Data Decay

In e-commerce, data starts decaying almost immediately as manufacturers update specifications or market trends shift. Industry studies suggest that B2B data decays at a rate of 2% to 3% per month. This means that without active management, nearly a third of your product information could be inaccurate within a single year.

While a PIM cannot stop the real world from changing, it prevents decay from reaching your customers. By centralizing data and using validation rules, a PIM like WISEPIM ensures that only verified and current information is published. It also provides the tools to update thousands of products simultaneously when a change occurs at the source.

The primary risk is the erosion of customer trust. If a buyer receives a product that differs from the online description, it leads to a return and a negative review. Over time, high return rates and poor reviews damage your standing on marketplaces and search engines, leading to lower visibility and higher customer acquisition costs.

You can identify data decay by performing regular data audits and comparing your database against current supplier feeds or master data sources. Start by flagging products that haven't been updated in over six months or those with high return rates due to description mismatches. Once identified, use automated validation rules in your PIM to update or enrich these attributes systematically.

Businesses should ideally schedule deep-dive data audits quarterly, though high-turnover industries like fashion may require monthly checks. Routine automated validation should happen daily as new data is imported from suppliers or ERP systems. Aligning these audits with seasonal product launches ensures your catalog remains accurate when traffic and sales potential are highest.

Pricing, stock levels, and promotional descriptions are the most volatile attributes that decay almost daily. Technical specifications, such as energy ratings or regulatory compliance details, also decay frequently as industry standards and laws evolve. Tracking these specific fields within your PIM allows you to prioritize updates for the information that impacts buying decisions the most.

Search engines prioritize fresh, accurate content, so outdated product descriptions or obsolete technical specs can signal a poor user experience. When attributes like keywords or categories become outdated, your products may no longer match the modern search queries used by consumers. Over time, this lack of relevance results in lower visibility and decreased organic traffic to your product pages.

While often used interchangeably, data decay specifically refers to product information becoming inaccurate because the real-world product or market has changed. For example, a manufacturer might update a warranty or a material list. Data rot, conversely, usually refers to technical degradation like file corruption or broken image links. In e-commerce, decay is more dangerous because the data looks technically correct but provides false information to the shopper, which directly leads to increased returns.

Product Information Managers and Catalog Managers typically own the responsibility for preventing data decay. However, it is a cross-functional effort. Sales teams often spot price discrepancies first, while customer support staff hear about incorrect specifications directly from buyers. In larger organizations, Data Governance Officers set the validation rules, but the daily task of updating attributes usually falls to content teams who monitor supplier updates and market changes to keep the PIM current.

The biggest mistake is treating product data as a one-time project rather than a continuous cycle. Many brands upload a catalog and assume it remains accurate indefinitely. Another pitfall is relying solely on manual spot-checks, which inevitably miss subtle changes across thousands of SKUs. Additionally, failing to synchronize the PIM with external supplier feeds causes decay, as manufacturer updates to materials or compliance standards never reach the storefront, leaving customers with obsolete information.

It does both. Automated feeds reduce decay by pulling real-time updates directly from manufacturers, ensuring your specifications stay current without manual entry. However, if the integration mapping is poorly configured, a supplier’s change in data format can cause errors or empty fields in your system. Successful integration requires regular mapping audits to ensure that the flow of information remains accurate and that your PIM correctly interprets any changes in the external data structures.

Even a store with only ten products faces data decay if those items have seasonal pricing, changing stock levels, or evolving regulatory requirements like energy ratings. While a small catalog is easier to audit manually, the rate at which information changes remains the same. A small business can actually lose a higher percentage of its total revenue to a single inaccurate product description than a giant retailer with millions of items, making decay a universal threat.