analytics

name	analytics
description	Use when the user asks about "analytics", "PostHog", "Mixpanel", "Google Analytics", "event tracking", "conversion funnel", "A/B testing", "feature flag", "LaunchDarkly", "Statsig", "user segmentation", "metrics", "KPI", "tracking plan", "product analytics", "experiment", or needs analytics, experimentation, and feature flag knowledge.
keywords	["analytics","PostHog","Mixpanel","Google Analytics","event tracking","conversion funnel","A/B testing","feature flag","LaunchDarkly","Statsig","user segmentation","metrics","KPI","tracking plan","product analytics","experiment"]

Analytics & Feature Flags Skill

Comprehensive guide for implementing product analytics, event tracking, A/B testing, and feature flags in web applications.

---

Analytics Tool Decision Tree

What do you need?
├── Full product analytics + session replay + feature flags?
│   └── PostHog (open-source, self-hostable, all-in-one)
├── Advanced product analytics + deep funnels?
│   └── Mixpanel (best funnel/retention analysis)
├── Website traffic analytics only?
│   ├── Need Google Ads integration? → GA4
│   └── Privacy-first, simple? → Plausible or Fathom
├── Feature flags only?
│   ├── Enterprise scale + targeting? → LaunchDarkly
│   ├── Stats + experimentation? → Statsig
│   └── Bundled with analytics? → PostHog
└── A/B testing only?
    ├── Visual editor + no-code? → VWO or Optimizely
    └── Code-based + stats? → Statsig or PostHog

Tool	Type	Self-host	Free tier	Best for
PostHog	All-in-one	Yes	1M events/mo	Startups wanting one tool
Mixpanel	Product analytics	No	20M events/mo	Deep behavioral analysis
GA4	Web analytics	No	Unlimited	Traffic + marketing attribution
Plausible	Web analytics	Yes	None (paid)	Privacy-first simple analytics
LaunchDarkly	Feature flags	No	Limited	Enterprise feature management
Statsig	Flags + experiments	No	1M events/mo	Data-driven experimentation

---

Event Tracking Architecture

Event Naming Convention

Use a consistent object_action or noun_verb pattern:

✅ Good                    ❌ Bad
──────────────────────────────────────────
user_signed_up             signup
page_viewed                pageview
button_clicked             click
subscription_created       new sub
invoice_paid               payment
feature_used               used_feature
onboarding_completed       done onboarding

Event Taxonomy

Category	Events	Key Properties
Identity	user_signed_up, user_logged_in	method, referral_source
Activation	onboarding_started, onboarding_completed	step, time_to_complete
Engagement	feature_used, page_viewed	feature_name, page_path
Conversion	subscription_created, checkout_started	plan, price, currency
Retention	session_started, daily_active	days_since_signup
Revenue	invoice_paid, subscription_upgraded	amount, plan_from, plan_to

---

Tracking Plan Template

Event Name	Trigger	Properties	Owner	Status
user_signed_up	After successful registration	method: string, referral: string	Auth team	Active
onboarding_step_completed	Each onboarding step done	step: number, step_name: string	Growth team	Active
feature_used	User interacts with feature	feature: string, context: string	Product team	Active
subscription_created	After successful payment	plan: string, price: number, trial: boolean	Billing team	Active
page_viewed	Route change	path: string, referrer: string	Engineering	Active

---

Implementation Patterns

PostHog Setup (React / Next.js)

// lib/posthog.ts
import posthog from 'posthog-js';

export function initPostHog() {
  if (typeof window === 'undefined') return;

  posthog.init(process.env.NEXT_PUBLIC_POSTHOG_KEY!, {
    api_host: process.env.NEXT_PUBLIC_POSTHOG_HOST || 'https://us.i.posthog.com',
    person_profiles: 'identified_only',
    capture_pageview: false, // Manual pageviews for SPA
    capture_pageleave: true,
  });
}

// Identify user after login
export function identifyUser(userId: string, traits: Record<string, unknown>) {
  posthog.identify(userId, traits);
}

// Track event
export function trackEvent(event: string, properties?: Record<string, unknown>) {
  posthog.capture(event, properties);
}

// Reset on logout
export function resetAnalytics() {
  posthog.reset();
}

// app/providers.tsx (Next.js App Router)
'use client';

import { useEffect } from 'react';
import { usePathname, useSearchParams } from 'next/navigation';
import { initPostHog, trackEvent } from '@/lib/posthog';

export function AnalyticsProvider({ children }: { children: React.ReactNode }) {
  const pathname = usePathname();
  const searchParams = useSearchParams();

  useEffect(() => {
    initPostHog();
  }, []);

  useEffect(() => {
    trackEvent('page_viewed', { path: pathname });
  }, [pathname, searchParams]);

  return <>{children}</>;
}

Server-Side Tracking (API Routes)

// lib/analytics-server.ts
import { PostHog } from 'posthog-node';

const posthog = new PostHog(process.env.POSTHOG_API_KEY!, {
  host: process.env.POSTHOG_HOST,
});

export function trackServerEvent(
  userId: string,
  event: string,
  properties?: Record<string, unknown>
) {
  posthog.capture({
    distinctId: userId,
    event,
    properties,
  });
}

// Flush before serverless function exits
export async function flushAnalytics() {
  await posthog.shutdown();
}

Client vs Server Tracking Decision

Track on...	When	Examples
Client	UI interactions, page views, clicks	button_clicked, page_viewed
Server	Business events, reliable tracking	subscription_created, invoice_paid
Both	Conversion with UI context	checkout_started (client) → checkout_completed (server)

---

Conversion Funnel Setup

Define Your Funnel

Landing Page → Sign Up → Onboarding → Feature Used → Subscription
   100%          30%        20%           12%             5%

Implementation

// Track each funnel step
trackEvent('landing_page_viewed', { variant: 'a' });
trackEvent('signup_form_started');
trackEvent('user_signed_up', { method: 'email' });
trackEvent('onboarding_step_completed', { step: 1, step_name: 'profile' });
trackEvent('onboarding_completed', { time_to_complete: 120 });
trackEvent('feature_used', { feature: 'dashboard' });
trackEvent('checkout_started', { plan: 'pro' });
trackEvent('subscription_created', { plan: 'pro', price: 29 });

---

A/B Testing Workflow

Process

1. Hypothesis → "Changing CTA color to green will increase signups by 10%"
2. Metric     → signup_rate (signups / landing_page_views)
3. Experiment → Create A/B test with variants
4. Run        → Wait for statistical significance (usually 1-2 weeks)
5. Analyze    → Check results, segment by user type
6. Ship       → Roll out winner to 100%

PostHog Experiment Example

// Check experiment variant
import posthog from 'posthog-js';

function SignupButton() {
  const variant = posthog.getFeatureFlag('signup-cta-experiment');
  // variant: 'control' | 'green-cta' | false (not in experiment)

  return (
    <button
      className={variant === 'green-cta' ? 'bg-green-500' : 'bg-blue-500'}
      onClick={() => trackEvent('signup_cta_clicked', { variant })}
    >
      {variant === 'green-cta' ? 'Start Free Trial' : 'Sign Up'}
    </button>
  );
}

Experiment Sizing Quick Reference

Daily traffic	Minimum detectable effect	Approx. runtime
100 visitors/day	20%+	2-4 weeks
1,000 visitors/day	5-10%	1-2 weeks
10,000 visitors/day	2-5%	3-7 days

Rule of thumb: Need ~400 conversions per variant for 80% statistical power with a 5% minimum detectable effect.

---

Feature Flag Patterns

Boolean Flag (Kill Switch / Gradual Rollout)

// Check flag
if (posthog.isFeatureEnabled('new-dashboard')) {
  return <NewDashboard />;
}
return <OldDashboard />;

Multivariate Flag

const variant = posthog.getFeatureFlag('pricing-page');

switch (variant) {
  case 'monthly-first':
    return <PricingMonthlyFirst />;
  case 'annual-first':
    return <PricingAnnualFirst />;
  default:
    return <PricingDefault />;
}

Server-Side Feature Flag

import { PostHog } from 'posthog-node';

const posthog = new PostHog(process.env.POSTHOG_API_KEY!);

export async function getFeatureFlag(userId: string, flag: string) {
  const isEnabled = await posthog.isFeatureEnabled(flag, userId);
  return isEnabled;
}

// With properties for targeting
const isEnabled = await posthog.isFeatureEnabled('beta-feature', userId, {
  personProperties: { plan: 'enterprise', company_size: 500 },
});

Feature Flag Tool Comparison

Tool	Flags	Experiments	Analytics	Pricing
PostHog	Yes	Yes	Yes (built-in)	Free to 1M events
LaunchDarkly	Best-in-class	Limited	No	$$$ (enterprise)
Statsig	Yes	Best-in-class	Basic	Free to 1M events
Unleash	Yes	Basic	No	Open-source

---

User Segmentation and Cohorts

Setting User Properties

// Set user properties for segmentation
posthog.identify(userId, {
  plan: 'pro',
  company_size: 50,
  industry: 'saas',
  signup_date: '2024-01-15',
  role: 'admin',
});

// Set group (company-level analytics)
posthog.group('company', companyId, {
  name: 'Acme Inc',
  plan: 'enterprise',
  employee_count: 500,
});

Useful Segments

Segment	Definition	Use for
Power users	>10 sessions in 7 days	Feature adoption, beta testing
At-risk	No login in 14 days, active last month	Churn prevention
New users	Signed up < 7 days ago	Onboarding optimization
Converted	Has active subscription	Revenue analysis
Enterprise	Company size > 100	Sales-led features

---

Privacy-Compliant Tracking

Consent Implementation

// Check consent before tracking
export function trackEvent(event: string, properties?: Record<string, unknown>) {
  const consent = getConsentStatus(); // from cookie/localStorage

  if (consent === 'granted') {
    posthog.capture(event, properties);
  } else if (consent === 'anonymous') {
    // Track without PII
    posthog.capture(event, {
      ...properties,
      $process_person_profile: false,
    });
  }
  // If 'denied', don't track at all
}

// Opt out completely
posthog.opt_out_capturing();

// Opt back in
posthog.opt_in_capturing();

Privacy Checklist

• Respect Do Not Track (DNT) header
• Implement consent banner before tracking
• Anonymize IP addresses
• Don't track PII in event properties
• Provide opt-out mechanism
• Document data retention policies
• See compliance skill for GDPR/CCPA details

---

Key SaaS Metrics Reference

Metric	Formula	Good benchmark
MRR	Sum of all monthly subscription revenue	Growing 10%+ MoM early stage
ARR	MRR × 12	-
Churn rate	Lost customers / Start customers × 100	<5% monthly, <10% annual
Revenue churn	Lost MRR / Start MRR × 100	<2% monthly
Net revenue retention	(Start MRR + expansion − contraction − churn) / Start MRR	>100% (good), >120% (great)
LTV	ARPU / Churn rate	>3× CAC
CAC	Total acquisition cost / New customers	<1/3 LTV
LTV:CAC ratio	LTV / CAC	>3:1
Activation rate	Users completing key action / Total signups	>25%
Time to value	Time from signup to "aha moment"	As short as possible
DAU/MAU ratio	Daily active / Monthly active	>20% (good), >50% (great)

---

Common Mistakes

Mistake	Problem	Fix
No tracking plan	Inconsistent events, missing data	Create a tracking plan before implementing
Tracking everything	Noise, slow queries, high costs	Track actions that map to business questions
Inconsistent event names	Can't query across features	Use strict object_action naming convention
Not identifying users	Can't track across sessions	Call identify() after login
Client-only tracking	Adblockers miss 15-30% of events	Use server-side for business-critical events
No consent management	GDPR/CCPA violations	Implement consent before tracking
Feature flags without cleanup	Tech debt, confusing code	Set expiration dates, remove old flags
Not segmenting experiment results	Missing insights	Always check results by user segment
Vanity metrics only	No actionable insights	Focus on activation, retention, revenue
Not flushing server-side	Lost events in serverless	Call posthog.shutdown() before exit

---

Pre-Delivery Checklist

• Tracking plan documented (event names, properties, owners)
• Event naming follows consistent convention
• User identification set up (identify on login, reset on logout)
• Page view tracking works for SPA navigation
• Server-side tracking for business-critical events
• Analytics flushes properly in serverless environments
• Consent management implemented before tracking
• Feature flags have cleanup/expiration plan
• Key funnels defined and instrumented
• User properties set for segmentation
• No PII in event properties
• Analytics works with ad blockers (server-side fallback or proxy)
• Dashboard created for key metrics
• Team has access to analytics tool

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References

• PostHog Docs
• Mixpanel Docs
• GA4 Docs
• LaunchDarkly Docs
• Statsig Docs