Industries · Apparel & Fashion

Review Software for Apparel & Fashion Brands

Review software for apparel and fashion brands is post-purchase review automation built to capture the sizing and fit feedback that drives apparel purchase decisions. In apparel and fashion, sizing and fit reviews are the purchase decision. Before a shopper adds a pair of joggers or a summer dress to cart, they're reading reviews for phrases like 'runs small,' 'true to size,' 'fits as described,' or 'order a size up.' A listing without that vocabulary — without enough reviews to establish a sizing consensus — loses the conversion.

GetReviews helps fashion brands build that review base systematically. A post-purchase survey engages every customer after delivery, routes sizing and quality concerns to support before they become public 1-star ratings, and guides satisfied customers toward leaving a detailed Amazon review. One fashion brand grew review volume from 299 to 689 — a 130% increase — while improving their average rating from 3.78 to 4.65 stars.

Every account includes Amazon Request a Review automation, QR code insert campaigns for packaging and tags, and AI review insights that surface what customers are saying about fit, fabric quality, color accuracy, and sizing consistency.

Built For Fashion Brands Selling

GetReviews works across apparel and fashion categories:

  • Clothing and casualwear brands
  • Activewear and athletic apparel
  • Shoes, bags, and accessories
  • Boutique and DTC fashion brands
  • Streetwear and lifestyle brands
  • Luxury and premium apparel
  • Body tape, shapewear, and intimates

Why Fashion Brands Choose GetReviews.ai

  • Build the sizing consensus that converts — 'true to size' reviews that eliminate the hesitation before purchase
  • Route fit complaints and exchange requests to support before they become public reviews
  • QR code inserts in packaging or on tags — reach customers at unboxing or at first wear
  • AI review insights that flag recurring sizing inconsistencies, color accuracy complaints, or fabric issues
  • Amazon Request a Review automation on every eligible order
  • Improve average ratings over time by capturing and resolving issues that cause low-star reviews
  • Works across Amazon, Shopify, DTC storefronts, and other channels fashion brands sell on

What's Included

  • Post-purchase survey engine with fit and quality-specific questions
  • Customer support routing — route sizing and fit complaints privately
  • QR code insert builder — works for hang tags, packaging inserts, and tissue paper cards
  • Amazon Request a Review automation — compliant, automated
  • AI review summaries — surface sizing feedback, color accuracy notes, and quality patterns by SKU
  • Giveaway and loyalty flows for repeat purchase brands
  • Multi-marketplace review collection — Amazon, Shopify, and more

Reviews that say 'true to size, great quality' win the conversion. GetReviews builds that library.

The Fashion Review Problem — and the Case Study That Illustrates It

Fashion and apparel have a unique review problem. The customers most likely to leave a review are the ones who were dissatisfied with the fit — a customer who received a dress that was too small is far more motivated to write about it than a customer who received one that fit perfectly and moved on with their day. The result is a review profile systematically skewed by sizing frustration, even for brands with genuinely good products.

The GetReviews post-purchase survey interrupts that pattern. After delivery, every customer receives a survey that asks about their experience — fit, quality, color accuracy, and overall satisfaction. Customers who had a fit issue are routed directly to your support team, where a simple exchange or size guidance response often turns the interaction positive. Customers who are satisfied with the fit and quality are directed toward leaving a review that captures exactly the 'true to size' or 'fits as described' language that other shoppers need to convert.

A fashion brand using GetReviews grew review count from 299 to 689 while improving their average rating from 3.78 to 4.65 stars — a 130% review increase alongside a meaningful rating improvement. That combination reflects what systematic support routing delivers over time: fewer low-star reviews reaching the public, and more authentic positive feedback from satisfied customers who needed a prompt to share their experience.

Learn more: why customers leave negative reviews · compliance center · QR code review funnels

Related Resources

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