EveryMatrix data strategy: turning player and market data into growth

EveryMatrix told iGB on 12 October 2026 that it is moving beyond reporting and analytics and using client and player data to act as a strategic growth partner for operators. Co-CEO Jonas Groes said the company is combining customer data with cross-market player behaviour and using AI to structure, interpret and operationalise those insights across product and client engagements.

EveryMatrix data strategy: making data actionable across products and markets

EveryMatrix has access to a large volume of information that originates in its platform suite, client deployments and the markets where those clients operate. The company is shifting focus from producing reports to turning that information into operational insight that informs product design and commercial conversations.

"AI is creating new opportunities to work with data more efficiently and extract greater value from it," Groes said in the iGB interview. "We have a lot of data together with our clients, our partners, and we see some opportunities towards how are we utilising them towards the market." The emphasis is on structuring data so it becomes relevant to an individual operator and comparable across jurisdictions.

EveryMatrix intends to combine operator-level data — for example specific product metrics and player cohorts — with a broader view of player behaviour across different markets. That combined view supports tailored product recommendations and more targeted optimisation of player journeys. The company sees AI playing a dual role: helping present data more clearly to clients and enabling internal teams to act on it faster.

How data-driven partnerships change client conversations

The shift in capability is altering the nature of EveryMatrix's client engagement. Historically the vendor role was reactive: build what an operator requested and deliver technology. With a deeper data foundation the company aims to take a more consultative stance, challenging assumptions and recommending actions based on observed player behaviour.

"We can be more on the consulting side, helping our clients realise the value that they can seek within their market […] whatever is good for our clients is good for us," Groes said. In practice that means EveryMatrix wants to move from feature delivery to strategic dialogue about product-market fit, customer segments and revenue opportunities.

This advisory role is particularly salient in revenue-share commercial models where supplier and operator incentives align. When EveryMatrix shares commercial upside with operators, data-driven recommendations that identify growth pockets can directly benefit both parties.

Creating a product feedback loop from real-world data

Products and data are now in a reciprocal relationship at EveryMatrix. The company describes a loop where deployed products generate usage data; that data surfaces insights into player behaviour and market response; and those insights feed back into product development.

"You have the product, you utilise it towards a market, getting data, and that should then come back to the product so that the product becomes better and reflects the needs of the market," Groes said. The stated outcome is product decisions informed by real-world usage rather than only by client requests or internal roadmaps.

That loop is intended to make products more relevant to specific jurisdictions and operator strategies. It also moves the company away from a purely reactive development model and toward incremental improvements prompted by observed metrics.

AI as an accelerator inside EveryMatrix and for clients

EveryMatrix identifies two principal use cases for AI. The first is product-facing: using AI to present complex datasets and insights back to operators in a way that supports decision-making. The second is internal: applying AI to team workflows so analysis and action happen more quickly.

The company frames the core challenge as structuring existing data so it becomes "relevant". The value of AI is not merely in producing more information but in making available information comprehensible and actionable. That requires tooling for data aggregation, normalisation across markets, and interfaces that translate insight into specific recommendations for product changes, marketing or risk management.

Commercial and operational implications for clients and suppliers

For operators the practical offer is twofold: better intelligence to shape product and marketing decisions, and a partner that can advise on how to deploy product changes that increase retention or yield. For EveryMatrix the commercial implication is a closer relationship with customers, framed as partnership rather than simple supplier-client dynamics.

For platform and product teams the roadmap priorities implied by Groes's comments include investments in data pipelines, AI models tuned to gaming behaviour, and clinician-grade presentation of insight so client teams can make decisions without heavy data science support. Those capabilities also matter in markets where local player behaviour differs materially from global norms.

What to watch next

EveryMatrix positions data and AI as the mechanism that will let it deepen client relationships and move closer to tier‑1 operator status. The company measures progress not only through traditional KPIs but by the quality of conversations it holds with customers — specifically, whether operators change how they operate based on EveryMatrix insight.

Operators and suppliers will watch how those consultative engagements scale, how data privacy and cross-market aggregation are handled in regulated jurisdictions, and whether AI-derived recommendations translate into measurable revenue or retention gains. EveryMatrix has signalled that its strategy is live across product, commercial and internal teams as of the October 2026 interview with iGB.

For more on product and platform developments in the supplier space see EveryMatrix's B2B-facing work and market commentary in the b2b section and recent company updates in news.

"AI is creating new opportunities to work with data more efficiently and extract greater value from it." — Jonas Groes, Co-CEO, EveryMatrix

"We can be more on the consulting side, helping our clients realise the value that they can seek within their market…" — Jonas Groes, Co-CEO, EveryMatrix