Electronic commerce on the Web is thriving, but consumers still have trouble finding products to meet their needs and desires. We introduce a novel recommender system technique which works even when users don�t necessarily know exactly what they're looking for. Users describe a goal for a real-life scenario, e.g., "I want something elegant to wear for my boss's birthday party." A common-sense reasoning system maps between the stated goals and possibly relevant characteristics of the product. Reasoning is based on an 800,000-sentence common-sense knowledge base, and spreading activation inference. Scenario-oriented recommendation breaks down boundaries between products' categories, finds the "first example" for existing techniques like collaborative filtering, and helps promote independent brands. We describe our scenario-oriented fashion recommendation system, What Am I Gonna Wear?.