What is measured sentiment?

Sentiment answers one question, for every AI answer that names you (or names a competitor you track): how favorably does this answer portray it to the person asking, on a scale of 0 to 100. 0 means clearly discouraged, 50 means neutral or simply listed among other options, 100 means strongly recommended.

It's the SAME scale for your brand and for every competitor you track — without a shared scale, a "you vs. them" comparison wouldn't mean anything.

What the score covers

Each scored answer receives:

  • An overall score, on the scale above.
  • A per-aspect score, but only for aspects the answer actually discusses for that entity. The six aspects are fixed and the same for every brand: Quality, Price, Support, Ease of use, Reliability, Offering. An aspect the answer doesn't mention does not appear in the score — a score of 50 on price means "price is discussed, the verdict is mixed," never "price isn't mentioned."

For your brand only, Mentova also checks whether the answer's framing contradicts your stated positioning (e.g. a premium brand described as a budget option). That's a separate signal, never blended into the score: a brand shouldn't be judged on a stricter scale than its competitors just because it filled in a positioning.

Every answer counts, not a sample

Every run is scored — up to 3 calls per model on the default panel — not just the first. A model's own noise is around 15% from one answer to the next: judging on a single run would throw away two-thirds of the sample and make aspects and competitor comparisons rarely displayable.

A missing score is never a neutral score

  • An entity not named in an answer has no score for that answer.
  • An entity named but whose text couldn't be analyzed (answer too long, or an unusual spelling) has no score either.
  • In both cases the missing score is null, never 50. A 50 is always an expressed mixed verdict, never an empty box.

Coming soon: the dedicated sentiment screens will always show coverage ("scored on N of M answers that name you") and, below 3 scored answers, say "sample too small" instead of showing a number that would look more precise than it is. The threshold already applies to what the Mentova assistant tells you; the CSV export delivers the raw numbers with their sample size (n), for you to judge.

Average of tracked competitors

The measurement computes the average of the competitors you track (the ones you haven't hidden): it's a comparison point, not a ranking. Coming soon: it will appear as a second series on the sentiment and mention-rate charts; meanwhile it's in the history CSV export.

  • A tracked competitor that's never named counts as 0% mention rate — it was measured, it's simply absent from the answers.
  • A tracked competitor qualifies for sentiment with at least 3 scored answers; otherwise it doesn't enter the average.
  • At least two tracked brands must qualify for an "average" to exist. With just one, the upcoming series will carry that brand's name instead of the word "average" (and the export leaves the "average" column empty).
  • With no tracked competitors at all, there's no average — never a zero average that would suggest something was measured when nothing was.

The method change is shown, never smoothed over

An earlier version of this measurement only scored your brand, only on the first of the three runs, on a scale relative to your stated positioning. The current measurement differs both in WHAT it scores (brand and competitors, on a shared scale) and HOW (every run).

These two methods are never blended or compared to each other: no variation (percentage, alert, report summary) is ever calculated across the change, and the PDF report flags when its period spans it. Coming soon: a vertical marker on the curve will flag the day the measurement changed. If you see a sudden sentiment drop on a given day, check whether it's a method change before assuming it's a real shift in tone.

No retroactive scoring

This measurement doesn't rescore the last 90 days of answers: scoring them today would produce scores dated in the past but based on today's judgment, which would be misleading. The new measurements therefore start with your next analysis. Coming soon: until a recent answer has been scored under the current measurement, the dedicated screens will say so plainly instead of showing an empty chart with no explanation.

Common pitfall

Never compare a point before and a point after a method change (the export's "Sentiment Method" column shows it) as if it were a real shift in how AI talks about you. Also only compare measurements backed by a sufficient number of answers: a few points of difference on 3 answers isn't a signal, it's noise.