Check if your users actually stick around
Understand your retention curve, compare against benchmarks for your product type, find where users drop off, and know what to fix first.
Your retention data
Enter the percentage of users who remain active at each time period. Day 0 is always 100% (the signup moment).
Try a preset
Retention curve
Day 14 is optional and will be estimated if left blank.
Common retention patterns
Here is what different retention curves usually mean.
SaaS tool, Day 1 at 55%, Day 30 at 26%
Pattern
Strong retention
The curve stabilizes after the first week. Users who survive early churn are finding ongoing value. Focus on acquisition, not retention.
SaaS tool, Day 1 at 22%, Day 30 at 4%
Pattern
Sharp early drop
78% of users leave before Day 1. The first session is not delivering enough value. Fix onboarding and time to first value before anything else.
Content product, steady decay from 30% to 8%
Pattern
Gradual decay
Some decay is normal for content. The question is whether 8% at Day 30 is enough to sustain growth. For weekly content, this is near the benchmark.
Marketplace, irregular usage, Day 30 at 11%
Pattern
Healthy for the type
Marketplaces have naturally lower retention because users return when they need something, not on a schedule. 11% at Day 30 is reasonable.
SaaS, Day 1 at 60%, Day 30 at 35%
Pattern
Flat retention (ideal)
The curve flattens early and holds. This is the pattern of a product with strong product-market fit. Users who get past Day 1 stay long-term.
Developer tool, good Day 1 but drops steadily to 6%
Pattern
Weak ongoing value
Users try the tool and initially engage, but do not find enough reason to return. The setup works, but the recurring value proposition is not strong enough.
What good retention looks like
Good retention is not a flat line at 100%. Every product loses users in the first days. What matters is the shape of the curve after the initial drop. A healthy curve drops early and then flattens, meaning the users who survive the first few days stick around long-term. A bad curve keeps declining without stabilizing. The benchmarks depend heavily on product type and usage frequency, which is why this tool compares your numbers against the right baseline.
Why retention matters more than traffic
Traffic fills the top of the funnel. Retention determines how much of that funnel accumulates into a real user base. A product that retains 30% of users at Day 30 builds a user base roughly 3x larger than one that retains 10%, given the same acquisition rate. This compounding effect is why retention improvements often produce more growth than traffic improvements. The Growth Impact Simulator shows this comparison in numbers.
How to read a retention curve
Look for where the curve flattens. If it flattens after Day 7, the users who survive the first week are your core audience. If it never flattens, the product is not creating a strong enough reason to return. The steepness of the initial drop (Day 0 to Day 1) tells you how well the first session works. A 50%+ drop on Day 1 means most users did not find enough value to come back. The Onboarding Drop-off Analyzer helps diagnose what is happening in that first session.
Why most products lose users early
The first session is the audition. Users arrive with a fixed window of attention. If the product does not deliver value before that window closes, they leave and almost never come back. Most early churn is not a product quality problem. It is a time-to-value problem. The product may be excellent once users reach the core experience. They just did not get there fast enough. For strategies on fixing this, see time to first value and why users do not come back.
Keep reading
Explore related tools, guides, and case studies.
Retention is what turns growth into a real product
Muro helps founders understand where users leave, when retention shifts, and what to do about it.
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