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 view their input, further increasing the likelihood of errors (first image). It is only after a password that doesn’t meet the requirements is submitted that the site discloses the requirements (second image).

The standard username and password combination required to create and sign in to an account is quickly being replaced by passkeys (e.g., fingerprint, Face ID, or device PIN) and one-time passcodes (OTPs), which are considered by many users to be more convenient — and more secure.

Indeed, account security is also top of mind for users — especially when personal information and saved payment methods are involved.

“I use two-factor authentication — it seems just to be standard now to get a code sent to either my phone number or email address. It seems like a lot of websites are doing that now for safety reasons”, remarked a participant viewing the sign in preferences at Walmart. Participants generally appreciated having the option to enable two-factor authentication (2FA).

“Two-factor authentication — not all the time, I’m going to be really honest. It’s kind of site-dependent, but do I use it — especially if it’s a large account or a large website — something I’m doing a lot on. It’s almost always on, but not always”, explained a participant at Home Depot, noting the two-factor authentication (2FA) banner at the top of the “Security & Password” page.

“I feel good that whoever may or may not have the password will not be able to log in anymore, but to ensure that doesn’t happen again, I would set up 2-factor authentication”, remarked a participant at Target. After updating her password she took the extra step to enable two-factor authentication (2FA). “It is enabled. I’m assuming the next time I sign in, I would need to receive a text message or an email code to be able to log in.” Offering optional account security features is a low-friction way for sites to allow security-conscious users to opt in without burdening other users who are less risk-averse.

During recent testing, 81% of participants reported saving credit card details in their account at sites they shop at frequently, and 60% appreciated when two-factor authentication (2FA), which requires confirmation from a user’s verified account email or phone number before being able to sign in, was available to activate.

It’s therefore key that ecommerce sites move beyond traditional username and password combinations to support users signing in to their accounts.

Indeed, as observed during testing, strong visible and optional security features such as two-factor authentication (2FA) and device management build confidence and trust with users.

However, these features must be implemented carefully to avoid becoming a roadblock to users checking out or managing their account details.

“Oh, okay. Maybe I typed it wrong. Um, it doesn’t like me”, laughed a participant (iOS) attempting to sign in at American Eagle (first image). She proceeded to reset the password, but was unable to verify the new password because it was also only displayed as masked (second image). “That was a little bit of a pain”, she remarked negatively after resetting the password.

Next, account sign in is viewed by many users as simply a hurdle to overcome to proceed with more productive tasks, such as checking out, tracking orders, managing account details, or initiating returns.

However, when account sign in is problematic, users’ frustration will mount, as they haven’t even reached the account feature they’re interested in yet.

2) Order Management and Tracking

Order management and tracking continue to be top priorities for users.

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Whether making a one-time purchase or subscribing to recurring shipments (e.g., every 3 weeks, every 4 months), recent testing reveals that users’ expectations regarding self-service order management and tracking features and information have only intensified since 2018.

“I often go to my previously ordered items to buy them again, rather than searching the site to try to find them. If I want to make sure I get that same thing again”, explained a participant at Bloomingdale’s as she scrolled the “Order List” page looking for a previous order containing a whisk. However, she couldn’t easily locate the desired order because only the order number and order date were visible by default (first image). Consequently, she opened 4 orders before stumbling across the whisk order (second image). Hiding basic item and order details in collapsed sections performed as poorly in testing as not providing these details at all (see guidelines #3218 and #925). Indeed, this design places the burden on users to interact with the interface simply to discover the contents of each order.

The “Order List” and “Order Details” pages serve as critical starting points for users when they are looking for specific order-related information, and when they want to modify or cancel an order, start a return, review a purchased item, or revisit a purchased item to buy it again.

Across multiple large-scale studies, we’ve observed that users need easy access to certain basic information and actions to effectively identify and manage their orders.

For example, without a clear understanding of order contents and status, and adequate features to identify desired orders on the “Order List” page, users will be needlessly delayed in beginning their order-related tasks, which can result in unwanted additional orders and place more strain on customer service.

Likewise, when key details for items on the “Subscriptions List” page are missing or unclear, users will be unable to easily identify and manage recurring orders.

“Right now it’s in Opa Locka, which is here in Miami. So, it’s arrived there, but it doesn’t give me an estimated delivery date. So that’s a little disappointing. I would hope that that information would be there”, complained a participant at Bloomingdale’s when he discovered the “Order Tracking” overlay lacked an estimated delivery date (first image). “Okay, so here it’s saying, the expected delivery date is today, the 23rd, by 9:00 PM.” He searched the tracking number at the carrier site and confirmed the expected delivery date and time (second image). “Yeah, see, it would be helpful if the information from USPS about the expected delivery date would also be included. I’m just not seeing it anywhere. I’m not seeing it anywhere on the website”, he lamented after he returned to his tracking information at Bloomingdale’s.

When it comes to order tracking, for most users the key details needed to track an order are the estimated delivery date, the carrier name, and the subevents or stages of the order delivery process.

Some tracking details will be contained in the order shipment notification email, but users who need more detail on order tracking than is in the shipping notification email will visit the “Order Tracking” page on the ecommerce site.

Ideally, the destination page on the ecommerce site will contain all the tracking information users need, including photo proof of the delivery.

3) Order Returns

“Let’s see, ‘View Details’. That’s not very clear. I’m looking for where I can start my return. I don’t see it here — the return part. So let me see, I’ll click ‘Return Policy’.” This participant at Wayfair searched for information about returning an item in the order listing (first image) and in the “Order Details” overlay (second image). She then resorted to opening the return policy link in the footer (third image). Simply removing the “Start Return” button when the return window has closed, as was the case at Wayfair, created needless uncertainty for participants, and often resulted in wasted time and effort.

“Um, this is the tricky part — this is where Amazon gets you — so sneaky! They generally don’t give you the option to put it back on your credit card, unless you’re very — there’s not a bubble here, right? If you’re being very quick about it, you’re going to click ‘Amazon account’, blah, blah, and you’re going to click ‘Return’. They still have your money! I actually want my money back. I don’t want to add this to my gift card amount or whatever. So I think this is a bit sneaky on Amazon’s part.” This participant at Amazon, having been duped by the “Refund Method” interface in the past, carefully located and clicked the “Refund to Visa” link (first image), which revealed the radio button for her preferred refund option (second image).

While for many sites returns are an undesirable aspect of ecommerce, how sites perform during returns is critical for end users.

A high-performing returns experience can, perhaps counterintuitively, become the basis of a loyal customer relationship.

On the other hand, a returns experience fraught with confusion, friction, and unnecessary obstacles will cause some users to avoid shopping at a site in the future.

Yet during large-scale testing, participants frequently struggled to determine an order’s eligibility for returns and to confidently navigate the return flow.

Moreover, returns has perhaps undergone the largest transformation since 2018.

Indeed, in 2018 returning an item typically required finding a box, printing a paper return shipping label, repackaging the item, dropping it off with a carrier, and waiting several weeks for a refund.

“’Label-Free at the UPS Store, no printer needed’. I will do that option. I don’t have a printer, so that’s generally how I do returns”, explained a participant (iOS) at Bloomingdale’s, as she chose the “Label-Free” drop-off at the UPS store (see guidelines #3279 and #3411).

“Okay, it’s giving me all the options. I’m going to do the ‘schedule for pickup’ option. ‘It’s free, choose a time and place, and we’ll pick it up.’ I’ve got to pack the item, that’s fine.” This participant (Android) returning an item at Walmart opted for the free FedEx pickup method.

On the contrary, during recent testing, participants benefited from label-free — and sometimes box-free — return shipping methods, as well as “Return Pickup”.

Additionally, for some participants, refunds were initiated as soon as the returned item was scanned during drop-off or pickup.

Overall, users expect a much more responsive returns experience with clear, easy-to-locate return details, multiple return options (including at least one free one), and straightforward refund options and confirmation.

Support Key Customers with High-Performing Accounts UX

“It looks like it’s only giving me an option to delete it, not actually update it. Okay. Let me go back — maybe I missed something.” A participant (iOS) at Wayfair wanted to update the expiration date on a saved credit card (first image). “Nope. Looks like that might be the only way. Let me see if maybe there’s a different option on this. Nope. Well, it looks like I will have to delete the debit card and then reenter it.” When she tapped to select the card, she discovered she could only delete it (second image). She spent over 2 minutes searching the “My Account” section for a method to edit the expiration date; she ultimately resorted to deleting the card and re-adding it with the updated expiration date.

Accounts & Self-Service is a unique aspect of the ecommerce user experience.

Unlike the other ecommerce themes we’ve researched, Accounts & Self-Service is often not part of the “direct purchase funnel” — but rather comes post-purchase.

However, this isn’t to indicate that Accounts & Self-Service is less important than the other ecommerce themes.

Returning users — those most likely to use self-service features most often — are critically important to a successful ecommerce business.

This means the Accounts & Self-Service UX performance can be just as important as the UX performance of the Product Page, Homepage, Category Taxonomy & Main Navigation, or any other ecommerce areas when it comes to a site’s overall long-term sales.

It’s therefore key that users’ experience in the Accounts area of a site is as smooth as possible to support an ongoing site-user relationship.

This article presents the research findings from just a few of the 700+ UX guidelines in Baymard – get full access to learn how to create a “State of the Art” ecommerce user experience.

If you already have access through your account, go explore the updated Accounts & Self-Service UX research.

If you want to know how your desktop site, mobile site, or app performs and compares, then learn more about getting Baymard to conduct a UX Audit of your site or app.

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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

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:

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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 features and specification labels were also often undefined.

Comparison was obstructed at every level, from plans to handsets to network coverage.

Contract length was missing from plan listings, comparison features were largely absent for handsets, every site listed specifications in inconsistent units and labels, and 4G and 5G coverage were displayed on separate maps.

The commercial terms of a financed device and ongoing service were routinely unstated.

Warranty upgrades were missing on all product pages in the benchmark, and returns, shipping cost, delivery timing, and the context around discounts were each missing from a substantial share.

As this benchmark shows, with no sites delivering even a “decent” or better overall user experience, there is plenty of room for improvement.

A publicly available overview of the research and benchmark can be found on our Telco UX research overview page.

Getting access: all 3,100+ UX performance scores, 2,400+ best practice examples, and the UX insights from researching the Telco ecommerce industry are available immediately and in full within Baymard. (If you already have access through an account, open the Telco UX Benchmark collection.)

If you want to know how your Telco desktop and mobile sites perform and compare, then learn more about getting Baymard to conduct a Telco UX audit of your site.

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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 Insurance quote flow
• Establishing trust with Insurance brands

Users Struggle with Insurance Concepts

Shopping for insurance, while having some similarities to traditional ecommerce shopping, poses unique challenges to users.

A key differentiator of Insurance sites is that users seeking coverage are often asked for information that is more complex and less familiar than the address and payment details requested in general ecommerce.

One reason for this is that getting insurance cover (or coverage) is an occasional task that happens only very infrequently for auto or home insurance.

“’What is the current market value of your home.’ Oh blimey! Crikey!…Err…Ohh..I think it was somewhere around £575,000.” This participant at Money Supermarket (iOS) reacted with surprise and then hesitated at the home value question. She made her best guess and moved on, though she wasn’t confident of the estimate.

“Now, I wouldn’t know what the rebuild cost is. I’ve got no idea…I’d be a bit worried about putting my own figure in because I’ve got to be way out!” This participant at Go Compare struggled to enter an accurate estimate of the “Property’s Rebuild Cost”, and proceeded to skip the question. His response reflects the risk of asking users questions they do not know: poor answers, skipped answers, and even site abandonments. As the participant said, “I think what I’d probably do at this stage is just try and continue without filling it in, see if it insists on me entering something in there. In which case, I might have to think again about using somewhere else for a quote.”

”There’s so many different [roof options] here!… Like ‘Shingle’, I have no idea what that is.” This participant at Money Supermarket slowly scrolled through the list of options for the “What is your roof made of?” question, eventually answered “Tile” as the material of her roof, and moved on.

As a result, there is a heightened risk of users being unfamiliar with concepts or physical items that are a key part of the quote process, such as “5-level mortice deadlock” in a home insurance quote.

Furthermore, when faced with unknown values, participants would frequently hesitate for extended periods, bypass fields, or resort to unguided guesswork.

“’Do you need more…?’ I’ll put in the amount that they suggest I need.” After seeing the site’s recommendation, this participant at Direct Line confidently adopted the exact suggested figure. This default almost certainly gave her an answer more accurate than those she had provided on other sites, where she announced that she was guessing wildly, since she did not know what cover level to choose. On one such site, she estimated her contents at less than 15% of this value.

“Roof is 50% flat? I’ll just adjust it.” Here at Compare the Market (iOS), this participant said that images made the process “quick and easy”, and answered the flatness percentage of her roof, the material of her external walls, and the material of her roof in under 8 seconds. Further, the visuals created a measurable time savings for the participants who struggled to answer these questions on other sites.

Thus, when users are asked to describe a component or attribute of a house or a car, a clear explanation should be provided, along with visuals if they are needed to fully understand the option.

It’s also important to help users to estimate values (such as the value of their home or its contents) by providing tools that allow them to reach an accurate estimation and default values that reflect; for example, the average of similar homes in that area.

Similarly, helping users with estimating their car mileage by being flexible about the relevant time period (e.g., daily, annually) will make the process that bit less troublesome.

Often suggesting default values that reflect the typical value of a home, car, or insurable component is a good idea.

Default values are typically fine for most users, and they prevent users from making what are often widely inaccurate guesses about the value of some insurable component (e.g., a roof).

Additionally, visual aids in Insurance were observed to benefit users — for example, showing types of roofs rather than only listing them in text (e.g., “tile”, “slate”, “concrete”, etc.).

Providing users with the information they need to make informed inputs during the quote flow will help achieve a more accurate estimate, benefiting both the site and the user.

The Interaction UX of the Insurance Quote Flow Can Bring Users to a Halt

The insurance quote flow is the centerpiece of most users’ journeys on Insurance sites.

The quote flow is typically a form that includes a series of questions users must respond to to determine the coverage they should purchase (or even if they’re eligible at all for purchasing coverage).

“It just keeps taking me back to this.” This participant on Allstate saw that her name had incorrectly populated as “Hannah Hannah [Last Name]”, so she clicked on the browser’s “Back” button to correct it (first image). The quote page did not respond to her “Back” button click, and so she clicked the “Allstate” logo, which took her back to the homepage and restarted the quote process (second image).

During testing, participants were observed to stumble often during the flow, with some disruptions so severe they led directly to a participant abandoning the site.

For example, if a user has invested 20 minutes in filling out an insurance form — only to get stuck entering data into a particular field, experience trouble going back in the flow, or run into an error that clears some previously entered data — the user is likely to simply give up in frustration.

In short, unlike in general ecommerce, where users may be more forgiving of interaction UX issues or glitches in relatively short checkouts, issues experienced by users during the quote flow process quickly compound to the degree that users will abandon the process entirely.

Moreover, users rely heavily on navigation and being guided through the quote flow in such a way that they can understand each step of the process and feel oriented while progressing through it.

Thus, it’s important to support users within this flow.

“Oh, too late now…I guess I can go back. Can I go back? I can go back.” This participant at Liberty Mutual was able to move to the previous step using the site’s on-page “Back” button, and the button shows several of the qualities that allow for findability. It appears in parallel with the site’s “Save & Continue” button, it contrasts effectively with the content around it in size and color, and it was consistently placed at the bottom of Liberty Mutual’s quote flow pages.

Likewise, Liberty Mutual’s “Add” and “Edit” links were easy for participants to find at the right margin of each coverage type (first image). Note the large, prominent button and the inclusion of “Edit” or “Add”, which immediately signifies to users that this is where they click to change their coverage. Activating the links opened a modal (second image).

This would include, for example, ensuring the “Back” button works as they would expect, that they are allowed to edit any details they provide at the point that they supply that information, and that there is an updated cost summary visible at each stage.

Furthermore, to save users wasting time and effort if they are not eligible for the cover they need, they should be informed of this blocker at the earliest opportunity, so they don’t even bother entering a quote flow for an insurance product they ultimately can’t purchase.

Users Struggle to Trust Insurance Brands

“Wow! None of these companies I’ve ever heard of…I’ll tell you, I wouldn’t call any of these people…Here’s your bottom of the barrel…’National General’. The ugly stepchild [of Allstate], so to speak…It’s the same with this ‘Bristol [West]’ company, ‘Dairyland’…I don’t know who they are…” This participant on Travelers’ Insuramatch aggregator system (iOS) equated unfamiliarity of insurance companies with low quality.

“’227’ seems a bit high for a site that’s not in the forefront of my mind. I’m not too familiar with it. I don’t know how popular it is with others, but for me, it’s a step below the others, just because I don’t have an experience or a history with them. I want something that’s been established.” As this participant showed on Lemonade (iOS), users are often unlikely to pay premium prices for an unfamiliar company’s insurance plan. As the participant noted, unfamiliar insurers are automatically seen as “a step below the others”.

Finally, trust and transparency are especially important for insurance customers.

Insurance can be costly, and the repercussions of buying a policy that doesn’t provide the expected coverage could be severe in the event of having to make a claim.

“So, for me that would stand out quite quickly…If a company or a brand have a good Defaqto score, then that would give me more confidence to want to shop with them. Knowing they’re 5-star rated, and just being reviewed by Defacto. I think that means it’s quite a reputable company.” This participant read about Aviva’s 5-star rating from Defaqto, which was featured front and center on the homepage. This gave him confidence in the company as he went on to shop Aviva’s home insurance.

Thus, external validation for both the company and its products is crucial, especially since users are likely to consider several providers before settling on one and could be swayed by another provider that seems to be more trustworthy.

This participant’s Insure and Go quote journey was 20 minutes, and four of those were spent learning the cost of one add-on and returning to her place. The participant saw the “Hazardous Activities” add-on and was interested that, according to her, “They actually say it’s covered for free”. She selected the add-on (first image) and in the next step saw her updated cost (second image) and recognized, “It’s actually £115 now, whereas it was like £56, £58? Something like that”. She decided to remove it from her quote. Getting from the add-on to the updated cost took 54 seconds, and the participant then spent another three minutes backtracking through loading screens and review steps to the page where she could remove the add-on.

Trust must also be earned in the process of getting a quote.

Across general ecommerce sites, 40% of users abandoned checkout because of extra costs that surfaced late in the journey.

Unexpected price changes have the same effect on users seeking insurance cover, so every cost should be disclosed upfront before users actually choose it so that they aren’t forced to recalculate premiums, or even worse, don’t know why the price suddenly jumped as they proceed through the quote process (see guidelines #3108 and #3105).

Provide Insurance Users with a Solid UX Foundation

“I don’t want to create an account…I’m gonna get constantly hounded…Also having another account out there that can potentially get hacked. This one has my driver’s license number, it has more proprietary information.” Some participants who abandoned Root referenced their concerns about data security as a reason for leaving the site when they were forced to “Create an account to save your progress”.

Insurance sites, perhaps uniquely in ecommerce, may have one shot to get it right with users.

Users are less likely to return to an Insurance site where they’ve struggled to achieve their goals.

And once users leave, if they find a competing insurance product, they’re more likely to stick with that product for longer, compared to general ecommerce, given the “buy it and forget it” mentality some users will adopt when shopping for insurance.

Therefore, it’s key that the Insurance site has high-performing UX that supports users navigating unfamiliar concepts, challenging quote flows, and brand-trust issues.

Our Insurance UX research topic contains the critical UX research that helps ensure your Insurance site is meeting users’ needs.

Users with access to the Insurance industry can start with the 41 “Essential” UX guidelines, before moving on to consider the other 150+ guidelines on improving Insurance UX.

Additionally, consider viewing our Insurance benchmark, which contains case studies on 7 top Insurance sites.

Getting access: all 190+ Insurance UX guidelines are available today within Baymard. (If you already have access through your account, open the Insurance study.)

If you want to know how your Insurance desktop and mobile site performs and compares, then learn more about getting Baymard to conduct an Insurance UX Audit of your site.

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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 call now

What the Calculator Outputs Reveal

Once your inputs are applied, the calculator provides clear projections broken down by total impact and site area.

• Annual recoverable revenue range: You will see a range (low, midpoint, and high) of annualized dollar value currently suppressed by UX friction
• Breakdown by UX theme: You can pinpoint where the largest financial gains are (for example, in checkout design, mobile navigation, or product detail pages)
• Plan tier impact: The output illustrates how expanding your access to additional Baymard guidelines unlocks cumulative revenue potential across your roadmap

How the Opportunity Sizing Tool Calculates Recoverable Revenue

The calculator projects potential conversion lifts by applying parameters derived from 200,000+ hours of UX testing across 40+ ecommerce industries.

Business Performance Inputs

To generate a baseline projection, the calculator evaluates your site’s monthly traffic alongside one of two standard performance metrics:

• Option A: Revenue per Visitor (RPV)
• Option B: Average Order Value (AOV) combined with Conversion Rate (CVR)

The tool also takes into account your industry to anchor the calculations to relevant benchmark data.

Standardized Guideline Scoring

Every UX best practice guideline in Baymard’s catalog carries an estimated lift based on two core factors:

1. Frequency of encounter: The percentage of users who interact with the problematic UI component
2. Severity of friction: The conversion impact observed during user testing when a site violates the guideline

Quantifying the individual guideline allows us to quantify the opportunity size for each UX theme, and for each Baymard subscription plan.

That means we can help you decide on the best plan for your team and organization, and show the ROI you can expect from implementing best practices available within that plan.

Compounding Fixes with Diminishing Returns

Fixing two separate UX issues on a website does not produce simple additive results.

For example, resolving an issue in the cart improves the baseline performance of the site, and any subsequent fix in the checkout flow operates on that newly improved baseline.

The calculator applies a compounding model to reflect diminishing returns, ensuring that combined projections remain mathematically grounded rather than artificially stacked.

Applied Revenue Caps

Even a complete overhaul of every UX issue will not double a site’s conversion rate overnight. There is a practical ceiling to the impact of usability improvements alone.

To maintain realistic financial projections, the methodology applies standard cap models to total revenue lift, preventing the opportunity size from being overinflated:

• Conservative (low): 15% revenue lift cap
• Baseline (midpoint): 25% revenue lift cap
• Aggressive (high): 35% revenue lift cap

Find Out How Much Revenue Your Site Is Leaving Behind

Leaving standard UX best practices unaddressed directly suppresses your revenue performance.

Stop guessing what drives conversion, and get the dollar values to back up your design recommendations.

Book a short call with our team to run your metrics through the Opportunity Sizing Calculator and get a personalized report for your site.

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• UX-Ray 2.0: Research-Backed UX To-Do List in Minutes
• UX-Query - Get Instant Answers to Any UX Question
• Product Page UX 2026: 10 Pitfalls and Best Practices
• Accounts & Self-Service UX 2025: 5 Common Pitfalls & Best Practices
• Checkout UX 2025: 10 Pitfalls and Best Practices
• Homepage and Category Navigation UX 2025: 67% of Mobile Sites Have Mediocre-to-Poor Performance
• Product List UX 2025: 8 Common Pitfalls & Best Practices (80% Have Serious Issues)
• Mobile UX Trends 2026: 10 Best Practices
• Desktop UX Trends: 10 Common Pitfalls & Best Practices

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

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 almost everything specific to this industry, rather than borrowed from general retail.

Repeat ordering was undersupported despite its importance within the industry.

With no route to past orders from the homepage, and order histories too sparse to identify them by, one of the most common things a customer does here was also one of the least accommodated.

Dietary and customization needs had no supported path at any decision point.

Category-specific filters were absent throughout and customization options went undescribed on the item page, leaving allergy and restriction constraints needlessly difficult to resolve.

Orientation and return paths failed at every step of the ordering flow.

Scope markers, breadcrumbs, and back-paths were missing throughout, so going one level deeper meant losing any reliable way back out.

Furthermore, fulfillment timing and tipping were presented without the detail needed to commit.

For an ecommerce industry built on habitual reordering from a phone, often under time pressure and dietary constraint, these are not refinements but the substance of the task.

As this benchmark shows, with no sites delivering even a “decent” or better overall user experience, there is plenty of room for improvement.

A publicly available overview of the research and benchmark can be found on our Food Delivery & Takeout UX research overview page.

Getting access: all 3,100+ UX performance scores, 1,900+ best practice examples, and the UX insights from researching the Food Delivery & Takeout ecommerce industry are available immediately and in full within Baymard. (If you already have access through an account, open the Food Delivery & Takeout.)

If you want to know how your food delivery or takeout mobile site and app performs and compare, then learn more about getting Baymard to conduct a Food Delivery & Takeout UX audit of your site.

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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 notable shifts since our previous annual study:

• Online return frequency among consumers has steadily declined over the last three years
• High email frequency from specific retailers has overtaken general inbox clutter as the top driver of newsletter unsubscribes
• Loyalty programs have climbed in priority, securing the fourth spot for online account expectations

Online Return Frequency Among Consumers Has Steadily Declined Over the Last Three Years

While more than half of online consumers (52%) report making an online return in the past year, multi-year tracking shows a continuous drop in high-frequency return behaviors since 2024. (See Quantitative Insight #GC054 for an interactive version of this graph alongside key findings and actionable insights).

Online consumers exhibit a clear shift in their shopping habits as multi-year tracking reveals that frequent return rates are steadily declining.

Our latest study shows that 52% of users say they have returned at least one item purchased online in the past 12 months, with 24% returning an item just once and 28% doing so more than once.

Interestingly, tracking these responses over time reveals that the segment of shoppers who say they return items more than once has steadily dropped from 44% in 2024, down to 34% in 2025, and hitting a low of 28% this year.

Adding to this, the percentage of online shoppers who report that they haven’t returned any items over the past year has climbed significantly, rising from 26% in 2024 up to 44% in our latest data.

This multi-year decline in return frequency suggests that either retailers’ optimization tools and smarter shopping habits are successfully minimizing incorrect purchases, or consumers are simply keeping wrong items to avoid the growing frustration with restrictive return windows and added fees.

From a strategic standpoint, it’s therefore critical to minimize any unnecessary friction by ensuring return policies are highly visible and easy to understand before a user reaches checkout.

See Quantitative Insight #GC054 for an interactive version of this graph alongside key findings and actionable insights.

Retailer Overcommunication Becomes the Leading Catalyst for Newsletter Unsubscribes

While overall inbox clutter remains a challenge, 48% of surveyed shoppers report unsubscribing because emails arrive too frequently from a single specific retailer. (See Quantitative Insight #GC056 for an interactive version of this graph alongside key findings and actionable insights).

While marketing newsletters remain highly critical customer retention channels, overcommunicating can quickly alienate an engaged audience.

The primary driver of customer churn has shifted since our last study, as 48% of users now say they choose to unsubscribe because marketing emails simply come too often from a specific retailer.

General inbox saturation follows closely behind on the chart, with 46% of respondents reporting that they receive too many newsletter emails in general across the collective volume of brands they follow.

Adding to this, content quality continues to heavily influence audience retention, given that 44% of users report unsubscribing because they ultimately lose interest in the newsletter content itself.

This inversion of the top two choices demonstrates that consumers are becoming less tolerant of high-frequency cadences from individual brands, making individual cadence management a higher priority than general email volume.

From a strategic standpoint, it’s therefore important to move away from binary all-or-nothing opt-outs and instead let users control email frequency through granular cadence adjustments in a dedicated preference center.

See Quantitative Insight #GC056 for an interactive version of this graph alongside key findings and actionable insights.

Loyalty Program Shifts Upward in Account Feature Priorities

While order tracking remains the dominant priority for 51% of shoppers, 24% say loyalty programs are a high-priority feature, moving it up into the fourth spot overall. (See Quantitative Insight #GC051 for an interactive version of this graph alongside key findings and actionable insights).

Shoppers continue to view customer accounts primarily as hubs for post-purchase utility, but their relative feature priorities are changing.

As expected, logistical tracking remains the highest-priority requirement, with 51% of respondents saying that checking order status or delivery tracking is one of the most important account features an ecommerce site can offer.

Additionally, managing payment options outside the checkout flow remains vital, with 30% of shoppers reporting that they want the ability to maintain their saved credit cards independently, while 26% prioritize reviewing past order history.

When looking closely at this chart, the most notable shift from last year is that 24% of users now report that loyalty programs are a high-priority account feature, reflecting its steady increase in importance to online consumers.

This indicates that post-purchase dashboards serve an increasingly valuable secondary purpose as a centralized portal for managing brand incentives and ongoing rewards status.

To align with this shifting user expectation, ecommerce platforms should ensure that loyalty point balances, point earning history, and available rewards are integrated directly into the main account dashboard view rather than buried in secondary submenus.

See Quantitative Insight #GC051 for an interactive version of this graph alongside key findings and actionable insights.

20+ Quantitative Insights to Inform General Ecommerce UX Improvements

In addition to the 3 insights presented here, all 20+ general ecommerce UX survey insights are available on Baymard along with our Quantitative Insights for Loyalty and other industry-specific studies.

These are just 3 of the insights from our general ecommerce quantitative study.

Explore the full set of insights to build an in-depth picture of how general ecommerce shoppers behave and what they expect online.

Pair these insights with our 700+ UX guidelines based on observed user behavior to ground your UX design decisions in both behavioral research and survey data.

Note that we also offer industry-specific Quantitative Insights for Flight Booking & Airlines, Apparel & Accessories, Furniture & Home Decor, and Home & Hardware ecommerce shoppers.

Getting access: all 20+ general ecommerce quantitative insights are available now within Baymard. (Already have an account? Go directly to the general ecommerce quantitative study).

To find out how your ecommerce desktop site, mobile site, or app performs against industry benchmarks, learn more about a Baymard UX audit of your site or app.

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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

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 with complex eligibility rules and layered cost structures — placing added pressure on clarity and structure throughout the user journey.

Most sites provided strong initial navigation and product descriptions, but many failed to support decision-making where it mattered most: in the Plan Matrix and during application.

The Plan Matrix, a critical comparison tool, was frequently hindered by dense layouts, missing feature links, and a lack of supporting tools like FAQs or live chat.

Meanwhile, the application flow often broke down due to vague pricing, unclear progress indicators, and form-level friction.

Collectively, these issues undermined users’ ability to confidently select and apply for services, despite the relatively small product catalog.

For most ISP sites, improving clarity, guidance, and transparency in these high-stakes areas would yield significant UX gains.

As this benchmark shows, with no sites delivering even a “decent” or better overall user experience, there is plenty of room for improvement.

A publicly available overview of the research and benchmark can be found on our Internet Service Providers UX research overview page.

Getting access: all 1,700+ UX performance scores, 1,100+ best practice examples, and the UX insights from researching the Internet Service Providers ecommerce industry are available immediately and in full within Baymard. (If you already have access through an account, open the Internet Service Providers UX Benchmark collection.)

If you want to know how your ISP desktop and mobile sites perform and compare, then learn more about getting Baymard to conduct a Internet Service Providers UX audit of your site.

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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 shift the focus away from what a research subscription costs, and instead look at how much you save by having instant access to prevalidated, ready-to-go UX research.

Let’s look at the math. To produce a single standard moderated usability study with 15 participants, your team will spend an average of 55 hours of labor to plan, execute, and analyze it.

When you factor in regional hourly labor rates and participant incentives (around $85 per person in the UK and Europe; $100 per person in the US), the true cost of generating your own insights becomes clear:

To generate a single UX insight, the cost is $362 in the US, and $262 in the UK and Europe.

Note: These calculations focus strictly on your cost of producing the research itself (Labor Hours × Cost Per Hour + Incentives, divided by an average of 15 insights generated per study). This specific calculation does not address the value of implementing the insights (like your conversion rate uplift), but focuses entirely on what you save by bypassing bespoke research.

What Cost Savings Do Key Ecommerce Industries See?

Our calculator shows that the average ecommerce business (across 35+ industries) realizes up to 715% in net savings with a Baymard subscription, compared to the equivalent in-house research cost.

Here are the average number of insights consumed across the average ecommerce site from several key industries:

• Retail ~60 unique insights consumed per year
• Apparel & Fashion ~53 unique insights consumed per year
• Automotive ~44 unique insights consumed per year
• Finance ~49 unique insights consumed per year
• Health & Wellness ~48 unique insights consumed per year
• Telco ~55 unique insights consumed per year
• Travel ~52 unique insights consumed per year

Discover Your Tailored Cost Savings

To help you calculate exactly how much your specific organization can save, we have developed a Baymard cost-savings calculator.

Instead of guessing, we use real-world data from over 1,200 accounts across various industries to map out your exact financial baseline.

To keep the data credible, we only track unique insights consumed within an account — requiring a team member to spend a minimum of 45 seconds on an insight for it to count toward your savings.

If the same insight is visited again, it won’t count again, which helps to keep the saving calculation conservative and reliable.

Depending on where you are in your UX journey, we can map out two distinct scenarios for you.

If You Are New to Baymard’s Research

We will calculate the average unique insights you need to leverage in year one to completely break even.

You will see the exact equivalent cost of trying to build that research in-house, alongside your projected annual net savings and net savings percentage.

If You Are an Existing Baymard Customer

We will calculate the average unique insights you need to leverage in year one to completely break even.

You will see the exact equivalent cost of trying to build that research in-house, plus a definitive look at the net savings and cost savings you have already realized to date.

This gives you the exact data you need to confidently justify your budget to your stakeholders.

See Your Custom Cost-Savings Breakdown

When it comes to UX research, you can protect your team’s valuable time by avoiding reinventing the wheel.

By leveraging existing, pre-validated industry UX best practices, you can bypass the overheads, protect your resources, and ship higher-converting designs faster.

Let’s look at your numbers together.

Book a call with our team today to run your personalized calculation and see exactly how much time and budget you can save.

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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 least one airline loyalty program
• Business travelers are more likely to bundle travel-related bookings

Flight Shoppers Use a Variety of Sources When Looking for Flights

Airline-owned channels like websites (50%) and apps (29%) dominate flight search, but online travel agencies remain well utilized at 38%. (See Quantitative Insight #FB017 for an interactive version of this graph alongside key findings and actionable insights).

Flight shoppers often have to weigh a variety of complex factors when searching for a flight and therefore, look to multiple sources and tools to do so — sometimes more than one.

According to our survey, airline-owned channels dominate flight search, with airline websites being by far the most used source by flight shoppers in their last purchase (50%).

Combined with airline mobile apps (another 29%), this suggests strong brand trust and preference for direct booking.

That said, online travel agencies (OTAs) remain the second-most-used resource at 38%, and aggregators such as Google Flights and Kayak are used by 23% of respondents.

Loyalty programs are also more significant in this industry, with 19% saying that they search their travel rewards or loyalty portal.

All of this suggests that flight shoppers have a broad spread of sources to search for options.

These findings also indicate that shoppers tend to look in more than one place, not necessarily just the direct airline source, underscoring the importance of a strong, prioritized search experience on a site or app’s homepage.

If the search function’s discoverability, autocomplete suggestions, or search results are not clear, users are likely to continue looking elsewhere.

Similarly, as flight shoppers consider and compare various factors, it’s important that pricing is clear across lists and search results, alongside other consistent and comparable attributes, including loyalty points and rewards balances when appropriate.

If users are not provided with clear, relevant, and comprehensive information right away, other sites or services will provide it for them.

See Quantitative Insight #FB017 for an interactive version of this chart alongside key findings and actionable insights.

Three Quarters of Flight Shoppers Are Part of at Least One Airline Loyalty Program

Membership in airline loyalty programs is common among travelers surveyed, with 78% saying they belong to at least one program, higher than the 60% seen in general B2C ecommerce. (See Quantitative Insight #FB046 for an interactive version of this graph alongside key findings and actionable insights).

Loyalty program participation differs across industries, but flight shopping may be among the most widely used.

Our survey shows that membership in airline loyalty programs is very high among travelers, with 78% saying they belong to at least one program, notably higher than the 60% seen in general B2C ecommerce.

Single-airline loyalty dominates the landscape, as 42% of respondents say they belong to a program for just one airline, outpacing multi-airline members (27%) by a wide margin and suggesting most shoppers focus on a primary loyalty relationship.

That said, a meaningful share of members remain disengaged, with 9% saying they belong to a program but do not actively use it, indicating that enrollment alone does not translate to meaningful participation.

With this high adoption rate in mind, information about loyalty programs should be top of mind across the entire flight shopping experience.

The platform should show the points and rewards balance on the user’s account, with the value of the program being prominently highlighted.

Other communication channels, such as loyalty emails, should also include points and reward balances, and a history of earned and redeemed points should also be easily accessible to communicate the continued value of returning to a particular airline or service.

See Quantitative Insight #FB046 for an interactive version of this graph alongside key findings and actionable insights.

Business Travelers Are More Likely to Bundle Travel-Related Bookings

Hotels are the most commonly co-booked add-on for both business and leisure travelers, but business travelers say they co-book hotels at a substantially higher rate (56%) than leisure travelers (35%). (See Quantitative Insight #FB026B for an interactive version of this graph alongside key findings and actionable insights).

Flight shoppers in our survey exhibited a tendency to “bundle” their most recent flight purchase with other travel-related bookings at the same time, including hotels, rental cars, travel insurance, or airport parking.

Interestingly, the frequency of this behavior differs depending on whether the trip was for business or leisure.

Hotels are the most commonly reported co-booked add-on for both business and leisure travelers, but business travelers co-book hotels at a substantially higher rate (56%) than leisure travelers (35%).

Adding to this, business travelers are more likely than leisure travelers to add a rental car (40% vs. 22%), travel insurance (26% vs. 14%), as well as airport transfers or parking (26% vs. 13%).

With that, nearly half of leisure travelers (46%) report making no additional bookings alongside their flight compared to only 18% of business travelers, indicating that leisure travelers are more likely to book travel components separately rather than all at once.

From a strategic standpoint, it’s therefore important to offer bundling cross-sells contextually.

Promotions and special offers should be made visible by default, but they shouldn’t be pushed too aggressively, and they may hold more relevance if targeted towards business flyers over leisure flyers, for example.

See Quantitative Insight #FB026B for an interactive version of this graph alongside key findings and actionable insights.

34 Quantitative Insights to Inform Flight Booking & Airlines UX Improvements

In addition to the 3 insights presented here, all 34 Flight Booking & Airlines UX survey insights are available on Baymard along with our Quantitative Insights for general ecommerce on Awareness & Product Discovery, Consideration & Purchase Behavior, Checkout & Post-Purchase, Loyalty, and other industry-specific studies.

These are just 3 of the insights from our Flight Booking & Airlines quantitative study.

Explore all 34 insights to get an in-depth understanding of the habits and preferences of flight shopping and airline shoppers online.

Use these insights along with our Flight Booking & Airlines UX guidelines based on observed user behavior to inform your UX design decisions for your Flight Booking & Airlines ecommerce store.

Note that we also offer Quantitative Insights for general ecommerce on Awareness & Product Discovery, Consideration & Purchase Behavior, Checkout & Post-Purchase, and Loyalty, many of which are also relevant to Flight booking & Airlines sites.

Getting access: all 30+ Flight Booking & Airlines quantitative insights are available today within Baymard. (If you already have access through an account, open the Flight Booking & Airlines quantitative study).

If you want to know how your Flight Booking & Airlines desktop and mobile site performs and compares, then learn more about getting Baymard to conduct a Flight Booking & Airlines UX audit of your site.

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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 barrier to loyalty enrollment
• Customer reviews serve as a proxy for fit evaluation in ways that go beyond general social proof

How Apparel Shoppers Describe Their Own Size Often Differs from Industry Definitions

Only 24% of female and 14% of male apparel shoppers self-identify as plus-size, despite the fact that common industry sizing standards put a majority of U.S. adults in that size category (see Quantitative Insight #AA037 for an interactive version of this graph alongside key findings and actionable insights).

Apparel shoppers carry a mental model of their own size, but that model doesn’t always align with the categories retailers use to organize their sites.

Despite the fact that common industry sizing standards classify a majority of U.S. adults as plus-size (size 14+), only 24% of female and 14% of male apparel shoppers in our survey say they identify as plus-size.

Most of the remaining female respondents describe themselves as shopping in standard sizing (48%), petite (16%), or short (4%), while male shoppers are more concentrated in standard sizing (63%).

This isn’t simply a question of label preference: Shoppers who don’t identify with industry-defined size categories are less likely to find or follow navigation paths, filter labels, and size-related copy built around those categories.

An apparel site that organizes all plus-size discovery around the term “plus-size” may be structuring a path that a large portion of its intended audience doesn’t recognize as their own.

Apparel & Accessories sites that offer extended sizing should therefore ensure that size discovery doesn’t depend on shoppers self-identifying with any single label.

Inclusive size filters, on-model imagery that reflects a range of body types across product pages and list thumbnails, and size guidance that helps shoppers find their fit regardless of how they describe themselves can all support this goal (see Quantitative Insight #AA037).

Infrequent Shopping Is the Most Commonly-Reported Barrier to Joining Loyalty Programs

Not shopping at a given retailer frequently enough (38%) is the top reason apparel and accessories shoppers say they haven’t enrolled in a loyalty program, ahead of email concerns (31%) and skepticism about value (26%) (see Quantitative Insight #AA039 for an interactive version of this graph alongside key findings and actionable insights).

For many apparel and accessories shoppers, loyalty enrollment comes down to a simple question: Do I shop here enough for this to be worth it?

Most of the time, the answer is no.

Not shopping at a given retailer frequently enough (38%) is the most common reason apparel and accessories shoppers say they haven’t joined any loyalty or rewards program, ahead of concerns about email overload (31%), not wanting to manage another account (26%), and feeling that the rewards aren’t worth it (26%).

Unlike categories where shoppers return to the same retailer out of convenience or necessity, apparel purchases are often distributed across many brands and sites.

A shopper may visit a given retailer once or twice a year and find genuine value in those purchases, but still not consider themselves a frequent enough customer to make enrollment feel worthwhile.

For UX teams, this means that the sign-up prompt itself carries more weight than it might in other categories.

Timing, framing, and the immediacy of the value offered all affect whether a shopper decides membership is relevant to them.

Sites that communicate loyalty benefits clearly, give shoppers control over email preferences upfront, and offer immediate value at enrollment are better positioned to convert occasional visitors into members (see Quantitative Insight #AA039).

Beyond Quality Concerns, Reviews Help Resolve Fit Uncertainty

Apparel and accessories shoppers use customer reviews primarily to resolve fit uncertainty, with size accuracy and fit details (48%) ranking well ahead of quality, durability, and other concerns (see Quantitative Insight #AA061 for an interactive version of this graph alongside key findings and actionable insights).

Customer reviews serve a distinct function in Apparel & Accessories compared to most other categories.

In categories where a product’s qualities are largely fixed and visible, reviews primarily help shoppers assess quality and reliability.

In apparel and accessories, they do something more specific in addition: they serve as a substitute for the fitting room.

Size accuracy and fit details (48%) are the most sought-after information in customer reviews among apparel and accessories shoppers, ahead of quality and durability over time (43%), problems or complaints (40%), and value for the money (36%).

Shoppers aren’t just turning to reviews for a general picture of a product’s merits — they’re looking for evidence that it will fit, from people who can peak from experience in a way that product descriptions and size charts cannot.

This behavior makes sense given the category’s core challenge: Without the ability to try items on, shoppers face a form of uncertainty that brand-provided content addresses only partially.

A size chart tells shoppers what the measurements are, and a reviewer who shares an image along with their height, weight, and the size they ordered shows them how those measurements translate in practice.

Therefore, Apparel & Accessories sites should treat fit-related review content as a primary feature rather than a secondary one.

Surfacing fit feedback prominently, providing a fit subscore within the reviews section, and encouraging reviewers to share images and sizing details can all help close the gap between what shoppers need to know and what product pages currently provide (see Quantitative Insight #AA061).

40+ Quantitative Insights to Inform Apparel & Accessories UX Improvements

In addition to the 3 insights presented here, all 40+ Apparel & Accessories UX survey insights are available on Baymard along with our Quantitative Insights for general ecommerce on Awareness & Product Discovery, Consideration & Purchase Behavior, Checkout & Post-Purchase, Loyalty, and other industry-specific studies.

These are just 3 of the insights from our Apparel & Accessories quantitative study.

Explore the full set of insights to build an in-depth picture of how apparel and accessories shoppers behave and what they expect online.

Pair these insights with our Apparel & Accessories UX guidelines based on observed user behavior to ground your UX design decisions in both behavioral research and survey data.

We also offer Quantitative Insights for general ecommerce on Awareness & Product Discovery, Consideration & Purchase Behavior, Checkout & Post-Purchase, and Loyalty, many of which apply directly to Apparel & Accessories sites.

Getting access: all 40+ Apparel & Accessories quantitative insights are available now within Baymard. (Already have an account? Go directly to the Apparel & Accessories quantitative study).

To find out how your apparel and accessories desktop and mobile site performs against industry benchmarks, learn more about a Baymard Apparel & Accessories UX audit of your site.

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