Mobile Game Analytics Tools by Studio Size (2026)
Last updated: August 2026. Pricing and free tiers are linked to each vendor's own page; check them before deciding, since they change.
Most studios don't buy one analytics tool. They end up with four layers, added in roughly this order as the studio grows. The expensive mistake is buying a layer before you have questions that need it. The short version, by team size:
Under 10 people. GameAnalytics or Firebase. Nothing else. Add the next layer when you start spending real money on user acquisition.
10 to 40 people. The above, plus an MMP, plus Amplitude or Mixpanel if designers are asking questions daily. Add the next layer when questions start spanning gameplay and spend and revenue.
40 or more people. A warehouse as the source of truth, every tool above feeding it, and BI or a decision layer on top.
The four layers those answers refer to:
- Layer 1, game telemetry. What are players doing in the game? GameAnalytics, Firebase/GA4, Unity Analytics, ByteBrew.
- Layer 2, attribution (MMP). Which ads produced players worth having? AppsFlyer, Adjust, Singular, Tenjin.
- Layer 3, product analytics. Why did this cohort behave differently? Amplitude, Mixpanel, PostHog.
- Layer 4, warehouse and decision layer. Questions that span all three above. BigQuery or Snowflake, then Looker, Metabase, Hex, climpt.
Disclosure: climpt makes a decision layer of the kind described in Layer 4. Everything else on this page is tooling we don't sell and earn nothing from.
How these were chosen. Tools are included if they are actually used by mobile game studios, and compared on four things a studio can verify before buying: published pricing, what the free tier really covers, how much instrumentation work the team takes on, and whether you can get your raw data out. Every number here comes from the vendor's own documentation or pricing page, linked inline, and was checked in August 2026. The recommendations are based on that research and on conversations with studios, not on running each tool through a full title launch, so weigh them against your own constraints rather than treating them as verdicts.
Layer 1: Game telemetry
This is the only layer every studio needs. It answers where players quit, which levels fail, and what retention looks like.
- GameAnalytics suits teams wanting game-native metrics with less setup. No MAU limit, but 500 events per user per day and cardinality caps; AnalyticsIQ Pro from $49/mo. Custom fields need the export product, and high event cardinality degrades the UI metrics.
- Firebase / GA4 suits studios already in Google's stack. Free. Not game-native, so you model progression and economy yourself.
- Unity Analytics suits Unity teams avoiding another SDK. Free to 50,000 MAU. Deepens Unity lock-in.
- ByteBrew suits indies wanting analytics and attribution in one SDK. Free tier, though confirm the current limits. Smaller vendor and ecosystem.
What separates them is whether game concepts are built in. GameAnalytics ships with progression, resource sources and sinks, and economy events as first-class ideas. Firebase gives you a generic event system and expects you to build those yourself. Cheaper and more flexible, but someone has to own the modelling.
Pick GameAnalytics if nobody on the team wants to maintain a data pipeline. Pick Firebase if you're already using Crashlytics and Remote Config, and you want raw events in BigQuery from day one.
Layer 2: Attribution
An MMP tells you which campaign produced an install, and more importantly whether those players were worth what you paid. AppsFlyer and Adjust are the two defaults; Singular and Tenjin are the lighter alternatives.
What matters is when. Not until paid UA is a meaningful line in your budget. Before that an MMP is a bill for data you won't act on. After that, it's the only way to connect CPI to D7 retention to payer conversion to ROAS.
Don't expect your telemetry tool to do this job. Attribution and gameplay analytics are separate systems in almost every studio, because attribution requires integrations with every ad network you buy from.
Layer 3: Product analytics
Add this when designers and PMs start asking questions your telemetry dashboards can't answer. Things like "among players who reached level 20 in three days and joined a guild, what's D30 retention?"
- Amplitude: 2M events/month, unlimited seats. Strongest experimentation; paid tiers scale with volume.
- Mixpanel: 1M events/month. The Growth plan starts at $0 and includes the first 1M free.
- PostHog: 1M events/month, then from $0.00005/event, decreasing with volume. Adds feature flags and session replay.
Event volume is where these plans actually differ. A moderately active player generates hundreds of telemetry events per session, so a free tier measured in millions is smaller than it sounds. Before signing anything, calculate monthly active players × events per player and ask the vendor to quote that number at 2×, 5× and 10×. All three price on usage, so this is where the real cost difference shows up, not in the feature comparison.
Between Amplitude and Mixpanel the analytical difference is small at your scale. Decide on pricing against your actual event volume and which interface your designers prefer after a week.
Layer 4: Warehouse and decision layer
Everything above is a product with your data inside it. At some point you'll want a question answered that no single product can see. Usually one joining gameplay, ad spend, IAP revenue and experiment assignment at once.
That's when raw data goes to BigQuery, Snowflake or ClickHouse, and something sits on top:
- BI. Looker, Metabase, Hex, Tableau. Governed metrics and dashboards. Looker is powerful and expects someone to own LookML; Metabase is the low-overhead choice.
- Warehouse-native AI. Snowflake Cortex Analyst, Databricks Genie. Natural language against your warehouse if you're committed to that platform.
- Cross-warehouse decision layers. ThoughtSpot, Omni, Sigma, Mitzu, Zenlytic, and climpt. These sit above the warehouse and answer questions in plain language rather than requiring SQL.
climpt connects to your existing warehouse, answers questions in natural language, and keeps no copy of your data. Queries run against your database on demand. It is not a telemetry SDK, not an MMP, and doesn't replace GameAnalytics; it reads the warehouse those tools feed. What is and isn't sent anywhere is set out on our security page, including the parts we'd rather not have to write.
Most studios reach for this layer before they need it. If every question you have fits inside GameAnalytics or Amplitude, a warehouse is infrastructure you're maintaining for no reason.
Three stacks, concretely
These are archetypes rather than named customers: what the stack tends to look like at each point, following the criteria above.
Five people, one game, no paid UA. Firebase, and nothing else. Crashlytics and Remote Config come with it, raw events land in BigQuery from day one if you ever want them, and there is nothing to maintain. A second tool here buys you work, not answers.
Twenty-five people, one live title, real UA spend. GameAnalytics for gameplay and economy, an MMP for attribution, both exporting to BigQuery. Amplitude or Mixpanel on top once designers are asking cohort questions weekly rather than occasionally. The warehouse earns its place because CPI, D7 retention and payer conversion live in three different products and somebody has to join them.
Eighty people, several titles, ad revenue and IAP. Telemetry and attribution per title, plus ad network and store revenue, all landing in BigQuery. A transformation layer such as dbt so every title reports the same way, because the hard problem at this size is that two games define "active player" differently. BI or a decision layer on top for questions that span titles.
The usual way this goes wrong at 10 to 40 people is reaching for the eighty-person stack early and having nobody to maintain it. Choosing the wrong tool does less damage than that.
Instrumentation matters more than the tool
This is the one part no vendor fixes for you, and it decides whether anything above was worth buying.
The failure looks like this: one engineer sends levelComplete, another sends level_completed. Currency amounts use different units across two screens. Level IDs get renumbered in version 2.4, so every historical comparison silently breaks. Somebody instruments 500 events because they might be useful one day, and now nobody can find the twelve that matter.
Three rules that prevent most of it:
- Start from questions, not events. Write down the twenty questions your team actually asks each month. That list is your tracking spec.
- Treat the event schema like an API. Naming changes get reviewed. Renaming a level ID is a breaking change.
- Write down one definition per metric. Especially retention, since tools calculate D7 differently, and if your CEO, designer and UA manager have three different numbers, people stop trusting all of them.
A free tool answers most questions when the instrumentation underneath is disciplined. Without that, the expensive one produces charts nobody trusts.
