Inaction Carries the Heaviest Price

The retail industry is full of bold promises around AI. Executives are told that conversational commerce, natural-language search, predictive analytics, and recommendation engines will revolutionize the way customers shop. But what often goes unsaid is that these technologies are only as strong as the data foundation beneath them. Without structured, accurate, and complete product data, AI fails to deliver.

For many retailers, the temptation is to delay investment in AI readiness until “later.” Yet postponing action is far from harmless. In fact, the cost of doing nothing can be greater than the cost of building a product data foundation today. From missed revenue to rising returns and wasted investments, retailers who wait risk falling behind in a market that is already moving fast.

Missed Revenue Opportunities

AI-driven retail isn’t just a futuristic vision, it’s already influencing how shoppers discover and buy. Search, recommendations, and PDP performance all benefit from structured product data. Without it, you are leaving revenue on the table.

• Global e-commerce conversion rates average 2–3%, but enriched product pages consistently lift conversion rates by double digit percentages.
• Poor or incomplete product data can push customers to competitors who present clearer, more trustworthy product information.
• In categories where purchase decisions are attribute-driven (size, material, compatibility), incomplete data is the fastest path to lost sales.

By delaying AI readiness, retailers give competitors a head start in capturing more conversions from the same traffic.

Higher Return Rates and Customer Dissatisfaction

Returns are a headache and for too many retailers they're seen as a cost of doing business. But they don't have to be. Many are caused not by product defects but by misaligned expectations created by poor product data.

• Inaccurate attributes (like sizing or material blends) can drive returns up to 28% for certain categories.
• Missing product images or inconsistent visuals erode customer trust and increase “bracketing” behaviors, where shoppers order multiple sizes/colors and return what doesn’t match.
• Poorly written or incomplete descriptions are among the top 3 reasons for cart abandonment.

Retailers who don’t invest in data quality today will continue absorbing higher return rates with each passing day, a cost that eats directly into margins and erodes brand affinity.

Wasted AI Investments

The AI landscape is moving fast, and many retailers are eager to pilot new solutions. But piloting AI on a weak data foundation is like building a skyscraper on sand: failure is inevitable.

• Conversational commerce agents cannot deliver relevant answers without standardized product attributes.
• Recommendation engines cannot make useful suggestions without complete and consistent metadata.
• Search engines and answer engines penalize incomplete schema and missing structured data, limiting visibility.

Investing in AI before investing in data readiness doesn’t just underperform, it actively wastes budget, drains confidence internally, and delays adoption of the very solutions executives are betting on.

Competitive Disadvantage

In a market where speed and differentiation matter, waiting is itself a liability. Competitors who act now will:

• Launch products faster by clearing SKU backlogs.
• Gain first-mover advantage on new AI-driven channels (answer engines, multimodal search).
• Deliver higher-converting PDPs that capture demand more effectively.

Meanwhile, those who wait will find themselves playing catch-up, unable to close the gap without even greater investment later.

The Takeaway: Delay is More Expensive Than Readiness

AI readiness it’s the foundation of every AI initiative in retail. The cost of doing nothing shows up in missed revenue, higher returns, wasted budgets, and lost competitive ground. For senior leaders, the choice is not whether to build a product data foundation, but when. The sooner you act, the faster your AI investments generate ROI and the lower your long-term costs will be.

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