Measure Engagement Growth Over Time

Business Context

FitLoop is a mobile habit-tracking app with reminders, streaks, and weekly progress summaries. The product team says users are "more engaged than before," but leadership wants a data-backed definition of engagement and evidence that it is improving over time.

Metric Scenario

Over the last 6 months, monthly active users increased from 420,000 to 560,000. However, average sessions per active user stayed roughly flat at 8.1 to 8.3 per month, while Day-30 retention moved from 31% to 36%. DAU/MAU improved from 0.24 to 0.29, but average session length declined from 11.2 minutes to 9.4 minutes after a redesign that made logging habits faster. Product leadership wants to know whether users are truly becoming more engaged, or whether the apparent gains are driven by acquisition mix, lighter-weight usage, or changes in measurement.

Requirements

1. Define what "users becoming more engaged over time" should mean for this product.
2. Identify the primary KPI and 3-5 supporting metrics you would use.
3. Explain how you would distinguish healthier engagement from superficial activity increases.
4. Describe how you would analyze engagement trends by cohort and user segment.
5. Call out metric pitfalls, including cases where one engagement metric improves while another worsens.

Data Available

• user_sessions: session_id, user_id, session_start, session_end, platform, app_version
• habit_events: user_id, event_time, event_type, habit_id, reminder_id
• daily_user_activity: user_id, activity_date, habits_completed, reminders_opened, streak_days
• user_profiles: user_id, signup_date, acquisition_channel, country, subscription_tier
• experiment_log: user_id, experiment_name, variant, exposure_time