What normal feedback misses
Star ratings and thumbs-up tests combine different reactions into one average. A marketing team may approve the average while a procurement manager rejects the offer because one claim is ambiguous.
Audit 02 · Variance risk: different buyers react differently
One average can hide the buyer you are losing.
A result such as “3.8 out of 5” can hide an important disagreement. The buyers who matter most may reject one sentence even when everyone else accepts it.
What this check does
Paste a landing page, email, or offer and name the buyer role you want to understand. An AI model reacts from that role's point of view. The app groups the response from doubtful to positive and keeps disagreements visible instead of reducing everything to one score.
The grouping method is called Semantic Similarity Rating (SSR). It compares the wording of a response with clear reference points; it is not a survey result or a prediction of actual sales.
Why a large company can use it
Leaders need more than a precise-looking AI score. This check shows the written reasoning behind the reaction and whether models agree. That gives brand, insights, and conversion teams a clear issue to investigate.
Why a small business can use it
You do not need a research department. Paste the copy you already use and name the buyer you need, such as a facilities manager, parent, or shop mechanic. The result points to wording that deserves another look.