"What Size Should I Get?" How to Answer Fit Questions in Chat and Cut Returns on Shopify

Short answer: fit questions are buying signals. Answer them fast with a structured approach: ask for one or two measurements, compare them with your product-specific size chart, add fit notes (runs small, relaxed fit, stretch), and give one clear recommendation. Do it consistently and you convert more hesitant shoppers and reduce returns caused by wrong sizes.

If you sell apparel, shoes, or accessories on Shopify, you already know the message: "I'm 5'5", 130 lbs. Small or medium?" It arrives dozens of times a week. How you answer it affects two of your most important numbers: conversion and returns.

The problem: size uncertainty costs you twice

Before purchase, an unanswered size question often means an abandoned cart. The shopper isn't sure, so they wait, and many never come back.

After purchase, a guessed size often means a return or exchange. Wrong size is widely reported as one of the most common reasons for apparel returns. Each one costs shipping, handling, and sometimes the customer relationship.

Some shoppers "bracket": they buy two sizes and return one. That's a signal that they don't trust your sizing guidance.

Why generic size charts don't solve it

Most stores have a size chart. Shoppers still ask. Why?

• Charts are generic. One chart for every product ignores that a slim-fit shirt and an oversized hoodie fit differently.
• Shoppers don't know their measurements. Many know their height, weight, and usual size in another brand, not their chest circumference.
• Fabric matters. Stretch, shrinkage, and drape change the answer.
• Personal preference matters. "I like a loose fit" changes the recommendation.

A good chat answer bridges the gap between the chart and the person.

A 5-step method for answering fit questions

Step 1: Ask for the minimum useful information

Don't send a long questionnaire. Ask for one or two things:

"Happy to help! What's your height and the size you usually wear in tops?"

Step 2: Use product-specific data

Compare their answer with the size chart for that exact product, plus any fit notes. Keep a "fit notes" field for every product: runs small, true to size, relaxed fit, size down if between sizes.

Step 3: Ask about preference

"Do you prefer a fitted look or something a bit roomier?"

Step 4: Give one clear recommendation, with a reason

"Based on your height and usual size M, I'd go with M in this shirt. It's true to size with a slightly relaxed fit. If you like it more fitted, S would work too."

One primary recommendation reduces hesitation. A short reason builds trust.

Step 5: Reassure about exchanges

"And if it doesn't fit perfectly, exchanges are free within 30 days." (Use your actual policy.)

This removes the final barrier to checkout.

Build a fit knowledge base your team (and AI) can use

Consistency is the hardest part. Different team members give different answers, and nobody remembers which products run small. Fix that with a simple internal resource:

• Size chart per product (not just per category)
• Fit notes from your own testing and from return reasons
• Fabric details: stretch, shrinkage after washing
• Model info: "Model is 5'9" and wears size S"
• Common comparisons: "Fits like brand X's regular cut" only if you've verified it
• Your exchange and return policy in plain language

Review return reasons monthly. If a product is returned for "too small" again and again, update its fit note so future answers improve.

Where AI fits in

Fit questions are repetitive, time-sensitive, and peak in the evening, which makes them a strong match for an AI assistant. But only if it:

• Answers from your size charts and fit notes, not generic guesses
• Asks a follow-up question instead of guessing when information is missing
• Hands off to a person for unusual cases (custom orders, accessibility needs, complaints)

How TaggoAI helps

TaggoAI for Shopify answers sizing and product questions on your store chat, Messenger, Instagram, WhatsApp, and email, 24/7:

• Learns from your own content: product catalog, size charts, fit notes, policies, and website
• Recommends products and variants based on what the shopper tells it, in a natural conversation
• Keeps answers consistent across every channel and every shift
• Hands off with a summary when a question needs a human
• Supports post-purchase too: order lookups and delivery tracking

You choose how much it does on its own. Many stores start with the AI drafting answers for review, then let it auto-reply to common questions once they're comfortable. During the 14-day trial, the first week runs in shadow mode: it drafts, you check.

FAQ

Should I recommend a size if the shopper gives incomplete information?

Ask one follow-up question first, such as height or usual size. If they still can't answer, share the product's fit note and size chart and suggest the more forgiving option, along with your exchange policy.

How do I reduce bracketing (buying two sizes)?

Give confident, product-specific guidance and make exchanges easy. Shoppers bracket when they don't trust the sizing information.

Can an AI assistant really give good sizing advice?

It can give consistent advice based on your size charts and fit notes. Its quality depends on the data you give it, so keep fit notes current and review its answers early on.

Which products should have fit notes first?

Start with your best sellers and the products with the highest return rates for size reasons.

Conclusion

"What size should I get?" isn't a support burden. It's a shopper telling you they want to buy. Ask a little, use product-specific data, recommend clearly, and reassure about exchanges. Do it consistently, day and night, and you'll see fewer abandoned carts and fewer boxes coming back.

Want every fit question answered in seconds? Try TaggoAI for Shopify free for 14 days at taggoai.com.