For platform providers
iGaming platform analytics.
Every operator in context.
iGaming analytics for platform providers that need to understand the network and the businesses within it.
Bring operator performance, payments and product activity into one analytical foundation. Give platform teams and operator teams a consistent view, with access defined for their responsibilities.
The platform perspective
A shared foundation.
A useful view for every team.
A network total can hide a problem inside one operator. A collection of operator reports can hide a pattern across the platform. Gamblitude connects the two, using agreed Metrics, Attributes and access rules so teams can explore the detail behind performance.
Understand the network and each operator
Track activity, revenue and payment performance across the operators in your agreed data scope. Drill into operator, brand, market, product or provider to see where a change started and how widely it spread.
Give operators answers they can use
Build Dashboards, Reports and Segments around each team’s questions. Use shared metric definitions and configure role and dataset permissions so people can work with the data they are entitled to see.
Make the next rollout repeatable
Start with a defined set of operators, sources and KPIs. Reuse validated definitions and reporting patterns as coverage grows, while checking each operator’s data mapping, access requirements and commercial scope.
The data foundation
Agree the scope.
Connect the context.
Start with the data the platform holds and is authorised to use. Add operator-managed sources where access and integration are agreed. Metric definitions, currencies, time zones and reporting periods need to be aligned before comparisons are meaningful.
Sources to connect
- Platform and player-account data, with operator and brand identifiers
- Casino, sportsbook or other product transactions within the agreed scope
- Payment attempts, statuses and provider references
- Product events and feature usage, where captured
- CRM, affiliate and paid-media data when the relevant operator authorises access
Metrics to define
- Active players and activity by operator, brand and product
- GGR and NGR using agreed revenue and deduction definitions
- Deposits, withdrawals and payment success
- Retention, player value and acquisition cohorts where data supports them
- Product adoption, feature usage and operational trends
Example questions
Start with the question
behind the number.
Which operators account for the change in net gaming revenue this month, and what changed in their product mix?
Is the fall in deposit success concentrated in one payment provider, one operator or one market?
Which operator cohorts adopted the new feature, and how does their activity compare with the previous period?
AI in the workflow
Ask. Follow. Investigate.
AI Agent
Explore a platform or operator question in natural language, using connected data and your defined Metrics. Follow up on the result and inspect the breakdown behind it.
Insight Radar
Define an operator or platform question and the schedule for reviewing it. Insight Radar repeats that investigation and brings back findings for your operations team.
Autonomous Agent
The agent selects threads across connected operator and platform data, follows related signals and presents findings with supporting evidence. Your team decides how to respond.
Explore the products
The capabilities
behind the workflow.
Data Warehouse
Connect source systems and build a consistent analytical foundation.
Business Intelligence Platform
Dashboards, Reports, Segments and controls for the teams working with your data.
AI for iGaming
Ask questions, schedule recurring checks and bring analysis into daily workflows.
Autonomous Agent
Independent investigations into opportunities, anomalies and business insights.
Predictive Models
Explore player-level predictions available for the data and use cases in scope.
Questions & answers
Platform analytics
explained.
What is analytics for iGaming platform providers?
It connects platform data and operator reporting so teams can analyse network performance and inspect the operators, products or payment flows behind a change. Gamblitude combines a data foundation, business intelligence and AI analysis around shared metric definitions.
Can platform teams and operator teams have different access?
Yes. Configure role and dataset permissions around the operators, records and platform functions each team needs. Validate those settings during implementation so network and operator views follow the agreed access.
Can Gamblitude include sources outside the core platform?
Yes, where the relevant sources can be connected and access is agreed. Operator-owned CRM, affiliate, paid-media and product-analytics data can add context to platform transactions. Available reporting depends on the data supplied and the identifiers that connect it.
How do you keep KPIs consistent across operators?
Metrics define the calculations teams use, while Attributes provide reusable descriptive context. Agree the treatment of deductions, bonuses, currencies and time periods before comparing operators. Genuine business differences should remain visible in the definitions and reporting.
How can we deliver analytics to operator teams?
Agree the intended users, operator coverage, access, branding and any embedding requirements as part of the delivery design. We then confirm the implementation and commercial arrangement for your platform and the teams that will use it.
How does a platform-provider rollout begin?
Start with the operators, source systems, business questions and access rules in scope. Validate the data and a first set of KPIs and workflows, then agree how to extend coverage. Rollout timing follows the integration requirements; Predictive Models are separately scoped and quoted.
See Gamblitude in action
Bring a platform question worth answering.
Choose an operator, a payment flow or a product change. We’ll explore how the data, definitions and access could fit together for your platform.