Hive Analytics Blog
Game Data Analytics Service

Data-Driven Decision Making Starts Here

From event-based analytics to user segments, funnels, and retention —
get all the insights you need for game operations in one place.

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AU, NU Summary AU 1,099 ▲ 75% NU 692 ▲ 1,093% PU, IAP Revenue Summary PU 120 ▼ 6.25% IAP Revenue 86,071,172 ▲ 19.46% AU, NU, PU Trend AU NU PU IAP Revenue Trend 03/06 03/10 03/14 03/18
60+
Built-in Events
MMP
Data Analysis with
MMP Integration
Real-time
Event Data
Collection & Analysis
Core Features

Analytics, Easier and Faster

Create chart, funnel, retention, and ranking analyses intuitively, and share them with your team via dashboards.
Create

Create analyses and share them with your team

Create charts, funnels, retention analyses, and rankings, then bring them together in dashboards so everyone can work from the same data.

  • Create charts, funnels, retention analyses, and rankings in the UI
  • Bring analyses together in dashboards for an at-a-glance view
  • Share dashboards with your team to work from the same metrics
Create
Daily active users
Users

Understand exactly who
is churning and why

Combine 40+ built-in attributes with custom events to segment users precisely, and track activity patterns to detect anomalies early.

  • Select targeted campaign audiences with segments (Hive push & promotion integration)
  • Compare abuser and high-spender behavior patterns with user activity tracking
  • View metrics by 6 user classification types: whale, dolphin, light, free, etc.
User Classification Status
Whale Users2.1%
Dolphin Users8.4%
Middle Users19.3%
Free Users53.7%
Data

Your data,
your way

Define events and metrics directly, integrate with third-party tools like MMPs, or export raw data to AWS S3 or GCP GCS for flexible use.

  • Define new events and manage properties
  • Unified analysis with MMP integration — no platform switching
  • Export raw event data to cloud storage
Data Integration Status
📡
MMP IntegrationAppsFlyer · Adjust · Airbridge
Connected
☁️
Data ExportAWS S3 · GCP GCS
Configured
Last ExportToday 04:00 AM
Done · 2.4 GB
All Features

From Analytics to Operations, All in One Place

Home

Home

View KPIs by project at a glance

Create

Chart · Funnel · Retention · Ranking

4-in-1 event-based visual analytics

Users

Segment · User Activity Tracking

Classify users and analyze behavior with condition combinations

Users

User Classification

Metrics and migration by 6 cluster types

Data

Event · Metric

Central management of analysis events and metrics

Data

Integration · Data Export

MMP integration and cloud storage export

Settings

Metric Settings

Manage exclusions, filters, currency, and time settings

Settings

Organization · Workspace · User Management

Role-based access control and member management

Insights

Practical Data Insights for Game Operations

Explore operational challenges and workflows covered by Hive Analytics. Read the full article on Hive Analytics Blog.
Axyl Plugin

Building Charts and Dashboards in Natural Language: Using Hive Axyl Plugin, Part 2

Ask Hive Axyl Plugin in natural language to create Hive Analytics charts and combine multiple charts into a single dashboard. Before creating or editing charts and dashboards, it shows what will be applied and runs only after you approve.

  • Get recommendations for metrics and chart types based on the context of earlier analysis
  • Create charts from the recommended metrics and combine them into one dashboard
View Related Guide ↗ Read more →
Axyl Plugin

Querying Game Metrics and Checking Changes in Natural Language: Using Hive Axyl Plugin, Part 1

With Hive Axyl Plugin installed in ChatGPT, you can query Hive Analytics metrics in natural language and narrow the scope of analysis by country, market, and product while carrying over the context of earlier questions. To use the plugin, set the account as an MCP member of the organization.

  • Compare yesterday’s user and revenue metrics with the same day last week in natural language
  • Follow up by country, market, and product to pinpoint likely causes of revenue changes
View Related Guide ↗ Read more →
Metric

Checking Estimated Google and Apple Proceeds Before Store Settlement

Payment amounts may include sales tax and come before store fees and country-specific taxes are applied, so the payment amount alone doesn't tell you how much the developer will receive. With Hive Analytics' Estimated Proceeds metric, you can see estimated proceeds with fees and taxes reflected by applying store-specific calculation rules to Google Play and Apple App Store payments.

  • Estimated proceeds calculation rules for Google Play and the Apple App Store
  • Comparing estimated proceeds by app, country, and store in a chart
View Related Guide ↗ Read more →
BigQuery

Querying Raw Analytics Data in BigQuery

Raw event data collected by Hive Analytics can be queried directly with SQL in the habq-storage project in BigQuery. When querying, convert dateTime, which is stored in UTC, to KST, remove duplicates based on checksum, and query only the partitions you need with date conditions.

  • Steps from requesting BigQuery access to running SQL
  • A query example with time zone conversion, deduplication, and partition conditions
View Related Guide ↗ Read more →
Event

Checking the Event Log Storage Structure and Failed Data: Sending Event Logs, Part 4

Among the events sent to Hive Analytics, events that meet the collection criteria are stored in t_raw_event_log, and events that do not are stored in t_raw_event_log_rescue together with the raw JSON and the quarantine reason. If you cannot find an event in the normal table, check the quarantine reason with errorReason, errorStackTrace, and rawData in the rescue table.

  • Check how the normal table and the quarantine table store events
  • Check the cause and action for each quarantine code
View Related Guide ↗ Read more →
Event

Sending Game Data as Event Logs: Sending Event Logs, Part 3

To apply an event structure you validated with test logs to the actual game, send the event with actual game data right after the player's action is confirmed. If required property names or the eventTime format are sent incorrectly, the log is stored in the quarantine table t_raw_event_log_rescue.

  • Send events with actual game data right after the action is confirmed
  • Check property setup and quarantine rules for each sending method
View Related Guide ↗ Read more →
Event

Validating Your Collection Structure and Metrics with Test Logs: Sending Event Logs, Part 2

Sending test logs before developing the event-sending feature lets you check in advance whether events and properties are collected in the intended structure and data types, and whether they can produce the metrics you need. Send logs with ETL Simulation, then check the results in Data Preview and BigQuery and the metric setup in Create.

  • Send test logs through ETL Simulation or direct sending
  • Check event-based metric setup
View Related Guide ↗ Read more →
Event

Defining Your Log Collection Structure with Event Templates: Sending Event Logs, Part 1

Event templates come with predefined event names and properties, so you can define your log collection structure without designing events from scratch. Select an event in Data > Event, edit or add properties, then generate log-sending source code for your development environment.

  • Review predefined properties and add new ones
  • Generate log-sending source code for client and server environments
View Related Guide ↗ Read more →
Chart

Grouping Dimension Values by the Criteria You Need

Raw dimension values are hard to compare in a way that fits your analysis. Use Bucket settings in charts to group country codes by region and split prices and levels into buckets, without changing the raw logs.

  • Group country codes by region to compare daily user counts
  • Split prices into equal-width buckets to check purchasing user counts
View Related Guide ↗ Read more →
Chart

Building the Metrics You Need with Multiple Calculations

A single aggregation makes it hard to see the day's login flow and the figures that represent a period together. Build a measure with a primary calculation in charts, then recalculate the maximum, minimum, average, or latest value at each interval with a secondary calculation.

  • Apply AVG to daily AU to check monthly average daily AU
  • Apply MAX to 2-minute concurrent users to check peak concurrent users
View Related Guide ↗ Read more →
Integration

Connecting MMP and Game Events to Track User Behavior

When acquisition and in-game behavior sit in separate screens, it's hard to judge user quality by channel. Connect an MMP to follow the whole funnel from install to login and purchase.

  • Integrate once, and MMP events are sent to Analytics automatically
  • See MMP events alongside game events in charts, funnels, and retention
View Related Guide ↗ Read more →
Retention

Tracking Players' Return Flow With Retention

A steady total user count can hide very different stories — loyal users returning, or new users simply joining. Set a base and return event to see which one it actually is.

  • Return visits checked across the same event or a different one
  • Narrow down further with dimensions and filters
View Related Guide ↗ Read more →
User Activity Tracking

Players Who Paid Soon After Joining: What Kind of Users Are They Now?

An early purchase alone doesn't show whether a new player keeps creating value. Group them with a segment and check their current user type and activity flow in User Activity Tracking.

  • See which early payers grew into whale or dolphin types
  • Trace one player's events from first purchase to today
View Related Guide ↗ Read more →
Chart

Finding the Players Who Drive Your Game Revenue

Aggregated revenue totals make it hard to find your top performers. Use Ranking to check revenue metric rankings by player and by product over a selected period.

  • Break the top 100 players by revenue down by market
  • Compare the top 10 products by number of sales as a ranking and pie chart
View Related Guide ↗ Read more →
Template

Building Game Analysis Content Quickly with Templates

Starting an analysis from scratch means deciding metrics, dimensions, and events every time. Hive Analytics templates load ready-made dashboard, chart, funnel, and retention setups so you only adjust what you need.

  • Selecting a template loads a setup screen with dashboard, chart, funnel, or retention fields pre-filled
  • Every panel, measure, and dimension stays editable after you apply it
View Related Guide ↗ Read more →
Organization Management

Managing Data Access Scope by Assigned Project

Organizations running multiple games need different data access depending on each member's role. Hive Analytics' organization management groups projects and members by organization so admins can match access scope to responsibility, and adjust it easily when the person in charge changes.

  • Group projects and members by organization to set data access to match each role
  • Reassigning members updates access permissions without changing the project setup
View Related Guide ↗ Read more →
Chart

Viewing a Game Metric's Composition by the Basis You Choose

Overall numbers alone don't show which date or dimension shaped a change. Switch the pie chart's ratio basis between date and dimension, then narrow the legend to compare just the items you care about.

  • Breaking down by country or OS narrows in on where a share grew
  • Excluding legend items recalculates the share among what's left
View Related Guide ↗ Read more →
Time Settings

Analyzing Data from After Game Launch

QA, soft launch, and CBT data mixed with real service metrics make it hard to see accurate performance. Register each project's launch date down to the minute in Hive Analytics' Time Settings to exclude everything before it.

  • Register a per-project launch date down to the minute to exclude pre-launch data
  • Applies at once to new charts, funnels, and retention, and to dashboards already in use
View Related Guide ↗ Read more →
Currency Settings

Revenue in Different Currencies, at a Glance

Different currencies make revenue impossible to compare directly. Register your organization's currencies once and compare on a consistent basis.

  • Currency Settings covering 162 currencies
  • Game revenue viewed against your organization's currency standard
View Related Guide ↗ Read more →
Chart

Comparing Game Metrics Against the Past

Looking at today's numbers alone doesn't tell you if a metric is high or low. Set a period comparison on Hive Analytics charts and dashboards to see the base and comparison period side by side, along with the rate of change.

  • Choose a Relative Date or a Fixed Date to compare the base and comparison period together
  • Set several comparison periods on a single chart at once
View Related Guide ↗ Read more →
Funnel

Analyzing User Flow from Content Start to Completion

Completion numbers alone don't show whether content is working. Break it into a funnel and you can see exactly where — and how much — users drop off.

  • If most users drop right before completion, look at the completion condition before touching the content itself.
  • Re-checking the same funnel after a change turns a hunch into a measured result.
View Related Guide ↗ Read more →
Metric Filter

Removing Test Data to Analyze Real Service Performance

QA and test-app events mixed into your data make user counts and revenue look higher than reality. Register a Server ID or App ID and they're filtered out of every chart and dashboard at once.

  • A registered Server ID or App ID filter applies automatically across every chart and dashboard
  • See real service KPIs once QA and test data are filtered out
View Related Guide ↗ Read more →
Metric

Where Data Analysis Starts: Aligning Your Organization's Metric Standards

When metrics like active users or revenue are calculated differently across teams, the same period can show different numbers. Hive Analytics' Metric feature lets you define and reuse a single calculation standard across every chart and dashboard.

  • Build metrics from a single event or by combining several with a formula
  • Any change to a metric automatically updates every chart and dashboard that uses it
View Related Guide ↗ Read more →
Excluded Users

Analyzing Real User Data by Filtering Out Internal Test Accounts

Register a User ID or Device ID once in Hive Analytics' Excluded User Management, and that user's events are automatically excluded from every chart and dashboard.

  • Register once and it applies to every chart and dashboard automatically
  • Check revenue, content engagement, and concurrent users based on real users only
View Related Guide ↗ Read more →
Dashboard

Checking Game Operations Status on the Go

View the dashboards you already built on PC from your phone, and track KPIs and day-over-day changes wherever you are.

  • View PC dashboards the same way on mobile
  • Use it for live events, leadership updates, and anomaly checks
View Related Guide ↗ Read more →
Chart

Finding Marketing Performance Differences by Dimension

Break down overall metrics by country, market, and OS to see performance gaps that averages hide, then narrow in on where the gap is concentrated.

  • Compare performance by country and market
  • Narrow down by OS and app version to find the cause
View Related Guide ↗ Read more →

Start analyzing your game data now

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