The highest commission is not automatically the best recommendation
A product recommendation has to survive several tests before economics matter: does it solve an audience problem, can the creator explain it credibly, can the difference be demonstrated, and is the buying decision realistic for the shopper?
Demonstrability is a trust filter
Products that can be shown, compared, and explained honestly give creators more useful material than products selected only because they are trending. Demonstrability also makes weak claims easier to spot before they reach the audience.
Demand quality matters
A useful portfolio can mix evergreen and seasonal demand without becoming dependent on fragile one-off trends. Price and purchase friction, category economics, and clear differentiation all affect whether a recommendation deserves continued attention.
Operate a testing queue instead of collecting random ASINs
Track the exact ASIN and variant being evaluated, define the shopper job it serves, document the test, and retire low-trust recommendations when the evidence no longer supports them. A monthly portfolio review keeps curation deliberate.
The Amazon Product Selection System™ turns this discipline into 12 chapters of workflows, decision rules, measurement, experiments, SOPs, and implementation worksheets.