What is DAU / MAU?

Daily Active Users (DAU) tracks the number of unique individuals who interact with your platform within a rolling 24-hour window. Monthly Active Users (MAU) does the same over a 30-day period. A user counts as active if they open the app, start a video, or trigger a significant event defined by your analytics setup. Most platforms define activity by session start, not just login. This distinction matters because a user who logs in but closes the app immediately still counts as active in many systems. However, some operators filter for users who watch at least one minute of content to get a cleaner signal. The ratio of DAU to MAU reveals stickiness. A ratio of 0.2 means the average user opens your app two days per month. A ratio of 0.5 means they open it half the days. You calculate this by dividing total DAU by total MAU. This metric helps you understand if your content creates a daily habit or serves as a weekly destination. It does not measure how long they watch, only if they show up. For live events, DAU spikes are expected. For VOD, steady DAU indicates a strong catalog.

Active user metrics drive your unit economics. You cannot monetize a user who never opens the app. Advertisers pay based on impressions, which require active sessions. Subscription models rely on perceived value, which often correlates with frequent usage. If your MAU is high but DAU is low, you have a large audience that does not return. This signals a content gap or a weak onboarding flow. Investors and partners look at these numbers to assess growth quality. A growing MAU with stable DAU suggests you are acquiring new users who are not engaging. A growing DAU with stable MAU suggests you are converting existing users into daily viewers. Both scenarios require different fixes. You use these metrics to allocate marketing spend. If your DAU/MAU ratio is low, spending on retention features like personalized recommendations or push notifications yields a higher return than spending on broad acquisition. These numbers also help you plan infrastructure. Live events require capacity for peak DAU, not average DAU. You size your servers for the highest expected concurrent load. Ignoring active user patterns leads to either over-provisioning costs or under-provisioning failures.

• Counting bots as users: Automated scripts can inflate DAU. Filter out non-human traffic in your analytics dashboard to keep data clean.
• Ignoring device fragmentation: A user on both mobile and web may count as two users if you do not deduplicate by account ID. Use a unified user ID to get accurate counts.
• Comparing raw numbers without context: A DAU of 1,000 is great for a niche sports league but small for a national broadcaster. Always look at trends and ratios, not just absolute numbers.
• Confusing activity with retention: A user who opens the app daily but watches no content is active but not retained. Pair DAU with Viewer Retention metrics to see if activity leads to value.