You are the PM responsible for the "Recommended for you" content strip in the Disney Plus app, and you have noticed a sudden 10% drop in total average minutes viewed. What do you do?
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Walt Disney
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Understanding of the problem statement is necessary and its potential impact which in this case could be reduced engagement, potential loss of subscribers, and decreased revenue. We should start with first eliminating any external potential cases to this problem.
Explore the answers to the questions like:
- Launch of new content or features by competitors that attract users away from Disney Plus.
- Price changes or promotions by competitors that make their offerings more appealing.
- Shifts in consumer preferences, such as a growing interest in other types of entertainment or platforms.
- Seasonal variations in content consumption, such as lower engagement during certain times of the year.
- Economic downturns that lead to reduced discretionary spending on entertainment subscriptions.
- Changes in consumer behavior due to global events (e.g., pandemics, political events).
- New regulations or legal challenges that affect content availability or distribution.
- Emergence of new technologies or platforms that change how users consume content.
Once it is established that none of these are the causes, we proceed to understand the internal factors that may have caused it. We start by understanding where the metric drop has its impact. Dive deeper into the metric drop by understanding;
- Is the metric drop consistent across all user types (new, returning)?
- Is the metric drop observed across all device types or specific (iOS, Android, others)?
- Is the metric drop observed on specific devices (Samsung devices, or One Plus devices, or Apple devices) or some specific brand models?
- Is the metric drop observed across a specific geography (within India, if specific areas see a bigger metric drop, or is it consistent across all geographies)?
- What is the pattern of metric drop across different times of the day?
- Are there any modifications in the recommendation engine (in a recent release) that may have caused lesser personalized recommendations leading to the metric drop? If the alog relies on incomplete user data, we may see quality issues in the content strip.
- Any UI changes recently that may have required a user behaviour modification? Navigational changes and content strip visibility on the app may hamper its usage.
- Have we onboarded new content on the app recently or not? If not, this may have caused some users to flock to other platforms for fresh content)
- Is there any observed latency in updation of the recommendation strip that has been observed implying that the users still see stale content on it for a few times, hampering usage?
This approach can systematically help one get closer to the root cause of what the issue might be, before jumping into the possible solutions. Spend a very high time on problem discovery, refinement and exploration. Solutioning should come at the last.
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