Suppose we use push notifications to convert Uber riders to Uber Eats users. How do we determine what kind of people get annoyed by the push notifications?

Question Analysis

The question is asking about a method to identify which users might find push notifications annoying when attempting to convert Uber riders into Uber Eats users. This is a classic example of user segmentation and behavioral analysis in marketing. The goal is to understand user preferences and tolerance levels for push notifications. Essentially, the question requires you to think about metrics, data collection, and analysis techniques to identify user segments that react negatively to push notifications.

Answer

To determine which users get annoyed by push notifications when trying to convert Uber riders to Uber Eats users, follow these steps:

1. Define Metrics:

   • Unsubscribe Rate: Track how many users opt out of notifications after receiving them.
   • Engagement Metrics: Measure user interaction with notifications, such as click-through rates and subsequent app engagement.
   • Feedback Analysis: Collect direct user feedback on notifications through surveys or app feedback features.

2. Segment Users:

   • Demographics: Analyze user demographics to see if certain age groups or regions are more prone to finding notifications annoying.
   • Usage Patterns: Identify users based on their Uber app usage patterns, such as frequency of rides or order history with Uber Eats.
   • Previous Behavior: Look at past interactions with notifications to find patterns, such as users who never engage with notifications.

3. A/B Testing:

   • Conduct A/B tests by sending different types or frequencies of notifications to different user groups to observe variations in responses and engagement.

4. Data Analysis:

   • Use data analytics tools to analyze user behavior post-notification, focusing on those who show decreased app usage or increased unsubscription rates.

5. Machine Learning Models:

   • Develop predictive models to identify characteristics of users who are likely to be annoyed by notifications, using historical data to train the model.

6. Iterate and Refine:

   • Continuously improve your understanding by iterating on your strategy based on the data collected and user feedback.

By applying these methods, you can effectively identify and understand the user segments that find push notifications annoying, allowing for a more tailored and user-friendly notification strategy.