Finding the Best First Market for a Start-up's Emotion-Recognition AI

You are the product manager at an early-stage company that has built technology for detecting human emotions. Evaluate the ways this technology could be put to use, compare them, and recommend which application the company should pursue first. ```hint Separate the buyer from the person being read Before naming industries, decide what a promising application needs from a signal that is sometimes wrong, and keep in mind that the customer who pays and the person whose emotions are read are often different people. ``` ### Clarifying Questions - What does the technology read: facial video, voice, text, body signals such as heart rate, or a combination? - How accurate is it, which emotions or states can it tell apart, and does it work in real time? - Is it sold as software that others build into their products, as a device, or as a finished application? - What does the company need most in the next year or two: revenue, a large addressable market, or proof that the technology works? ### What a Strong Answer Covers - Clarifying the technology's inputs, accuracy and form before brainstorming, and explaining how the answers change which uses are feasible. - A broad, structured set of candidate applications that identifies, for each, who pays and whose emotions are read. - Explicit evaluation criteria applied consistently, ending in a prioritized recommendation with reasons. - The scientific, ethical and legal limits of inferring emotions, and which applications to rule out because of them. - A plan to validate the chosen application, with success metrics and guardrails. ### Follow-up Questions - How would you price the product for the first customers you chose? - A large retailer offers a big contract to run the technology on its store cameras to read shoppers' moods. Do you accept? - How would you show a skeptical buyer that the readings are accurate enough to act on?