Your Website Is No Longer Your Only Signal Source: What AI Reads About You

When AI recommends a B2B supplier, it reads more than the brand’s own site: employer profiles on job boards, industry cluster member pages, trade magazines, catalogs uploaded to document-sharing sites and public agency pages. In one Recro simulation, a source that carried a competitor onto the shortlist was that competitor’s profile on Kariyer.net, Turkey’s largest job board. The brand we were researching had no trace outside its own website. Signals are now gathered from everywhere a brand is written about; a brand that invests only in its website leaves an incomplete file in front of the buyer.

Picture a shipyard’s technical manager. Unplanned downtime on deck equipment is driving up costs, and they’re looking for a domestic supplier. Their question to AI is precise: “Which domestic deck equipment manufacturers comply with IMO and SOLAS standards and have a strong service network?”

This person was one of the personas in a simulation Recro built for a marine equipment manufacturer. When we read the sources behind the competitor that stood out in the answer, the picture was: the competitor’s own site and its shipyard site, a defense industry cluster’s member page, two trade news sites and the competitor’s employer profile on Kariyer.net. The only visible source for the brand we were researching was its own website. Outside it, there wasn’t a single line the model could read.

This isn’t an isolated case. In a recent simulation based on external search data, the same pattern appeared: The brand we were researching showed no signal at all, while the profile text on its competitor’s Kariyer.net page was carried into the answer as a signal.

Which sources does AI use to get to know a supplier?

Before recommending a brand, a model looks for consistent information about it across several sources. The brand’s own site is only one of them, and in the model’s eyes the least independent. In Ahrefs’ analysis of 75,000 brands, the factor most strongly related to AI visibility was the number of web mentions of the brand. Most of those mentions happen on pages the brand doesn’t control.

In Recro simulations where source links were visible, the following source types came up again and again alongside the brand’s own site:

Source type	Example from our simulations	What it tells the model
Job-board and employer profiles	A Kariyer.net company profile	Company size, line of business and how it describes itself
Industry cluster and association pages	A defense industry cluster’s member list	Acceptance within the sector and area of competence
Document-sharing sites	Catalogs and presentations on Scribd (cited in 13 runs)	Product details, reference lists, technical values
Trade magazines and news sites	Shipbuilding, marketing and advertising publications	Projects, investments, independent coverage
Public agency pages	A public procurement agency’s page	Official records and approved supplier information
Industry marketplaces and directories	International equipment marketplaces, agency directories	Category membership, comparable product information
Social network pages	Corporate Facebook pages (cited in 5 runs)	Recent activity and contact trail

What surprised us most was Scribd. Catalog and presentation files that companies uploaded once and often forgot were among the most frequent places the model found technical information. That information may be out of date; the model reads it anyway.

Why does a job-board profile become a sales signal?

Employer profiles are written by HR teams to attract candidates. But the information they contain overlaps with what a buyer looks for: what the company makes, how many people it employs, where its facilities are, which sectors it serves. For AI, that text is validation independent of the brand’s own site.

The lesson is about who writes the text. Profiles that become signal sources are often written by HR rather than marketing, an association page is filled in by the association’s office, the catalog on Scribd was uploaded years ago by a sales rep. A brand’s digital representation becomes the sum of texts written by different teams at different times.

Keywords get measured, and so do key people

Classic SEO measures which keywords a brand’s site ranks for. That approach focuses on answering the buyer’s question with a single page. A model answering the shipyard technical manager’s question looks for evidence that supports that person’s decision: standards compliance, service network, sector acceptance, scale.

That’s why Recro doesn’t start measurement with a keyword. It sets up the key person with buying intent and that person’s question, then looks at which sources carry the answer. A keyword shows how the site performs. A key person shows whether the brand is present where the decision is made.

How do you build an off-site signal inventory?

Update employer profiles. On Kariyer.net, LinkedIn and similar platforms, the company description, product groups, sectors served and facility details should be current and written in sales language.
List the organizations you belong to. Industry clusters, associations, exporter unions, chambers of commerce. Check what each member page says about you.
Find old documents. Search document-sharing sites and old dealer sites for catalogs and presentations about your company. Have outdated ones removed or replaced with current versions.
Map your trail in trade publications. Which industry magazines mentioned you in the last two years, and on what topic? Which publications feature your competitors?
Set one description sentence. The same line of business, product groups and scale should appear across all of these sources.

We covered which signals competitors send first in these sources in if AI recommends your competitor, and how to turn field authority into digital proof in the Authority GAP.

How does Recro make this gap visible?

The Recro Insight Model reads where a brand is represented through the buyer’s question. The source list doesn’t stay an abstract audit; it shows which source carries the decision in which person’s question.

One simulation · 4 key pillars · 90+ steps

What sets Recro apart is four pillars built from scratch for each brand. Together they form a single simulation of 90+ steps, with each pillar producing the input for the next.

Persona builder: Decision-maker profiles that represent the brand’s real buyers, specific to its sector and sales structure.
Question builder: The brand-specific decision questions these people ask AI along their buying journey.
Report builder: A report that reads the answers against the brand’s goals and competitors, together with the sources behind them.
Action recommendation builder: A prioritized list of actions that closes the sector-specific signal gaps.

For off-site signals, each pillar produces the following:

The persona builder defines the key person looking for signals: a shipyard technical manager and an investment firm’s procurement specialist trust different sources.
The question builder sets up that person’s decision questions. It separates which of the standards, service network or scale questions depends on off-site sources.
The report builder extracts the links that source the conversation and shows which off-site sources carry the competitor.
The action recommendation builder ranks, within the sector-specific LLM signal list, which profile, membership page and document to fix first.

From a Recro simulation · anonymized

Persona: Shipyard technical manager · Deck equipment · Turkish
Question: Elimination · Standards-compliant domestic manufacturers with a strong service network
Target brand: Mentioned in 8% of 48 runs; in answers with sources, it appeared only through its own site.
Competitor’s sources: Own site, cluster member page, two trade news sites, Kariyer.net company profile.
Class: Authority GAP
Action: Update the employer profile in sales language; complete cluster and association pages; publish project stories in trade media.

Executive summary

When recommending a supplier, AI reads employer profiles, cluster member pages, trade publications, uploaded documents and public pages alongside the brand’s own site.
In a Recro simulation, one of the sources that put a competitor ahead was its Kariyer.net company profile; the target brand had no off-site trace.
A brand’s digital representation is the sum of texts written by different teams; build an off-site signal inventory and align it to one description.

Frequently asked questions

Does an employer profile really affect a buying decision?

Indirectly. The profile is one of the independent sources a model uses to confirm a brand’s scale and line of business. In our simulations, such a profile appeared among the sources of an answer recommending a competitor.

Which off-site source should we start with?

The type cited most often in answers for your category. In marine equipment, clusters and trade publications stood out; in agency services, directories and industry magazines. Measurement sets the order.

Our old catalogs are still online. Is that a problem?

It can be. The model may treat product or capacity details in an old catalog as current. Find your company’s files on document-sharing sites and replace or remove them.

Who should manage these sources?

Different teams may write the texts, but marketing should own the single description. HR, sales and corporate communications should align on the same line-of-business statement.

How far can these findings be generalized?

They come from Recro simulations across a limited number of brands and sectors. They show the general pattern of source types; each sector’s source map should be drawn from its own measurement.

Where, and how, is your brand described outside your website? Recro builds a sample simulation with your buyers’ questions and shares the source map in a demo report.

Request a demo insight report →