Why bad product data is sabotaging your brand — and how to fix it

Why is bad product data bad for business?

As well as being counter-productive, bad product data is a silent revenue killer — and businesses that fail to properly maintain their product data can end up suffering in several different ways.

Fewer searches and lower conversions

As search engines usually prioritize the most well-structured, detailed product listings, incomplete, inaccurate product data can soon result in lower rankings and fewer customers discovering your products. All of this inevitably results in lower conversion rates.

More customer returns and more complaints 

Levels of customer returns and complaints can be negatively impacted when poor product data quality leads to disappointed customers. This ultimately incurs additional costs for the business; including return postage costs, restocking fees, and of course, a loss in revenue.

Damage to your brand reputation 

It doesn’t matter whether a customer has one poor shopping experience or many by interacting with your business; it can quickly lead them to steer well clear of your brand.

Bad experiences with brands today can quickly translate into negative reviews and damaging social posts that only serve to permanently ward others away from dealing with your business.

Why does bad product data happen?

In order to fix the problems with your product data, it’s important to understand where those problems might stem from.

Common culprits include:

• Human errors made during manual data entry: With many businesses still relying on manual, human effort to input and manage product data, errors such as typos, missing attributes, and inconsistent information can occur. Add to this the usage of multiple spreadsheets or outdated systems, and you have a recipe for an even higher error rate.
• Lack of a clear taxonomy and proper data governance: Without clear governance in place, product data can soon become disorganized and inaccurate.
• Product data stored in multiple systems: Data kept in several disconnected systems makes it challenging to maintain accurately. This can lead to incidents of, for example, mismatched product descriptions appearing across live listings.
• Inaccurate data sent from suppliers: Outdated and incomplete information provided by a supplier that isn’t moderated and checked by the business before it’s used can contribute towards higher levels of product listing errors being made.

How to rebuild customer trust and increase revenue with better Product Information Management (PIM)

It’s not just about fixing mistakes in your product data as a one-off exercise. Getting your house in order means being proactive and putting the right foundations in place to ensure that your product data remains accurate and consistent for the long term.

Several strategies can be deployed to help make this happen:

Use a PIM system to centralize and standardize your data.

This type of platform acts as a single source of truth; allowing you to keep product information up-to-date and consistent across all channels.

At its core, a market-leading PIM solution can support how you manage product data by:

• Eliminating duplicated or conflicting product data.
• Enforcing a clear taxonomy and facilitating data governance protocols.
• Ensuring real-time updates occur across your marketplace channels.

A study conducted by the Gartner Market Guide found that businesses using a PIM platform had product data that was, on average, 90% accurate — compared to only 60% for businesses that did not employ a PIM solution.

Invest more time in enhancing your product content

Improving the quality of your product content can often lead to better shopping experiences for customers — and there are many ways you can do this.

• Add rich media content like high-quality images, videos — or even an interactive 360-degree view, if this is appropriate for your product.
• Re-evaluate existing product description copy for better SEO. Make sure that any key benefits and features are highlighted. Enhancing your listings in this way can improve the likelihood of your products being found by search engines.
• Check that any ‘practical’ content elements like sizing charts and technical specifications match the product. This reduces the chance of disappointing or frustrating customers.

Harness automation to help drive better data accuracy

An AI-powered PIM can help businesses automate the validation of product data, the identification of gaps in attribute information, and flag up formatting errors — all factors that can negatively influence buying decisions.

A cutting-edge PIM with AI capabilities can also manage other tasks that would usually require high volumes of manual effort — including consistency checks, enriching data, and assigning attributes.

The most advanced platforms on the market also allow businesses to reconfigure their AI models so that they can serve specific product categories and business needs.

Put continuous feedback loops in place

Utilizing different types of customer insights can be instrumental in driving a process of continuous improvement when it comes to product data.

By monitoring incoming customer reviews, and analyzing qualitative data from sources like support tickets and customer returns, businesses can begin to identify where data inconsistencies and inaccuracies lie.

Putting this kind of system in place is rarely straightforward. It relies on taking a more strategic approach to data integration and refinement — but as stated in the Gartner Market Guide for PIM Solutions in 2025:

“This loopback process is becoming even more critical in remaining competitive and delivering the best product experiences.”

Using an AI-powered PIM can help businesses ‘close the loop’ effectively; correcting and updating information like product attributes and descriptions with more speed and ease.

Eradicate bad product data and set your business up for long-term success

While a build-up of bad product data can spell trouble for your business in several ways, there are actions you can take to help restore trust, improve customer experiences, and boost business revenue.

Investing in better product information management by implementing an AI-powered PIM solution like inriver is key to this; empowering your business to identify and fix errors in product data, streamline internal processes, and unlock new competitive advantages.

In 2025, the Gartner Market Guide recognized inriver’s PIM Solutions as a closed-loop PIM system that can provide data-driven insights that help drive improvements to product content from directly within the platform.