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Mobile Analytics and KPIs Flashcards

6 cards from real Mobile Marketing practice questions. Tap to flip, then mark Knew It or Still Learning โ€” missed cards come back until you master them.

Read the first 6 Mobile Analytics and KPIs flashcards as text
  1. An analyst calculates a mobile app's 'Stickiness Ratio' (DAU/MAU) and finds it to be consistently low. What is the most likely user behavior this KPI indicates?

    Answer: Users open the app once or twice but do not return regularly throughout the month.

    The Stickiness Ratio (Daily Active Users divided by Monthly Active Users) measures how frequently users engage with an app. A low ratio signifies that while many unique users open the app at some point during the month (MAU), a small percentage of them return on any given day (DAU). This points to a problem with long-term engagement and forming a daily habit.

  2. When analyzing monetization metrics for a mobile app, what is the key distinction between Average Revenue Per User (ARPU) and Average Revenue Per Paying User (ARPPU)?

    Answer: ARPU averages revenue across all active users, while ARPPU only averages revenue across users who have made a purchase.

    ARPU (Average Revenue Per User) is calculated by dividing total revenue by the total number of active users, including those who do not pay. ARPPU (Average Revenue Per Paying User) provides a more specific view by dividing total revenue only by the number of users who have made a purchase. This makes ARPPU a crucial metric for understanding the value of monetized users.

  3. A marketing team has launched several paid advertising campaigns to drive downloads for their new app. Which KPI is the most direct measure of the cost-effectiveness of these specific campaigns?

    Answer: Cost Per Install (CPI)

    Cost Per Install (CPI) is a standard performance marketing metric calculated by dividing the total ad spend by the number of new app installs generated from that campaign. It directly assesses how much it costs to acquire one new user through paid channels, making it the most direct measure of a paid acquisition campaign's cost-effectiveness.

  4. The product manager for a mobile commerce app wants to optimize the checkout process after noticing many users add products to their cart but fail to complete the purchase. Which analytical approach is most crucial for quantifying this specific drop-off point?

    Answer: Creating a funnel analysis from 'Add to Cart' to 'Purchase Confirmation'.

    A funnel analysis visualizes the user journey through a series of defined steps. By setting up a funnel that tracks users from an 'Add to Cart' event to a 'Purchase Confirmation' event, the manager can precisely measure the conversion rate between these steps and identify the exact percentage of users who are abandoning their carts, thereby quantifying the problem.

  5. What does the 'Churn Rate' KPI represent in the context of mobile app analytics?

    Answer: The percentage of users who uninstall the app or become inactive over a specific period.

    Churn Rate, or attrition rate, measures the percentage of users who stop using an app (either by uninstalling or becoming inactive) over a given time frame. It is the inverse of the retention rate and is a critical indicator of user satisfaction and the app's long-term viability. While revenue loss is a consequence, the core churn rate KPI typically refers to the loss of users.

  6. A product manager for a new mindfulness app has the primary business goal of making the app a daily habit for its users. Which pair of KPIs should they monitor most closely to measure progress toward this specific goal?

    Answer: Daily Active Users (DAU) and Retention Rate

    To measure the formation of a daily habit, the most important KPIs are those that track frequent, repeat usage. Daily Active Users (DAU) directly measures how many unique users engage with the app each day. Retention Rate measures the percentage of users who return over time (e.g., Day 1, Day 7). A high and stable DAU combined with a strong retention curve indicates the app is successfully becoming part of users' daily routines.