Why AI Search Rewards Problem Descriptions, Not Product Descriptions

By Stefan Hospes - Wednesday July 15, 2026 Share (Twitter) WhatsApp Summarize ChatGPT Perplexity Grok Google AI The State of PPC 2026 asked 1,306 professionals about their biggest challenge in managing product feeds. Over half (54%) percent said data errors and missing product information.

That number has not shifted meaningfully in years and after twelve years of building feed management infrastructure for over 17,000 brands, in my experience, there is one recurring reason – the channels keep moving. Above: The State of PPC Global Report 2026 was released in March 2026 There is now a second reason that is becoming harder to ignore.

The optimization discipline itself is shifting and where performance marketing has traditionally been a creative problem solved by better copy, stronger imagery and sharper bidding, it is increasingly becoming a data infrastructure problem. B2C no longer works – it’s now about B2R (business-to-robot.)

The signals that determine whether a product surfaces in Google Shopping, Performance Max, and increasingly in AI-generated results like Gemini and Perplexity, are not creative signals but technical ones – attribute completeness, feed consistency, and data accuracy.

By fixing their feed quality now, brands are not just solving a maintenance problem but building the foundation that the next generation of agentic commerce discovery runs on. Which brings us back to the plight of the 54%. Amazon requires ten attributes this month and adds five more the next.

European regulatory requirements introduce mandatory fields including product safety documentation and compliance links that can make previously complete feeds non-compliant overnight. Google continuously updates its taxonomy and popularity of channels differs across markets.

Keeping up with changes across multiple channels simultaneously is where most brands lose ground, not because of access to technology but because of the operational discipline required. Start with the foundation When a brand has poor feed quality and needs to improve fast, the approach is always the same, start with the must-dos, not the nice-to-haves.

Most brands trying to fix everything at once end up fixing nothing well. Every channel has a hierarchy of requirements. There are fields that will cause your products to be rejected or suppressed if they are missing or wrong. There are fields that are recommended and will meaningfully improve performance.

Then is a long tail of optional optimizations that matter once the foundation is solid. Get 100% of your products listed and eligible. That single step gets you to roughly 80% of the performance gain available from feed optimization. The fields that do the most work across almost every channel are consistent – titles, descriptions, and core attributes.

A title needs to be long enough to communicate what the product is and who it is for, but shaped to fit how that channel presents listings. A title that works on Google Shopping may be too long for Amazon and too short for a comparison site.

Every channel is unique, and treating them as interchangeable is one of the most common and most costly mistakes in feed management. What completeness looks like is also evolving.

Google recently introduced Conversational Attributes for Merchant Center – six new fields including Question & Answer, Document Link, and Popularity Rank – designed to help AI better understand and surface products. The brands adopting them early are building an advantage as Google continues to expand its AI-driven shopping experiences.

Attribute completeness is not a fixed target but one that moves, and keeping up with it is part of the discipline. The hero and underperformer framework Once your foundation is solid, the next step is performance segmentation. Not all products deserve equal attention and not all optimization work returns equal value.

Look at your catalogue in two dimensions: clicks and revenue. Your heroes are the products with high clicks and strong revenue – these are working. Your underperformers are the products with high clicks but low conversion. These are the ones worth prioritising for content optimization, because the demand signal is already there.

Someone is finding these products and clicking on them but the data is letting them down at the point of decision.

For underperformers, the diagnosis is almost always one of three things – the title is not specific enough to set the right expectation, key attributes are missing so the product appears in too broad a match, or there is an inconsistency in the data. This means there is a price or availability mismatch that is eroding trust at the moment of comparison.

The impact of fixing this can be significant. German retailer Deiters applied this framework during carnival season, using performance segmentation to identify prod