Answer-engine visibility

A growing share of buying research never reaches a results page. LLM Visibility measures how the client appears when someone asks an AI assistant instead of searching.

Three panels: Test runs a fresh visibility check, Analytics shows the current standing across assistants, and Reports keeps the history of previous runs so you can compare over time.

How it works

1. 1

   Build a prompt set

   Prompts are the real questions a buyer asks: "best plumber in Austin", "who repairs tankless water heaters near me". The platform can generate a starting set from the client profile.

2. 2

   Run the checks

   Each prompt is run and the response is analysed for brand mentions, position in the list, sentiment, and which sources were cited.

3. 3

   Read the dashboard

   Mention rate, share of voice against named competitors, sentiment, and the domains the answer engines trust for this topic.

4. 4

   Schedule

   Prompt sets re-run on a cadence so you see trends, not one reading.

Reading a worked example

A prompt set of 20 questions for a local HVAC client might return a 35% mention rate, with the client appearing third when mentioned and cited less often than two competitors with more extensive, question-driven blog content. That gap, mentioned but rarely cited, usually means the client's content answers questions indirectly (through service pages) rather than directly (through a dedicated article), which is exactly the fix below.

AI Overview monitoring

A separate daily job checks Google AI Overviews for tracked queries and records whether the client is cited. Losing a citation raises an anomaly alert, because it usually costs traffic before rankings move.

Improving visibility

• Answer questions directly and early on the page. Answer engines lift concise, factual passages.
• Publish the specifics assistants need: service areas, pricing structure, credentials, brands serviced, hours.
• Keep structured data accurate; it is how machines confirm what a page is about.
• Earn mentions on the sources that already get cited for the topic. Those citation lists are a link-target shortlist.
• Publish an llms.txt style summary of the business so assistants have a canonical description to read.

Common problems