Agentic Commerce
Product feed readiness
Make the catalogue an assistant reads accurate enough that it recommends you rather than working around you. Scoped as its own piece because that is how it is usually bought.
What are you buying when you buy product feed readiness?
Make the catalogue an assistant reads accurate enough that it recommends you rather than working around you. In practice that means merchant Center feed health taken to the level that gates eligibility for Google’s shopping surfaces rather than merely passing validation, and then the harder half: live stock, price and shipping accuracy, because an agent quoting yesterday’s availability sends the buyer elsewhere.
Why this work exists
Put bluntly: the alternative is making decisions on numbers nobody has checked.
It belongs to Agentic Commerce and is described here because it is the piece clients recognise and ask for.
The nearest piece of work to it is surfacing the review themes a model summarises instead of the star average. Where that is already handled, this moves faster than the estimate; where it is not, the two get done together or neither of them holds.
What good looks like
The test is whether somebody outside the team would reach the same conclusion from the same evidence. If they would not, this is not finished.
The gap between that and where most accounts start is why this is scoped as product feed readiness rather than as a line inside something larger. Answering the comparison question in a field rather than in a paragraph is the usual second step once it is in place.
When this is the right work
The tells:
- Merchant Center shows disapprovals nobody has worked through
- Shoppers report prices or availability that do not match the site
- Your products do not appear in assistant answers while competitors with worse products do
If none of those is true, something else is probably the constraint, and the Agentic Commerce overview maps the alternatives. The usual neighbours are monitoring parity continuously, because that is where the trust breaks and treating feed health as a revenue control rather than a maintenance chore.
What the work covers
In order, the work is:
- Merchant Center feed health taken to the level that gates eligibility for Google’s shopping surfaces rather than merely passing validation, revisited rather than finished, because the inputs keep moving.
- Live stock, price and shipping accuracy, because an agent quoting yesterday’s availability sends the buyer elsewhere, usually the first thing to show a result, so it goes early.
- Attribute completeness against the fields assistants actually read, which go well beyond title and price. The effort here scales with the size of the estate, not with the size of the brief.
- Variant and GTIN handling, where most catalogues quietly lose matches. Usually quick; occasionally the thing that reopens the whole scope.
How it runs
Three stages. Most of the risk sits in the first one.
Where the judgement goes
What is left needs a decision rather than a fix. These get taken with whoever owns the consequence, not resolved quietly in a ticket.
Checking it held
Changes get re-checked after a fortnight, because a surprising number of them do not survive the next deployment or the next platform update.
Handing it over
Whatever is left running ends up with a named owner and a schedule, or it stops happening within two months.
What each part runs into
What each part actually contends with:
- Merchant Center feed health taken to the level that gates eligibility for Google’s shopping surfaces rather than merely passing validation, and in Delhi NCR the constraint on it is a market where buyers qualify by area rather than by city
- Live stock, price and shipping accuracy, because an agent quoting yesterday’s availability sends the buyer elsewhere, harder in Bengaluru because of a competitive set that changes street by street
- Attribute completeness against the fields assistants actually read, which go well beyond title and price – in Surat, complicated by the fact that a decision made by somebody who never visits the site
- Variant and GTIN handling, where most catalogues quietly lose matches, which in Sharjah runs into a procurement step nobody accounted for
The avoidable version of this
Treating feed errors as a technical chore for whoever has time. Feed health is the eligibility gate for every agentic surface, so it is a revenue control rather than a maintenance task.
This is the version most often delivered, which is why the discipline has a worse reputation than it deserves.
How it is measured
Feed health percentage, disapproval count, and share of catalogue eligible for the shopping surfaces. Reported monthly against a baseline taken before anything changed.
Reported with its own caveats attached, rather than cleaned up for the deck.
What you end up with
You finish with a feed audit with every error categorised, the fixes applied at source, and a monitoring setup so it stays fixed.
Versioned, so the next pass starts from this one rather than from scratch.
How it differs by sector
By sector, the same scope produces different priorities:
- In Marketplaces and platforms the binding constraint is that two sides to acquire, and a programmatic page set that can sink the whole domain.
- Finance and fintech: the thing that changes the scope here is that regulated claims, compliance review in the publishing path, and trust signals that have to be real.
- For Real estate and property, portals own the generic demand, so the win is locality authority and the specific listing. and that shapes how far this can go.
The industry pages carry the rest of that detail. Marketplaces and platforms and Finance and fintech are the two where this piece of work most often decides the outcome.
Common questions
How good does the feed have to be?
Comfortably above ninety-five per cent healthy before you are reliably eligible everywhere. Most catalogues that have never been audited land somewhere in the seventies.
Does this matter if we are not on Shopify?
Yes. The protocols are open and the requirement is the same: a live, accurate, complete feed. Platform only changes how much of it is automatic.
Is there a minimum worth doing?
There is a point below which the measurement cannot detect a change, and we would rather say so than take the work. Feed health percentage, disapproval count, and share of catalogue eligible for the shopping surfaces has to be able to move for the engagement to mean anything. AI Automation and Workflows is the part that scales. AI Platform Optimization is the part that never will.
Does this have to be bought separately from Agentic Commerce?
No. It is usually part of a wider Agentic Commerce engagement, and it is described separately because it is the piece clients most often ask about by name. It can also be scoped on its own where that is genuinely what is needed, and we will say which applies after looking. If this is the part you came for, First-party data or Third-party data goes further into it, and GA4 or Matomo covers what sits either side.
What is a realistic timeline?
Two to three weeks to establish what is true, then a phase sized to the finding. Quoting the whole thing before the diagnosis would be guessing, and the guess is usually wrong in the expensive direction. If this is already in place, Is paid search better than SEO? and What is the difference between SEO and GEO? are the next two things to fix.
Ask about product feed readiness
A line about the situation is enough. The first reply will say what we would check rather than what we sell.
Get a scoped answer rather than a proposal
Bring the numbers you have. We will tell you which ones are measuring the wrong thing before we suggest anything new.