Visibility history

The history keeps every test run and lets you see whether your visibility is improving, holding or falling. It is available both in aggregate, on the per-query-type cards, and in detail inside each query.

What gets recorded#

Every time a query is tested, AgentFi sends it to ChatGPT, Perplexity, Gemini and Claude, and records whether your site appears in each answer. That record is not wiped when you test again: it accumulates.

Per-engine history#

In the detail of a query, each engine gets its own row. The coloured dots are individual runs, oldest on the left, most recent on the right.

Hover a dot
Shows the date, the time and the exact outcome.
The summary on the right
Shows the most recent outcome and how long ago it ran.
The arrow
Expands the full chronological list of every run for that engine.

The colours#

OutcomeWhat it means
Found in answerThe engine cited or named your site. When a citation position is available it reads Found at #N: lower numbers mean the engine placed your site higher in its list of sources.
Not mentionedThe engine answered the query, but neither cited nor described your site. This is the metric with the most room for improvement.
Engine errorThe AI engine did not return a usable answer: provider outage, timeout or content filter. It counts neither as found nor as not mentioned, so it does not penalize your percentage.

The daily squares on the cards#

On the Visibility by query type cards, each square represents one day of history for one engine. The colour reflects that day's success rate for that engine, following the five-band legend.

Note

Squares only appear on days when tests ran. With weekly auto-tests you get one square per week; at a daily cadence the grid fills in and trends become far easier to read.

Strength labels#

LabelHow to read it
StrongThe engines find you consistently.
ModerateThey find you sometimes. There is clear headroom.
Needs workThey rarely find you. Review optimization coverage and your custom rules.
No dataNot enough tests yet.

How to use the history#

  1. Set a baseline: run every query once, before changing anything.
  2. Make one change at a time — optimize a group of pages, adjust the custom rules, publish new content.
  3. Wait for the next scheduled run and compare the discovery visibility card.
  4. Look at the queries that moved from Not mentioned to Found in answer and work out what they have in common.
Warning

AI engines are not deterministic: the same query can return different results in two consecutive runs. Never draw conclusions from a single test; look at the trend across several runs.

Reputation analysis#

Beyond measuring whether you appear, AgentFi can analyse how your brand is talked about. Reputation analysis generates its own queries, runs them across all four engines and analyses the sentiment of the answers.

Health score
Excellent, Good, Needs Attention, Poor or Critical.
Sentiment
Positive, neutral, mixed or negative, broken down by aspect.
Reputation sources
Where the models take their opinion from: articles, comparisons, forums, news or review sites.
Engine Comparison
Score, status and trend for each engine separately.
Action Items
Concrete suggestions derived from the analysis.
Warning

Reputation analysis spends tokens: on top of the generated queries, the system creates follow-up queries while studying the sources it finds, and each one costs tokens.