Rewards Maximizer
AI recommendation signal analysis across 176 domains for the Rewards Maximizer persona in Credit Cards.
This report tracks how AI models and search engines recommend companies across 100 industries. If you want the same analysis run specifically against your own site and competitors, get in touch.
Get in touch →How to use this page
Know who AI recommends
This is the headline metric: the brands AI models actually recommend when buyers ask. If you are not on these lists, you are invisible in AI search. Benchmark your position, then study what the winners have in common.
Where the numbers come from
We ask multiple LLMs thousands of buyer-intent questions for this industry and record every domain they recommend. Score is a weighted reciprocal-rank sum across models and runs, with each model scaled by its influence weight; count and % are plain tallies.
What's on this page
Overall recommendation rankings, per-model filtering, and a side-by-side comparison of any two models.
Top LLM-recommended domains
How often AI models recommended each domain when answering Rewards Maximizer queries. The left chart shows raw recommendation counts, the right shows what percentage of queries included that domain.
Score (below) is the primary ranking metric: a weighted-reciprocal-rank sum across every model and run, where each model's contribution is scaled by that model's influence weight.
Top LLM-recommended domains by model
Same ranking as above, scoped to whichever models you select below: pick one, several, or none. Updates automatically as you check/uncheck.
Compare two models
Pick a model for each column to compare their recommendation patterns side by side.
All recommended domains
Every domain the AI models recommended for Rewards Maximizer, ranked by the influence-weighted score from the Score chart above, with each domain's link authority from the Common Crawl web graph. Click a domain for its site profile.