How PMs can measure the success of their Product — Tracking actionable utility metrics
The overall performance of the product can be measured by actionable utility metrics. Usually, Chief Product Officer owns the high-level metrics & tracks them on regular basis. The PMs who own the particular feature or module track the L2 metrics which measure the percentage of users who are exposed to the feature & achieve their goals.
The most common actionable utility metrics are :
- Activation Rate (%) ⏺️ — Activation rate measures the percentage of people who successfully complete a certain goal in the onboarding journey. The goal can be any event that increases the chance that the user will come back and continue using the product. For example, if 1Mn users are onboarded on Swiggy & 250K of them added items to the cart then the activation rate is 25 %.
- Retention rate (%)🔁—The percentage of users a business retains over a given period of time. It can be measured by dividing the active users that continue their subscriptions at the end of a given period by the total number of active users you had at the beginning of that time period. It can be measured in terms of repeat transactions, paid renewals, or regular usage of a product over time. In Swiggy’s instance, it can be observed that 30% of the users over 1 month don’t return to the app to place the order or engage with Swiggy in the next month. 70% is the monthly retention rate for Swiggy.
- Stickiness ( %) ➕ — Stickiness is generally calculated as the ratio of Daily Active Users to Monthly Active Users. A DAU/MAU ratio of 40% would mean that the average user of your app is using it 12 out of 30 days that month. High frequency implies users become more active on your app & will increase the odds of experiencing various services offered by the app.
- Time Spent on App ⏰— The total time the average active user engages with your app over a defined period. It is a key metric for social & gaming apps & not so critical for e-commerce/ payments app. For example, if the average Swiggy user returns 10 times in a month and spends 5 minutes placing the order or browsing through the restaurant menu, the total Time spent on App is 50 minutes per month per user.
- Match rate ( %) 🤝— It measures the accuracy of recommended content to the users. This metric is critical for services with a high degree of personalization. For instance, Netflix's value proposition relies heavily on its recommendation engine. By measuring how many of those content recommendations are then consumed by the user, Netflix can improve the quality of its content and its capability to match useful content to the user’s taste.
- Viral Coefficient 🦠 — It measures the number of new users the average user generates. The viral coefficient is not limited to the number of referrals a user makes, it’s the number of those referrals that convert into registered users. The formula is mentioned below.
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