Framework
Term

DAU / MAU

Daily Active Users and Monthly Active Users — the two most-used engagement counts for consumer products. The DAU/MAU ratio (often called the 'stickiness ratio') measures how habitual usage is: 50% means the average user shows up half the days in a month.

DAU (Daily Active Users) and MAU (Monthly Active Users) count the unique users who took a defined action in the relevant window. The action is usually "opened the app" or "logged in", though more rigorous teams require a meaningful event ("sent a message", "watched a video to completion").

DAU/MAU stickiness ratio

The ratio of DAU to MAU expresses how habitual usage is:

Stickiness = DAU / MAU
  • 50%+: messaging-app territory — the average user shows up most days (WhatsApp, Snapchat, Discord)
  • 20–40%: typical for social, productivity, and content products
  • Under 10%: sessional products — users return occasionally but not habitually (booking, e-commerce, ticketing)

A 50% stickiness ratio means the average MAU is also a DAU every other day. Above 50% is rare and typically signals a product with strong daily-habit positioning.

What DAU/MAU misses

The ratio averages across all users, which hides bimodal distributions: a product can have 50% stickiness because half of users open it daily and half once a month. For diagnostic work, use L-metrics (e.g., L7: users active 7 out of last 7 days) which expose the distribution directly.

DAU/MAU also doesn't capture depth of usage — two products with the same stickiness can have very different revenue or strategic value if one drives 5 minutes per session and the other drives 60. Pair DAU/MAU with session length or core-action count.

When DAU is the wrong metric

For products built around infrequent but valuable usage (tax software, wedding planning, B2B procurement), DAU isn't relevant — weekly or monthly active is. Picking the wrong frequency window inflates expectations and makes good products look bad.

Related

See also

Nearby terms

All terms →
Cohort Analysis

A method of analyzing user behavior by grouping users into cohorts based on a shared event (usually signup date) and tracking how each cohort's behavior evolves over time, rather than averaging across all users at once.

CSAT (Customer Satisfaction Score)

A satisfaction metric measured by asking customers to rate a specific interaction or experience, typically on a 1–5 or 1–7 scale. CSAT is calculated as the percentage of customers who rate 4–5 (or 6–7), making it a transaction-level complement to NPS's relationship-level measurement.

Flywheel

A self-reinforcing business mechanic where each part of the system makes the next part stronger — producing compounding rather than linear growth.

ICP (Ideal Customer Profile)

A precise description of the customer type for whom a product delivers the highest value at the lowest cost to acquire and serve. ICP is the operational filter that prevents a sales team from chasing every lead.