How Does ReleVantage Track and Improve a Restaurant's AI Visibility?

Stage one: discover the questions that matter

We start from the questions a diner actually asks before choosing someone in your category, not from keyword volume. Those questions are grouped by intent, by service, by geography or use case, and by direct category comparisons.

The set is written down and agreed with you before anything is measured, because a question set that keeps changing cannot produce a trend. Local covers 25 tracked questions and Pro covers 100, with additional questions available.

Stage two: record the baseline

Before any optimization work, we run the agreed questions across ChatGPT, Gemini, and Google AI Mode and store the results as the reference point for everything that follows.

• •Whether the restaurant is mentioned, and how often across repeat runs
• •Where the restaurant appears inside the answer
• •Which sources the answer cites, and whether they are yours or third party
• •Which competitors are named alongside you
• •The full answer text, kept so it can be re-read later

Stage three: diagnose what is driving each answer

This stage is human work. A strategist reads the stored answers and the sources behind them and identifies the reason for the result: missing or unindexable content, an entity a model cannot resolve confidently, facts that conflict between your site and external profiles, a competitor's page doing the explaining, or a third-party source carrying something inaccurate.

Accuracy problems are logged separately from visibility problems, because a wrong fact repeated across engines usually traces back to a single correctable source.

Stage four: prioritize the work

Findings become a queue of specific actions, ordered by likely impact against the questions you care about and by how quickly each can be done. The queue is visible to you rather than delivered as a surprise at month end.

• •On-site pages to create, rewrite, or restructure so an answer can be extracted from them
• •Entity and profile corrections so the same facts appear everywhere a model can read them
• •Structured data that matches what the page visibly says
• •Third-party source coverage to pursue on the domains the answers already cite
• •Community replies drafted in your voice for threads the answers rely on

Stage five: implement with your approval

ReleVantage is a managed service, so the work is done by our team rather than handed to you as a task list. What that means in practice is that drafts, page changes, and anything that would be published under your name go through an approval step first.

Nothing publishes publicly without your sign-off. Work in progress, waiting for approval, and completed items are all visible in the dashboard, so at any point you can see what is being done and what is waiting on a decision.

Stage six: retest against the same questions

The same question set runs daily on the same three engines, so change is measured against the baseline rather than against a new set of questions chosen after the fact.

Where an item has not moved, it goes back into the queue with a different approach rather than being quietly dropped. Anything still uncited after 30 days is re-attempted with a new strategy.

What do you see in the dashboard?

Every plan includes 24/7 access to a branded client dashboard. It is the working record of the engagement, not a separate product you have to operate.

• •Your tracked question set and how each question is performing per engine
• •Full answer text and the sources cited, so you can read the evidence yourself
• •Mentions, position, citations, and the competitors named alongside you
• •The action queue: what is planned, in progress, awaiting your approval, and done
• •Historical runs, so a change can be looked at in context

How is progress reported?

Once a month you get a performance report covering the period against the baseline, followed by a strategy review with a person who can explain what moved, what did not, and what changes next. Business outcome reporting is included where the data supports it: referral and branded demand signals from your analytics, and enquiries you attribute to an AI conversation.

We are explicit about what those outcome figures can and cannot prove. Assistant referrals are incompletely reported and diners often arrive later through another channel, so outcomes are presented as supporting evidence alongside the answer-level measurements.

What is deliberately outside the scope?

• •Engines other than ChatGPT, Gemini, and Google AI Mode are not tracked and are not claimed
• •No guaranteed placement, position, or timeline
• •No published claims about your business that cannot be verified
• •Nothing posted in your name or on your site without approval
• •No proprietary ranking factor is claimed; the platforms do not publish one

Frequently asked questions