User readiness often determines product success; products and design can be adequate while users are not ready to buy. Different product types require different expectations for purchase frequency and risk tolerance, for example daily purchases for food versus hesitation for investments. A four-month build of a robo advisor delayed implementing simple behavioral or email automations that could nudge users to invest. A feature was built without user research, skipping examination of anxieties, doubts, and behaviors. Product managers rushed into user stories and designers were involved late. Users need a guided journey with reassurance, feedback loops, and real-time feedback prompts.
At the end of the day, sometimes your success simply comes down to user behavior. Your product isn't broken. The design isn't bad. Users simply aren't ready to buy. Because of this, you need to understand the type of product you're selling. If you sell food, you expect people to buy it every day. But if you sell investments, where there's always the fear of losing money, you can't expect users to click "buy" immediately after signing up.
These were my exact words during a product performance review. However, it took my team building a robo advisor feature that dragged on for eight sprints (four months) to finally realize it (time we could've used to set up a simple behavioral/email automation flow to nudge users into investing). You'd think that with all the tools and data we have today it'd be easy to build a feature that users would adopt. So how did we still miss the mark?
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