Not every metric deserves a dashboard. Some numbers look impressive but don't drive decisions. Others seem mundane but reveal exactly where your growth is breaking.
This guide covers the 15 metrics that actually matter for mobile app growth, what each one tells you, how to calculate it, and what benchmarks to aim for.
Engagement Metrics
1. Daily Active Users (DAU) / Monthly Active Users (MAU)
What it measures: The number of unique users who open your app in a given day (DAU) or month (MAU).
Why it matters: DAU and MAU are your baseline health metrics. They tell you the size of your actively engaged audience, not just how many people downloaded your app.
How to use it: Track trends, not snapshots. A single day's DAU is noisy. The 7-day rolling average of DAU reveals the real trajectory.
2. DAU/MAU Ratio (Stickiness)
What it measures: The percentage of monthly users who use the app on any given day.
Formula: DAU / MAU
Benchmarks:
- Social/Messaging: 40-60% (excellent)
- E-commerce: 15-25%
- SaaS/Productivity: 20-35%
- Gaming (casual): 15-25%
- Health/Fitness: 10-20%
Why it matters: A high DAU/MAU ratio means users are forming a habit. An app with 100,000 MAU and 50% stickiness has a much healthier business than one with 100,000 MAU and 10% stickiness.
3. Session Length and Frequency
What it measures: How long users spend per session and how often they open the app.
Why it matters: These metrics reveal depth of engagement. High session frequency with short sessions (messaging apps) or low frequency with long sessions (streaming apps) are both healthy patterns depending on your app type.
How to use it: Track by user segment. Power users will have very different session patterns than casual users. Changes in session behavior for a cohort often predict retention changes.
Retention Metrics
4. Retention Rate (D1, D7, D30)
What it measures: The percentage of users who return to your app on day 1, day 7, and day 30 after their first use.
Benchmarks (industry averages):
| Category | D1 | D7 | D30 |
|---|---|---|---|
| Social | 30-40% | 15-25% | 8-15% |
| E-commerce | 20-30% | 10-15% | 5-10% |
| Gaming (casual) | 25-35% | 10-15% | 3-8% |
| Finance | 25-35% | 15-20% | 10-15% |
| Health/Fitness | 25-30% | 12-18% | 5-10% |
| News/Media | 25-35% | 10-20% | 5-12% |
Why it matters: Retention is the single most important growth metric. Without retention, every other metric is a vanity number. Improving D1 retention by 5 percentage points compounds into significantly more active users over time.
For a deeper look at the retention vs acquisition tradeoff, see Retention vs Acquisition: Where to Invest First.
5. Churn Rate
What it measures: The percentage of users who stop using your app over a given period.
Formula: Users lost during period / Users at start of period
Why it matters: Churn is the inverse of retention but framed as a problem to solve. High churn in the first week points to onboarding issues. High churn after week 4 points to a lack of ongoing value.
How to use it: Track churn by cohort and by acquisition channel. If users from one channel churn 2x faster than another, that channel is delivering lower-quality users (or setting wrong expectations in the ad creative).
6. Retention Curve Shape
What it measures: The shape of your retention curve over time (plotting retention rate vs. days since install).
What to look for:
- Flattening curve: Good. The curve drops initially but stabilizes, meaning users who survive the first week tend to stay.
- Continuously declining curve: Bad. Users keep leaving even after weeks or months. There's no stable engaged base.
- Smile curve: Great. Retention initially drops, then increases as users who left come back (often due to re-engagement campaigns or seasonal patterns).
The shape of the curve matters more than any single retention number.
Acquisition Metrics
7. Cost Per Install (CPI)
What it measures: How much you spend on average to acquire one app install.
Formula: Total ad spend / Total installs from that spend
Why it matters: CPI tells you the cost of filling the top of your funnel. But CPI alone is misleading; a $1 CPI is worthless if those users churn in 24 hours.
How to use it: Always pair CPI with retention and LTV metrics. A $5 CPI that delivers users with $20 LTV is better than a $1 CPI that delivers users with $2 LTV.
8. Cost Per Action (CPA)
What it measures: The cost to acquire a user who completes a specific valuable action (registration, first purchase, subscription).
Formula: Total spend / Users who completed the action
Why it matters: CPA is more meaningful than CPI because it accounts for activation quality. Optimizing for CPA instead of CPI means you're paying for users who engage, not just users who install.
9. Organic vs Paid Install Ratio
What it measures: The percentage of installs that come from organic sources (app store search, word of mouth, direct) vs paid channels.
Why it matters: A healthy app has a strong organic base. If 90% of your installs are paid, your growth stops when you stop spending. Aim for at least 40-60% organic.
How to use it: Track this ratio over time. Organic installs often increase when paid campaigns run (the "halo effect"), and healthy ASO and deep linking strategies strengthen the organic baseline.
Revenue Metrics
10. Lifetime Value (LTV)
What it measures: The total revenue a user generates over their entire relationship with your app.
Why it matters: LTV is the ceiling on what you can spend to acquire a user. If LTV is $10, spending $15 per install is unsustainable regardless of how good your acquisition campaigns look.
How to calculate: For subscription apps: ARPU x (1 / monthly churn rate). For in-app purchase apps: Average revenue per paying user x conversion-to-payer rate x average lifetime. For ad-supported apps: ARPDAU x average user lifetime in days.
How to use it: Segment LTV by acquisition channel, geography, and platform. Users from different sources have very different LTV profiles.
11. Average Revenue Per User (ARPU)
What it measures: Revenue generated per user over a specific period (usually monthly).
Formula: Total revenue / Total active users
Why it matters: ARPU combines monetization rate and average spend into a single number. Track it monthly and by cohort.
12. LTV:CPI Ratio
What it measures: How much lifetime revenue you generate relative to what you spend to acquire a user.
Benchmarks:
- Below 1.0: Losing money on every user acquired
- 1.0-2.0: Marginally profitable but fragile
- 2.0-3.0: Healthy economics
- Above 3.0: Strong unit economics, room to scale aggressively
Why it matters: This is the ultimate unit economics metric. If LTV:CPI is above 3:1, you can scale acquisition confidently. Below 1:1, you need to either improve retention/monetization or reduce acquisition costs.
Funnel Metrics
13. Activation Rate
What it measures: The percentage of new users who complete a key action that indicates they've found value (the "aha moment").
Examples of activation events:
- Social app: Added 3 friends
- E-commerce: Browsed 5 products or added one to cart
- Fitness app: Completed first workout
- Productivity app: Created first project or document
Why it matters: Activation is the bridge between install and retention. Users who activate retain at 2-3x the rate of those who don't. Improving activation rate is often the highest-leverage growth investment.
14. Conversion Rate
What it measures: The percentage of users who complete a desired action (free to paid, trial to subscription, browse to purchase).
Why it matters: Conversion rate directly impacts revenue. A 1% improvement in free-to-paid conversion on a user base of 100,000 means 1,000 more paying customers.
How to use it: Build funnels in your analytics to track every step from install to conversion. Identify where users drop off and fix those steps. See Deep Link Analytics: Measuring What Matters for guidance on setting up attribution and funnel tracking.
15. Virality (K-Factor)
What it measures: How many new users each existing user generates through invites, shares, or referrals.
Formula: K = (invites sent per user) x (conversion rate of invites)
Benchmarks:
- K > 1.0: Viral growth (rare; exponential)
- K = 0.3-0.7: Strong organic supplement
- K < 0.1: Minimal organic spread
Why it matters: Even sub-1.0 K-factors meaningfully reduce effective CPI. If K = 0.5, every two users you acquire bring in one additional user for free, reducing your effective CPI by 33%.
How to Use These Metrics
Build a Dashboard
Don't track all 15 metrics daily. Set up a tiered dashboard:
Daily review (2 minutes): DAU, session count, crash rate, new installs Weekly review (15 minutes): D1/D7 retention by cohort, CPI by channel, activation rate, ARPU Monthly review (1 hour): D30 retention, LTV calculations, LTV:CPI ratio, churn analysis, K-factor
Focus on One Metric at a Time
Having 15 metrics doesn't mean optimizing all of them simultaneously. Identify your biggest bottleneck and focus on one or two metrics until they improve:
- Low activation? Focus on onboarding and activation rate.
- Good activation but poor retention? Focus on D7 retention and engagement loops.
- Strong retention but slow growth? Focus on CPI optimization and K-factor.
- Great growth but poor economics? Focus on LTV and conversion rate.
Segment Everything
Aggregate metrics hide insights. Always segment by:
- Acquisition channel: Paid vs organic, and by specific paid channel
- Cohort: Group users by install week to track trends
- Platform: iOS vs Android (often very different behavior)
- Geography: Tier 1 markets vs emerging markets
For a comprehensive growth strategy that ties these metrics to specific actions, see Mobile App Growth: 25 Strategies That Work.
Get deep linking tips in your inbox
One email per week. No spam.
