Most returns happen because the product received does not match what the customer expected. That expectation gap is usually created on the product page. Unclear descriptions, missing dimensions, and inconsistent information across channels make it harder for customers to choose correctly.
This article is written for retailers and e-commerce teams looking to reduce product returns by improving product data accuracy with AI-powered Product Information Management.
Key Takeaways: How to Reduce Product Returns Effectively
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Product returns increase when product data is unclear, outdated, or inconsistent.
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Accurate, structured product information is one of the most effective ways to reduce returns in e-commerce.
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AI helps scale product data accuracy across large catalogues without slowing teams down.
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Product Information Management (PIM) software creates a single, reliable source of product truth.
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AI-powered PIM improves descriptions, images, translations, and data quality checks, lowering return rates over time.
Common Issues Leading to Product Returns
Imagine ordering a jumper described as a “soft wool blend” and receiving an itchy synthetic fabric. Or buying a “compact” device that turns out to be much larger than expected.
These mismatches stem from poor product data on the product detail page and lead to disappointed customers.
By poor product data, we mean:
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Incorrect or incomplete descriptions. Customers expect details like dimensions, materials, or compatibility, but these are often missing or incorrect.
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Outdated content. Old information, like discontinued features or stock availability, leads to confusion.
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Lack of standardisation. Inconsistent terminology across channels frustrates customers.
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Unclear visuals. Low-quality images can mislead buyers about the product’s appearance or size.
For instance, in 2022, 56% of U.S. online shoppers reported returning items because the product didn’t match its description, and in Germany, 47% of consumers said better product details would reduce their returns. Industries such as fashion and electronics are especially vulnerable, with clothing return rates as high as 25%.
Better product data could drastically reduce these numbers.
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Best Ways to Improve Product Data Accuracy to Lower Returns
Improving product data accuracy means removing guesswork from the buying decision.
High-impact actions include:
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defining mandatory attributes for each product category
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validating dimensions, materials, and technical specifications
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checking descriptions against images and structured data
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flagging missing or conflicting information before products go live
AI can scan entire catalogues continuously and surface issues that manual reviews often miss.
Best Practices for Product Data Management to Reduce Returns
Strong product data management relies on structure, ownership, and control.
Best practices include:
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a single central system for all product information
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clear ownership of attributes and content
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approval workflows before publishing
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version control for updates and changes
Product Information Management systems support these practices by design.
What Are The Top Strategies For Minimising Product Returns?
Reducing product returns starts with addressing these common pitfalls. By eliminating ambiguity, you can set realistic customer expectations and reduce returns.
Here are some actionable steps to consider.
Provide accurate, detailed product information
Accurate and detailed product information helps customers feel confident enough to buy from you, thus reducing the likelihood of returns. Make sure to include:
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Exact measurements and dimensions. Specify size details to avoid misunderstandings about product fit or compatibility.
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Materials and components. Clearly state what the product is made of to set the right expectations.
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Specific uses and care instructions. Explain how to use, maintain, or assemble the product to ensure long-term customer satisfaction.
Use high-quality product images
High-quality product images create a strong first impression and help customers understand what they’re buying. So ensure that your images:
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Show multiple angles and close-up details. Give customers a full view of the product to reduce uncertainty.
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Feature true-to-life colour representation. Avoid surprises by ensuring colours match real-life appearances.
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Provide context for size and scale. Include objects like rulers or models to clearly show product dimensions.
Highlight customer reviews
Customer reviews offer authentic insights that build trust and reduce hesitation. Display them prominently to:
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Showcase real-life experiences. Help potential buyers understand how the product performs in everyday use.
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Address common concerns. Reviews often answer questions that product descriptions can’t fully cover.
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Build credibility and trust. Genuine feedback reassures customers that your product delivers as promised.
Localise product descriptions
Localised product descriptions ensure that customers understand key product details, no matter where they are. Tailor your content by:
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Using region-specific measurements. For example, metric for Europe and imperial for the U.S. to avoid confusion.
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Adapting language and terminology. Speak the same language as your customers by using familiar terms that resonate with them.
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Reflecting cultural preferences. Adjust product descriptions to align with local customs and expectations.
If you're looking to not only reduce your return rates with AI-powered PIM but also boost your ROI, download our free e-book today:
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Popular Solutions for Managing Product Information to Cut Returns
Retailers that successfully cut return rates rarely rely on e-commerce platforms alone.
This challenge is what Product Information Management (PIM) was created to solve. PIM software gives teams control over product data across the entire catalogue and every sales channel. It is designed to handle scale, variation, and change without introducing errors.
PIM systems support return reduction by:
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centralising product attributes and digital assets in one place
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distributing consistent product data across all channels
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managing localisation and translations for different markets
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integrating smoothly with ERP, DAM, and commerce systems
By working from a single, reliable source of product truth, teams reduce duplication, avoid inconsistencies, and prevent the kinds of data errors that lead directly to product returns.
How AI-Powered PIM Supports These Strategies
AI-powered PIM systems combine structure with automation to address the root causes of product returns.
Solutions such as Bluestone PIM bring together centralised data management, DAM capabilities, and AI features that improve product data quality at scale.
Product Data Enrichment at Scale
AI-powered product data enrichment fills in missing details and improves existing attributes automatically. By extracting information such as colour, size, style, and key characteristics from product images and source data, it creates descriptions that reflect the actual product.
This reduces ambiguity on product pages and helps customers understand what they are buying before checkout. Enrichment runs consistently across the catalogue, making it easier to launch new products faster with fewer errors.
Product Data Translation and Localisation
Accurate translations play a direct role in reducing returns, especially for cross-border commerce.
AI-powered translation and localisation generate clear, market-appropriate product information in multiple languages. Content is adapted to local terminology, measurements, and language nuances while keeping tone and brand voice consistent across regions.
This ensures customers receive the same level of clarity and accuracy, regardless of market or channel.
Product Data Analysis and Quality Control
AI-driven product data analysis continuously reviews the catalogue to identify gaps, errors, and inconsistencies.
It flags missing attributes, incorrect descriptions, and misclassified products, helping teams prioritise fixes that have the biggest impact on customer decisions. Each suggestion is backed by confidence scoring, so teams know where to focus first.
Corrections can be automated, but final control remains with the business. Changes are reviewed and approved before publication, ensuring accuracy without sacrificing governance.
Business Benefits of Accurate Product Data Using AI-Powered PIM
Inaccurate product data does more than drive returns. It damages trust and long-term revenue.
With AI-powered PIM, retailers see:
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fewer returns through clearer expectations
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higher customer satisfaction and confidence
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lower operational costs through automation
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stronger brand trust across channels
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Product returns are not just a cost line. They signal where product information falls short and where customer expectations break down.
Ready to see the difference? Contact our advisors for a free consultation or book a demo meeting to discover how AI-powered PIM solutions can transform your e-commerce business.
Take control of your product data today and watch your return rates drop.
