Answers · The decision turn
When a buyer is ready to purchase, will AI recommend us?
You can't tell from visibility data. You find out by running the conversation a buyer would have, up to the moment they ask what to choose, many times and on each assistant, and scoring what happens at that final turn.
Why the decision turn is different
Early in a conversation, assistants list options. At the end, when the buyer asks which one to pick, they narrow to one or two and give reasons. That final turn is where a purchase is won or lost, and it is the turn most measurement doesn't look at.
Being the best-known name is not enough. Models recognized 95.7% of brands at the first turn. Yet in AIVO, Inc.'s research, 87.3% of brands named at the start of a buying conversation were displaced by a competitor by the fourth turn (n=1,427 brand probes across ten industries and four AI platforms).
Measuring it reliably when answers change
AI answers vary from one run to the next, so a single conversation tells you very little. A reliable reading needs:
- the same buyer conversation run many times on each assistant, reported as a range;
- conversations with your brand named and without it, to separate winning new buyers from keeping the ones who already ask for you;
- the final turn scored on its own, with outright wins kept separate from shared shortlists;
- a note of whether the assistant searched the web or answered from memory, because the two change on different timescales.
How AIVO Meridian scores it
AIVO Meridian's Reasoning Chain Score (RCS) is a 0–100 measure of a brand's position across a four-turn buying conversation, weighted toward the decision: the final turn carries half of the weight. It is run both with the brand unnamed and with the brand named, so it shows whether the brand is chosen by buyers who don't yet know it and kept by buyers who do.
Alongside the score, AIVO Meridian records the turn where a brand drops out and the evidence the assistant used, which is what tells you what to fix.
What to look for in a provider
Measures the recommendation, not the mentionIt reports what happens when the buyer asks what to choose — chosen, shortlisted, a competitor, or generic advice — not just whether you appeared.
Uses multi-turn buying conversationsReal buyers ask, compare, push back and then decide. A single question can't show where you drop out.
Repeats runs and reports rangesAI answers vary from run to run. One answer is a sample of one.
Reports outright wins separatelyBeing shortlisted alongside a rival is not the same as being chosen, and the two should never be blended into one number.
Separates searching from memoryAssistants answer some questions by searching the live web and others from what they learned in training. The two move on very different timescales.
Fixes, then re-measuresA report that stops at the diagnosis leaves you where you started. The test of a fix is the same measurement, run again.
Publishes its methodYou should be able to read how a score is built before you take it to a board.
Common questions
When a customer asks AI who to buy from, will it pick us?
Only measurement can tell you. Run your buyers' conversation to the decision on each assistant, repeatedly, and score the final turn. Most brands named at the start of these conversations are not the one chosen at the end.
How do I know if ChatGPT will recommend my product when someone is ready to buy?
Ask it the way a buyer would, over several turns, ending with “which should I choose?”, and repeat the conversation enough times to see the pattern. Then compare ChatGPT with Gemini, Perplexity and the other assistants your buyers use.
How do you measure recommendation likelihood at the decision point, not just presence?
Score the decision turn separately from earlier turns, across many runs and assistants, with outright wins reported separately from shortlisting, and with the turn of drop-out recorded.
The answer changes every time you ask. How can anyone measure it reliably?
By treating each answer as one sample. Repeated runs give a range; the same conversation set, re-run later, shows whether the range moved.
Will AI just recommend the biggest brand?
No. Assistants recognize almost every established brand, but most brands named at the start of a buying conversation are displaced by a competitor by the decision. Size helps you get mentioned; it doesn't decide the recommendation.
Sources
AIVO Meridian measures whether AI assistants recommend your brand at the decision, finds where it is lost, and fixes it. Request a demo.