Plan a 30-Day Analytics Audit (with Real Fixes)

Marketing leaders at web and app startups don’t need more dashboards—they need analytics they can trust. This 30-day audit plan helps you clean up tracking, fix identity resolution, and close the loop with ad platforms—all without ripping out your current stack.

Building from scratch? If you’re standing up a new analytics stack, see our 90-Day CDP Launch Plan for a comprehensive Segment + Amplitude + AppsFlyer implementation.

Need the strategic context? Read Bridging Data Silos: Identity Resolution and CDPs to understand why clean identity and attribution matter.

Who This Is For

Marketers at web/app startups who want:

• Cleaner attribution across channels
• Reliable funnels that match backend reality
• Conversions that ad platforms can actually optimize
• No platform switches required—fix what you have first

You’ll need a friendly developer for a few hours each week, but you don’t need a data engineering team or a six-month project.

What You’ll Have by Day 30

By the end of this audit, your team will have:

Clean, consistent events for moments that matter: sign-up, onboarding, purchase/subscription. Revenue events always include value, currency, and unique transaction IDs.

Identity that behaves: When someone logs in, their earlier activity connects to the same profile—even across devices.

Decision-ready dashboards: A funnel, a retention view, and a simple LTV-by-source chart you can review every week.

Closed-loop conversions: The same purchase/subscription you see in analytics is sent to ad platforms (deduped and privacy-safe) so bidding improves.

Week 1: Inventory and a Tiny Tracking Plan

Goal: Pick a small set of events (10–20) to fix first and standardize their fields.

List What’s Live Today

Export current events from your analytics tools (Google Analytics, Amplitude, Mixpanel, etc.). Note:

• Duplicate event names (e.g., “Signup” vs “signup_completed” vs “SignUpComplete”)
• Missing required parameters (revenue without currency, events without UTM passthrough)
• Events you no longer use or understand

Choose Your Core Events

Start with 10–20 events maximum. For most monetized apps:

Authentication & Onboarding

signup_started:
  properties: [method, utm_source, utm_medium, utm_campaign]

signup_completed:
  properties: [method, utm_source, utm_medium, utm_campaign]

onboarding_completed:
  properties: [variant, duration_seconds]

Monetization

paywall_viewed:
  properties: [placement, offer_id]

purchase_initiated:
  properties: [product_id, price, currency]

purchase_completed:
  properties: [product_id, price, currency, transaction_id]

Subscription-Based Apps

subscription_started:
  properties: [plan_id, price, currency, billing_period]

subscription_renewed:
  properties: [plan_id, price, currency, term_count]

subscription_canceled:
  properties: [plan_id, reason]

Engagement Signals

feature_used:
  properties: [feature_name]

session_started:
  properties: [platform, app_version]

Ship Quick Fixes

These are small code changes your developer can ship this week:

1. Add required revenue fields: Ensure purchase_completed and subscription_started always include value, currency, and transaction_id
2. Mark true conversions: Configure your analytics and ad tools to recognize the right conversion events (not just page views)
3. Pass campaign fields: Send UTM parameters on key events (signup, purchase), not just landing pages

Deliverables This Week

✅ One-page tracking plan (event names + required fields) ✅ Short list of code fixes to ship immediately ✅ Agreement on which 10–20 events to fix first

Week 2: Make Identity Behave

Goal: One person should look like one person across sessions and devices.

Decide What Identifies a Person

Usually this is:

• Account ID (if you have user accounts)
• Email (hashed if needed for privacy)
• Phone number (for SMS-first apps)

Write down your rule: “A user is identified by [field] once they [action].”

Example: “A user is identified by user_id (account UUID) once they complete signup or log in.”

Test Three Simple Journeys

Run these manually with your developer watching the analytics:

Journey 1: Anonymous → Sign Up → Log In (Same Device)

1. Browse anonymously (don’t log in)
2. Complete signup
3. Log in

Expected result: All anonymous events before signup should attach to the identified user profile.

Journey 2: Browse on Phone → Log In on Desktop

1. Browse app/site on mobile (not logged in)
2. Log in on desktop

Expected result: Mobile and desktop activity should merge into one profile after login.

Journey 3: Log Out → Log In as Different Person

1. Log in as User A
2. Log out
3. Log in as User B

Expected result: User B shouldn’t inherit User A’s history. Identity should reset on logout.

Ship the Small Fixes

If any journey fails, fix these:

1. Call “set user ID” on login: Most analytics SDKs have an identify() or setUserId() method
2. Clear identity on logout: Call reset() or equivalent to prevent profile contamination
3. Persist UTMs into meaningful events: Don’t just capture UTMs on page load—pass them through to purchase_completed, signup_completed, etc.

Deliverables This Week

✅ Identity rules documented (what counts as user ID, when it’s set/cleared) ✅ Confirmation that all three test journeys work correctly ✅ Code changes shipped to fix identity gaps

Week 3: Publish Dashboards and Send Conversions to Ads

Goal: Give marketing and finance one place to look, and let ad platforms optimize to real outcomes.

Dashboards to Build (Keep Them Simple)

Build exactly three dashboards, no more:

1. Funnel Dashboard

Events: signup_completed → onboarding_completed → purchase_completed (or subscription_started)

Breakdown: By source, medium, campaign

Why it matters: Shows drop-off points and which channels drive complete conversions

2. Retention Dashboard

Metric: How many users return and do something valuable after Day 1/7/30

Valuable actions: Another purchase, a renewal, or core feature usage

Breakdown: By cohort (signup week) and source

Why it matters: Separates channels that drive one-time users from channels that drive long-term value

3. LTV by Source

Metric: Lifetime value (total revenue per user) by acquisition channel/campaign

Use corrected events: Based on the purchase_completed and subscription_renewed events you fixed in Week 1

Why it matters: Shows true ROI per channel, not just cost-per-acquisition

Send Conversions Back to Ad Platforms Correctly

Close the loop so Meta, Google, TikTok, etc. can optimize bidding to your real outcomes:

Deduplication Strategy

Use the same transaction/event ID in both:

• Browser-side pixel/tag
• Server-side conversion API

Example (Meta CAPI):

// Client-side (Meta Pixel)
fbq('track', 'Purchase', {
  value: 29.99,
  currency: 'USD',
  eventID: 'txn_abc123'  // ← Shared ID
});

// Server-side (Conversions API)
POST https://graph.facebook.com/v18.0/{pixel-id}/events
{
  "data": [{
    "event_name": "Purchase",
    "event_id": "txn_abc123",  // ← Same ID = dedupe
    "event_time": 1234567890,
    "user_data": {
      "em": "7d8c3c6c7e3c9a5e..."  // hashed email
    },
    "custom_data": {
      "value": 29.99,
      "currency": "USD"
    }
  }]
}

Privacy-Safe Matching

Where supported, send hashed identifiers (SHA-256) to improve match rates without sharing raw data:

• Email → SHA256(lowercase_email)
• Phone → SHA256(normalized_phone)

Google Enhanced Conversions and Meta Conversions API both support this.

Deliverables This Week

✅ Links to three live dashboards (funnel, retention, LTV-by-source) ✅ Note listing which conversion events go to which ad platforms ✅ Confirmation that conversions are deduped (browser + server using shared event ID)

Week 4: Reconcile, Add Guardrails, and Document

Goal: Make the numbers predictable and keep them that way.

Reconcile Counts

Compare analytics numbers to your database truth table for the events you fixed.

Example reconciliation:

Write down expected differences so weekly reviews don’t get stuck on tool mismatches:

• Ad blockers and browser privacy controls (expect 5–15% loss on client-side events)
• iOS ATT opt-outs (~70–80% of iOS users)
• Attribution window differences (ad platforms vs. analytics)

Add Guardrails

Turn on basic quality checks that flag problems before they break reports:

Option 1: Analytics Platform Features

• Google Analytics 4: Data quality indicators in DebugView
• Amplitude: Govern feature flags unknown events/properties
• Mixpanel: Lexicon alerts for schema violations

Option 2: Segment Protocols (if using Segment)

Enforce your tracking plan in real time—blocks or flags events that don’t match schema.

Option 3: Simple CI Check

Add a test that fails if new events ship without required fields:

test('purchase events include required fields', () => {
  const event = trackPurchase({ product_id: 'prod_123' });
  expect(event).toHaveProperty('value');
  expect(event).toHaveProperty('currency');
  expect(event).toHaveProperty('transaction_id');
});

Leave a One-Page Runbook

Create a single document your team can reference forever. Include:

1. Event Management Process

• How to add or change an event (and who approves)
• Required fields for all revenue events
• Naming conventions (e.g., snake_case, past tense: purchase_completed)

2. Identity Rules

• What field identifies a user (user_id, email, etc.)
• When identity is set (signup, login)
• When identity is cleared (logout, account deletion)

3. Ad Platform Conversion Fields

• Required fields: transaction_id, value, currency
• Deduplication strategy: shared event_id across browser + server
• Hashed identifiers: SHA256(email), SHA256(phone) where supported

Deliverables This Week

✅ Short reconciliation note (analytics vs. database, expected deltas documented) ✅ Basic event-quality checks enabled ✅ One-page runbook saved and shared with team

Common Pitfalls (and Quick Fixes)

Problem: Multiple Names for the Same Action

Example: “Signup”, “signup_completed”, “SignUpComplete”, “user_registered”

Fix: Choose one canonical name (signup_completed) and enforce it. Deprecate the others.

Problem: Missing Revenue Details

Example: Purchase event with no value or currency

Fix: Always include value, currency, and transaction_id on purchases and subscriptions. Make this a required check in CI or analytics governance.

Problem: People Counted Twice

Example: Same person shows up as two users after logout/login

Fix: Set user ID on login and clear identity on logout. Test the logout→login journey (Week 2).

Problem: Double-Counted Conversions in Ads

Example: Meta reports 2x more conversions than your database

Fix: Use one shared event ID in both browser pixel and server API. Platforms deduplicate when event_name + event_id match.

Problem: Dashboards Nobody Trusts

Example: Ten different dashboards, all showing different numbers

Fix: Build only three dashboards (funnel, retention, LTV-by-source) tied to the corrected events. Reconcile with backend data and document expected deltas.

Copy-Paste Checklist

Use this to track your 30-day progress:

Week 1: Tracking Plan

• Core events defined (10–20 max) with required fields
• Purchases/subscriptions include value, currency, transaction_id
• Quick fixes shipped (revenue fields, UTM passthrough)

Week 2: Identity

• Identity rules set (login sets user ID, logout clears)
• Three test journeys verified:
  • Anonymous → signup → login (same device)
  • Browse mobile → login desktop (cross-device)
  • Logout User A → login User B (identity reset)

Week 3: Dashboards & Conversions

• Funnel dashboard live (by source/campaign)
• Retention dashboard live (Day 1/7/30, meaningful return action)
• LTV-by-source dashboard live and reviewed with finance
• Ad platforms receiving conversions with shared event_id
• Hashed identifiers enabled where supported (email → SHA-256)

Week 4: Guardrails & Documentation

• Reconciliation complete (analytics vs. database, deltas documented)
• Event-quality checks enabled (unknown events/missing fields flagged)
• One-page runbook saved:
  • Event management process
  • Identity rules
  • Ad conversion fields & deduplication strategy

What Comes After Day 30?

Once your audit is complete, you’ll have:

• Trustworthy numbers that match your backend reality (within expected deltas)
• Attribution that works across channels, devices, and sessions
• Ad platforms that optimize to real outcomes instead of proxy metrics

When to Consider a CDP

If you find yourself:

• Fighting recurring drift as teams ship new features
• Manually syncing events to 5+ tools (analytics, ads, CRM, warehouse)
• Losing signal to browser controls and need more server-side collection

…then explore a Customer Data Platform (CDP) like Segment or RudderStack. But you don’t need a CDP to succeed with this 30-day audit.

Ready for a full CDP implementation? See our 90-Day CDP Launch Plan for a comprehensive Segment + Amplitude + AppsFlyer rollout.

Need budget planning? Check out What a CDP Really Costs in 2025 for software pricing and implementation ranges.

Want Help Running This Audit?

MetaCTO runs this exact audit for startups in 30 days. We deliver the tracking plan, fix identity and conversions, build your three core dashboards, and leave your team with the one-page runbook to keep it clean going forward.

Need a full CDP implementation? We also deliver 90-day CDP rollouts with Segment, Amplitude, and AppsFlyer.

Contact us to discuss your analytics audit and implementation timeline.

Additional Resources

Analytics Platform Documentation

• Google Analytics 4: User-ID for Cross-Platform Analysis
• Amplitude: Identify API and User Properties
• Mixpanel: Identity Management Best Practices

Ad Platform Conversion APIs

• Meta Conversions API: Getting Started
• Meta CAPI: Event Deduplication
• Google Enhanced Conversions Setup
• TikTok Events API Documentation

Data Quality & Governance

• Segment Protocols: Schema Enforcement
• Amplitude Govern: Data Quality Tools

A month is enough to make your numbers trustworthy. Keep the plan small, ship fixes weekly, and protect the gains with simple guardrails.