Stickiness
Stickiness is a measure of how frequently users return to a product, most commonly calculated as the ratio of daily active users (DAU) to monthly active users (MAU), indicating how habit-forming and indispensable a product is.
Also known as: DAU/MAU ratio, product stickiness, engagement frequency
Formula
(Daily Active Users / Monthly Active Users) x 100
Why It Matters
Stickiness answers a fundamental question about your product: of the people who use it each month, what fraction uses it every day? A DAU/MAU ratio of 50% means the average user engages with your product roughly half the days in a month - a sign that the product has become a daily habit. A ratio of 10% means users come back only a few times per month.
This metric is particularly revealing because it cannot be gamed by growth alone. You can increase DAU or MAU through aggressive acquisition, but the ratio only improves when your existing users genuinely come back more frequently. It is a measure of product quality and habit formation rather than marketing effectiveness.
However, stickiness benchmarks vary dramatically by product category. A social media app might target 50%+ DAU/MAU, while a monthly expense reporting tool might be perfectly healthy at 10%. The key is understanding what frequency is natural for your use case and measuring whether you are achieving it.
How to Calculate
Stickiness (DAU/MAU ratio) is calculated by dividing the number of daily active users by the number of monthly active users for the same period. Typically, you average the DAU across all days in the month for a more stable metric. If your average DAU is 15,000 and your MAU is 50,000, your stickiness ratio is 30%.
Stickiness (DAU/MAU) Calculator
(Daily Active Users / Monthly Active Users) x 100
Industry Applications
A grocery delivery app achieves a DAU/MAU ratio of 35%, indicating users shop multiple times per week. They use stickiness data to identify "lapsed frequent shoppers" for targeted win-back campaigns.
Benchmark: Strong ecommerce app DAU/MAU: 15-25%
A SaaS collaboration tool tracks DAU/MAU of 42% for users on team plans vs 18% for individual plans, validating that the product is stickier when used collaboratively and informing their pricing strategy to incentivize team adoption.
Benchmark: Good SaaS DAU/MAU: 10-25% (varies by category)
How to Track in KISSmetrics
In KISSmetrics, use the Metrics report to track daily and monthly active user counts over time. Define "active" based on meaningful product usage, not just login. Create a custom metric that divides average daily active users by monthly active users to track your stickiness ratio trend.
Common Mistakes
- -Defining "active" as any visit or login rather than a meaningful product action, inflating the metric with passive users.
- -Comparing your stickiness ratio to products in completely different categories with different natural usage frequencies.
- -Not accounting for weekly patterns - B2B products naturally have lower DAU/MAU because users do not log in on weekends.
- -Ignoring that a rising MAU with flat DAU (declining stickiness) indicates you are acquiring users faster than you are engaging them.
Pro Tips
- +Calculate stickiness for different user segments to understand which users are the most engaged and what they have in common.
- +Track WAU/MAU (weekly/monthly) alongside DAU/MAU for products that have a weekly rather than daily usage pattern.
- +Use stickiness trends rather than absolute values to measure the impact of product changes on engagement.
- +Identify your "sticky features" - the specific actions that correlate with higher return frequency - and promote them in onboarding.
Related Terms
Retention Analysis
Retention analysis measures the percentage of users who continue to return to and engage with a product over time, tracking how well a product sustains its user base beyond initial acquisition.
Power Users
Power users are the most highly engaged segment of a product's user base, characterized by frequent usage, deep feature adoption, and disproportionately high value generation through activity, content creation, or revenue.
Engagement Score
An engagement score is a composite metric that combines multiple user activity signals - such as login frequency, feature usage, and content consumption - into a single numerical score that indicates how actively and deeply a user engages with a product.
Feature Adoption
Feature adoption measures the percentage of users who discover and begin using a specific product feature, tracking both the breadth of usage across the user base and the depth of ongoing engagement with that feature.
Cohort Analysis
Cohort analysis groups users by a shared characteristic or experience within a defined time period - typically their signup or first purchase date - and tracks their behavior over subsequent time intervals to reveal trends in retention, engagement, or revenue.
See Stickiness in action
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