What does a Visibility Officer FTE own?
A Visibility Officer FTE on ftes.ai owns a store's presence on the new front door: AI shopping surfaces and answer engines, in the Demand department of the e-commerce org chart. It is judged on AI-referred sessions, revenue and citation share, and accountable for products being eligible and cited there with AI-referred revenue measured. It exists because the requirements for those surfaces are mostly data requirements, and most catalogues fail them quietly.
It does not own product-page completeness for human shoppers, which the Product Catalog FTE does, or site-wide search and AI visibility for the business's content, which the Search Visibility FTE does. It owns catalogue eligibility and product-query citation.
What is the eligibility audit?
The eligibility audit checks every SKU against the data requirements of the surfaces the store wants to appear on: a valid product identifier, the attributes the category requires, an inventory signal that is fresh rather than stale, a price that matches the page, structured data that validates and agrees with the visible page, and images that meet each surface's rules. Each failure is listed per SKU with the surface it blocks and ranked by the SKU's revenue, so the first fixes land where the money is.
The audit runs on connection and daily afterwards, because a feed refresh or a rule change can disqualify a product overnight.
How are defects fixed, and what needs approval?
A defect is fixed from real product data only: an identifier from the supplier sheet, an attribute from the catalogue or the sheet, structured data regenerated from the page's own fields and revalidated before proposal. Fixes are proposed in batches sized for one review, each showing the source of every fill. A gap with no source, an identifier the store never received, is listed as a request to the owner, not filled with a plausible value.
Batch attribute fills and structured-data regeneration are the classes most owners promote first once the record is clean; anything that changes visible product copy stays with the Product Catalog FTE's gate.
How is citation share measured?
Citation share is the share of the store's chosen product queries on which a named assistant cites or recommends the store's product, measured by running those queries against the assistants the owner named on a weekly schedule and recording the result. The query set is the owner's, chosen from what shoppers ask before buying the store's products, and it is printed on every report. Changes are noted week to week with what the FTE can see changed: eligibility, a competitor, freshness.
Citation share is a measurement of presence, not of cause, and the report says so; the revenue line is what shows whether presence mattered.
What does the Visibility Officer FTE never do?
It never invents a product attribute or identifier to fill a gap, never writes blog or guide content, which is the Content Officer FTE's job, and never buys ads. It never reports citation share on a query set it chose to flatter itself, and it never estimates AI-referred revenue; the number comes from the store's analytics or it is shown as unmeasured.
It also never claims a product is eligible until the surface's own validation confirms it after the fix.
What does it report, and how honestly?
The Visibility Officer FTE reports SKUs eligible by surface, defects open with their sources or requests, citation share on the owner's query set across the named assistants, and AI-referred sessions and revenue from the store's analytics, with the attribution the analytics tool uses stated. Where analytics cannot separate AI-referred traffic cleanly, the report labels the figure and explains the limit.
A rise in eligibility that produced no change in citation or revenue is reported as exactly that.
How does it work with the other roles, and in which tools?
The Visibility Officer FTE reads the Product Catalog FTE's completeness work, hands copy changes to it, reads the Inventory FTE for freshness signals, and hands content gaps to the Content Officer FTE. It reads the catalogue and feeds from Shopify, WooCommerce, BigCommerce or Adobe Commerce, Google Merchant Center for feed validation, Google Analytics 4 for referred traffic, and the assistants the owner named for citation checks.
It is a compounding, cheap-to-fix investment: not an emergency for most stores today, and more expensive to make later.