Mobile App Analytics Platforms Compared for 2023
You cannot improve what you do not measure. For mobile apps, analytics is the difference between guessing why users churn and knowing exactly where your onboarding funnel breaks down. But the analytics landscape has grown crowded, and choosing the wrong platform means either migrating later (painful) or living with gaps in your data (costly).
After implementing analytics across apps ranging from early-stage startups to enterprise applications, here is an honest comparison of the platforms that matter in 2023: Firebase Analytics, Mixpanel, Amplitude, PostHog, and Segment.
What to Evaluate
Before comparing platforms, establish your evaluation criteria. The right platform depends on your specific needs:
- Event volume: How many events per month will you track?
- Analysis complexity: Do you need basic funnels or advanced cohort analysis?
- Team capabilities: Is your team technical enough for SQL-based tools?
- Privacy requirements: Do you need data residency in Australia?
- Budget: What can you realistically spend on analytics?
- Integration needs: What other tools need to connect to your analytics?
Firebase Analytics (Google Analytics for Firebase)
**Be
st for**: Early-stage apps, Google ecosystem users, budget-conscious teams
Firebase Analytics is free, unlimited, and deeply integrated with the Google ecosystem. For many Australian startups, it is the default choice simply because it costs nothing and comes bundled with other Firebase services.
Strengths:
- Completely free with unlimited event volume
- Automatic event tracking (app opens, screen views, in-app purchases)
- Deep integration with Google Ads, BigQuery, and other Firebase services
- Real-time event monitoring for debugging
- Audience builder for targeted messaging via Firebase Cloud Messaging
- Predictive analytics for churn and spend likelihood
Weaknesses:
- Limited event parameters (25 per event, 500 distinct events)
- Analysis capabilities are basic compared to dedicated product analytics tools
- Data latency of several hours for most reports
- Custom funnels and cohort analysis are rudimentary
- BigQuery export required for advanced analysis (adds complexity and cost)
- Data is processed in the US, which may concern privacy-sensitive applications
Implementation:
// iOS
Analytics.logEvent("add_to_cart", parameters: [
"item_id": product.id,
"item_name": product.name,
"price": product.price,
"currency": "AUD"
])// Android
firebaseAnalytics.logEvent("add_to_cart") {
param("item_id", product.id)
param("item_name", product.name)
param("price", product.price)
param("currency", "AUD")
}Verdict: Start here if you are building an MVP or have limited budget. Migrate to a more capable platform when you need deeper analysis.
Mixpanel
**Be
st for**: Product-led growth companies, teams focused on user behaviour analysis
Mixpanel pioneered event-based analytics and remains one of the strongest platforms for understanding user behaviour. Their free tier (up to 20 million events per month) is generous enough for most growing apps.
Strengths:
- Powerful funnel analysis with conversion tracking
- Cohort analysis to understand retention by user segments
- Flow analysis showing actual user navigation paths
- Interactive reports that non-technical team members can build
- Excellent mobile SDKs with offline event queuing
- Data governance tools for managing PII
Weaknesses:
- Advanced features require paid plans (starting around $25/month)
- Can become expensive at high event volumes
- Learning curve for advanced analysis features
- Data residency limited to US and EU (no Australian option)
Implementation:
// iOS
Mixpanel.mainInstance().track(event: "Add to Cart", properties: [
"product_id": product.id,
"product_name": product.name,
"price": product.price,
"category": product.category
])
// User identity
Mixpanel.mainInstance().identify(distinctId: user.id)
Mixpanel.mainInstance().people.set(properties: [
"$name": user.name,
"$email": user.email,
"plan": user.subscription.plan
])Verdict: Excellent choice for product teams that need to understand user behaviour in depth. The free tier is generous and the analysis tools are best-in-class.
A
mplitude
Best for: Data-driven product teams, companies with dedicated product analytics roles
Amplitude positions itself as a “digital analytics platform” rather than just an analytics tool. It offers the deepest analysis capabilities of any platform in this comparison, with features like behavioural cohorting, path analysis, and predictive analytics.
Strengths:
- Most powerful analysis engine with SQL-like query builder
- Behavioural cohorts that update in real time
- Experiment analysis (A/B testing integration)
- Portfolio analysis for multi-product companies
- Governance features for enterprise data management
- Generous free tier (up to 10 million events per month)
- Session replay (recently added)
Weaknesses:
- Steep learning curve — requires dedicated analyst or training
- Premium features are enterprise-priced
- Mobile SDK is heavier than alternatives
- Can be overwhelming for small teams
- Setup requires careful event taxonomy planning
Implementation:
// Android
val event = JSONObject().apply {
put("product_id", product.id)
put("product_name", product.name)
put("price", product.price)
put("category", product.category)
}
Amplitude.getInstance().logEvent("Add to Cart", event)
// User properties
val identify = Identify()
.set("plan", user.plan)
.set("signup_date", user.signupDate)
Amplitude.getInstance().identify(identify)Verdict: Choose Amplitude if you have a dedicated product analytics function or plan to build one. The depth of analysis is unmatched, but you need the team to leverage it.
PostHog
Best for: Technical teams, privacy-conscious companies, self-hosting requirements
PostHog is the open-source alternative that has matured significantly. It offers product analytics, session recording, feature flags, and A/B testing in a single platform. Critically, you can self-host it, giving you full control over your data.
Strengths:
- Open source with self-hosting option
- Full data control — host in Australia if needed
- Product analytics, session recording, feature flags, and experiments in one tool
- Generous free cloud tier (1 million events per month)
- SQL access to raw data
- Active open-source community with rapid development
- No data sampling on free tier
Weaknesses:
- Self-hosting requires DevOps capability
- Mobile SDKs are less mature than Mixpanel or Amplitude
- Fewer pre-built integrations
- Session recording for mobile is still in development
- Smaller community and ecosystem than established players
Implementation:
// iOS
let posthog = PHGPostHog.shared()
posthog.capture("Add to Cart", properties: [
"product_id": product.id,
"product_name": product.name,
"price": product.price
])
// Feature flags
if posthog.isFeatureEnabled("new_checkout_flow") {
showNewCheckout()
} else {
showLegacyCheckout()
}Verdict: Ideal for technically capable teams that value data ownership, especially if Australian data residency is a requirement. The all-in-one approach reduces tool sprawl.
Segment (Customer Data Platform)
Best for: Teams using multiple analytics tools, companies with complex data pipelines
Segment is not an analytics tool itself — it is a customer data platform that collects events once and routes them to any number of destinations. Use Segment if you want to send data to Firebase AND Mixpanel AND your data warehouse without implementing each SDK separately.
Strengths:
- Single SDK replaces multiple analytics integrations
- Route events to over 300 destinations
- Identity resolution across platforms
- Data governance and compliance tools
- Replay historical data to new destinations
Weaknesses:
- Adds cost on top of your analytics platform
- Free tier limited to 1,000 monthly tracked users
- Adds a layer of abstraction that can complicate debugging
- Paid plans start at $120/month
Implementation:
// iOS - one SDK for all destinations
Analytics.shared().track("Add to Cart", properties: [
"product_id": product.id,
"product_name": product.name,
"price": product.price,
"currency": "AUD"
])
// Event automatically forwarded to Firebase, Mixpanel, your warehouse, etc.Verdict: Worth the investment if you use three or more analytics tools or anticipate switching platforms. The flexibility to change destinations without code changes is valuable.
Recommended Stacks by Stage
Early Stage (Pre-Revenue)
- Firebase Analytics for basic metrics
- Total cost: Free
Growth Stage (Finding Product-Market Fit)
- Mixpanel free tier for product analytics
- Firebase Analytics for Google Ads attribution
- Total cost: Free to $25/month
Scale Stage (Optimising Retention and Revenue)
- Segment for data routing
- Amplitude for deep product analytics
- BigQuery for custom analysis
- Total cost: $500-2,000/month
Enterprise (Multiple Products, Large Teams)
- Segment for data governance
- Amplitude or Mixpanel enterprise for product teams
- Data warehouse (BigQuery or Snowflake) for custom analytics
- Total cost: $2,000+/month
Implementation Best Practices
Regardless of which platform you choose, follow these practices:
-
Define your event taxonomy before implementation. Document every event name, property, and expected value. Inconsistent naming makes analysis impossible.
-
Track what matters, not everything. Tracking every tap creates noise. Focus on events that answer specific product questions.
-
Include context with every event. User properties (plan type, signup date, platform) make segmentation possible.
-
Test your implementation. Verify events fire correctly, properties contain expected values, and user identity resolves properly.
-
Plan for privacy. Australian Privacy Principles apply to analytics data. Ensure your implementation respects user consent choices and avoids collecting unnecessary personal information.
The right analytics platform is the one your team will actually use to make decisions. Start simple, measure what matters, and upgrade as your analysis needs grow.
Need help implementing analytics in your mobile app? Our team at eawesome sets up data-driven mobile apps for Australian businesses.