Key Takeaways
- Some users have difficulty gauging the overall “fit” in reviews
- Users unable to find useful “fit” info in reviews risk selecting an incorrect size or discarding suitable items
- Yet 33% of sites fail to aggregate “fit” info provided in individual reviews
In Baymard’s large-scale UX testing of Apparel & Accessories, users were observed to predominantly turn to reviews in order to determine how an apparel item fits — for example, whether a pair of pants or a top fits “too small”, “too large”, or “true to size”.
However, several participants in testing had difficulty finding the “fit” info in the user reviews, leading them to incorrectly assess an item’s overall “fit”.
As a result, without a clear way to identify and assess relevant “fit” info in reviews, some users might select the wrong size — or even pass on purchasing an item.
To enable users to efficiently pinpoint an item’s fit, apparel and accessories sites should include an aggregate “fit” subscore in the reviews section.
However, our e-commerce UX benchmark shows that 33% of sites don’t aggregate any “fit” info provided in individual reviews, leading users to — often inaccurately — try to interpret the aggregate score themselves.
This article will discuss our latest Premium research findings on how to present “fit” info in the user reviews:
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Why users have difficulty finding useful “fit” info
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How providing an aggregate “fit” subscore helps users efficiently determine an item’s overall fit
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How providing “fit” info as a structured component for individual reviews helps corroborate the aggregate subscore
Why Users Have Difficulty Finding Useful “Fit” Info
During testing, several participants who approached the reviews to discover the fit of an apparel item were not able to easily pinpoint any “fit” info provided by reviewers.
Some participants therefore attempted to read every review in granular detail in an effort to draw out any “fit” info within.
Even more problematically, participants had to then mentally gauge the overall consensus about “fit” across all the reviews in order to apply the feedback to their size-selection process — a task difficult to accurately perform on the fly.
In particular, in cases where an item had a large number of reviews — one item had 2,155 — participants couldn’t realistically read every review and therefore based their findings about fit on the handful of reviews that they were able to read.
As a result, given that they based their findings on a subset rather than the entirety of reviews, some participants risked incorrectly gauging the overall fit of items.
During testing, some sites did call out “fit” information in individual reviews; for example, including “Fit: true to size / runs large / runs small” as a structured component to each individual review.
However, this forces users intent on knowing the aggregate “fit” subscore for an item to mentally tally up each individual subscore on an invisible continuum from “too small” to “too big”.
By relying on their overall impression of the individual “fit” subscores (not all of which users will bother to read) — rather than on actual calculations — users’ interpretation of the aggregate score will frequently be inaccurate.
How Providing an Aggregate “Fit” Subscore Helps Users Efficiently Determine an Item’s Overall Fit
Therefore, to provide an overview of an apparel product’s fit, it’s important to include an aggregate “fit” subscore in the reviews section.
As one participant indicated, the aggregate “fit” subscore allows one to understand an item’s overall fit at a glance: “Well, I usually would read the reviews if the site didn’t have the thing [aggregate “fit” subscore] that basically said that the customer said it was true to size. So I would usually read the reviews to find out whether they thought they fit true to size.”
An aggregate “fit” subscore saves users the time and effort of having to scan individual reviews for this information — an insurmountable task if there are hundreds of reviews.
During testing, an aggregate subscore represented by a bar chart scale that was rated from “too small” to “too large” (or similar terminology) performed well.
How Providing “Fit” Info as a Structured Component for Individual Reviews Helps Corroborate the Aggregate Subscore
While it might seem redundant to provide both individual “fit” subscores in addition to an aggregate “fit” subscore, testing showed that participants differed in how they liked to digest information provided in reviews.
At one extreme some wanted to quickly get to the point about “fit”, while at the other extreme other participants enjoyed the granular aspect of “researching” all the reviews by reading through each one.
Moreover, users who take note of an aggregate “fit” subscore might still want more context around why specific reviewers rated the fit of an item the way they did.
Without an aggregate “fit” subscore, users will take longer to figure out the fit of an item.
Likewise, only providing the high-level aggregate “fit” subscore will sit uneasily with some users, who will wonder on what evidence the site relied to calculate their score.
Providing the “fit” subscores as a structured component in individual reviews as a means to corroborate the aggregate subscore provides a level of transparency around the reviews that users will appreciate — thus also boosting their trust in the site.
Notably, consider also implementing these review-specific “fit” ratings as bar charts, since text summaries may be overlooked by users.
Help Apparel Users Quickly Determine an Item’s Overall Fit from the User Reviews
As our research has shown, arriving at a useful consensus regarding the feedback about fit in reviews can be a difficult task for users.
By including an aggregate “fit” subscore in the reviews section — and providing individual “fit” subscores in addition — sites can help users efficiently select their correct size.
However, when reviews make it difficult to determine the overall fit at a glance, users are burdened with the unrealistic task of calculating the overall “fit” score on their own.
Yet 33% of sites don’t allow users to easily understand an item’s overall fit — risking that users incorrectly gauge the fit and select the wrong size.
Getting access: Our current Apparel & Accessories research study is ongoing and new Apparel guidelines are published every month in Baymard Premium. The full study is expected to be completed in Fall 2024.
If you want to know how your apparel or accessories desktop site, mobile site, or app performs and compares, then learn more about getting Baymard to conduct an Apparel & Accessories UX Audit of your site or app.