Job boards and dating sites face recommendation objectives that are more complex than single-sided platforms because they must optimize for the satisfaction of multiple parties simultaneously under constraints. Unlike e-commerce or streaming, success requires a match between two parties, meaning a recommendation that satisfies one side may not satisfy the other. This multi-stakeholder optimization problem is structurally distinct from maximizing a single metric like watch time or conversion rate. Any platform operating a two-sided or multi-party marketplace should account for this asymmetry when defining success metrics and evaluating recommendation quality.