# Baymard Institute Solve real ecommerce UX challenges with 200,000+ hours of research. Get clear answers for every decision and improve conversion with confidence. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## B2B Medical & Pharma UX Benchmark: 3,400+ Performance Scores and 2,600+ Best Practice Examples DevFeed: [B2B Medical & Pharma UX Benchmark: 3,400+ Performance Scores and 2,600+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-09-15T09:30:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [Testing](), [web applications](), [Mobile]() Tags: [b2b](), [benchmark](), [desktop](), [ecommerce](), [mobile](), [performance](), [research](), [testing](), [ux]() ### AI overview Baymard reports on a UX benchmark covering 10 B2B Medical & Pharma ecommerce sites, assessed across more than 400 research-based UX parameters. The sites ranged from poor to mediocre overall, with recurring issues in product information, pricing, search, and collaborative cart workflows. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 10 "B2B Medical & Pharma" UX case studies. This follows from our large-scale user testing and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 10 B2B Medical & Pharma UX Case Studies and the Overall Performance AbCam mediocre B2B Medical & Pharma 40 page designs: desktop, mobile Waters mediocre B2B Medical & Pharma 38 page designs: desktop, mobile Allegro Medical mediocre B2B Medical & Pharma 41 page designs: desktop, mobile Medline mediocre B2B Medical & Pharma 25 page designs: desktop, mobile Cole-Parmer mediocre B2B Medical & Pharma 50 page designs: desktop, mobile Mckesson poor B2B Medical & Pharma 22 page designs: desktop, mobile Thermo Fisher poor B2B Medical & Pharma 42 page designs: desktop, mobile Henry Schein poor B2B Medical & Pharma 38 page designs: desktop, mobile Bound Tree Medical poor B2B Medical & Pharma 41 page designs: desktop, mobile Sigma Aldrich poor B2B Medical & Pharma 41 page designs: desktop, mobile YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 10 in-depth B2B Medical & Pharma UX case studies. The 10 sites have been manually assessed across 400+ research-based UX parameters relevant to B2B Medical & Pharma, resulting in 3,400+ weighted UX performance scores and 2,600+ best practice examples from these desktop and mobile sites. Each of the 3,400+ UX performance scores from the 10 B2B Medical & Pharma case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:medical-pharma + view-structure-id=gemini-st ## Accounts & Self-Service UX Research Update and Expansion: 3 Key Takeaways DevFeed: [Accounts & Self-Service UX Research Update and Expansion: 3 Key Takeaways]() Original publisher: [Read original article]() Author: Sally Collins Published: 2026-09-09T08:05:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User interface design](), [Authentication](), [passwords](), [MFA](), [web applications](), [password reset]() Tags: [article](), [authentication](), [insights](), [mobile](), [passwords](), [research](), [security](), [usability](), [web]() ### AI overview Baymard's updated Accounts & Self-Service UX research examines how ecommerce account experiences have changed since 2018. Based on more than 4,000 hours of research, 1,400 usability issues, and a survey of over 1,000 US adults, the article highlights account security and sign-in changes, including passkeys, one-time passcodes, and two-factor authentication. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Takeaways Baymard has new research on Accounts & Self-Service UX The research uncovered UX issues and identified UX solutions specific to the Accounts area of ecommerce sites Much has changed in account security and sign in, order management and tracking, and order returns since our last large-scale research in 2018 Key Stats 4,000+ new hours of Accounts & Self-Service research 1,400+ usability issues observed in testing 1,000+ US adults surveyed as part of our complementary quantitative research Today at Baymard, we're announcing the launch of our new updated and expanded Accounts & Self-Service UX research. We first investigated UX issues in Accounts & Self-Service in 2018. In this update, we've retested all the UX issues observed in 2018, verified all our UX solutions, wrote new guidelines based on newly observed Accounts & Self-Service UX issues, and rewritten the bulk of our verified guidelines for improved usefulness and clarity. This work has resulted in 57 new and updated Accounts & Self-Service guidelines based on 1,400+ usability issues observed during testing. The 57 guidelines are a key foundation for ensuring a high-performing Accounts and Self-Service UX. Additionally, we've included mobile test observations for the first time. As a result, this study represents our most comprehensive findings on Accounts & Self Service ecommerce UX. In this article, we'll highlight 3 high-level insights from our new Accounts & Self-Service UX research findings. New Insights for Accounts & Self-Service UX Compared to 2018, the landscape of Accounts & Self-Service has changed dramatically, particularly in 3 areas. 1) Account Security and Sign In At J.Crew, participants updating their passwords were provided no guidance regarding the site's password requirements, and they were unable to ## Telco UX Benchmark: 3,100+ Performance Scores and 2,400+ Best Practice Examples DevFeed: [Telco UX Benchmark: 3,100+ Performance Scores and 2,400+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-09-01T08:45:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [web applications](), [GUI]() Tags: [article](), [benchmark](), [case-studies](), [comparison](), [ecommerce](), [mobile](), [performance](), [research](), [testing](), [ux](), [web]() ### AI overview Baymard presents a Telco UX benchmark based on seven case studies, manually assessed across more than 500 research-based parameters. The benchmark reports poor overall UX performance and highlights unclear plan and specification labels, weak comparison tools, missing contract and device terms, and incomplete warranty, returns, shipping, delivery, and discount information. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 7 "Telco" UX case studies. This follows from our large-scale user testing on Telco UX and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 7 Telco UX Case Studies and the Overall Performance AT&T mediocre Telco 51 page designs: desktop, mobile Xfinity poor Telco 47 page designs: desktop, mobile Lebara poor Telco 45 page designs: desktop, mobile Orange poor Telco 56 page designs: desktop, mobile Vodafone UK poor Telco 49 page designs: desktop, mobile Bell poor Telco 44 page designs: desktop, mobile Verizon poor Telco 49 page designs: desktop, mobile YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 7 in-depth Telco UX case studies. The 7 Telco sites have been manually assessed across 500+ research-based UX parameters relevant to Telco providers, resulting in 3,100+ weighted UX performance scores and 2,400+ best practice examples from these desktop and mobile sites. Each of the 3,100+ UX performance scores from the 7 Telco case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:telco + view-structure-id=gemini-st_47eezi8l }} The overall UX performance of the Telco sites is "poor," with only 1 site in the "mediocre" range. Here are some of the overarching UX issues. On the benchmarked sites, proprietary plan names and technical specifications were presented as labels without explanation. No site explained its industry-specific filters or provided inline help for technical specifications within comparison features, and plan feature ## New Insurance UX Research: 3 Key Takeaways DevFeed: [New Insurance UX Research: 3 Key Takeaways]() Original publisher: [Read original article]() Author: Mark Crowley Published: 2026-08-25T08:30:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [Usability](), [Benchmark]() Tags: [article](), [benchmark](), [launch](), [research](), [usability](), [ux]() ### AI overview Baymard announces qualitative Insurance UX research based on 4,700+ hours of research and usability testing across 20 US and UK insurance sites. The study identified more than 1,700 medium-to-severe usability issues and produced over 190 guidelines. It highlights users' difficulties with unfamiliar insurance concepts, friction-filled quote flows, and trust in insurance brands. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Takeaways Baymard has new qualitative UX research on Insurance UX The research uncovered UX issues and identified UX solutions specific to Insurance users and sites At a high level, Insurance users struggle with unfamiliar concepts, friction-filled quote flows, and brand trust Key Stats 4,700+ hours usability testing, analyzing, and researching the UX of Insurance sites 220 qualitative participant/site usability test sessions following the "Think Aloud" protocol 1,700+ medium-to-severe usability issues in testing Today at Baymard, we're announcing the launch of our new Insurance UX research. 8 US and 12 UK Insurance sites were tested, including providers (some of whom are also banks) and aggregators (where test participants could compare Insurance quotes across many providers). The 9 UK Insurance sites tested were Halifax, Aviva, Direct Line, LV/Liverpool Victoria, TSB, Insure and Go, Allianz, Avanti, and Santander, while the 3 aggregators were Compare the Market, MoneySuperMarket, and Go Compare. The 8 US Insurance sites tested were Liberty Mutual, Travelers, Progressive, GEICO, Amica Mutual, Lemonade, Root Insurance, and Allstate. This primary research is supplemented by our ecommerce UX benchmark, which includes AXA UK, Generali, "Progressive", "Liberty Mutual", "Travellers", "Allstate", and State Farm. During testing, the participants encountered 1,700+ medium-to-severe usability issues as they attempted to use Insurance sites to explore options and eventually add coverage. Our analysis of these issues has resulted in 190+ guidelines on Insurance industry UX, available in our research findings. In this article, we'll provide 3 high-level observations on where users on Insurance sites struggle: Understanding unfamiliar Insurance concepts and descriptions Progressing through the I ## The Hidden Cost of Bad UX: How Much Revenue Are You Leaving on the Table? DevFeed: [The Hidden Cost of Bad UX: How Much Revenue Are You Leaving on the Table?]() Original publisher: [Read original article]() Author: Christian Holst Published: 2026-08-19T08:12:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [Usability](), [web applications](), [coding]() Tags: [article](), [best-practices](), [business](), [checkout](), [cost](), [design](), [ecommerce](), [insights](), [leadership](), [metrics](), [product](), [research](), [revenue](), [usability](), [ux]() ### AI overview Baymard presents an Opportunity Sizing Calculator that estimates the revenue recoverable from reducing ecommerce UX friction. It translates user research and usability improvements across areas such as checkout, navigation, and product pages into projections that can support roadmap prioritization, budget decisions, and executive buy-in. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) How much revenue is your site losing each month because of unnecessary UX friction? If you are like most ecommerce leaders or UX managers, you know that friction points across checkout, product pages, and navigation cause shoppers to abandon. Yet, when competing for roadmap resources or budget approvals, UX research is often categorized as an internal software or subscription expense rather than a top-line revenue driver. Without concrete financial estimates to back up your design priorities, critical usability improvements often get pushed aside. To help you translate UX friction into clear commercial impact, Baymard has developed an Opportunity Sizing Calculator. This tool converts Baymard's actionable user research into quantifiable projections, showing you the exact revenue you can unlock by systematically applying proven UX best practices to your site. Moving from Opinions to Research-Backed Forecasting Prioritizing a product roadmap often turns into a debate of subjective opinions, where the loudest voice in the room or the most senior person's viewpoint takes priority. UX designers and product managers must frequently advocate for critical usability fixes against competing internal requests, relying on qualitative arguments that struggle to secure executive support. Baymard's Opportunity Sizing Calculator bridges the gap between design priorities and executive decision-making, helping you secure buy-in. This means you're better able to: Connect specific usability insights directly to top-line revenue Build an unshakeable business case for leadership Give directors and VPs clear line-of-sight into the ROI of resolving site friction Get your personalized opportunity metrics: Book a short call with our team and find out how much revenue you could recover with better UX. Book a demo ## Food Delivery & Takeout UX Benchmark: 3,100+ Performance Scores and 1,900+ Best Practice Examples DevFeed: [Food Delivery & Takeout UX Benchmark: 3,100+ Performance Scores and 1,900+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-08-13T08:01:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [Benchmark](), [User experience (UX)](), [App](), [web applications]() Tags: [apps](), [article](), [benchmark](), [case-studies](), [customer](), [ecommerce](), [insights](), [mobile](), [performance](), [research](), [retail](), [user-testing](), [ux]() ### AI overview Baymard presents a Food Delivery & Takeout UX benchmark based on eight mobile sites and apps assessed across more than 390 research-based UX parameters. The benchmark reports over 3,100 weighted performance scores and 1,900 best-practice examples, with overall experiences ranging from poor to mediocre. Key weaknesses include repeat ordering, dietary and customization support, category filters, navigation, fulfillment timing, and tipping details. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 8 "Food Delivery & Takeout" UX case studies. This follows our large-scale user testing on Food Delivery & Takeout UX and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 8 Food Delivery & Takeout UX Case Studies and the Overall Performance Just Eat mediocre Food Delivery & Takeout 49 page designs: mobile, app KFC mediocre Food Delivery & Takeout 48 page designs: mobile, app Uber Eats mediocre Food Delivery & Takeout 54 page designs: mobile, app Domino's Pizza poor Food Delivery & Takeout 34 page designs: mobile, app DoorDash poor Food Delivery & Takeout 48 page designs: mobile, app McDonald's poor Food Delivery & Takeout 39 page designs: mobile, app Deliveroo poor Food Delivery & Takeout 53 page designs: mobile, app Burger King broken Food Delivery & Takeout 41 page designs: mobile, app YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 8 in-depth Food Delivery & Takeout UX case studies. The 8 mobile sites and apps have been manually assessed across 390+ research-based UX parameters relevant to Food Delivery & Takeout, resulting in 3,100+ weighted UX performance scores and 1,900+ best practice examples from these mobile sites and apps. Each of the 3,100+ UX performance scores from the 8 case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:online-food-delivery + view-structure-id=gemini-st_l9jw5tjp }} The overall UX performance of the Food Delivery & Takeout sites and apps ranges from "poor" to "mediocre". What is missing is a ## Ecommerce Quantitative UX: 3 High-Level Trends & Takeaways from 20+ Charts DevFeed: [Ecommerce Quantitative UX: 3 High-Level Trends & Takeaways from 20+ Charts]() Original publisher: [Read original article]() Author: Anja Feibel Meerwald Published: 2026-08-04T08:21:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [User Experience](), [data]() Tags: [article](), [checkout](), [data](), [ecommerce](), [research](), [time](), [ux]() ### AI overview Baymard presents quantitative UX findings from a survey of 1,083 US online shoppers, covering more than 20 ecommerce insights. The article highlights declining online return frequency, retailer-specific email frequency as a leading cause of newsletter unsubscribes, and the rising priority of loyalty programs in online account expectations. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Stats & Takeaways 20+ new insights on general ecommerce shopper habits and preferences 1,083 US online shoppers surveyed in this quantitative UX study General ecommerce shopping habits remain consistent overall, but a few noteworthy shifts stand out this year, from declining return frequencies to changing newsletter preferences At Baymard, we've released updated Quantitative Insights into the habits and preferences of online shoppers across key ecommerce stages. These insights are survey-based data visualizations that complement and deepen our large-scale UX research findings. The 20+ insights cover the online shopping experience across a wide range of topics: product discovery, cross-sell preferences, sale-seeking behaviors, checkout friction, return behaviors, account feature expectations, and newsletter management. Ecommerce shoppers make decisions with deeply ingrained expectations regarding transparency, flexibility, and convenience, standards that continually evolve as the online shopping landscape evolves. While the vast majority of our foundational data remains highly stable year after year, tracking this data over time reveals a few subtle, critical shifts in reported consumer habits. Over the last 3 years, consumer habits show clear directional changes in how frequently shoppers make online returns for their past purchases. Further down the funnel, they frequently leverage accounts to manage post-purchase utility, carefully balancing their participation in brand incentive structures with their tolerance for direct retailer outreach. Each of these evolving dynamics plays out at a different stage of the user experience, highlighting exactly where optimization priorities should be re-evaluated. In this article, we'll highlight 3 high-level findings that reflect the most notab ## Internet Service Providers UX Benchmark: 1,700+ Performance Scores and 1,100+ Best Practice Examples DevFeed: [Internet Service Providers UX Benchmark: 1,700+ Performance Scores and 1,100+ Best Practice Examples]() Original publisher: [Read original article]() Author: Anders Nielsen Published: 2026-07-28T05:27:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [Benchmark](), [User experience (UX)](), [User Experience](), [web applications]() Tags: [article](), [benchmark](), [case-studies](), [ecommerce](), [performance](), [research](), [user-testing](), [ux]() ### AI overview Baymard presents a UX benchmark covering seven Internet Service Provider websites. Based on large-scale user testing, the benchmark reports 1,700+ weighted UX performance scores and 1,100+ best-practice examples. Overall performance is described as mediocre, with recurring problems in plan comparison and application flows, including dense layouts, unclear pricing, weak guidance, and form friction. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) At Baymard, we've just released a new UX benchmark with 7 "Internet Service Providers (ISP)" UX case studies. This follows from our large-scale user testing and adds to our existing ecommerce UX benchmark. In this article, we give you a snapshot of the overall UX performance. 7 Internet Service Providers UX Case Studies and the Overall Performance BT mediocre Internet Service Providers 26 page designs: desktop, mobile Telekom mediocre Internet Service Providers 35 page designs: desktop, mobile Frontier mediocre Internet Service Providers 25 page designs: desktop, mobile COX mediocre Internet Service Providers 24 page designs: desktop, mobile CenturyLink mediocre Internet Service Providers 25 page designs: desktop, mobile Viasat mediocre Internet Service Providers 32 page designs: desktop, mobile Spectrum mediocre Internet Service Providers 15 page designs: desktop, mobile YourSite.com? Want to know how your site performs? Get Premium access to review your own site or have it audited by Baymard researchers. These are the 7 in-depth ISP UX case studies. The 7 ISP sites have been manually assessed across 280+ research-based UX parameters relevant to Internet Service Providers, resulting in 1,700+ weighted UX performance scores and 1,100+ best practice examples from these desktop and mobile sites. Each of the 1,700+ UX performance scores from the 7 ISP case studies is summarized in the interactive scatterplot below -- showing you how they perform collectively and individually: {{ scatterplot-graph: size=big + habitat=public + base-sites=collection:internet-service-providers + view-structure-id=gemini-st_9en1b7zd }} The overall UX performance of the ISP sites is "mediocre," with 1 site just on the border of "poor". ISP sites typically offer a narrow set of services, but these services come wi ## Time is Money: How Pre-Validated UX Research Protects Your Resources & Budget DevFeed: [Time is Money: How Pre-Validated UX Research Protects Your Resources & Budget]() Original publisher: [Read original article]() Author: Christian Holst Published: 2026-06-30T11:45:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User Experience](), [Usability](), [Testing](), [Website]() Tags: [cost-savings](), [subscription](), [usability](), [user-research](), [ux]() ### AI overview The article presents a calculator intended to estimate initial savings from using Baymard's pre-validated UX research instead of conducting new in-house research. It states that a moderated usability study with 15 participants requires about 55 hours of labor and estimates the cost of producing one UX insight at $362 in the US and $262 in the UK and Europe. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) When you try to prove the value of your design decisions, you often hit a wall. To back up your designs confidently, you need robust usability research. But conducting that research yourself for every minor UI change or UX decision is expensive and time-consuming. Baymard's pre-validated research gives teams like yours access to established UX best practices in an instant, which helps you ship designs faster, more confidently, and protects your costs by reducing the research overheads. To demonstrate that value, we've created a calculator that shows how a Baymard subscription helps you move faster and keep your UX research costs down. Note: This calculator demonstrates initial cost savings based on consuming Baymard's insights versus running new user research yourself. Baymard users typically see further value realizations from implementing those insights and improving website user experience and conversion rates. The Hidden Cost of Your In-House User Research It's easy to fall into the trap of thinking: "We can just replicate this research in-house for less cost." But when you try to build everything from scratch without access to pre-validated UX insights, your team quickly runs into three major roadblocks: You move slower: Your product teams lose momentum and your project timelines stretch out because you are forced to conduct research from scratch You risk harming conversions: When timelines get tight, you risk making critical UX decisions based on gut feelings, which can ultimately harm your conversion rates You spend more money: To keep up with research demands, you end up spending vastly more on external agency services or expanding your internal headcount just to conduct baseline testing What It Actually Costs You to Produce a UX Insight To protect your resources, you need to sh ## Flight Booking & Airlines Quantitative UX: 3 High-Level Takeaways from 30+ Charts DevFeed: [Flight Booking & Airlines Quantitative UX: 3 High-Level Takeaways from 30+ Charts]() Original publisher: [Read original article]() Author: Richard Lam Published: 2026-06-24T08:04:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [Flight](), [User experience (UX)](), [data](), [benchmarking](), [Mobile](), [A/B Testing]() Tags: [a-b-testing](), [airline](), [apps](), [article](), [booking](), [desktop](), [mobile](), [research](), [survey](), [travel](), [ux]() ### AI overview Baymard reports quantitative UX findings from a survey of 3,125 US online shoppers who use flight-booking and airline sites. The article highlights that shoppers use multiple sources when searching for flights, three quarters belong to at least one airline loyalty program, and business travelers are more likely to bundle travel-related bookings. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Stats & Takeaways 30+ new insights on Flight Booking & Airline shopper habits and preferences 3,125 US online shoppers surveyed in this quantitative UX study Flight Booking & Airline shoppers use a variety of sources when looking for flights, are highly likely to participate in loyalty programs, and commonly bundle other travel-related bookings at the same time, particularly when travelling for business. At Baymard, we've just released new Quantitative Insights into people who shop on "Flight Booking & Airlines" sites, expanding our understanding of the habits and preferences of online shoppers in this category. These insights are visualizations based on survey data that supplement and support our large-scale UX research findings and benchmarking of the Flight Booking & Airlines industry. The 30+ insights address the Flight Booking & Airlines online shopping experience, spanning a breadth of topics: sources for flight searching, types of add-ons purchased, usage of apps and external tools, importance of cancellations, sales and scarcity incentives, and motivations for bundling and loyalty programs. Some of the charts also explore sub-segments of the broader audience such as business travelers and whether they are more likely to purchase add-ons, or how device usage between desktop and mobile changes as flight price becomes more expensive. These Quantitative Insights empower you to align stakeholders through objective, survey-backed data, streamline A/B testing with high-potential hypotheses, and discover and address industry-specific UX challenges. In this article, we'll highlight 3 high-level findings that reflect how shoppers evaluate and purchase flights online: Flight shoppers use a variety of sources when looking for flights Three quarters of flight shoppers are part of at leas ## Apparel & Accessories Quantitative UX: 3 High-Level Takeaways from 40+ Charts DevFeed: [Apparel & Accessories Quantitative UX: 3 High-Level Takeaways from 40+ Charts]() Original publisher: [Read original article]() Author: Niel Gan Published: 2026-06-12T08:02:00Z Content type: article Language: en Sources: [Baymard Institute]() Topics: [User experience (UX)](), [data](), [benchmarking]() Tags: [article](), [benchmarking](), [customer](), [data](), [ecommerce](), [online-shopping](), [research](), [reviews](), [shopping](), [survey](), [ux]() ### AI overview This quantitative UX study examines apparel and accessories shoppers' habits and preferences using survey data from 1,922 US online shoppers. It presents more than 40 insights on topics including sizing and fit confidence, product-page evaluation, reviews, returns, loyalty programs, and delivery expectations. The article highlights uncertainty throughout the shopping journey, including mismatches between shoppers' self-reported sizes and industry definitions, infrequent shopping as a barrier to loyalty enrollment, and reviews serving as a proxy for fit evaluation. ### Source excerpt (Note: Unfortunately, e-mail and RSS don't support advanced layouts and features. If the graphics in this article look strange, you may want to read the article in your web browser.) Key Stats & Takeaways 40+ new insights on Apparel & Accessories shopper habits and preferences 1,922 US online shoppers surveyed in this quantitative UX study Apparel and accessories shoppers face uncertainty at every stage of their journey, from how their self-identification corresponds to retailer categories to how they evaluate fit on the product page We've released new Quantitative Insights into people who shop on "Apparel & Accessories" sites, adding to our growing body of data on the habits and preferences of online shoppers across key ecommerce categories. These insights are survey-based data visualizations that complement and deepen our large-scale UX research findings and benchmarking of the Apparel & Accessories industry. The 40+ insights cover the Apparel & Accessories online shopping experience across a wide range of topics: online trip drivers, size and fit confidence, product page evaluation, reviews usage, returns, loyalty programs, and delivery expectations. Apparel and accessories shoppers make decisions with incomplete information at every stage of their online journey. They can't feel a fabric, try out a fit, or know whether a size label will translate to their body. Beyond that, they may not know whether the items they buy will ultimately feel "worth it" to them, or whether they'll shop frequently enough to make a rewards program worth joining. Each of these uncertainties plays out at a different stage of the journey, and each has distinct implications for how Apparel & Accessories sites should be designed. In this article, we'll highlight 3 high-level findings that reflect how apparel and accessories shoppers navigate that uncertainty: Shoppers' self-reported size categories often diverge from industry definitions Infrequent shopping, not program design, is the top