Browse vs. Search are the two organic discovery paths in an app store — search (users typing a query) and browse (charts, categories, and editorial featuring) — which reward different optimizations.
Search and browse send different users with different mindsets. Search traffic is intent-driven: someone types "calorie counter" and is ready to pick one, so it rewards keyword relevance and a listing that converts a decided shopper. Browse traffic — top charts, category lists, the Today tab, "apps we love" — is discovery-driven: the user wasn't looking for you specifically, so it rewards strong charts performance, category fit, and an icon and first screenshot that win a glance.
Most ASO effort goes toward search because it's the larger and more controllable channel, but browse compounds it: a featured placement or a chart climb drives a download spike that improves the very velocity signals search ranking depends on. The two channels feed each other, so a complete strategy optimizes for both rather than treating browse as luck.
Example
A budgeting app wins search by ranking for "expense tracker," then a Today-tab feature sends a browse-driven install spike that lifts its chart position and, in turn, its search rankings. Optimize for both: a browse-driven spike feeds the velocity that lifts search rank, and strong search keeps the charts warm.