results_df[results_df['model'] == model_name]
    accuracy = accuracy_score(model_results['sentiment'], dataset["airline_sentiment"].iloc[:len(model_results)])
    print(f"Accuracy for {model_name}: {accuracy}")

Output:

Accuracy for qwen2.5-72b: 0.8
Accuracy for llama3.1-70b: 0.77

The above output shows that the Qwen 2.5-72b model achieves 80% accuracy while the Llama-3.1-70b model achieves 77% accuracy. Qwen 2.5-72b model wins the battle for zero-shot text classification.

Let's now see which model performs better for zero-shot text summarization.

Qwen 2.5-72b vs Llama 3.1-70b For Text Summarization

We will use the News Articles Dataset to summarise text using the Qwen and Llama models.

The following script imports the dataset into Pandas DataFrame.

# Kaggle dataset download link
# https://github.com/reddzzz/DataScience_FP/blob/main/dataset.xlsx

dataset = pd.read_excel(r"D:\Datasets\dataset.xlsx")
dataset = dataset.sample(frac=1)
print(dataset.shape)
dataset.head()

Output:

Next, we will check the average number of characters in all summaries. We will use this number as output tokens in the LLM model response.

dataset['summary_length'] = dataset['human_summary'].apply(len)
average_length = dataset['summary_length'].mean()
print(f"Average length of summaries: {average_length:.2f} characters")

Output:

Average length of summaries: 1168.78 characters

We will define the generate_summary() helper method, which takes in the model client, the system prompt, and the user query as parameters and returns the model client response.

def generate_summary(model, system_role, user_query):

    response = model.chat_completion(
    messages=[{"role": "system", "content": system_role},
        {"role": "user", "content": user_query}],
    max_tokens=1200,
    )

    return response.choices[0].message.content

We will also define the calculate_rouge helper method that takes in actual and predicted summaries as parameters and returns ROUGE scores.


# Function to calculate ROUGE scores
def calculate_rouge(reference, candidate):
    scorer = rouge_scorer.RougeScorer(['rouge1', 'rouge2', 'rougeL'], use_stemmer=True)
    scores = scorer.score(reference, candidate)
    return {key: value.fmeasure for key, value in scores.items()}

Finally, we will iterate through the first 20 articles in the dataset and summarize them using the Qwen 2.5-72b and Llama 3.1-70b models. We will use the generate_summary() function to generate the summary of the model and then use the calculate_rouge() method to calculate ROUGE scores for the prediction.

We create a Pandas DataFrame that contains ROUGE scores for all article summaries generated via the Qwen 2.5-72b and Llama 3.1-70b models.

models = {"qwen2.5-72b": qwen_model_client,
          "llama3.1-70b": llama_model_client}

results = []

i = 0
for _, row in dataset[:20].iterrows():
    article = row['content']
    human_summary = row['human_summary']

    i = i + 1

    for model_name, model_client in models.items():

        print(f"Summarizing article {i} with model {model_name}")
        system_role = "You are an expert in creating summaries from text"
        user_query = f"Summarize the following article in 1150 characters. The summary should look like human created:\n\n{article}\n\nSummary:"

        generated_summary = generate_summary(model_client, system_role, user_query)
        rouge_scores = calculate_rouge(human_summary, generated_summary)

        results.append({
            'model': model_name,
            'article_id': row.id,
            'generated_summary': generated_summary,
            'rouge1': rouge_scores['rouge1'],
            'rouge2': rouge_scores['rouge2'],
            'rougeL': rouge_scores['rougeL']
        })

# Create a DataFrame with results
results_df = pd.DataFrame(results)

Output:

Finally, we can take the average ROUGE scores of all the article summaries to compare the two models.

average_scores = results_df.groupby('model')[['rouge1', 'rouge2', 'rougeL']].mean()
average_scores_sorted = average_scores.sort_values(by='rouge1', ascending=False)
print("Average ROUGE scores by model:")
average_scores_sorted.head()

Output:

The Qwen model wins here as well for all ROUGE scores.

Conclusion

Open-source LLMs are quickly catching up with proprietary models. Qwen 2.5-72B has already surpassed GPT-4 turbo, introduced at the beginning of this year.

In this article, you saw a comparison between Qwen 2.5-72b and Llama 3.1-70b models for zero-shot text classification and summarization. The Qwen model performs better than Llama on both tasks.

I encourage you to use the Qwen model for text generation tasks like Chatbot development and share your work with us.

How to Successfully Use ChatGPT for SEO

Large Language Models (LLMs) can significantly improve your SEO success and at the same time lower your workload. Here are the Dos and Don'ts of using ChatGPT for SEO.

What's the best way to integrate AI into keyword research? How to create engaging content with ChatGPT? And what other ways are there to streamline your SEO with LLMs?

Here are my 2 cents on the topic as an SEO consultant with 15 years experience. The following guide offers some (maybe unexpected) ways to integrate AI into your workflows, while at the same time improving quality and reducing hours.

#1 Trouble Shooting

One often overlooked way to boost your SEO is to use ChatGPT for troubleshooting. It is excellent at helping you fix technical errors pretty much anything that might affect the Core Vitals in Google Search Console or lower your score on the web.dev checker. Got a weird CLS- or LCP-error affecting your WordPress site? Need to fix someone else's PHP code on a 9-year-old stand-alone page? Talk it through with ChatGPT and you might be surprised how easy some fixes come these days.

I previously used to spend countless hours looking through old threads on different message boards when troubleshooting. Now it's one short chat with my assistant, and I usually find more elegant fixes than before too. To clarify: ChatGPT does not "fix" anything by itself. But it assists you in locating the source of an error and resolving it. Of course, you have to provide the context, goal, and, if applicable, relevant code snippets.

#2 Keyword Research

Keyword research is still a mostly "manual" task and I use quotation marks here because it has relied on various tools since the beginning of SEO such as the Google Keyword Planner, list generators, suggestion-tools, etc. In my opinion, AI hasn't really impacted the initial steps and strategies of keyword research yet. However, ChatGPT and other LLMs are good at identifying things you might have overlooked.

When I start to compile my keyword list, I show every column of the list separately to an LLM and ask it to suggest additions. This helps me to identify expressions that I might not have considered. The rest of the process is mostly as before: I use a tool from pre-AI times to automatically compile all possible combinations of my keyword columns. After checking the search volume for all those phrases, I am left with a list of potentially useful keywords. This list I show to an LLM once more, just to double check that I didn't miss anything obvious.

There is a variety of plugins for keyword research with ChatGPT available, but in my experience, they don't contribute much more than the standard version (4o at the time of writing).

#3 Content Writing

Using LLMs for creating written content is a controversial topic on the one hand, it can be difficult (if not impossible) to identify texts written by AI; on the other hand, AI is often applied so unprofessionally, that it is painfully obvious when a text was written this way. Even worse, we have seen content like that rank much higher than it should for a while. Google tried to address the issue with a core update to its algorithm earlier this year, but there is still lack of consensus among SEO experts as to how successful this was.

In my experience, LLMs can be helpful for phrasing if you provide the right input, structure, context, and ideas. Don't try to have the chatbot come up with the content for the text, it will most likely spit out something bland. Give it clear instructions and it will provide fitting phrasing for almost every context, or at least be able to suggest (sometimes better) alternative formulations that you can use to improve your own writing. Moreover, it's best not to try to make an LLM write an entire landing page at once. Better take it step by step and only ask for single parts/slides/paragraphs/headlines etc. Also: Claude is much better at this than ChatGPT at the moment.

#4 Image Generation

If there is one thing I am certain about regarding Google's search algorithm, then it is that it absolutely loves relevant, unique photos and illustrations. DALL-E is great for generating images that just perfectly fit the content of your site, and it also makes it much easier to create your own infographics.

Please note that DALL-E couldn't create an entire infographic, as it is not meant to accurately visualize data, and it has serious troubles spelling anything correctly that is more than a few characters or words. For such things, we still rely on image editing software. But DALL-E can provide individual elements, icons, frames, etc. and ChatGPT is helpful for bouncing ideas for data visualization.

If I use a photo generated by AI 1:1 on a website, I always adjust the dimensions and filename and delete the metadata just to be sure I don't make it too easy for bots to identify it as generated content. You're not sure how to delete a file's metadata? Ask ChatGPT! ;)

Conclusion: Increase Quality & Decrease Hours

I'd estimate that AI tools have improved the quality of my work in SEO by at least 20% and slightly reduced my hours at the same time.

Other ways of successfully integrating AI into SEO are definitely on the horizon, and I'd advise all SEO professionals to familiarize themselves with the latest tools and to stay up to date. In my opinion, AI is today approximately where the Internet was in 1998, and the landscape will most likely continue to change rapidly. Hence, what works today might not work tomorrow bear that in mind when developing your long-term SEO strategies. Stay flexible, keep learning, and be prepared to adapt as AI continue to evolve.

Understanding B2B2C Marketing: A Comprehensive Overview

As a content writer in the digital marketing space, I spend a lot of time breaking down industry terms, concepts, and strategies, some of which can be more confusing or difficult to grasp than others.

However, I have also found that some terms, including “B2B2C marketing,” might seem to be overly complicated at first, but turn out to be much easier to understand once you investigate them.

In this post, I’ll guide you through what B2B2C marketing is and how it works, as well as provide a few examples of popular and effective B2B2C marketing strategies.

Table of Contents

What is B2B2C marketing?
Why B2B2C Marketing Works
How B2B2C Marketing Works
3 Effective B2B2C Marketing Strategies

Importantly, B2B2C marketing is distinct from B2B or B2C marketing, in which businesses sell exclusively to other businesses or directly to consumers.

B2B2C marketing is actually incredibly common, and most of us engage with businesses utilizing this model on a regular basis.

In fact, B2B2C marketing has been around for ages but has grown increasingly prevalent over the years as technological innovation has made it easier and more beneficial for businesses to collaborate.

Now that I’ve provided you with a basic definition of B2B2C marketing, let’s look at exactly why — and how — it works and explore some real-world examples.

Why B2B2C Marketing Works

Personally, I have seen B2B2C marketing take many forms and be used in various contexts across industries.

In many cases, these have been simple arrangements between two businesses, in which the underlying strategies and mutually beneficial nature of the partnerships were incredibly straightforward.

And in others, the inner workings and processes have been considerably more intricate, sometimes including a product manufacturer, global distributor, and hundreds of independent retail organizations operating around the world.

However, in virtually every example I’ve encountered, B2B2C marketing strategies tend to follow the same basic set of rules and target similar outcomes. Here are some of the ways that this model is beneficial for businesses.

Shared Benefits of Partnership and Collaboration

The first thing to understand is that B2B2C marketing is essentially a partnership or collaboration between businesses.

These partnerships are typically formed by recognizing that each business has something the other needs or can benefit from.

In most cases, the first business has a particular product, and the second, intermediary business has access to consumers who would be interested in buying that product.

Put simply, when B2B2C marketing is utilized effectively, everybody wins.

Elevated Brand Awareness and Growth

It’s also important to note that the benefits of B2B2C marketing often go far beyond increasing sales.

For one, collaborative content creation and marketing efforts between businesses help build brand awareness and grow each company’s consumer base.

Increased Access to Consumer Data and Insights

Additionally, in many cases the first business will gain access to valuable consumer data and insights, allowing them to better identify and understand their target audience. This in turn helps them provide more personalized experiences.

How B2B2C Marketing Works

Now that I’ve given a general description of why B2B2C marketing works and how it benefits businesses, I’d like to highlight a few examples of companies that use this model.

The examples I’m about to share will demonstrate how B2B2C marketing strategies can vary depending on the product and/or industry.

B2B2C Marketing Strategy Example 1: Frito-Lay

Frito-Lay is a great company to start with because it offers one of the oldest, most basic iterations of B2B2C marketing.

As a manufacturer of popular snacks, Frito-Lay partners with grocery stores around the world, which act as intermediaries that buy, market, and sell its products directly to consumers.

One common aspect of B2B2C marketing to keep in mind as we go through these examples is that consumers will always be aware of the partnership.

In this example, when I go to the grocery store to buy my favorite chips, I understand that I am buying the chips from the store, but also that the chips originated from and were manufactured at one of Frito-Lay’s facilities.

B2B2C Marketing Strategy Example 2: Instacart

Sticking with groceries as a product category, Instacart is another, more modern example of B2B2C marketing in action. In this case, however, the grocery store is the first business and Instacart is the intermediary.

More specifically, if I own and operate a grocery store, I am limited to selling my products to consumers who walk into the physical location to purchase groceries.

But by partnering with a delivery service like Instacart, I now have a way to sell my products to people in their home, and without the need to worry about the logistics involved with food delivery.

B2B2C Marketing Strategy Example 3: Apple

Moving on to the tech industry, Apple is an excellent example to look at for a few reasons. For one, it engages in different B2B2C strategies related to both hardware and digital services.

Secondly, Apple is an example of a company whose business model consists of B2B, B2C, and B2B2C all at once.

In terms of hardware, Apple sells its iPhones to telecommunications companies, such as Verizon and T-Mobile, who then sell the iPhones directly to consumers (B2B2C). At the same time, Apple also sells its products directly to consumers at its own stores and on its website (B2C).

Regarding digital services, Apple provides its marketplace, the App Store, to software developers who can then sell their mobile applications to consumers (B2B2C).

Meanwhile, Apple also sells its own software solutions and platforms, such as Apple Business Manager, directly to business owners to support their operations (B2B).

B2B2C Marketing Strategy Example 4: Amazon

Amazon runs one of the largest and most successful B2B2C marketing operations in the world.

By providing an ecommerce marketplace, along with warehouse, customer support, and delivery services, businesses and manufacturers across industries gain the ability to sell their products to a wider range of consumers than they would normally have access to.

It’s also worth mentioning that, like Apple, Amazon also manufactures and sells its own products to consumers on its website (B2C), while also producing and distributing its own software solutions to businesses (B2B).

By this point, I hope you’ve gained a better understanding of what B2B2C marketing is and how it works in different industries and contexts.

Now, I want to examine a few specific strategies that can help businesses maximize the impact of their B2B2C marketing efforts.

3 Effective B2B2C Marketing Strategies

From what I’ve seen, the most successful B2B2C marketing strategies are those in which both businesses lean into the collaborative element of their partnership, finding creating ways for each to benefit while optimizing the experiences and satisfaction of the end consumer.

For example, I once worked for a small clothing company with a uniquely talented creative team and exclusive access to influential brand ambassadors. But they also had extremely limited capital, ecommerce capabilities, and access to consumers.

By partnering with a much larger, more established fashion brand, they were able to execute a collaborative campaign and get their products in front of a larger audience — all while providing their partner with high-quality creative content and a valuable influencer co-sign to help revive the brand’s image.

Here are just a few effective B2B2C marketing strategies that emphasize collaboration and mutually beneficial outcomes.

1. Collaborative Marketing Campaigns

Fostering brand awareness is often important to both businesses within a B2B2C marketing partnership.

As such, broadcasting your collaboration via creative advertising campaigns can be a great way to call attention to both brands as well as their specific services and product offerings.

For example, influencer marketing has become an increasingly effective way to reach online consumers and bring brands into the spotlight.

Whether it’s launched on social media or in the form of a television or streaming service advertisement, engaging a celebrity to promote the collaboration between brands will help ensure the partnership doesn’t fly under the radar.

Best for: B2B2C partnerships in which both companies have a significant consumer-facing element. For instance, if Samsung and Verizon collaborate on a campaign advertising a new mobile device combined with a service promotion, both businesses can increase sales based on the same campaign.

Pro tip: Using unified marketing software like Marketing Hub can be a big help here as you collaborate on campaigns.

2. Referral Programs

While by no means a new concept, establishing a referral program remains one of the most effective ways for businesses to collaborate to each party’s benefit.

In the case of B2B2C marketing specifically, this can allow an intermediary to be compensated for the sale of the first business’s product rather than merely supporting them or providing access to consumers.

Referral programs can be rolled out in a variety of ways, but in many cases, it’s as simple as agreeing on a fair commission for the intermediary based on each individual sale of a product or service.

As an example, if I own a SaaS company and partner with an online marketplace to sell my solutions, it might make sense to offer a 10% commission on each sale, particularly considering the sale wouldn’t have been possible without their services.

Best for: Businesses selling high-ticket items or services, such as SaaS and FinTech companies. In B2B2C marketing, referral programs tend to work best when the products being sold are more expensive.

Put simply, high-ticket items provide a better incentive for the intermediary, and the financial impact of the referral arrangement for both parties is much easier to estimate and track.

3. Personalization Based on Data Sharing

Finally, in many B2B2C partnerships, data sharing is one of the most important and valuable components of the relationship.

This is primarily because it allows businesses to gather and analyze consumer insights to create more personalized experiences, ensuring both a customer’s immediate satisfaction and making it easier to market similar products to them in the future.

For example, if I run an ecommerce platform that hosts and sells a company’s products, evaluating data related to that company’s consumer base will tell me more about who they are and what they like.

I can then use this information to offer those consumers additional products that align with their past purchases, behaviors, and preferences.

Best for: Businesses across industries that have advanced data management capabilities and processes. Personalization is an excellent tool, but there are certain instances in which data sharing is not a part of the B2B2C marketing partnership, or in which a business may not have the level of digital maturity or marketing software needed to make sufficient use of consumer data.

B2B2C marketing is a versatile solution.

The main thing I’ve learned from this post — and I hope you have too — is that B2B2C marketing is an incredibly diverse business model. It can take on virtually limitless forms and be implemented via a wide range of strategies.

The bottom line is that B2B2C marketing is a versatile solution for addressing a variety of needs. While the specific way it’s implemented will depend on both the businesses’ capabilities and what they’re looking to accomplish, it definitely has something to offer companies at all stages of their journey.

New Product Development Process: Everything You Need to Know

If you need a refresher — or a first-time lesson — on the new product development process, you’ve come to the right place.

In trying to understand for myself how to generate a new idea and bring it to market, I found so much vague advice scattered around that I decided to reach out to product development pros to round up their tips for success.

And with a cache of information in hand, the path to propelling a product from idea to launch got much clearer.

The first major lesson I learned from the pros is that whether you’re a small business owner developing your first idea or a successful company itching to open a new market, new product development is a long and winding road.

And that’s exactly why you need a strategic process with step-by-step guidance — like the one I’m about to describe — to move the vision from your mind into the real world, where it can be picked up and purchased by the right people.

In this guide, I’ll walk you through the steps, how to implement them, and what mistakes to sidestep. Plus, I’ll dive into some real-world examples of new product development and the take-home lessons I learned from studying their successes and failures.

Table of Contents

What is product development?
When do you need an NPD process?
Who should be involved in the new product development process?
What is the new product development process?
Examples of New Product Development
From Brainstorming To Reality

What is product development?

Before we get too deep into this, let’s define “product development.”

The easiest way to think of it is like a lifecycle. It’s the journey of creating a product, from its conception to its release into the market, and even beyond, as you measure its success.

New product development (NPD), then, is the journey of an entirely new concept onto the market. This is different from improving an existing product or building a product on an idea that’s already proven successful.

In either case, the goal of product development is finding solutions to meet customer needs.

When do you need an NPD process?

Any time you’re developing a new product, you’ll need a stable and strategic process in place to organize your workflow and teams and, ultimately, to help ensure success.

This way, you can break down tasks into parts, make sure you don’t miss any key steps, and collaborate across teams so that all the expertise you have at your fingertips doesn’t go to waste.

And it doesn’t matter if the product you’re creating is a physical object or designed for ecommerce, as the process is largely the same.

It involves identifying a market need, building out a concept, designing a mockup, and launching a product — with lots and lots of research and iteration at every stage along the way.

This is why one of the key pieces of advice I heard from the people on the ground was to gather all your teams and get them working together as early in the process as possible.

Who should be involved in the new product development process?

So, exactly who should you tap for collaboration? It will depend on the product you’re creating and the size of your outfit, but in general, you’ll want to include marketing, design, engineering, manufacturing, development, and sales teams.

In addition, you’ll likely need a product manager to lead the whole NPD process and oversee tasks across teams. And if the project is big, you may also want to bring a project manager on board for goal tracking.

“I get all relevant teams involved right from day one, starting from development all the way to marketing,” John Russo, a VP of healthcare solutions at OSP, tells me. This can help you avoid a breakdown in communication later down the line.

Plus, “siloed teams hinder innovation,” Simon Lee, CEO of Glance, adds. “When we built our first app, I brought in a marketing expert early on to help shape user personas and messaging.” This type of collaboration can go a long way in developing products that resonate better with users.

The thing to keep in mind is that building a new product is not only a strategic endeavor — it’s also a creative one. And so, that’s the kind of collaborative team you’ll want to promote before you even begin.

Lastly, you’ll need to involve potential users at every stage of the process. Since users are at the heart of NPD, their feedback can make or break your product’s success.

What is the new product development process?

As I discovered from the experts, there can be a lot of variation in how the new product development process is carried out, depending on your industry, company size, and product.

But, that being said, every company — big or small — goes through seven essential stages to develop a new product.

If you stick to the steps below, and learn from the ups and downs of people who have been through this before, you can rest assured you’ll be on the right track.

Although, as I found out, the NPD track is a bumpy one. Hiccups will certainly arise — but that’s just a part of the process.

Remember, while product development can be a lengthy process that requires iteration, it’s all done to ensure that your product is the best it can be before it hits the market and reaches your customers. The point is to solve their needs in the best possible way, and that’s what this process will help you do.

And now, let’s discuss the different stages of the new product development process.

1. Idea Generation

The new product development process begins with idea generation, where you brainstorm an idea (or ideas) that will help you solve a customer problem in a new and innovative way.

As you’re coming up with ideas that will help you solve customer needs, it’s important to have a robust understanding of your target market and the pain points they have that you want to solve.

But how do you get to know your target market and its pain points? This is the question I posed to the pros, and they had all sorts of advice.

“Social listening,” says Michael Nemeroff, the CEO and co-founder of RushOrderTees, “is a great jumping-off point if you’re getting into NPD and don’t know where to start.” This is the practice of using social media conversations as data to see what’s being said about your company and the competition online.

“You get to listen in on what’s working and not working for customers in the current market so you can improve and differentiate new offerings,” says Nemeroff.

John Russo has another tactic. “I often drive brainstorming sessions through analysis of emerging trends, customer feedback, and technological advancements. The key here is ideation from the user's perspective — what problem is it that they want to solve?”

“Immerse yourself in customer environments,” Simon Lee advises me. “Spend time where your users live or work. For instance, while developing a productivity app, I attended local coworking spaces to observe behaviors and interactions.”

And that firsthand observation revealed a critical need for a new tool.

The important point here is that you can’t ideate in a vacuum. Even if you’re just tossing out ideas, you’ll still need a little bit of research to get you started.

2. Research

Once you’ve developed and selected a product idea or two, the next step is to conduct more in-depth research to flesh out those ideas. There are various steps you can take to do this, like:

Market research to understand the current sentiment in your industry and if there are any holes that your product will fit into, or if there will be demand for it.
Competitor analysis to understand if customers think there are things your competitors‘ products or services lack that you can incorporate into your product to better fit your target market’s needs.

During this stage, you should also get more feedback from customers about what they think of your ideas before coming up with a final definition for your product.

This type of validation is to ensure you don’t waste time, money, or energy on a product that won’t sell.

One of the best ways to get this feedback from existing customers is through surveys, where you can easily and quickly collect information.

A high-quality tool like Lucky Orange can help you create these surveys, and with it, you can ask multiple-choice questions about types of products they may be interested in, or open-ended questions that give you more insight into customer opinions.

This stage will likely require a bit of iteration because your research may tell you that you need to refine your original ideas and adjust your research scope before moving on to the next stage.

When I asked Rob Stevenson, founder of BackupVault, about his approach, he replied, “In my first NPD experience, I realized how easy it is to get excited about the product features without fully grasping the problem you’re trying to solve.”

While his team was initially focused on adding tons of features, “what users really needed was simplicity and reliability.”

Following this shift in focus, users’ needs guided their decisions at every stage.

3. Planning

The third stage is planning, where you clarify your final product idea/definition and begin coming up with plans to bring it to life. This step can look like a blueprint or sketch, where you map out all the details.

For example, if you’re creating a physical product, here is where you’ll need to source the necessary materials or find production partners that will assist in manufacturing.

Planning also involves solidifying your marketing strategy to help you effectively market your product when it’s completed. What pricing models make sense? What will customers pay?

Now is the time for the nitty gritty. But you can make this step easier by automating your marketing efforts with HubSpot’s Marketing Hub to unify customer insights and help you generate leads.

Still, having a plan doesn’t mean it’s carved in stone.

“Build flexibility into your development process,” Rob Stevenson tells me. “Being rigid with your roadmap can actually limit the potential of your product.”

4. Prototyping

The prototyping phase is when you come up with a sample product to demonstrate what will be created during mass production.This is when your idea goes from 2D to 3D.

Your prototype — which is a very rough sample — helps you to identify risks before you move into full production.

It’s also something tangible that you can show to stakeholders and potential users to get them on board, as Nemeroff pointed out to me. Even if you have a small team, “learn CAD and 3D print your prototype,” he recommends.

This prototype will later become your minimum viable product (MVP), which is the most basic version of your tool that’s ready for release. Prototyping will help you get a sense of how your product functions and identify any areas that need to be improved before you build a costlier product.

You may make multiple prototypes and go back and forth between this stage and the testing stage before you have a finalized prototype.

“The biggest lesson I learned in the NPD process is to have a systematic approach to prototyping,” product developer Gavin Yi recounts from his experience as CEO of Yijin Hardware.

“Prototyping is the time to experiment, but some product developers get carried away and spend too much time at this stage. Prototypes should not focus on perfecting the design but on testing assumptions and validating solutions.”

5. Testing

Before launching your product you need to test it to ensure it will work as advertised and effectively solve your customer needs. So, during this stage, you’ll share your prototypes with target audiences and ask for actionable feedback on how the product works.

Essentially, you want your product to be used in situations that are similar to real-world use cases so you know exactly what works and what doesn’t. Sometimes the results of your testing will require you to go back and make changes to your prototype, as mentioned above.

“One thing I learned was that moving too fast can sometimes mean cutting corners, which can hurt in the long run,” Rob Stevenson notes. When you release early versions of your product to gather feedback, make sure you maintain a certain level of quality.

“If the product is buggy or doesn’t deliver as promised, early adopters won’t come back. Striking a balance between speed and quality was something we had to master quickly,” he tells me.

Once you feel as though your prototype is finished and ready to solve your customer needs, you’ll begin production.

6. Production

This stage involves creating the final product that will be commercialized once completed. You’ll use the insights gained from testing your prototypes to make final touches to your product and begin mass production.

Depending on your type of business, you’ll likely have a different process for production. For example, if you’re a SaaS business, your internal software development or programming teams will likely work to finalize code.

If you create a physical product, you may outsource labor for certain components and assemble final products in your warehouse.

No matter your process, your planning stage should have helped you identify how the production stage will go.

For small businesses especially, Brooke Webber, head of marketing at Ninja Patches, advises me that it’s essential to lock in the manufacturing details early to avoid delays. The smallest changes at this stage can increase production time. Modifying “even a simple stitch,” she says, can throw off your schedule.

7. Commercialization

The final stage of your new product development process is commercialization, where you introduce your products to market. This is the culmination of your brainstorming, research, and iteration, where your audiences can finally make use of what you created.

You’ll enact your marketing plans to make your audiences aware of your new product, and initiate campaigns that will entice them to become customers.

Although this is the final stage, many businesses launch their products and, over time, return to make improvements to their products based on customer feedback and market changes to ensure they’re always providing the best possible customer experience.

“Embrace the MVP mindset,” Lee advises. “Focus on launching the simplest version of your product that solves a core problem.” This way, consistent iteration is baked into the process.

And it’s worth remembering that sometimes the market just isn’t ready for a new idea. Russo tells me that “a very common pitfall is under- or overestimation of market readiness.” Don’t be discouraged. It might just be the wrong time for your new and awesome idea.

Examples of New Product Development

My favorite approach to understanding expert advice in practice is to look at real-world examples. And case studies – especially when they’re familiar – are the perfect way to discover patterns and learn from the past.

To that end, I gathered up three classic cases of products that either succeeded or failed on the market in an epic way. And while not every product is going to be such a headliner, the take-home lessons from these cases can be applied to any NPD process (even yours).

Amazon Kindle

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While Amazon didn’t produce the first e-reader, it was the first to succeed massively. In 2007, the year the first Kindle was launched, Amazon was an online bookseller — not a hardware developer. Yet, it knew its target market (readers) and that reading online was an uncomfortable experience.

Its goal was to make an e-reader that was thin, light, and comfortable to hold (like paper). It embedded a dictionary, search function, and built-in wireless — a unique feature at the time — which allowed almost 90,000 titles to become available instantly.

The new device was like reading a book, but with thousands of titles.

The first Kindle sold out in five and a half hours after its release. But even with the huge success, Amazon continued to iterate the product. Each package included a thank you note with an email address to submit feedback. And from that, it later added new features that users wanted, solidifying the Kindle’s place in the market.

My Key Takeaways: Know your users’ pain points in and out. Develop a product that addresses these pain points and only add features that build toward the specific solution. And, even if you’re successful, you still have to iterate and listen to feedback to continue that success into the future.

Nintendo Entertainment System (NES)

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Nintendo has had tons of products over the years, but the 1983 NES changed the face of video gaming by pivoting its design, marketing, and overall concept to enter the U.S. market.

In the early 80s, U.S. consumers were oversaturated with video games, which made the prospect of marketing a new gaming console difficult. To counter this, Nintendo turned away from video game marketing and called its new product an “entertainment system.”

Also, since household computing was on the rise and all the rage, it incorporated this trend with a gray, block-like design (reflecting early home computers) and cartridges that were inserted into the console much like VHS tapes into a VCR (technology that was both familiar and state of the art then).

Each time that it tested its product with consumers, Nintendo adapted its concept to get closer to the final product before launch, which eventually marked its place in history.

My Key Takeaways: Flexibility and adaptation to the market can make or break a product. Understand not just what users need, but also how to approach the larger market to see where your product fits. Be willing to adjust at all levels, from concept and design to branding and market approach.

Google Glass

Image Source

Successes are not the only (or maybe even the best) way to learn by example. Sometimes looking at a massive failure can teach a meaningful lesson.

In the case of Google — with its much-hyped smart glasses that failed to catch on with consumers after multiple re-releases — there were problems with design, technology, and marketing from the outset.

Google Glass went on and off the market various times from 2013 to 2023, when the product was finally scrapped for good.

Worn on the face like any pair of glasses, the technology offered a built-in camera and hands-free computing, among other features, like the ability to look at an object and identify it through an automatic Google search.

But problems started as soon as the prototype was released to a small, high-profile group with the intent to drum up press. Early on, users noted short battery life, poor-quality photos, and discomfort in wearing the product.

Plus, without proper marketing, there was a storm of privacy concerns around the product’s functions. Between the tech and design problems, the high price tag, and a lack of public understanding about the purpose, users weren’t ready to buy.

My Key Takeaways: Understand your users’ core needs and don’t rely on assumptions. The coolest product in the world won’t sell if it doesn’t solve a real-world problem.

From Brainstorming To Reality

So now you’re ready to get started. Following the new product development process will allow you to bring your brainstorming ideas to fruition and create a product or service that solves a customer need.

And if you find success, you’ll have established a valuable strategy to replicate that will help you continuously innovate and create new products to give customers the delightful experiences they desire.

Editor's note: This post was originally published in December 2021 and has been updated for comprehensiveness.

Using Multimodal AI models For Your Applications (Part 3)

In this third and final part of a three-part series, we’re taking a more streamlined approach to an application that supports vision-language (VLM) and text-to-speech (TTS). This time, we’ll use different models that are designed for all three modalities — images or videos, text, and audio( including speech-to-text) — in one model. These “any-to-any” models make things easier by allowing us to avoid switching between models.

Specifically, we’ll focus on two powerful models: Reka and Gemini 1.5 Pro.

Both models take things to the next level compared to the tools we used earlier. They eliminate the need for separate speech recognition models, providing a unified solution for multimodal tasks. With this in mind, our goal in this article is to explore how Reka and Gemini simplify building advanced applications that handle images, text, and audio all at once.

Overview Of Multimodal AI Models

The architecture of multimodal models has evolved to enable seamless handling of various inputs, including text, images, and audio, among others. Traditional models often require separate components for each modality, but recent advancements in “any-to-any” models like Next-GPT or 4M allow developers to build systems that process multiple modalities within a unified architecture.

Gato, for instance, utilizes a 1.2 billion parameter decoder-only transformer architecture with 24 layers, embedding sizes of 2048 and a hidden size of 8196 in its feed-forward layers. This structure is optimized for general tasks across various inputs, but it still relies on extensive task-specific fine-tuning.

GPT-4o, on the other hand, takes a different approach with training on multiple media types within a single architecture. This means it’s a single model trained to handle a variety of inputs (e.g., text, images, code) without the need for separate systems for each. This training method allows for smoother task-switching and better generalization across tasks.

Similarly, CoDi employs a multistage training scheme to handle a linear number of tasks while supporting input-output combinations across different modalities. CoDi’s architecture builds a shared multimodal space, enabling synchronized generation for intertwined modalities like video and audio, making it ideal for more dynamic multimedia tasks.

Most “any-to-any” models, including the ones we’ve discussed, rely on a few key concepts to handle different tasks and inputs smoothly:

Shared representation space
These models convert different types of inputs — text, images, audio — into a common feature space. Text is encoded into vectors, images into feature maps, and audio into spectrograms or embeddings. This shared space allows the model to process various inputs in a unified way.
Attention mechanisms
Attention layers help the model focus on the most relevant parts of each input, whether it’s understanding the text, generating captions from images, or interpreting audio.
Cross-modal interaction
In many models, inputs from one modality (e.g., text) can guide the generation or interpretation of another modality (e.g., images), allowing for more integrated and cohesive outputs.
Pre-training and fine-tuning
Models are typically pre-trained on large datasets across different types of data and then fine-tuned for specific tasks, enhancing their performance in real-world applications.

Reka Models

Reka is an AI research company that helps developers build powerful applications by offering models for a range of tasks. These tasks include generating text from videos and images, translating speech, and answering complex questions from long multimodal documents. Reka’s models can even write and execute code, providing flexible, real-world solutions for developers.

These are the three main models Reka offers:

Reka Core
A 67-billion-parameter multimodal language model designed for complex tasks. It supports inputs like images, videos, and texts while excelling in advanced reasoning and coding.
Reka Flash
A faster model with a 21-billion-parameter, designed for flexibility and rapid performance in multimodal settings.
Reka Edge (PDF)
A smaller 7-billion-parameter model was built for on-device and low-latency applications, making it efficient for local use and local or latency-sensitive applications.

Reka’s models can be fine-tuned and deployed securely, whether on the cloud, on-premises, or even on-device. Let’s start by testing Reka’s capabilities directly through its playground. This allows us to experiment with its multimodal features without writing any code, providing a hands-on way to see how the models handle various tasks, such as image and video comprehension.

Alright, we’ll kick things off by uploading an image of a diagram outline of the PaliGemma architecture and ask Reka for a detailed explanation.

Can you provide a more detailed explanation of this image?

Here’s what we get from Reka Core:

“This image is a schematic representation of a machine-learning model named PaliGemma. The model appears to be designed for multimodal input, combining both image and text data. At the top, there are two input sources: ‘Image Input’ and ‘Text Input’. The image input is processed by a ‘SigLIP Image Encoder’, which likely stands for a specific type of image encoding technique. The output of this encoder is then subjected to a ‘Linear Projection’, which is a common step in machine learning to transform data into a lower-dimensional space. The text input is directly fed into the model. Both the projected image data and the text input are then concatenated into ‘Concatenated Tokens’, which are then processed by a component labeled ‘Gemma’. The final output of the model is ‘Text Output’, which suggests that the model is designed to generate text based on the input data.”

It’s a clear and detailed breakdown of the PaliGemma architecture. The model accurately identifies image and text inputs, the SigLIP image encoder, and the linear projection step. It also grasps how the image and text inputs are combined and processed to generate text output. I should admit that the response is quite neat, offering a solid explanation of the architecture.

Let’s try a video input instead. We’ll upload the video about Genny, a software, and ask a question to see how well Reka Core handles video comprehension.

What is this video about?

“This video is a screen recording of a group of friends discussing their plans for the weekend.”

Well, it’s not a good answer compared to what LLaVA gave us in the previous article. Now let’s try a longer video, but with the Reka Flash model. The video is about a TTS model called Parler TTS. Instead of asking what the video is about, let’s prompt it like this:

I’m an AI developer, and I’m not sure how this TTS model can help me in my projects. Can you explain how I can use it or what it’s useful for?

Reka Flash generates a solid answer this time:

“Of course! This TTS (Text-to-Speech) model can be incredibly useful for developers, especially those working on projects that involve creating more human-like interactions or providing audio feedback to users. Here are some ways you can leverage this TTS model in your projects:

Accessibility: TTS models can greatly enhance the accessibility of your applications for users with visual impairments or reading difficulties. By providing spoken feedback or narrating content, you can make your applications more inclusive

Voice Assistants: You can integrate this TTS model into voice assistants or chatbots, allowing them to generate more natural-sounding responses. This can improve user experience and make interactions with your bots more engaging.

Multimedia Applications: This TTS model can be used in multimedia applications, such as e-books, educational tools, or games, to provide spoken narration or instructions. This can make the content more engaging and easier to understand.

Audio Notifications: You can use the TTS model to generate audio notifications for your applications, providing users with spoken alerts or reminders. This can be particularly useful for users who may not always have their screens visible.

Language Learning: The TTS model can be used in language learning applications to provide users with correct pronunciation and intonation. It can also generate spoken feedback or narrate lessons, making the learning process more immersive.

Audio Books: You can use the TTS model to generate audio books, allowing users to listen to written content instead of reading it. This can be especially helpful for users who prefer auditory learning or have difficulty reading.

Explainer Videos: The TTS model can be used to generate voiceovers for explainer videos, providing users with spoken narration that explains the content on the screen. This can make the content more engaging and easier to understand.

Audio Feedback: You can use the TTS model to generate audio feedback for users in your applications, such as confirming actions, providing instructions, or giving feedback on their performance. This can make the interactions more natural and intuitive.

In summary, the TTS model can be a valuable tool for developers looking to create more human-like interactions, improve accessibility, and enhance the user experience in various applications.”

It’s a good answer that’s informative and quite practical for developers. Let’s compare what happens when we try the Reka Edge model with a PDF input titled “Meta AI — Responsible Use Guide” (PDF).

As an AI developer, how can I ensure that I am following the responsible AI guidelines outlined in this document?

“To ensure that your use of AI aligns with the principles outlined in this guide, you can follow these steps and best practices:

Familiarize yourself with the principles of responsible AI, such as transparency, accountability, and user empowerment, as outlined in the guide.

Understand the potential impacts of AI on users and society, and be aware of the risks and challenges associated with the development and deployment of AI systems.

Embrace an iterative model-development mindset, continuously striving for improvement and learning from feedback and errors.

Build a responsible AI ecosystem by working with partners, experts, and communities to develop and share best practices, tools, and benchmarking resources.

Follow the guidelines and best practices outlined in the guide for each stage of model development, from data collection and preparation to fine-tuning, evaluation, and deployment.

Consider the specific use case and requirements for your AI system, and tailor your approach accordingly.

Regularly monitor and evaluate the performance and safety of your AI system and make adjustments as needed to ensure it aligns with the principles outlined in the guide.

Be transparent and accountable in your interactions with users and stakeholders, and be open to feedback and suggestions for improvement.

Stay informed about the latest developments and research in the field of AI, and be prepared to adapt your approach as needed to address new challenges and opportunities.

Follow the specific guidelines and best practices outlined in the addendum for Code Llama, such as defining content policies, evaluating and benchmarking models, and addressing input- and output-level risks.”

Reka Edge’s answer is quite thorough and detailed, too!

If you want to dive into coding, start by creating a Reka account and getting an API key. Then you can follow along with this notebook. Try out their Python SDK, and make sure to explore the different models available. It’s a great way to see how these tools work under the hood!

Gemini Models

Gemini 1.5, developed by Google DeepMind, is designed to handle complex tasks efficiently, thanks to the new Mixture-of-Experts (MoE) system. MoE is like packing several specialized models inside one big model. Instead of using the whole network for every task, Gemini 1.5 activates only the parts (or what they call “experts”) that are most relevant. This means Gemini 1.5 can tackle complex tasks with less processing power than a typical monolithic model.

We can explore Gemini’s features in Google AI Studio since it’s already baked right in. We’ll begin by uploading the following image illustrating VLM capabilities.

We’ll ask Gemini to analyze the image and extract details or concepts:

Explain this image. What are the specific details or concepts it represents?

“The image is a flowchart illustrating different types of image understanding tasks with a Vision Language Model.

Object Localization: This task aims to identify the precise location of objects within an image. The example question asks, “Is one cat behind another?”

Zero-shot Segmentation: This task involves segmenting an image into different regions based on a given label, even if the model has never seen that specific label before. The example question asks to segment “striped cat.”

Zero-shot Visual QA: This task requires answering questions about an image, even if the model has not been specifically trained to answer that type of question. The example question asks, “What is the breed of these cats?”

One-shot Learning with Instructions: This task involves providing the model with a single example and instruction to learn a new concept and apply it to other images. The example question asks, “Striped cats are called tabby cats. What is the breed of the cats in the image?”

Well, Gemini nailed it — it clearly understood the image and recognized the tasks a VLM handles. This is exactly what you’d expect from a model designed for advanced image analysis.

Now, we’ll upload another image — this time of an Italian dish — and ask Gemini if it can recognize the dishes and list the ingredients needed for them. This type of “food recognition task” will help us test its ability to identify foods and ingredients.

List the different dishes in this image, also from which country, and give me the ingredients I need to make them.

“The image shows an Italian feast with the following dishes:

Seafood Stew: A rich and flavorful stew with seafood like clams, mussels, shrimp, fish, and vegetables in a tomato broth.

Spaghetti with Tomato Sauce: Classic spaghetti pasta tossed in a simple yet flavorful tomato sauce.

Meatballs in Tomato Sauce: Tender and juicy meatballs simmered in a rich tomato sauce.

Lasagna: Layered pasta with meat sauce, cheese, and tomato sauce.

Side Salad: A refreshing side salad with mixed greens, tomatoes, and other vegetables.

Garlic Bread: Toasted bread slices rubbed with garlic and olive oil.

Marinara Sauce: A simple tomato-based sauce.

This is a typical Italian meal with various dishes showcasing the flavors of Italian cuisine.

As for the ingredients, you’ll need tomatoes for many of these dishes, specifically for the sauces and the side salad.”

Well, the model did a good job recognizing the dishes, but it also didn’t give me all the necessary ingredients. Let’s see how it does with videos instead, using the same video we used earlier with the Reka models. This time, the task will focus on action recognition.

What is the purpose of this video, and what key actions or processes are being demonstrated?

“The video is a tutorial about the importance of friendship and how it can impact our lives. It demonstrates the use of a video editing software called “Genmy” to create a video and add text subtitles. The video creator is using Genmy to:

Record their voice: This is seen at the top of the screen with the mic icon.

Add text to speech: You see the “Text to Speech” option, which is likely being used to generate subtitles or captions for the video.

Edit the timeline: They’re working with a video timeline, adding and arranging different elements.

Add voice-over: The speaker is adding commentary to the video.

Create a visually appealing presentation: They’re using a combination of video footage, text, and voice-over to create an engaging tutorial.”

Well, Gemini gave a clear breakdown of the video, identifying it as a tutorial demonstrating the Genmy video editing software to highlight how it’s used for recording voice, adding text-to-speech, editing video timelines, and allowing voice-over. Impressive!

Let’s upload one more video, the same one we used for Reka about the Parler TTS model, and ask Gemini to analyze and summarize the contents.

Summarize this video and explain how the contents might be relevant or helpful for software engineers.

“This video showcases different voice samples generated by a text-to-speech (TTS) system called “Parler-TTS.” The video highlights various voice characteristics like gender, pace, pitch, and even the simulated environment. For software engineers, this video demonstrates the progress made in TTS technology. These are some insights:

Voice Variety: The video shows that Parler-TTS can create diverse voices, potentially useful for applications needing different personas or tones.

Fine-grained Control: The video emphasizes the ability to control voice parameters like pace and pitch, showcasing the potential for customizability.

Quality and Naturalness: The video focuses on the quality of the generated speech, demonstrating the advancements made in speech synthesis, which is crucial for user experience.”

Nicely done! I can go with that answer. Gemini explains adjusting voice settings, like pitch and speed, and how having different voices can be useful. Gemini also emphasizes the importance of natural, high-quality speech, which is handy for developers working with TTS systems!

Alright, for coding, you can grab the code from Google AI Studio by clicking the Get Code button. You can choose between formatting the code in Python, Swift, and Java, among other languages.

Conclusion

Both Reka and Gemini are strong multimodal models for AI applications, but there are key differences between them to consider. Here’s a table that breaks those down:

Feature	Reka	Gemini 1.5
Multimodal Capabilities	Image, video, and text processing	Image, video, text, with extended token context
Efficiency	Optimized for multimodal tasks	Built with MoE for efficiency
Context Window	Standard token window	Up to two million tokens (with Flash variant)
Architecture	Focused on multimodal task flow	MoE improves specialization
Training/Serving	High performance with efficient model switching	More efficient training with MoE architecture
Deployment	Supports on-device deployment	Primarily cloud-based, with Vertex AI integration
Use Cases	Interactive apps, edge deployment	Suited for large-scale, long-context applications
Languages Supported	Multiple languages	Supports many languages with long context windows

Reka stands out for on-device deployment, which is super useful for apps requiring offline capabilities or low-latency processing.

On the other hand, Gemini 1.5 Pro shines with its long context windows, making it a great option for handling large documents or complex queries in the cloud.

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30+ Key Logo Design Trends for 2025

Need a new logo? Whether you’re starting from scratch or just planning a tweak to a current mark, understanding shifts in logo design trends can help you create a design with a modern touch.

The theme in logo design is to create something simple and distinctive. With so many new websites and brands and companies coming online almost every day, it’s no wonder that logos are trending toward designs that stand out.

Here’s a look at a few logo design trends, and how you can make them work for you (and while you’re at it, be sure to look through our full guide on how to design a logo!)

Bold Minimalism

One of the key logo design trends that’s been growing in popularity is the bold minimalist logo designs. Over the past couple of years, we saw many brands transition from colorful, creative logos with shapes and intricate details into extremely minimalist designs. And this trend doesn’t appear to be going away anytime soon.

In 2024, we saw several brands adopt this new bold minimalist logo design trend as well. The new Lamborghini and PayPal logos were the most noticeable of them all. Lamborghini switched to a highly minimalist logo after 20 years, ditching its iconic gold-colored symbol. PayPal also removed all of its colors and replaced the instantly recognizable lettermark with a more simplistic design. We will likely see more brand follow this trend in the coming months.

Here’s how to make the most out of this logo design trend:

Use fewer colors, shapes, and details in your designs
Utilize thin lines and geometric shapes
Use simple typography with fewer decorative elements

Responsive Logos

One of the main reasons why brands have been adopting the bold minimalism trend is to make their logos responsive and flexible. Unlike the good old days, logos now need to be dynamic enough to be displayed flawlessly across multiple platforms and mediums, including the many different sizes of device screens.

Crafting responsive logos is the answer to this process as it allows brands to create multiple variations of their logos for different platforms. As a result, every reputable and popular brand now has responsive logo designs.

This is a trend that you should study carefully as it will be an important part of your future logo design projects. From now on, every logo you design will need to be responsive!

Here’s how to make the most out of this logo design trend:

Craft minimal logos that can be easily displayed across different platforms
Design multiple variants of a logo suitable for each platform
Design with scalability in mind

Negative Space Designs

The negative space logo design is nothing new. They have been around for decades. But it seems the trend is resurfacing in a new way.

More than a few of the recent logo remakes featured negative space designs. The new Reddit and Bolt logos are the most noticeable pair in the bunch. Many other brands like Propel and Indiana also switched from classic logo designs to more minimal logos with negative space elements.

Negative space logos spark creativity and offer a refreshingly unique look for brands. So this is a logo trend we’re excited to see grow throughout this year.

How to make the most out of this logo design trend:

Find clever ways to use negative space to create symbols and shapes
Use fonts that with dynamic letterforms

Chaotic Typography

If the text on a design is unreadable, we usually consider it a bad design. But that seems to be changing. This latest logo design trend utilizes chaotic, edgy, and basically unreadable text to create a bold look for brands.

The example above comes from a reputable design studio that has designed the chaotic logo for a fashion brand called Queen of Chaos, which specializes in designing uniquely weird apparel for celebrities like Lady Gaga.

This chaotic typography logo approach would fit perfectly well for brands and companies that seek to create an edgy look.

How to make the most out of this logo design trend:

Go crazy with typography and add your own decorative elements
Use weird and edgy-looking fonts
Use your imagination!

Illustrative Logos

Even though most of the latest trends are all about minimalism and simplicity, we always love to see logos with intricate details and stylish designs. This new logo trend will keep that trend alive and strong for a long time.

It’s great seeing illustrative logos making a comeback. These logos see more complex designs that feature detailed illustrations. They also use creative design trends such as Art Deco and vintage geometric designs to make each logo look much more attractive.

This logo trend is quite popular among luxury and high-end brands, especially in hotel, jewelry, and fashion brands.

Here’s how to make the most out of this logo design trend:

Incorporate your line art illustrations into your logo designs
Use thin lines, shapes, and outline fonts
Utilize gold, black, silver, and other colors to give a luxury vibe to the logo

Dark Color Tones

Dark color schemes are making a comeback! There have been many different logo design trends over the past few years with different styles of color themes like flat colors, pastel colors, material design, and more. And we’ve circled back to dark and bright colors once again.

In 2023, we saw several different brands redesigning their logos by changing the color tones. The most notable logo redesign came from Facebook. The company casually changed the color by making the blue color much darker. It was a subtle change but very noticeable.

Pepsi also made rounds in the news with its unexpected brand redesign. Their iconic light blue color was replaced with a much darker blue and with a brighter red. This new redesign came 15 years after its last branding change.

Here’s how to make the most out of this logo design trend:

Consider adjusting the tone of your logo’s existing color
Use darker color tones in your logo designs
Be mindful of the color combinations

Retro 3D Look

If there’s one logo design trend we can never get tired of it’s classic retro designs. While some brands rushed to redesign their logos with modern looks in 2023, we saw several companies take the opposite approach with their logo redesigns.

7Up’s brand-new retro-themed logo redesign was the most noteworthy one to follow this new trend. It featured a classic retro look with elaborate 3D-like lines that highlighted the logo in an entirely new way.

Several other brands also followed this trend, including the iconic Jell-O. The outdated logo was replaced with a retro 3D look.

This new retro 3D logo trend was mostly adopted by much older brands that have been around for many decades. It is the perfect way to evoke emotions through nostalgia.

Here’s how to make the most out of this logo design trend:

Consider using retro color palettes. Find inspiration from classic logo designs from the 1960s and 70s
Add elaborate 3D looks to text and objects
Aim to make logos look more fun with a bit of nostalgia

Single Color Logo Design

The multicolor logo designs appear to be slowly fading away. Except for a few brands, like Google and eBay, many brands are now switching over to single-color logo designs. Even Google has replaced its multicolor logo with a single-color logo on the dark theme version of the homepage.

Channel 4 replaced its multicolor logo with a single-colored logo design in 2023. Several other brands also adopted this new trend in 2023. Including Wise ( previously Transferwise), Fanta, and Minute Maid.

We can expect to see more brands following this trend this year to replace multicolor logos with single-color designs.

Here’s how to make the most out of this logo design trend:

Replace your color palette with a single color that represents the brand
Use brighter or darker color tones to make the logo stand out

Edgy Typographic Logos

While retro logo designs look cool, it’s not suitable for all types of brands. Especially for tech-related brands, going for a cool and edgy look is the ideal approach. At least that was the case for several tech brands that rebranded with new edgy typography logo designs in 2023.

The X (previously Twitter) logo redesign was the most notable one from the bunch. Following Elon Musk’s acquisition, X’s rebranding of Twitter was quite a radical change. And it saw the cute Twitter bird logo being replaced with a more edgy monogram-style typographic logo.

Nokia also introduced a brand redesign featuring an edgy typographic logo with a very stylish look. We’ll probably see more tech brands following this trend this year as well.

Here’s how to make the most out of this logo design trend:

Experiment with edgy and futuristic fonts
Think outside the box and try removing parts of letters to achieve a unique look

Psychedelic Vibes

Typographic logos with psychedelic designs have been trending for a while. We saw a rise in this trend in the past year and it will surely be adopted by more brands this year. And we’re not complaining.

Psychedelic logo designs take inspiration from classic trippy text designs from the 1960s and the 70s. They add a fun and funky look to logo designs to make brands look much more casual and human.

Here’s how to make the most out of this logo design trend:

Use fonts with funky and psychedelic designs
Manipulate letters to make them look more squiggly and trippy
Use retro color palettes with either soft or dark colors

Classic Cartoony Mascots

When it comes to mascot logos, nothing beats the classic vintage mascots from the 1930s brands. Those old cartoony mascot logos still look perfect for many different types of brands. And it’s probably why the trend appears to be making a comeback.

Vintage mascot logos are appropriate for various types of brands from food brands to coffee shops, restaurants, and especially for product packaging. They always immediately stand out from the crowd as well.

Here’s how to make the most out of this logo design trend:

Consider designing the mascot themed around a product of the brand
Find inspiration from classic mascots from the 1930s
Use vintage fonts for typography

Liquid Blobs

Liquid-style logos often fit perfectly with food and drink brands. However, we’ve been seeing various alternate styles of this trend being used by other types of brands as well.

Liquid-like text and blob-like shapes are the key features of this logo design trend and it perfectly serves a brand that focuses on making a casual and friendly appearance.

When used properly, this trend is also suitable for travel and nature-themed brands.

Here’s how to make the most out of this logo design trend:

Use fonts with liquid-style letter designs. Blob, bubble, and psychedelic fonts are ideal
Try to incorporate liquid or blob-style shapes or backdrops to logo icons

Circle Icons

Circles are always a trending element in logo design. There are so many nice qualities about a circle that make it a popular option from the shape and meanings to being able to create an icon that works anywhere.

Here, we are seeing more circle icons that can work with text elements or alone to highlight a logo and brand. The thing that stands out here is that text elements are not inside the circle.

Here’s how to make the most out of this logo design trend:

Create a circle icon that’s interesting and works well at a small or large size.
Consider line art, such as There’s More to Life, above.
Place text outside the circle for added flexibility.

Sideways Orientation

Switch up your brand or add an element of whimsy with a sideways orientation for a logo design.

Each of the examples here did it a different way, but all work well as part of this logo design trend. Dictionary of Online Behavior uses a logo design that seems to shrink away from you and isn’t straight-on, Echt uses a logotype that reads from bottom to top on one side, and Adidas Metaverse takes the traditional three-stripes logo and rotates it 90 degrees.

Each different variation is an option if you want to explore logo styles that have a sideways orientation.

Here’s how to make the most out of this logo design trend:

Play with type that rotates if you have short words. This can be a lot more tricky for longer brand names.
Turn a common mark sideways for an alternative brand style.
Consider a subtle twist; you don’t have to completely turn the logo.

Outlined Typefaces

Outline typefaces have been trending in all facets of graphic design for some time and are starting to show up in logos as well. Outlined typefaces can be interesting, help create contrast between text elements, and even provide a lighter feel for a logo.

On the other hand, outline styles can almost get lost if not weighted properly in context with the rest of the design, so it is important to use a typeface that can carry the logo.

Outlined typefaces can serve as the lettering for an entire logo, such as Shannon (above), or for part of the brand name, such as GolfSpace (above). Both options can look great and provide visual focus.

Here’s how to make the most out of this logo design trend:

Pick an outline font that has enough weight for the overall brand feel.
Use an outline font for a simple brand icon, such as Felipe Castro (above).
Consider the trendiness of this style. If outline fonts fade out of fashion, your logo could look dated and it’s not something you want to redesign regularly in most cases.

Exaggerated Spacing

In almost every industry, there’s a conversation around elements that disrupt and bring attention to different things. That’s what this logo design trend does. Exaggerated spacing – between words, between letters, or between lines of text – makes you look a little longer at the logo design.

There are pros and cons to this style of spacing. While it can look extremely interesting, it can be more difficult to read, putting a greater cognitive load on the user. The exaggerated spacing provides a certain feel that’s lighter but can take up more space for the overall logo. This style has a great deal of variability so you can make it your own, but it can be difficult to use with some other design elements because it is a powerful element on its own.

Use exaggerated spacing in a logo to help create a pause between words or phrases in the name, like a natural speech pattern. It can actually help convey meaning for your brand.

Here’s how to make the most out of this logo design trend:

Try to contain the text elements in a container so that they don’t get confused with other parts of the design.
Stick to a single typeface if you can to help hold it together.
Play with variations of spacing. Does it work better vertically or horizontally? Are the words or phrases understandable?

Custom or Experimental Typefaces

Custom or experimental typefaces can be a lot of fun and really show the personality of a brand, making them a popular – and trendy – design choice for logos.

What’s nice about these styles is that everything about your logo design will feel uniquely custom and yours. The downside is that they can take some time to develop. (But what brand doesn’t take some time to get off the ground?)

Here’s how to make the most out of this logo design trend:

Determine how custom you want your logo font to be. Do you want a truly custom typeface or is a more commercially-available experimental design viable?
Weigh the pros and cons of typeface features such as color or animation to determine what your needs are. A color font, for example, isn’t the best choice if you foresee needing a one-color logo regularly.
Ask for exclusivity if you are determined to have something that’s 100% yours and unique. You can come to an agreement with a type designer about licensing and usage rights.

Simple Logotypes

It’s hard to beat the innate beauty of a simple logotype. These logos use beautiful lettering to pull together brand identity and it’s something that we are seeing a lot more of.

You can almost think of a logotype as a gateway logo for a startup or new company. For many, this is the first envisioning of a brand mark and company name before the business gets truly established. Some of these logos last forever while others eventually evolve.

One of the reasons this trend is so popular may be because of the number of freelancers, entrepreneurs, and small businesses popping up everywhere.

Here’s how to make the most out of this logo design trend:

Don’t assume that a logotype is easier, cheaper, or faster to create than other types of logos. Working with just the right lettering can be a challenge.
Don’t get hung up on a font or style until you see it with your brand name in print. Some fonts look great and then fall flat due to certain character combinations. Type out the words you plan to use in the font style of your choosing as a starting point. If you hate it, move on.
The more elaborate the typeface, the less you need other embellishments. Aim for a logotype that represents the simplicity or complexity and mood and voice of your brand.

Logos That Look Like Buttons

Logos for website design can be a funny thing. One of the trends we are seeing is logos that have a button-style look. This includes square outlining or elements that look click- or tappable.

What’s nice about this trend from a usability perspective is that it further enhances the idea that the logo is a home button in the website design. (So, make sure that the logo does include a home click-action.)

The tricky part is to design a logo that still looks like a brand mark with the button style. You’ll want to use a different color or style of button throughout the design to differentiate the two.

Three ways to try it:

Use a ghost or outline style around your logo. This can create the idea of a button and allow the logo to stand on its own as well.
Use a button-like element with another text element for an almost yin and yang effect with contrasting styles in the logo design.
Use a graphic element, such as an icon, that represents something to click. The example above from Data Shield is a solid example with a “play” button next to the company name. It almost demands to be clicked.

Simplified Logos

All the big brands are doing it. And that’s when most big trends start to steamroll.

There’s a shift to simplify logos with easy-to-understand fonts with clean lines and simple imagery. (Or sometimes, no imagery at all.)

Many times, these logos are evolutions of previous versions that result in some simplification, but new designs can start with a simple outline as well.

Here’s how to make the most out of this logo design trend:

Pick a shape or color and stick to this theme.
Develop a design that feels true to your brand, and redesigns should carry the essence of the logo being redeveloped.
Don’t overthink it; simplicity is key.

Gradients

It seems like we just can’t get enough gradients in design projects. Logo design trends are no exception.

Like the trend above, this is another place where big brands are using gradient options in their logos. And while pinks, purples, and oranges are necessarily part of this trend, it is a popular color palette.

What’s nice about gradients is that they add depth to an image. It can be a little tricky with logo designs because of the variance in size for logo usage. The gradient choice has to look good at huge sizes – such as billboards – and for tiny sizes – such as phone app icons.

Design a gradient that’s interesting but not overwhelming to make the most of this trend.

Three ways to try it:

Layer different colors of gradients throughout the logo design for a more elaborate look.
Use a gradient pattern within thick lines to create visual interest.
Create more of a stacked gradient with an ombre effect, but using a monotone color palette.

Animated Logos

Animated logos are starting to become more of a website staple. Many brands are animating existing logos or creating newer, trendier animated options.

What’s great about an animated logo is that it makes you look. Think about common website patterns: There’s often a logo in the top left corner. Do you even look at it anymore?

Animated logos break up the monotony of this design pattern with a motion that almost forces you to look at the logo. It’s pretty smart when you think about it.

Here’s how to make the most of this trend:

Keep the animation simple. Too much movement can have the opposite of the intended effect if the logo is hard to read or understand.

Consider speed carefully. Quick animations can be dizzying; slow animations feel off; it takes a lot of practice to find the speed that’s just right.

Don’t forget to create your animated logos in color and one-color options.

Squares

The change in shape is natural. With so many circle logos – thanks to social media icon shapes – more logo designs are featuring distinctive squares.

The change in shape is simple. A square also fits inside a circle logo but looks different. It’s a subtle change that can make a brand or logo stand out.

Most designers are using squares in a way that stacks elements, such as a square icon or brand mark with typography next to or above it that creates more of a rectangle. When used in those circular icon shapes, the logo drops to just the icon element.

Ways to make it work for you:

Create modular elements that you can mix and match in the logo design.
Keep the overall element to a simple icon-style graphic. Overly complex pieces can be tough to break apart or read at small sizes.
Don’t forget lettering. It’s easy to create a cool square element, but you need a brand identifier to really make it work in the long run.

Clean Lines

Clean lines and geometric patterns can create classic logos that work practically anywhere. There’s a great deal of flexibility in this trending style, which is one reason that it’s so popular.

Clean lines give this logo variation a classic feel, unlike some of the hand-drawn styles that have trended in the past. These logos are simple and elegant and the concept can be combined with other design trends as well. (Just look back to the Instagram logo, it features gradients and clean lines.)

How to make clean line logos work for you:

Keep imagery and lettering separated. Overlapping can end up making both design elements hard to read.
Choose a typeface with a similar stroke width as the line drawing to create harmonious consistency.
Don’t be afraid of color. While many line styles, feature one color, you can have more fun and stretch the palette somewhat.

Small Serif Logotypes

A logo doesn’t have to be complicated to be elegant and effective. More brands are turning to small serif logotypes to portray who they are.

When we refer to small serifs, it’s less about the font size and more about the size of strokes used within the type family. This trend is exemplified by characters that include tiny serifs. They are simple, light, and almost fall into the background of the lettering.

These serifs might be sharp or rounder and as with any logotype are a contributing factor in how the brand should feel to users.

Small serifs can be a great option because:

They are different. With so many sans serif logotypes out there, this style immediately stands out.
Serifs communicate a little more about a brand without imagery. These divots can establish mood and feel in a logotype where no other “art” is used.
These typefaces are interesting without being hard to read. While simple minimalism has been a trend for a while, there’s a movement toward somewhat more complex design elements.

Overlapping Elements

It’s one of those design rules that you don’t expect to be broken with small elements such as logos. But designers are breaking this rule … and it works.

From big brands like PayPal to smaller studios such as Moxy and Oust, logo designs are using elements that stack and overlap to create depth and visual interest. Overlapping styles tend to work best for logos that have a simple mark or lettering and that are contained to s specific part of the logo.

PayPal, for example, uses an overlapped letter for its iconic “P” but the word “PayPal does not use this treatment.

How do you use overlapping logo elements?

Pick one element to overlap; too much overlapping can get difficult to understand.
Use an overlapping element to create depth. Think about what the design technique does for an understanding of the mark.
Use color. This trending technique is made for high-color designs. (You might even consider an overprint style.)

Intricate Details

This logo design trend is a fresh take on visual elements after such a long period of minimalism – logos with intricate details.

From line-style logos has come an extension to more detailed logos with plenty of varying lines, color variations, type choices, and plenty of small elements that bring it all together.

This logo style can be a lot of work to create, but the result can be pretty amazing and creates a piece of art that is more than a logo. A great intricate design can be used everywhere at any size and maintains that same level of interest.

These designs beg users to look and then continue to engage with the design, trying to see every hidden stroke and meaning of the brand mark.

Here’s how you use the intricate detail logo design trend:

Take care with color. Too much color in an intricate style can get overwhelming quickly.
Make every detail count. The design should not be complicated because it can; it should be complex and intricate because it should be.
Pair simple typefaces with complicated artwork for readable balance.

Lowercase Lettering

These logos would make e.e. cummings proud. The style features great typography in all lowercase characters.

With so many designers focusing on typography for their projects, the shift to a type-based logo isn’t that far-fetched. Using all lowercase letters is a little more unusual and can be an attention-grabbing solution.

The catch is whether this use of your brand or company name meets visual standards and usage.

Here’s how to make it work for you:

Use a beautiful typeface. Any old sans-serif won’t do here.
Amp up the contrast between letters and the background to ensure that the smaller stance is seen.
Take care with readability. Is the word clear in all lowercase letters?
Opt for a heavier weight. Lowercase letters have a little less heft and presence than title or uppercase options. Create that balance with a thicker stroke weight.
Give it plenty of room. Whitespace can add weight and visual interest to a simple lowercase logotype.
Try it with short and simple words. Too many letters or words without capitals can get a little cumbersome in terms of readability.
Don’t crowd it with other elements. Lowercase lettering is the design trick with this logo style. Avoid other effects to maximize its impact.

Simple Shapes and Lines

The use of geometric shapes and lines is another popular trend for design projects overall that’s rapidly becoming a logo staple. With clean lines, simple shapes, and splashes of color, geometry is a logo must.

It’s important to note that many of these shapes are simple and fit into a square or circle format with uniform (or close to it) heights and widths. This initiative could be in part due to the need to have such a shape for common online mediums and logo usage, such as social media profiles.

Tips to make the most of the logo trend:

Don’t overthink it. A bold line or stroke can make simple lettering pop.
If you love the idea of a simple shape or geometry, but can’t quite make it work for the main logo, consider this treatment as a secondary option.
Give purpose to divots and shapes so that they frame or accent lettering, just dropping elements around a word isn’t quite enough to be effective.

Flat Design

Flat design remains a popular logo option because it is so easy to work with. While flat design as a whole is beginning to recede from the trends radar, logos are still using flat treatment.

Flat logos remain trendy because of how they are used. Many design projects feature full-screen video or images, particularly in website design, in full color. Flat logos often rest on a foreground layer and need to have some separation from the background.

Even brands that have more ornate logos often create a secondary, flat-style logo for this kind of use.

Going flat? Get the best result with these tips:

Use one (or just a few) colors in the design. Black or white options are the most popular.
Stick to simple typography that matches an icon or visual element in the logo.
Remember the basics of flat design and don’t feel tempted to add design techniques; simple is better if you want a logo that’s truly flat.
Consider a combination of a visual divot and text to tie the logo together.
Don’t overthink it. Often there’s not a lot of substance to a flat logo. The logo is often made to fall into the rest of the design.

Initials

LOL. OMG. SMH. It seems like the whole world talks in acronyms and initials these days. And logo design is no different.

While most commonly used for secondary logos, initials are everywhere. While there are three examples above, this collection could have easily included hundreds of designs with a three-letter (or less) logotype.

Most of these logos feature interesting or custom typography that’s designed to have a personal feel. The logo should speak right to the user and create an instant connection. The idea is further emphasized by the fact that the user needs to know what the letters actually mean (or have the desire to find out).

Here’s how you do it:

For designers or portfolio sites, use your initials to create a logotype that reflects your personality.
Add a simple animation to draw more interest to a logo that likely doesn’t carry a lot of visual weight in the design.
Consider boxing the letters to add more emphasis.
Acronyms and initials for logos are often secondary messaging and are subtle in placement and scale.

Circles

Circles are fluid and associated with energy, power, harmony, and infinity. And that’s why the shape is a trending logo design element.

Circles are also easy to plug into other places where a logo needs to appear, such as social media profiles, and in corner locations on printed designs, such as business cards or letterhead. Like many of the other elements that are trending in logo design, circles have become a more popular shape in website design overall in recent months.

Here are a few tips for using round logo shapes:

Don’t force it. Some words and elements just don’t fit into round shapes.
Match the meaning of your brand and the shape. Do the associations match?
Use a circle with a harmonious color palette to create a sense of balance between the logo and branding.
Don’t get stuck inside the shape; consider elements that break through the perfect roundness of the shape.
Opt for lettering that goes outside of the circle, particularly if words are long. (Short words are less of an issue.

One Color

Aside from black or white, logos with a single color a wildly popular.

While it’s not something that you would jump to design, these logos are classically beautiful with a simplicity that showcases the associated brands well. By chance or maybe as a color trend of its own, each of the examples above features a one-color logo style that uses a variant of orange.

Tips for designing a one-color logo:

Think of the design as colorless. Even with black and/or white and one color, use will be much like a true single-color logo.
With only one color, the meaning of that hue will speak volumes. Be mindful of color choice.
Don’t force too much color. A small swatch in a subtle location can have an impact.
Add color in a way that means something. Does it make your logo, brand, or product easier to understand?

Conclusion

Logo trends are interesting elements because, while what’s popular is always changing, logos are made to be constant. This creates an innate struggle for designers that are trying to create a logo that’s both modern and will withstand time. (It’s a pretty tall order.)

For the best chance at longevity, opt for a trend that includes some classic styling and is rooted in design theory. Design a logo that has a great aesthetic quality, is recognizable and readable and you’ll have the best chance at it lasting for years to come.

Continue reading "Reevaluating Link Building: Its Relevance in 2024"

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I’m linking this up because it’s notable for a few reasons:

WPGraphQL is a must-have plugin for creating headless WordPress sites and making it a canonical plugin is WordPress making a big step in that direction.
Jason is leaving WP Engine to join Automattic and we all know what a dumpster fire that relationship has become. (WP Engine also has a big foot in headless WordPress.)
You might be hearing about canonical plugins for the first time.

Congrats, Jason! I didn’t know you were in Denver — maybe we’ll bump into each other and I can give you a well-deserved high-five. ✋

WPGraphQL Becomes a Canonical Plugin: My Move to Automattic originally published on CSS-Tricks, which is part of the DigitalOcean family. You should get the newsletter.