The two options
Product data structured so a model can judge suitability, not just match filters.
- Buyers ask assistants which product suits them
- Your products have compatibility or fit constraints
- Assistants currently recommend competitors
Cleaning and enriching feeds for ad platforms and comparison engines.
- Shopping ads are a primary channel
- Disapprovals or missing attributes are costing reach
- Comparison engines drive material traffic
How they differ
| Agent-readable feeds | Conventional feed optimisation | |
|---|---|---|
| Consumer of the data | Language models answering questions | Ad platforms and comparison engines |
| Optimises for | Suitability judgements | Matching and filtering |
| Key fields | Fit, constraints, compatibility, context | Title, category, identifiers, availability |
| Measured by | Share of recommendation prompts | Impressions, clicks, disapproval rate |
| Maturity | Emerging | Established |
What actually decides it
The difference comes from what is being asked. A comparison engine filters a catalogue against criteria the shopper selected. An assistant is asked which product suits a described situation, and it needs the information a knowledgeable salesperson would use — what this fits, what it does not, where it falls short. Conventional feeds rarely carry any of that.
This is emerging territory and should be described as such. Agent shopping behaviour is changing quickly, standards are unsettled, and anyone claiming a proven playbook is ahead of the evidence. What is defensible now is making product data genuinely complete and honest, which is robust to whatever the interfaces settle into.
None of this displaces conventional feed hygiene. Disapprovals, missing identifiers and bad categorisation cost real money today in channels that are demonstrably working. Agent readiness is an addition for businesses whose buyers have started asking assistants, not a replacement for the channel currently paying the bills.
Questions
Are shopping agents actually driving purchases yet?
In some categories, at modest volumes that are growing. It is early. The honest position is that this warrants preparation for most retailers and a restructured strategy for very few.
What data do agents need that feeds lack?
Suitability context — what a product fits, what it is incompatible with, where it underperforms, and how it compares. Conventional feeds carry identifiers and attributes, not judgements.
Does this replace conventional feed work?
No. Feed hygiene affects channels that generate revenue today. Agent readiness is additive, and pursuing it while shopping ads are disapproved is the wrong order.
Related services
- Product Feeds for Agents — GEO
- E-commerce SEO — SEO
- Retrieval-Optimized Content — GEO
- GEO Baseline Audit — GEO
Still not sure?
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