HOW THE WORKSPACE WORKS

From an AI response
to a record you can review.

A practical routine for collecting, comparing and reporting a manual answer sample.

Set the matching rules

Add your brand name, domain and aliases. Add competitors if you want a side-by-side comparison.

Build a prompt set

Save consistent questions by topic in the prompt library. Use them in your own provider research process.

Record or import responses

Paste the answer and any source URLs, or import a structured CSV. Keep platform, model, region and date labels.

Filter, inspect and report

Review mention and citation rates, open the original observations and export a report with the assumptions included.

THREE SIGNALS. DIFFERENT MEANINGS.

Mention

Is the name present?

Find configured brand names and aliases in the saved response text.

Citation

Is your domain linked?

Match extracted or supplied URLs to the domain you configured.

Context

What was the prompt?

Keep the question, platform label, date and response together.

A STRONGER SAMPLING ROUTINE

Keep the conditions
as consistent as you can.

Use comparable prompts

Changing the wording can change the answer. Keep a clear record of the actual question.

Record collection context

Note the platform, model, region and date you observed. These are your labels, not verified provider metadata.

Inspect the underlying evidence

A percentage is a summary of records. Read the responses and source links before making a claim.

START WITH AN ANSWER YOU CAN INSPECT

Less guesswork.
More visible evidence.

Organise your prompts, record the responses and see where your brand appears in your sample.

Explore the AI visibility tracker → Read the methodology

Manual observations and CSV imports. No live provider connection.

From an AI responseto a record you can review.