You received user feedback that Yelp's restaurant recommendation is not personal enough. What would you do?

First, I'd quantify the problem by analyzing user behavior data to understand the scope of the "not personal enough" feedback. This would involve looking at metrics like conversion rates from the homepage, user engagement with recommendations, and potentially conducting user surveys or interviews to pinpoint why users feel this way.

If the data confirms a significant issue, I'd segment users to identify which groups are most affected and what their specific needs are. For example, are they looking for new discoveries, or struggling to find familiar types of cuisine?

Based on this understanding, I would propose and prioritize solutions. This could range from improving the recommendation algorithm with more sophisticated personalization techniques (e.g., collaborative filtering, content-based filtering, or hybrid approaches), to enhancing UI elements that allow users to explicitly state preferences or filter recommendations more effectively. Iterative A/B testing would be crucial to validate the effectiveness of any implemented changes.