iGaming analytics

Payment and operational analytics for iGaming teams.

I help teams connect payment performance, monitoring and recurring reporting across PSPs, brands and markets so a material change can be identified, explained and assigned to the right owner.

Connected context

The useful answer often sits between systems and teams.

A strong analytics view makes KPI definitions, data freshness and ownership explicit instead of presenting isolated charts.

01

Monitoring & Alerts

Distinguish provider degradation, traffic changes and recovery states with actionable alert context.

See the monitoring scope
02

Automated Reporting

Reduce manual payment-report preparation and create dependable daily or management views with shared definitions.

See the reporting scope
03

BI Dashboards

Compare acceptance, approvals and declines across PSPs, brands, markets and methods in one operating view.

See the dashboard scope

Where work can begin

Start with one high-friction reporting or analysis process.

A focused first scope can reveal definition gaps and data dependencies without turning the project into a platform rebuild.

  • A multi-brand payment view whose KPI definitions are difficult to reconcile.
  • A PSP performance view that stops at high-level acceptance totals.
  • A recurring payment or operational report assembled manually from several sources.
  • An alert that lacks the context needed to begin an investigation.
  • A data-quality problem discovered only after stakeholders receive the report.

Why aggregates mislead

A steady overall acceptance rate can hide a segment that has stopped working.

The headline figure is a weighted average, and the weight sits with your largest market and method. A serious failure somewhere smaller moves it by a fraction of a point.

By the time a company-level rate visibly drops, the underlying problem has usually been running for days. The teams that catch it earlier are not watching a better dashboard; they are comparing each segment against its own recent behaviour rather than against the company total.

That means holding the comparison steady: the same method, market and issuer group, at the same point in the week, measured against what that segment normally does. It also means separating a fall in approvals from a change in attempt volume. Both move the headline number and each calls for a different response, so an alert that cannot tell them apart sends the investigation in the wrong direction.

Independent of any provider

A provider's dashboard reports that provider's own traffic.

It can describe what happened inside one gateway. It cannot tell you whether a second provider would have approved the same transaction, and it has no particular reason to make that comparison convenient.

Once a business runs several providers across several brands, the questions that matter are comparative. Which provider handles this issuer better in this market? Did a routing change help or simply move the failures somewhere less visible? Is a brand underperforming, or is it carrying a harder traffic mix?

None of those can be answered from inside a single provider's reporting. They are answered on your own data, with one set of definitions applied across every provider and brand, which is the work described on this page.

Relevant project proof

See the operating systems behind the approach.

These anonymised projects show payment dashboards, monitoring logic and recurring reporting workflows. Every visible demo name and value is synthetic.

Bring one iGaming reporting question into focus.

Describe the current workflow, the teams involved and the decision that needs a clearer view.