[Digital commerce & conversion]() / [Use cases]() / [Size and fit]() [How it works]() [What you get]() [Scope]() [Start a review]() [Digital commerce & conversion]()[Guidance]() # Give shoppers size confidence that holds after delivery. A size recommendation shoppers can trust, honest about how sure it is, and judged on what stays sold. [Start with a conversion review]() [How it works]() I’m 5’10” and usually a medium. Which size in the Canvas field jacket? Medium, with moderate confidence. Most shoppers your height keep the M. A few size up to layer under it, so if you’ll wear a mid-weight layer, take the L. The size chart has the exact measurements. From past orders and return reasons for this style What the shopper sees: a size, how sure it is, and when to size up. ## Sound familiar? - “True to size?” was asked 27 times about one jacket. - The size chart is correct and still doesn’t help. - The same two sizes keep coming back for exchange. A wrong size costs the return, the shipping both ways and often the customer. ## What changes. ShowTodayWith the engine Advice A size chart and a quiz A recommendation with how sure it is Thin data A confident guess The chart and a range when the data is thin Judging it Quiz completions Contribution after returns and exchanges Claims Fewer returns, promised Measured by size and by product ## How it works. 5 steps, 4 stages. - AI**1** - Rules and automation**3** - Your team**1** - Approval 1. 1 Gather 1. Rules and automation ### Join sizing, orders and return reasons Garment measurements by size, what shoppers kept, exchanged or returned, and why. - Shopify 2. 2 Recommend 1. AI ### Explain a size in plain words Takes height, build and how it will be worn, and returns a size, a confidence level and a reason. 3. 3 Fall back 1. Rules and automation ### Fall back when the data is thin Below a set number of orders for a size, the shopper sees the chart and a range, not a confident guess. 2. Your team Approval ### Tune the rules Category owners set the thresholds and review styles that keep coming back for fit. 4. 4 Judge 1. Rules and automation ### Judge on what stays sold Held-out shoppers, and contribution after returns and exchanges, by product and size. - GrowthBook Return reasons sharpen the next recommendation ## What you get. Real work, every week. Fit data by style **2 of 4**styles with enough data to recommend - Canvas field jacket Enough orders in M and L - Merino crew - Trail pant Waist and inseam: thin data, chart shown - Waxed field jacket Return reasons not tagged Where a recommendation is safe to show. Elsewhere the chart does the job. Exchanged for fit, by size Canvas field jacket - MMost orders **4%**Recommend - LShoppers who layer size up **6%**Recommend - SFew orders **Thin**Show the chart The cohort view the category owner reads each month. ## How you’ll know it’s working. 1. Contribution after returns A size recommendation only helps if the order stays sold. 2. Exchanges and fit returns, by size Shows where the recommendation or the chart is wrong. 3. Repeat purchase A size that fits brings the customer back. Baselines agreed before we build. ## Works with what you have. Commerce - Shopify - True Fit Support - Gorgias We configure first A clear size chart and fit notes drawn from your own return reasons come first. A specialist fit vendor is worth pricing once your data shows a real gap. We build when You have enough orders and return reasons per style to learn from, and fit is a main reason things come back. ## What a first build includes. Built in your accounts, around your team. Scope, fee and baseline agreed before we start. 1. 1 Design 2. 2 Build [Start with a review]() [Scope this build]() ### We build - Garment sizing joined to orders and return reasons - A fit card with a confidence level - A chart fallback for thin data - A readout by product and size ### We start from - Garment measurements by size - Orders and return reasons - Product pages and size charts ### From your team Owner Head of ecommerce, with merchandising Involves - Ecommerce - Merchandising - Customer service - Product development ## Questions teams ask. Will this reduce returns? We can’t promise that. A peer-reviewed 2025 study of a Swedish apparel retailer’s size finder linked its use to slightly higher returns. It was observational, so it can’t show cause. So we measure contribution after returns, by size, on your own orders. Do we need a fit vendor? Not at first. Your own orders and return reasons go a long way. A specialist such as True Fit makes sense when you want its data and the cost is justified, and we’d compare it with the simpler version first. Who owns it once it’s running? You do. It’s built in your accounts, documented, with training for the people who run it. Ownership usually sits with your head of ecommerce, with merchandising. We can keep running it with you, or step back. How do we start? Usually with a conversion review: two to four weeks, a fixed fee credited to the build, and a plan that’s yours. If the job is already clear, we can scope the build directly. ## Part of your conversion engine. One of 14 use cases, in 5 parts. [See the whole conversion engine]() 1. [Evidence & decisions **2**]() 2. [Search & discovery **2**]() 3. [Guidance **4**]() 4. [Cart & checkout **4**]() 5. [Releases **2**]() In guidance - [**Guided shopping**Build a shopping assistant that helps customers choose]() - [**Product page answers**Answer the buying questions your product pages leave open]() - **Size and fit**You’re here - [**Project baskets**Turn “what do I need?” into a complete basket]() Works with - [**Conversion diagnosis**Find what’s costing you sales, and what to fix first]() See it at work - [**Also in**Customer service & support]() ## Help shoppers pick the size they’ll keep. Start with a conversion review. [Start with a conversion review]() [**Talk it through first**15 minutes]() We reply within one business day. --- Source: [https://www.thekeating.co/use-cases/size-fit-confidence/]() [Contact Keating & Co](mailto:nelson@thekeating.co) · [Agent guidance](https://www.thekeating.co/llms.txt)