Customer Journey Analytics
Unify, analyse, and optimise player interactions across all touchpoints to drive engagement, retention, and lifetime value.
Customer Journey Analytics (CJA) is the process of collecting, unifying, and analyzing player interaction data across all touchpoints—from first ad impression to long-term retention—to create a complete, visual map of a player's experience with your game. It reveals patterns, bottlenecks, and opportunities to improve engagement, personalise experiences, and drive better outcomes like conversion, retention, and monetisation.
CJA moves beyond simple journey mapping by adding analytical depth to understand how each interaction influences player behavior and business goals. For Gaming operators, this means connecting pre-registration marketing touchpoints (ads, affiliate sites, search) with post-registration behaviors (KYC completion, first deposit, betting patterns, retention milestones) to optimise the entire player lifecycle.
Why Gaming Operators Need CJA
- Break down data silos between marketing, product, and player operations teams
- Understand which acquisition channels deliver players with best deposit frequency and LTV
- Identify friction points causing drop-off in registration, KYC, FTD, or ongoing engagement
- Personalize player experiences based on journey patterns and behavioral segments
- Optimize marketing spend by connecting campaign touchpoints to long-term player value and GGR
1. Unified Data
Integrates data from various sources (ad platforms, MMP, in-game analytics, CRM, support) into a single view, breaking down data silos that prevent holistic understanding.
Gaming Data Sources to Unify:
- Pre-Registration: Ad impressions, clicks, landing page visits, creative interactions
- Attribution: Registration source, campaign parameters, affiliate tracking, fraud signals
- Player Actions: KYC completion, payment method addition, game browsing, demo plays
- Monetisation: Deposits, withdrawals, bet/spin activity, bonus usage, GGR/NGR
- Engagement: Session data, login patterns, game preferences, cross-sell behavior
- Support: Tickets, live chat conversations, responsible gambling interactions, feedback
2. End-to-End Visibility
Provides a holistic view of the entire player lifecycle, from initial awareness (ad exposure) through advocacy (organic referrals and community engagement).
| Lifecycle Stage | Key Touchpoints | Analytics Focus |
|---|---|---|
| Awareness | Ad impressions, social media, affiliate content, search visibility | Reach, brand lift, creative effectiveness |
| Consideration | Site visits, reviews, game demos, bonus comparisons, friend recommendations | Landing page conversion rate, review sentiment, referral paths |
| Acquisition | Registration, KYC verification, payment method addition, first deposit | Registration-to-FTD rate, KYC completion rate, D1 retention |
| Engagement | Daily sessions, game type exploration, betting patterns, cross-sell | DAU, session frequency/length, game diversity, D7/D30 retention |
| Monetisation | Deposit frequency, bet sizing, bonus usage, VIP progression | Conversion rate, ARPU, LTV, payback period |
| Retention | Push notifications, live ops events, new content, re-engagement campaigns | Churn rate, win-back success, long-term retention curves |
| Advocacy | Referrals, reviews, community participation, user-generated content | K-factor, organic installs, community sentiment |
3. Contextual Insights
Visualizes sequences of interactions, showing the full context and impact of each touchpoint. Understand not just what happened, but the order, timing, and relationships between events.
Sequence Analysis
Track common paths players take through your game:
- Install → Tutorial → Level 1-5 → First IAP → Daily player
- Install → Tutorial drop-off → Re-engagement push → Return → Monetize
- Install → Skip tutorial → Confusion → Churn within 24 hours
Timing & Velocity
Understand how quickly players move through stages:
- Time from install to first session (install-to-open lag)
- Time from first session to tutorial completion
- Time from tutorial to first purchase (conversion velocity)
- Session frequency patterns (daily vs. weekly players)
4. Behavioral Analysis
Analyzes player behavior, motivations, and emotions at each stage to identify what drives engagement, conversion, and loyalty. Goes beyond metrics to understand the "why" behind player actions.
| Behavioral Segment | Characteristics | Optimisation Strategy |
|---|---|---|
| Power Users | High DAU, long sessions, feature exploration, social engagement | VIP programs, exclusive content, community leadership roles |
| Whales | High spend, frequent IAP, premium content consumption | Personalized offers, early access, dedicated support |
| Casual Players | Weekly sessions, short play time, ad-supported monetisation | Rewarded video ads, simple progression, social features |
| At-Risk Players | Declining session frequency, progression stalls, reduced engagement | Re-engagement campaigns, difficulty adjustments, incentives |
| Tutorial Drop-offs | Install but don't complete onboarding, high early churn | Tutorial simplification, skip options, better UX |
5. Actionable Insights
Helps pinpoint friction points, optimise paths, and guide decisions for improving player experience and business outcomes. Insights must lead to concrete actions.
Friction Point Identification
- Tutorial step with 60% drop-off → Simplify or make skippable
- Level 10 difficulty spike causing churn → Adjust difficulty curve
- Payment flow with 40% abandonment → Reduce friction, add payment methods
- Push notification causing uninstalls → Adjust frequency and timing
Optimisation Opportunities
- Players from TikTok have 2x LTV → Increase TikTok budget
- Tutorial completers have 5x D30 retention → Incentivize completion
- First purchase within 48 hours predicts high LTV → Trigger early offers
- Social feature users have 3x retention → Promote social features
Enhanced Player Experience
Creates more seamless, personalised, and satisfying player journeys by understanding and removing friction points.
Example: Identifying that players struggle with level 15 allows you to adjust difficulty or provide hints, improving retention.
Improved Conversions
Identifies effective touchpoints and optimises the path to first purchase and recurring monetisation.
Example: Discovering that players who complete tutorial are 5x more likely to purchase enables targeted incentives.
Increased Engagement & Loyalty
Satisfied players who have smooth journeys are more likely to stay engaged long-term and become advocates.
Example: Players with positive onboarding experiences have 3x higher D30 retention and refer more friends.
Better Team Alignment
Strengthens alignment between UA, product, monetisation, and support teams with a shared view of the player.
Example: UA team sees which channels deliver best long-term players, product team sees which features drive retention.
Data Collection
Gather interaction data from every channel and device across the player lifecycle. Use MMPs (AppsFlyer, Adjust) for attribution, analytics SDKs (GameAnalytics, Firebase) for in-game events, and ad platform APIs for campaign data.
Identity Resolution
Link interactions across devices and sessions to a single player identity. Match anonymous ad clicks to attributed installs, then to in-game user IDs and monetisation events.
Journey Mapping & Visualisation
Create visual representations (flowcharts, sankey diagrams, path analysis) of typical and atypical player paths. Show how players move through stages, where they drop off, and which paths lead to best outcomes.
Analysis
Analyze patterns, drop-off points, and the impact of specific interactions. Use cohort analysis, funnel analysis, path analysis, and segmentation to uncover insights.
Optimisation
Use insights to refine UA strategies, product features, monetisation tactics, and player support. Test changes with A/B tests and measure impact on key metrics.
| Phase | Timeline | Key Activities | Success Metrics |
|---|---|---|---|
| 1. Foundation | Weeks 1-4 | Set up MMP, implement analytics SDK, define key events, establish data warehouse | All critical events tracked, data flowing to warehouse |
| 2. Identity Resolution | Weeks 5-8 | Implement user ID mapping, connect attribution to in-game events, set up postbacks | 90%+ events linked to player identity |
| 3. Visualisation | Weeks 9-12 | Build dashboards, create journey maps, set up cohort analysis, path visualisation | Key stakeholders can view player journeys |
| 4. Analysis & Insights | Weeks 13-16 | Identify friction points, segment players, analyse drop-offs, find optimisation opportunities | 3-5 actionable insights identified |
| 5. Optimisation | Ongoing | Implement changes, run A/B tests, measure impact, iterate based on results | Measurable improvements in retention, LTV, or conversion |