Recognition heuristic
If you recognize one option but not the other, bet on the familiar one.
What it means
A decision rule for inferring which of two objects scores higher on some criterion: if one is recognized and the other is not, infer that the recognized one ranks higher. It exploits the fact that recognition is often correlated with real-world magnitude — bigger cities, more successful companies, and stronger teams are mentioned more and so become more familiar — making partial ignorance informative. The heuristic produces the 'less-is-more effect,' where people who recognize fewer objects can paradoxically outperform those who recognize more or even domain experts, because the experts have no unrecognized option to leverage. Its validity is wholly ecological: it works only when recognition tracks the criterion, and it can mislead in domains where fame is uncorrelated with the quantity in question. It matters as a vivid demonstration that limited knowledge, used well, can beat more information.
Examples
Asked which city is more populous, San Diego or San Antonio, people who have heard of only one tend to pick it — and are usually right.
Picking Wimbledon winners, a casual fan who has heard of only one player in each pair backs that one — and does surprisingly well, because famous players are usually the stronger ones.
Faced with a shelf of unfamiliar olive oils, a shopper reaches for the one name that rings a bell — though here fame tracks advertising budgets, not quality, so the rule misfires.
First described in Goldstein & Gigerenzer (2002).