Growth

Analytics Interpretation

Interpret your app's metrics, diagnose problems, and make data-driven decisions. Works with App Store Connect data, third-party analytics, or raw numbers the user provides.

When This Skill Activates

Use this skill when the user:

• Wants to understand their app metrics or analytics
• Asks about retention, LTV, ARPU, or churn
• Wants to know if their metrics are good or bad
• Needs help interpreting App Store Connect analytics
• Wants a data-driven growth plan
• Asks "what should I focus on to grow?"
• Has metrics data and wants to know what it means

Process

Step 1: Gather Context

Ask the user via AskUserQuestion:

1. App type and monetization model

• Free with ads, freemium, subscription, paid upfront, or hybrid?

2. Current metrics they have access to

• App Store Connect? Third-party analytics (Mixpanel, Firebase, Amplitude)?

3. Specific numbers they can share

• Downloads, DAU/MAU, retention, revenue, conversion rates?

4. What they want to know

• "Are my metrics good?" / "What should I fix?" / "Should I keep going?"

Step 2: Identify Key Metrics by App Type

Different monetization models have different north star metrics.

Free with Ads

Freemium (One-Time Unlock)

Subscription

Paid Upfront

Step 3: App Store Connect Analytics Interpretation

The App Store Funnel

Impressions (your app appeared in search/browse)
    ↓ Tap-through rate = Product Page Views / Impressions
Product Page Views (user tapped to see your page)
    ↓ Conversion rate = Downloads / Product Page Views
Downloads (user installed your app)
    ↓ D1 retention
Day 1 Active Users
    ↓ D7 retention
Day 7 Active Users
    ↓ D30 retention
Day 30 Active Users
    ↓ Monetization
Paying Users

Interpreting Each Funnel Step

Impressions → Product Page Views (Tap-Through Rate)

What to fix if low:

• App icon not standing out (test bolder colors, simpler design)
• Title not communicating value (add keyword after brand name)
• Subtitle too vague (make it specific: "Budget Tracker" not "Finance App")
• Poor search ranking (see keyword-optimizer skill)

Product Page Views → Downloads (Conversion Rate)

What to fix if low:

• First 3 screenshots not showing core value
• No app preview video (adds 15-25% lift)
• Description too long before showing key benefits
• Bad ratings visible (address review issues first)
• Price too high relative to perceived value

Downloads → Day 1 Retention

What to fix if low:

• Onboarding too long or confusing
• App Store screenshots overpromised
• Core value not visible in first session
• Permissions requested too early (camera, notifications)
• Performance issues (slow launch, crashes)

Day 1 → Day 7 Retention

What to fix if low:

• No reason to come back (add notifications, reminders, streaks)
• Core loop not engaging enough
• Too complex — users haven't learned enough features
• Missing "aha moment" in first week

Day 7 → Day 30 Retention

What to fix if low:

• Feature depth too shallow (users exhaust value)
• No progression or new content
• Competitor doing it better
• Consider: is this a "use once" tool, not a habit app?

Step 4: AARRR Funnel Analysis

The pirate metrics framework — diagnose where your funnel leaks.

Acquisition: How do users find you?

Questions to ask:

• What are your top 3 acquisition sources?
• Is organic growing or shrinking?
• What's your cost per install (if running ads)?

Activation: Do users experience the core value?

Questions to ask:

• What is the one action that defines "this user gets it"?
• How many steps to reach that action?
• What percentage of new users complete it?

Retention: Do users come back?

Questions to ask:

• Where is the biggest retention drop-off?
• What do retained users do differently from churned users?
• Is there a retention cliff at a specific day?

Revenue: Are users paying?

Questions to ask:

• At what point do users encounter the paywall?
• What's the conversion rate at each paywall touchpoint?
• Do longer-retained users convert at higher rates?

Referral: Do users tell others?

Questions to ask:

• Is there a share feature in the app?
• Do you ask for ratings at the right moment?
• What triggers a user to recommend your app?

Step 5: Cohort Analysis (Subscription Apps)

How to Read a Cohort Retention Table

              Month 0  Month 1  Month 2  Month 3  Month 4  Month 5
Jan cohort    100%     62%      55%      50%      48%      46%
Feb cohort    100%     58%      51%      46%      44%      —
Mar cohort    100%     65%      59%      54%      —        —
Apr cohort    100%     70%      63%      —        —        —
May cohort    100%     68%      —        —        —        —

What to look for:

1. Month 0 → Month 1 drop: The biggest drop. Industry average is 30-50% churn. If yours is > 50%, trial experience needs work.

2. Flattening curve: Retention should flatten over time. If Month 3 → Month 4 → Month 5 are similar, you've found your "natural retention floor."

3. Improving cohorts: Compare Jan vs. Apr cohorts at the same month. If Apr Month 1 (70%) > Jan Month 1 (62%), your product improvements are working.

4. Retention cliff: A sudden drop at a specific month often indicates:

• Month 1: Annual subscribers who don't renew
• Month 3: Users who gave it a fair try and decided no
• Month 12: Annual subscribers hitting renewal

Comparing Cohorts to Measure Impact

When you ship a change, compare cohorts before and after:

Before change (Jan-Mar avg):  Month 1 retention = 58%
After change (Apr-May avg):   Month 1 retention = 69%

Improvement: +11 percentage points → significant positive impact

Rules of thumb:

• < 3 percentage point change: likely noise
• 3-10 percentage point change: meaningful, keep the change
• > 10 percentage point change: major win, double down on this direction

Step 6: Diagnostic Decision Trees

Use these when the user says "my [metric] is bad, what do I do?"

Low Impressions (< 1,000/day for established app)

Low impressions
├── Are you ranking for any keywords?
│   ├── NO → ASO problem: optimize title, subtitle, keywords
│   │        See keyword-optimizer skill
│   └── YES → Are those keywords high-volume?
│       ├── NO → Target higher-volume keywords
│       └── YES → Are you ranking in top 10?
│           ├── NO → Improve rankings (more ratings, better conversion)
│           └── YES → Expand to more keywords or new markets

High Impressions, Low Product Page Views (TTR < 4%)

Low tap-through rate
├── Is your icon professional and distinctive?
│   ├── NO → Redesign icon (test 3 variants)
│   └── YES → Is your title clear and keyword-rich?
│       ├── NO → Rewrite title: [Brand] - [Value Keyword]
│       └── YES → Is your subtitle compelling?
│           ├── NO → Rewrite subtitle with specific benefit
│           └── YES → Check competitor positioning — are you differentiated?

Good Downloads, Bad Retention (D1 < 25%)

Poor day-1 retention
├── Is onboarding complete rate > 70%?
│   ├── NO → Simplify onboarding (fewer steps, skip option)
│   └── YES → Do users reach "aha moment" in first session?
│       ├── NO → Restructure first-run experience to show core value immediately
│       └── YES → Are there performance issues (crashes, slow load)?
│           ├── YES → Fix stability first (check crash reports)
│           └── NO → Does the app match what screenshots promised?
│               ├── NO → Align marketing with actual product
│               └── YES → Core value may not be strong enough → user research needed

Good Retention, Low Revenue (conversion < 3%)

Low monetization
├── Do users see the paywall?
│   ├── NO → Add natural paywall touchpoints (feature gates, usage limits)
│   └── YES → Is the paywall compelling?
│       ├── NO → Redesign paywall (show value, social proof, feature comparison)
│       └── YES → Is the price right?
│           ├── TOO HIGH → Test lower price point or add cheaper tier
│           ├── TOO LOW → Users may not perceive enough value — test higher price
│           └── SEEMS RIGHT → Is trial experience showcasing premium features?
│               ├── NO → Onboard users to premium features during trial
│               └── YES → Test different trial lengths or offer types

Step 7: Invest, Iterate, Pivot, or Sunset?

Based on the overall picture, recommend one of four paths:

Invest (Double Down)

Signals:

• D7 retention > 40%
• Growing organically (installs increasing without paid acquisition)
• Users actively requesting features
• Conversion rate improving over time
• Strong ratings (> 4.5 stars)

Action: Increase development speed, consider marketing spend, expand to new platforms.

Iterate (Keep Improving)

Signals:

• D7 retention 20-40%
• Some organic growth but not accelerating
• Mixed user feedback (some love it, some confused)
• Conversion rate stable but not great

Action: Focus on the retention cliff. Find what retained users do differently and make all users do that. A/B test paywall and onboarding.

Pivot (Change Direction)

Signals:

• D7 retention < 20% after 3+ iterations
• Engagement concentrated in unexpected feature
• Users using app differently than intended
• Specific segment retains well, others don't

Action: Double down on the unexpected use case. Rebuild around what users actually do, not what you planned.

Sunset (Move On)

Signals:

• Declining metrics across the board
• No organic growth despite multiple iterations
• Users not engaging even after onboarding improvements
• Opportunity cost too high (other ideas with more potential)

Action: Put app in maintenance mode. Stop active development. Consider open-sourcing or selling. Redirect energy to next project.

Important caveat: Sunsetting is not failure. Most successful indie developers shipped several apps before finding the one that worked.

Reference Files

See metrics-reference.md for:

• Detailed metric definitions and formulas
• Benchmark ranges by app category (social, productivity, games, utilities)
• App Store Connect specific metric definitions
• Red/yellow/green thresholds for all key metrics

Output Format

Present analysis as an Analytics Health Report:

# Analytics Health Report: [App Name]

## Overview
**App type:** [Free/Freemium/Subscription/Paid]
**Stage:** [Pre-launch/Early/Growing/Established]
**Data period:** [Date range analyzed]

## Funnel Health

| Stage | Metric | Value | Rating | Action |
|-------|--------|-------|--------|--------|
| Acquisition | Impressions/day | X,XXX | 🟢/🟡/🔴 | ... |
| Acquisition | Tap-through rate | X.X% | 🟢/🟡/🔴 | ... |
| Activation | Conversion rate | X.X% | 🟢/🟡/🔴 | ... |
| Retention | D1 retention | XX% | 🟢/🟡/🔴 | ... |
| Retention | D7 retention | XX% | 🟢/🟡/🔴 | ... |
| Retention | D30 retention | XX% | 🟢/🟡/🔴 | ... |
| Revenue | Conversion rate | X.X% | 🟢/🟡/🔴 | ... |
| Revenue | LTV | $XX.XX | 🟢/🟡/🔴 | ... |

## Primary Bottleneck
**[Stage name]** — [One sentence explanation of the biggest problem]

## Recommended Actions (Priority Order)
1. 🔴 [Critical fix] — Expected impact: [X]
2. 🟠 [High priority] — Expected impact: [X]
3. 🟡 [Medium priority] — Expected impact: [X]

## Overall Assessment
**Recommendation:** [Invest / Iterate / Pivot / Sunset]
**Rationale:** [2-3 sentences]

References

• metrics-reference.md — Metric definitions, formulas, and benchmarks
• app-store/keyword-optimizer/ — For ASO-related fixes
• monetization/ — For pricing and paywall optimization
• testing/ — For A/B test methodology

Metrics Reference

Definitions, formulas, and benchmarks for key app metrics. Use this as a lookup when interpreting user data in the analytics-interpretation skill.

Metric Definitions and Formulas

Engagement Metrics

DAU (Daily Active Users) Users who open the app at least once in a calendar day.

DAU = count of unique users with at least one session on a given day

MAU (Monthly Active Users) Users who open the app at least once in a 30-day rolling window.

MAU = count of unique users with at least one session in the last 30 days

DAU/MAU Ratio (Stickiness) Percentage of monthly users who use the app on any given day. Higher = more habitual usage.

DAU/MAU = DAU / MAU × 100

Session Length Average time spent per app session, from foreground to background.

Avg Session Length = total session time / total sessions

Sessions Per User Per Day How many times the average daily user opens the app.

Sessions/User/Day = total daily sessions / DAU

Retention Metrics

Day N Retention (D1, D7, D30) Percentage of users who installed on Day 0 and returned on Day N.

DN Retention = users active on Day N / users installed on Day 0 × 100

Note: This is "classic retention" (active on exactly Day N), not "rolling retention" (active on Day N or later).

Rolling Retention (Return Rate) Percentage of users who installed on Day 0 and returned on Day N or any day after.

Rolling DN Retention = users active on Day N or later / users installed on Day 0 × 100

Rolling retention is always >= classic retention and gives a more optimistic view.

Weekly Retention Percentage of users active in Week 1 who are also active in Week N.

Week N Retention = users active in Week N / users active in Week 1 × 100

Churn Rate (Monthly) Percentage of subscribers who cancel in a given month.

Monthly Churn = subscribers lost in month / subscribers at start of month × 100

Revenue Metrics

LTV (Lifetime Value) Total revenue expected from a single user over their entire lifetime.

LTV = ARPU / Monthly Churn Rate
or
LTV = ARPU × Average Customer Lifetime (in months)

ARPU (Average Revenue Per User) Revenue per user across all users (including free users).

ARPU = total revenue / total users (in period)

ARPPU (Average Revenue Per Paying User) Revenue per paying user only.

ARPPU = total revenue / paying users (in period)

MRR (Monthly Recurring Revenue) Predictable monthly revenue from active subscriptions.

MRR = number of active subscribers × average monthly subscription price

ARR (Annual Recurring Revenue) Annualized version of MRR.

ARR = MRR × 12

CAC (Customer Acquisition Cost) Cost to acquire one new user through paid channels.

CAC = total acquisition spend / new users acquired

Payback Period Months to recoup the cost of acquiring a user.

Payback Period = CAC / monthly ARPU (in months)

Trial Start Rate Percentage of downloads that start a free trial.

Trial Start Rate = trial starts / downloads × 100

Trial Conversion Rate Percentage of free trials that convert to paid subscriptions.

Trial Conversion = paid conversions / trial starts × 100

App Store Metrics

Impressions Number of times your app appeared in App Store search results, featured sections, or browse pages. Counts views of your icon/title, not full page views.

Product Page Views (PPV) Number of times users tapped through to your full product page (screenshots, description, reviews).

Tap-Through Rate (TTR)

TTR = Product Page Views / Impressions × 100

Conversion Rate (CVR)

CVR = App Units (downloads) / Product Page Views × 100

App Units First-time downloads. Does not include re-downloads or updates.

Benchmarks by App Category

Social / Communication Apps

Productivity / Business Apps

Games (Casual)

Utilities / Tools

Note: Utility apps often have low DAU/MAU because they are used only when needed (e.g., a calculator). Low stickiness is not necessarily bad for utilities — focus on retention and satisfaction instead.

Subscription Apps (General)

App Store Conversion Benchmarks

Tap-Through Rate (Impressions → Product Page Views)

Product Page Conversion Rate (PPV → Downloads)

Quick Threshold Reference

Use these stoplight ratings in analytics reports:

Note: These are general guidelines. Always consider app category, target audience, and monetization model when evaluating. A utility app with 8% DAU/MAU might be performing excellently, while a social app at 8% has a problem.

Pitch Templates

Email templates for press and media outreach. Customize every template for each recipient — generic mass emails get ignored.

General Tips (Apply to All Templates)

• Subject line: Keep under 60 characters, include app name, be specific
• Opening line: Reference something the journalist recently wrote or covered — proves you did your homework
• Body: Under 200 words total. Journalists receive hundreds of emails daily.
• One screenshot inline: Embed one compelling screenshot directly in the email (not as attachment)
• Links: Include App Store link, press kit link, TestFlight link (if pre-launch)
• Call to action: One clear ask — "Would you like a TestFlight invite?" or "Can I send a promo code?"
• Signature: Name, title, website, social media handle

---

Template 1: Launch Pitch

Use for new app launches. Best sent 2-3 weeks before launch.

Subject: [App Name] — [One-Sentence Value Proposition] (launching [date])

Hi [First Name],

I loved your recent piece on [their article/topic] — [brief, genuine comment showing you read it].

I'm reaching out because I'm launching [App Name], a [category] app for [platform] that [one sentence explaining what it does and why it matters].

[App Name] is different because [unique angle — privacy-first / solo developer story / innovative tech use / solves a specific problem]. [One sentence expanding on the story angle.]

Key details:
- Launch date: [date]
- Price: [free / $X.XX / subscription at $X.XX/mo]
- Platforms: [iOS 17+ / macOS 14+]
- Press kit: [URL]

[Embedded screenshot — choose your most visually impressive screen]

I'd love to offer you early access via TestFlight if you're interested. Happy to answer any questions or hop on a quick call.

Best,
[Name]
[Website] | [Twitter/X handle]

---

Template 2: Major Update Pitch

Use for significant feature updates. Best for apps that already have some users.

Subject: [App Name] [version] — [headline feature] now available

Hi [First Name],

[App Name] just shipped its biggest update yet, and I thought it might interest you given your coverage of [relevant topic/category].

What's new in [version]:
- [Feature 1]: [one sentence — the hero feature]
- [Feature 2]: [one sentence]
- [Feature 3]: [one sentence]

The headline feature, [Feature 1], lets users [specific benefit]. I built it because [brief story — user request / personal need / new Apple API].

[App Name] now has [social proof — X downloads / X rating / featured by Apple]. This update is free for existing users.

Press kit with new screenshots: [URL]
App Store: [URL]

Would you be interested in taking a look?

Best,
[Name]
[Website] | [Twitter/X handle]

---

Template 3: Story Angle Pitch (Developer Story)

Use when the story is about YOU, not just the product. Best for outlets that cover indie developers.

Subject: [Compelling one-line story hook]

Hi [First Name],

I've been following your coverage of indie developers, especially [specific piece they wrote]. I have a story that might resonate with your audience.

[2-3 sentences telling your story — why you built this app, what personal experience drove it, what makes your journey unusual or interesting.]

The result is [App Name], a [category] app that [what it does]. [One sentence on traction or reception — downloads, ratings, user testimonials, Apple feature.]

I'm not just pitching an app — I think there's a story here about [broader theme: indie sustainability / building for accessibility / leaving big tech / solving personal problems with code]. I'd be happy to share more details or do an interview.

App Store: [URL]
Press kit: [URL]

Thanks for considering,
[Name]
[Website] | [Twitter/X handle]

---

Template 4: Podcast Pitch

Use for podcast hosts. Keep it shorter — they need to see interview value, not just app features.

Subject: Podcast guest pitch — [one-line hook about your story]

Hi [Host Name],

I'm a listener of [Podcast Name] and particularly enjoyed your episode about [specific episode]. [One genuine sentence about why it resonated.]

I'm [Name], an indie developer who [brief personal hook — quit FAANG / built app while traveling / went from zero to $X revenue / overcame specific challenge]. I recently launched [App Name], a [category] app that [one sentence].

I think your listeners would enjoy hearing about:
- [Topic 1 — something practical they can learn from]
- [Topic 2 — a challenge you faced and how you solved it]
- [Topic 3 — a broader insight about indie development]

I'm comfortable on mic and can keep things conversational. Happy to work around your schedule.

Best,
[Name]
[App Name] — [URL]
[Twitter/X handle]

---

Template 5: Follow-Up

Use exactly once, 5-7 business days after the initial pitch. Add new information — do not just repeat the original pitch.

Subject: Re: [original subject line]

Hi [First Name],

I wanted to follow up on my email from last week about [App Name].

Since then, [add one piece of new information]:
- "[App Name] was just featured in [Apple editorial / another outlet / award]"
- "We hit [milestone — 1,000 downloads / 4.8 star rating / featured by Apple]"
- "I just shipped [new feature] that I think adds to the story"
- "A user shared this testimonial: '[brief quote]'"

If the timing isn't right or [App Name] isn't a fit for your coverage, no worries at all — I appreciate your time either way.

Press kit: [URL]
TestFlight: [URL]

Best,
[Name]

---

Personalization Checklist

Before sending ANY pitch, verify:

• [ ] Used the journalist's first name (spelled correctly)
• [ ] Referenced a specific recent article they wrote
• [ ] Explained why THIS journalist is the right person for THIS story
• [ ] Kept total email under 200 words
• [ ] Included one inline screenshot
• [ ] Included press kit and App Store links
• [ ] Proofread for typos (nothing kills credibility faster)
• [ ] Sent on Tuesday-Thursday, 9-11 AM in their time zone
• [ ] Subject line is specific and under 60 characters

What NOT to Do

• Do not send identical emails to multiple journalists at the same outlet
• Do not CC or BCC multiple journalists (always individual emails)
• Do not attach large files (link to press kit instead)
• Do not use "Dear Sir/Madam" or "To whom it may concern"
• Do not send more than one follow-up
• Do not pitch on the same day as a major Apple event
• Do not ask "did you get my email?" — it's passive-aggressive
• Do not offer payment for coverage (violates journalistic ethics)
• Do not get upset or respond negatively if they don't cover you