Nobody needs a new job title for this.
AI Commerce Readiness does not map to one role: it maps to four that already exist. Each rung of the ladder lands on a team you already have, and each has a product and a sub-score of its own. Find yours below.
One person convenes the four. That is the job the Readiness Score was built for.
Growth and brand marketing own the answer.
Does AI know and recommend you?
Buying decisions now happen inside conversations your analytics never see. A shopper asks an assistant what to buy in your category, three brands come back, and being absent from that answer means never being in the running.
This is the rung growth already owns, in a surface it cannot yet report on. Herm watches what a fixed five-model panel says about your category, shows the explanations and cited sources carried in those answers, for the mentions and the absences alike, and produces the content that changes it.
Ecommerce and digital own the catalogue.
Can AI actually complete the recommendation: specs, price, stock, where to buy?
Recommendation and purchase are collapsing toward one surface. A brand that is visible but not sellable, with no live catalogue a model can quote and no destination verified to ship to the shopper, gets mentioned and skipped.
This rung is assessed from your product feed. Herm tests whether specs, price, stock and where-to-buy are legible to an agent, then turns the failures into a work order your development team can actually run.
CRM and retention own the signed-in relationship.
Are your own experiences right for the shopper in front of them?
This is the rung most teams skip, because it looks like a CRM problem and is not. Customer Intelligence works inside your own signed-in experiences: your surface sends the options it could already show, for a shopper who chose to connect, and Herm returns the order. The profile behind that decision stays inside Herm.
This rung scores the surfaces you control in session: product carousels, your own assistant, offer slots. It does not write to your CRM or feed email and lifecycle programmes, which keep running on your own first-party data. It does not measure, and Herm does not influence, what a frontier AI assistant recommends to an individual shopper.
The revenue owner owns the number.
Do the shoppers who buy your category buy you, and keep buying you?
Every rung below produces a capability. This one produces the answer to the question the board actually asks: is any of this producing sales.
Offers converts verified category shoppers who buy from everyone but you, into a funnel that ends in verified revenue. It is also the rung that inherits the honest limit: a receipt proves a purchase happened, and the cross-surface link proving one specific AI answer caused it does not exist yet, for Herm or for anyone. Herm publishes exactly where that join breaks.
Running this for clients rather than for one brand?
Agencies map the same four rungs onto engagements they can scope today: measurement and content as a retainer, the feed audit as a project, enrichment and offers as expansions. That conversation has its own page.
Herm for agencies →Four sub-scores. One per owner.
The Readiness Score exists so each team gets a result of its own, one per rung. It takes two minutes to see where you stand on each.