{"id":177,"count":0,"description":"","link":"https:\/\/tenjin.com\/ja\/glossary\/cost-per-n-day-retained-user\/","name":"Cost Per N-Day Retained User","slug":"cost-per-n-day-retained-user","taxonomy":"glossaries","parent":0,"meta":{"status":["1","1"],"order":["0","0"],"glossary_term_description":["
\r\n\r\nDefinition:<\/b>\r\n\r\nCost per N-day retained user is a metric that measures how much it costs to acquire a user who remains active on your app after a specific number of days. The \"N\" represents the time window you are measuring, commonly 7, 14, or 30 days, and the metric is calculated by dividing your total campaign spend by the number of users still active at that point.<\/span>\r\n\r\nFormula:<\/b>\r\n
Cost Per N-Day Retained User = Total Campaign Spend \u00f7 Users Active After N-Days\r\n\r\n<\/span><\/pre>\r\n<\/div>\r\n
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What is Cost Per N-Day Retained User?<\/strong><\/h2>\r\nInstalling an app is easy. Staying engaged with it is another matter entirely. Most apps lose the majority of their users within the first few days after install, which means the cost of acquiring an install tells you very little about the cost of acquiring a user who actually sticks around.<\/span>\r\n\r\nCost per N-day retained user addresses that gap. Instead of measuring the cost of getting someone through the door, it measures the cost of getting someone who stays. That makes it a much more meaningful signal of acquisition quality and of the long-term value of your marketing spend.<\/span>\r\n
How to Calculate Cost Per N-Day Retained User<\/strong><\/h2>\r\nFormula:<\/b>\r\n
Cost Per N-Day Retained User = Total Campaign Spend \u00f7 Users Active After N-Days\r\n\r\n<\/span><\/pre>\r\nExample:<\/b> A campaign costs <\/span>$10,000<\/b> and <\/span>1,000 users<\/b> are still active after 30 days:<\/span>\r\n
Cost Per N-Day Retained User is $10,000 \u00f7 1,000 = $10\r\n\r\n<\/span><\/pre>\r\nYou can apply the same formula at any retention milestone. Running it at Day 7, Day 14, and Day 30 gives you a picture of how retention and acquisition cost efficiency changes over time for a given cohort.<\/span>\r\n
Why This Metric Matters<\/b><\/h3>\r\nCPI tells you what an install costs. Cost per N-day retained user tells you what a genuinely engaged user costs. Those two numbers can look very different, and the gap between them is often where campaign performance really lives.<\/span>\r\n\r\nA campaign with a low CPI but poor retention will produce a high cost per retained user. A campaign with a higher CPI but strong retention can end up being significantly more efficient when you account for who actually stayed. Without measuring retention cost, you are only seeing part of the picture.<\/span>\r\n\r\nThis metric is particularly useful for:<\/span>\r\n
Comparing Acquisition Channels<\/strong><\/h4>\r\nTwo channels might deliver installs at a similar CPI but perform very differently on retention. Cost per N-day retained user surfaces that differ.<\/span>\r\n
Evaluating Creative and Targeting Decisions<\/strong><\/h4>\r\nRetention is a signal of user quality. If a specific audience segment or creative approach consistently produces users who stay longer, that shows up here.<\/span>\r\n
Informing LTV Modeling<\/strong><\/h4>\r\nUsers who are retained at Day 7 or Day 30 are far more likely to generate meaningful lifetime value. Cost per retained user connects acquisition spend to the users most likely to contribute to long-term revenue.<\/span>\r\n
Justifying Higher CPIs<\/strong><\/h4>\r\nSometimes paying more per install is the right call \u2014 if those installs retain better. This metric gives you the data to make that argument confidently.<\/span>\r\n
How to Improve Your Cost Per N-Day Retained User<\/strong><\/h2>\r\nImproving this metric comes from two directions: reducing the cost of acquisition, or improving the retention of the users you acquire. The most effective approaches usually work on both at once.<\/span>\r\n
Target the Right Audience<\/b><\/h4>\r\nNot all users retain equally. Use performance data to identify the segments, channels, and creatives that consistently bring in users who stay active past your key retention milestones. Focus your spend there.<\/span>\r\n
Invest in Onboarding<\/b><\/h4>\r\nThe first few sessions after install are where most churn happens. A clear, frictionless onboarding experience that gets users to a meaningful moment quickly makes a significant difference to Day 1 and Day 7 retention, which flows through to your cost per retained user.<\/span>\r\n
Monitor Retention by Cohort<\/b><\/h4>\r\nRetention rates can vary significantly across cohorts from different channels, countries, or time periods. Cohort-level analysis helps you identify where retention is strong and where it is falling short, so you can act on it.<\/span>\r\n
Connect Retention Data to Your UA Decisions<\/b><\/h4>\r\nRetention should not be measured in isolation from acquisition. When your attribution data and retention data sit in the same place, you can see exactly which campaigns are producing users who stick around and make faster, better decisions about where to invest.<\/span>\r\n
Cost Per N-Day Retained User and pLTV<\/strong><\/h2>\r\nRetained users are the users most likely to generate long-term revenue. That makes cost per N-day retained user a natural bridge between acquisition efficiency and lifetime value modeling.<\/span>\r\n\r\nWhen you pair this metric with pLTV data, you can start to answer a more precise question: not just what does it cost to keep a user for 30 days, but what is that retained user actually worth over their full lifetime? That combination gives you a much stronger foundation for deciding how much to spend on acquisition and where.<\/span>\r\n\r\nTenjin's pLTV modeling, accurate to over 90%, is built to work alongside metrics like this, giving you the confidence to make forward-looking decisions, not just backward-looking ones.<\/span>\r\n\r\n
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Related Terms<\/b><\/h3>\r\n
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