PostHog vs Google Analytics 2025: Product Metrics Guide for SaaS Teams

Introduction

You open Google Analytics. You see traffic numbers. But can you answer: "Why did users stop using our new feature?" or "Which users are about to churn*?"

If you're a PM or designer working on a SaaS product, website traffic isn't what keeps you up at night. You need to understand user behavior inside your product. That's where Google Analytics falls short—and where tools like PostHog shine.

Who this is for:

• Junior Product Managers new to analytics
• UX and Product Designers tracking feature adoption
• Early-stage SaaS teams choosing their analytics stack

What you'll learn:

• Why GA4 frustrates product teams (and the GDPR* risks in 2025)
• How PostHog solves common product analytics problems
• Every metric you should track—with exact events and dashboards
• A glossary of every industry term marked with (*)

Why GA4 Falls Short for Product Teams in 2025

Google Analytics 4 was built for marketers tracking ad campaigns. If you're building a SaaS product, you'll hit walls fast.

Session-Based vs Event-Based Tracking: What's the Difference?

Think of it this way:

Session-based (old Universal Analytics): Tracks visits as chunks. "User came, viewed 3 pages, left." Good for notess. Bad for apps.

Event-based (GA4 and PostHog): Tracks actions. "User clicked 'Create Project,' then 'Invite Team,' then 'Upgrade Plan.'" Good for understanding product usage.

GA4 moved to event-based tracking—but it's complicated to set up. You need Google Tag Manager, custom configurations, and engineering time for anything beyond pageviews.

What GA4 Can't Do Well

The Learning Curve Problem

GA4's interface is notoriously difficult. Reports that took seconds in Universal Analytics now require custom exploration builds. As one expert put it: "GA4 feels like it was designed with a data engineer's mindset, not a marketer's."

Data retention is capped at 14 months. Custom dimensions are limited to 50. If you hit these ceilings, your only option is archiving—there's no way to delete unused dimensions.

GA4 GDPR Compliance 2025: The Legal Risk You Can't Ignore

Here's the uncomfortable truth: using Google Analytics may be illegal in your country.

Current EU Rulings on Google Analytics

By mid-2025, six national data protection authorities have ruled against GA4:

Why This Happens

The problem isn't analytics—it's data transfer. When you use GA4:

1. User data (IP addresses, browser fingerprints) goes to Google's US servers
2. US surveillance laws allow government access to this data
3. GDPR requires "adequate protection" for EU citizens' data
4. Courts ruled that Google's protections aren't adequate

The EU-US Data Privacy Framework (DPF) Problem

In 2023, the EU and US created a new data transfer agreement. Google certified under it. Problem solved?

Not quite. In early 2025, the framework's oversight board was gutted. Privacy advocates expect legal challenges. Max Schrems (who killed two previous frameworks) recommends businesses "have a 'host in Europe' contingency plan."

Risk Summary for Your Team

If you have EU users, the safest path is an analytics tool that keeps data in Europe—or on your own servers.

PostHog as a GA4 Alternative: Built for Product Teams

PostHog isn't just "Google Analytics but different." It's a complete product analytics platform designed for teams building software.

Core Advantages for SaaS Products

1. Event-Based by Design

PostHog uses autocapture—it automatically tracks clicks, pageviews, and form submissions without manual tagging. When you need custom events, the SDK is straightforward:

posthog.capture('feature_used', {
  feature_name: 'dark_mode',
  user_plan: 'pro'
})

2. User-Level Tracking

Every visitor can become a person profile. When someone signs up, all their anonymous history merges into one identified user. You can view a complete timeline across sessions and devices.

3. Built-In Product Tools

PostHog includes:

• Session replay: Watch real users interact with your product
• Feature flags: Roll out features to specific user segments
• A/B testing (Experiments): Test changes with statistical significance
• Surveys: Collect NPS* and feedback in-product
• Heatmaps*: See where users click on any page

4. EU Hosting and Self-Hosting

Choose PostHog Cloud EU (Frankfurt servers) or self-host on your own infrastructure. Your data never touches US servers if you don't want it to.

Feature Comparison: GA4 vs PostHog

Pricing Reality

GA4 is "free" until you need to export data or exceed thresholds. Then GA360 starts at $50,000/year.

PostHog gives you 1 million events free monthly. After that, it's usage-based: $0.000031 per event, dropping as volume increases. Most startups pay nothing for their first year.

Product Metrics to Track in PostHog: The Complete Guide

Now the practical part. Here's every metric a SaaS product team should track, with exact PostHog implementation.

AARRR Framework: The Pirate Metrics

AARRR* stands for Acquisition, Activation, Retention, Revenue, and Referral—the five stages of the user lifecycle. Track these to understand your growth funnel*.

Acquisition

How to track in PostHog:

• Events to capture: $pageview (automatic), user_signed_up
• Properties: utm_source, utm_medium, utm_campaign, referrer
• Visualization: Trend chart filtered by signup event, broken down by UTM source
• Template: Create a dashboard with signup trends by channel. Compare Week 1 retention across acquisition sources.

Activation

How to track in PostHog:

• Events to capture: onboarding_started, onboarding_step_completed, first_value_action (define based on your product)
• Properties: step_number, time_since_signup, user_role
• Visualization: Funnel from signup → each onboarding step → first value action
• Template:

Funnel Steps:
1. user_signed_up
2. onboarding_completed
3. first_project_created (or your key action)
4. invited_team_member

Use Session Replay to watch users who drop off at each step.

Retention

How to track in PostHog:

• Events to capture: session_started or your core usage event (e.g., document_edited, report_generated)
• Properties: user_id, session_count, days_since_signup
• Visualization: Retention chart (cohort-based)
• Template:

Retention Insight:
- First event: user_signed_up
- Return event: Any core action (or specific feature)
- Period: Day / Week / Month

Look for the "flattening point" where retention stabilizes—that's your product's natural retention floor.

Revenue

How to track in PostHog:

• Events to capture: subscription_started, plan_upgraded, plan_downgraded, subscription_cancelled
• Properties: plan_type, price, billing_period, previous_plan
• Visualization: Trend chart of revenue events, Funnel from trial → paid
• Template:

Revenue Funnel:
1. trial_started
2. trial_day_3_active
3. trial_day_7_active
4. subscription_started

Break down by: plan_type, acquisition_source

Referral

How to track in PostHog:

• Events to capture: referral_link_shared, referral_invite_sent, referred_user_signed_up
• Properties: referrer_user_id, share_channel (email, link, social), referral_code
• Visualization: Trend of referral events, Funnel from share → signup → activation
• Template: Create a cohort of "referrers" (users who have shared). Compare their retention and LTV* to non-referrers.

B2B SaaS Revenue Metrics

These metrics matter for subscription businesses tracking financial health.

MRR (Monthly Recurring Revenue)

How to track in PostHog:

• Events to capture: subscription_started, subscription_renewed, subscription_cancelled, plan_changed
• Properties: mrr_value, plan_type, change_type (new, expansion, contraction, churn)
• Visualization: Trend with formula: Sum of mrr_value where event = subscription events
• Template: Build a dashboard showing New MRR + Expansion MRR - Churned MRR = Net New MRR

ARR (Annual Recurring Revenue)

Formula: ARR = MRR × 12

Track in PostHog using the same events as MRR, with a formula insight multiplying by 12.

Churn Rate

How to track in PostHog:

• Events to capture: subscription_cancelled, account_deleted
• Properties: cancellation_reason, plan_type, tenure_months, last_active_date
• Visualization: Trend of churn events / total active users at period start
• Template:

Churn Analysis:
1. Create cohort: Users who cancelled in last 30 days
2. Compare behavior to retained users
3. Use Correlation Analysis to find churn predictors

Churn formula: Churn Rate = (Customers lost in period / Customers at start of period) × 100

LTV (Lifetime Value)

Formula: LTV = ARPU × Customer Lifetime

Or: LTV = ARPU / Monthly Churn Rate

How to track in PostHog:

• Events to capture: All revenue events with revenue_amount property
• Visualization: Trend of cumulative revenue per user cohort over time
• Template: Use cohort analysis to track revenue from each signup month over 12+ months

CAC (Customer Acquisition Cost)

Formula: CAC = Total Sales & Marketing Spend / New Customers Acquired

PostHog tracks the "New Customers Acquired" numerator. For full CAC, combine with your finance data in a spreadsheet or data warehouse.

NRR (Net Revenue Retention)

Formula: NRR = (Starting MRR + Expansion - Contraction - Churn) / Starting MRR × 100

How to track in PostHog:

• Events to capture: plan_upgraded (expansion), plan_downgraded (contraction), subscription_cancelled (churn)
• Properties: mrr_change_amount, previous_mrr, new_mrr
• Visualization: Trend with formula calculating NRR monthly
• Template: Create a monthly cohort showing starting MRR and how it changes over 12 months

Benchmark: B2B SaaS companies should aim for NRR above 100%. Best-in-class companies hit 120%+.

Product Health Metrics

These metrics tell you if your product is building habits and delivering value.

DAU/MAU (Daily/Monthly Active Users)

How to track in PostHog:

• Events to capture: Any activity event, or use $pageview
• Visualization: Trend with "Unique users" count, daily and monthly views
• Template: PostHog has built-in DAU/MAU tracking in web analytics dashboard

Stickiness (DAU/MAU Ratio)

Formula: Stickiness = DAU / MAU × 100

How to track in PostHog:

• Visualization: Stickiness insight (built-in tool)
• Or: Trend with formula mode: Series A (DAU) / Series B (MAU)
• Template:

Stickiness Insight:
- Event: Your core usage event
- Shows: How many days users performed action in the period

Benchmarks:

• Social apps (Facebook): 68%
• B2B SaaS average: 13%
• Good for SaaS: 20%+

Feature Adoption Rate

How to track in PostHog:

• Events to capture: feature_viewed, feature_used, feature_used_again
• Properties: feature_name, user_tenure, user_plan
• Visualization: Funnel from feature discovery → first use → repeat use
• Template:

Feature Adoption Funnel:
1. feature_available (users who could see it)
2. feature_clicked
3. feature_completed_action
4. feature_used_week_2 (repeat usage)

Use feature flags to roll out to 10% of users first and measure adoption before full release.

Cohort Analysis

How to track in PostHog:

• Create cohorts by: Signup week, acquisition source, plan type, company size
• Visualization: Retention chart with cohort breakdown
• Template:

Cohort Comparison:
1. Create cohort: Users signed up in January
2. Create cohort: Users signed up in February
3. Compare Week 4 retention between cohorts

This shows if product changes are actually improving retention.

Getting Started: Your First 3 Metrics

Don't try to track everything at once. Start here:

Week 1: Activation Funnel

1. Define your "aha moment" (the first valuable action)
2. Create a funnel from signup → aha moment
3. Find where users drop off
4. Watch session replays of users who didn't activate

Week 2: Retention Curve

1. Set up a retention insight with your core usage event
2. Look for the "flattening point"
3. Create cohorts to compare different user segments
4. Identify what activated users do differently

Week 3: Feature Adoption

1. Pick one key feature
2. Track views → first use → repeat use
3. Use feature flags to test with a subset of users
4. Measure impact on retention

Next Steps

• Add revenue tracking events once you have paid users
• Build a dashboard combining all AARRR metrics
• Set up alerts for significant metric drops
• Share dashboards with your team for alignment

CTA: Start with PostHog's free tier (1M events/month). No credit card required.

Glossary

All terms marked with (*) in this article, alphabetized:

AARRR — A framework for tracking the user lifecycle: Acquisition, Activation, Retention, Revenue, Referral. Also called "Pirate Metrics" because it sounds like "Arrr!"

Aha moment — The point when a user first experiences the core value of your product. Users who reach this moment are significantly more likely to retain.

ARR (Annual Recurring Revenue) — Your MRR multiplied by 12. The standard metric for measuring and comparing SaaS company size.

CAC (Customer Acquisition Cost) — The total sales and marketing spend divided by the number of new customers acquired. Tells you how much it costs to get each customer.

Churn — When a customer stops using (and paying for) your product. Churn rate is the percentage of customers lost in a given period.

Cohort — A group of users who share a common characteristic, typically signup date. Used to compare how different groups behave over time.

DAU (Daily Active Users) — The count of unique users who were active in your product on a given day.

Feature flags — A technique for enabling or disabling features for specific users without deploying new code. Used for gradual rollouts and A/B testing.

Funnel — A visualization of users moving through a series of steps (like signup → onboarding → first value action). Shows where users drop off.

GDPR (General Data Protection Regulation) — EU law governing data privacy. Requires explicit consent for data collection and restricts transferring EU citizens' data outside Europe.

Heatmaps — Visual representations of where users click, scroll, or hover on a page. Warmer colors indicate more activity.

LTV (Lifetime Value) — The total revenue you expect to earn from a customer over their entire relationship with your company.

MAU (Monthly Active Users) — The count of unique users who were active in your product during a given month.

MRR (Monthly Recurring Revenue) — The predictable revenue you receive each month from subscriptions. The foundation of SaaS financial metrics.

NPS (Net Promoter Score) — A customer satisfaction metric based on asking "How likely are you to recommend us?" on a 0-10 scale. Scores 9-10 are Promoters, 0-6 are Detractors. NPS = % Promoters - % Detractors.

NRR (Net Revenue Retention) — The percentage of revenue retained from existing customers, including expansions and subtracting contractions and churn. Above 100% means you grow from existing customers alone.

Retention — The ability to keep users coming back over time. Usually measured as the percentage of users who return after their first visit/action.

Stickiness — How often users return to your product. Commonly measured as DAU/MAU ratio—what percentage of monthly users engage daily.

Internal Linking Suggestions

1. "How to set up PostHog for your SaaS" — Technical setup guide (link from "Getting Started" section)
2. "Understanding user retention: A complete guide" — Deep-dive on retention analysis (link from Retention metric)
3. "Feature flags best practices" — Guide to using flags effectively (link from Feature Adoption section)

Featured Snippet Target

Target query: "What is stickiness in product analytics?"

Snippet-optimized answer:

Stickiness measures how habit-forming your product is. It's calculated as DAU (Daily Active Users) divided by MAU (Monthly Active Users), expressed as a percentage. A stickiness ratio of 20% means 20% of your monthly users engage with your product every day. The SaaS industry average is 13%. Higher stickiness indicates users can't live without your product.