Service
AI Recommendation Baseline
Find out whether AI assistants currently recommend your business, who they recommend instead, and which sources they relied on to decide.
The problem this addresses
You have no idea whether ChatGPT names your company when a customer asks who to hire — and neither does anyone else selling you marketing.
A baseline is a measurement, not an opinion. We build a library of buyer-intent questions real customers in your market would actually ask an AI assistant, run them on a fixed schedule across the platforms in the benchmark, and record every answer in full.
The output is a count, not an impression: how many times you were named, in what position, which competitors appeared instead, which websites the answer leaned on, and whether what the AI said about you was factually correct. Every number traces back to a stored answer you can read yourself.
This is the starting line. Without it, any later claim of improvement is unverifiable — which is why we will not sell optimisation work to a business that has not been measured first.
What it includes
- A benchmark prompt library built from your services, cities and buyer language
- Prompts run across the benchmark platforms, each repeated so a single odd answer cannot distort the result
- Every response captured verbatim and stored as evidence
- Competitor identification — who is being recommended when you are not
- Citation and source review — the domains influencing the answers
- Factual accuracy check against your verified business facts
- Your AI Recommendation Score, with the full component breakdown
What you receive
A baseline report containing your score, the six component rates, platform-by-platform coverage, the competitor set that appeared, the sources cited, and the raw evidence behind every figure.
What this does not do
A baseline measures. It does not change anything. If your score is low, the baseline tells you that clearly rather than softening it — the work to improve it is a separate engagement you are free to take elsewhere.
How this is measured
Every service sits inside the same measurement loop. Work is proposed from recorded evidence, and its effect is assessed by re-running the identical benchmark rather than by asserting that it must have helped.
Usually paired with
AI Visibility Optimization →
Improve the signals that affect how AI systems find, read and understand your company — then re-measure to see whether it worked.
AI Source Gap Analysis →
Discover which third-party sources support the competitors AI recommends, and which of them have no record of your business at all.
Every engagement starts with a measurement
Tell us about your business and we will establish where you currently stand.