How much do models disagree on brand recommendations? | Trakkr Research

A lot. 14.6% of prompts fall into the high-divergence bucket, and average agreement is still only 43.3% even when measured across a large, cleaned comparison set.

Methodology: Built from 797,644 valid comparisons across 44,088 reports and 8 models, covering 6,439,133 model responses in the observed window.

Direct Answer

A lot. 14.6% of prompts fall into the high-divergence bucket, and average agreement is still only 43.3% even when measured across a large, cleaned comparison set.

What this means

This answer matters because it turns a study finding into an operating rule teams can use when they decide what to publish, refresh, or measure next.

Evidence table

Metric Value Why it matters
High divergence rate 14.6% Prompts in the 0-25% agreement bucket.
Average agreement 43.3% Mean cross-model agreement rate.
Valid comparisons 797,644 Cross-model recommendation comparisons in the study.

Frequently Asked Questions

How much do models disagree on brand recommendations?

A lot. 14.6% of prompts fall into the high-divergence bucket, and average agreement is still only 43.3% even when measured across a large, cleaned comparison set.

Which numbers from Same Question, Different AI, Different Answers matter most here?

High divergence rate: 14.6%. Prompts in the 0-25% agreement bucket. Average agreement: 43.3%. Mean cross-model agreement rate.

What should a team do next?

Track visibility across multiple models instead of using one platform as a proxy for the whole market. Prioritize query classes where disagreement is highest because that is where share can move fastest. Treat consensus as a benchmark, but treat divergence as the operating reality.

What to do next

Related pages

Continue through the same study cluster.

Data & Sources