Interview with Yana Makarochkina: Can AI Decode the iGaming Market?

For years, iGaming operators and regulators have made high-stakes decisions with surprisingly limited competitive data. Aggregated traffic estimates, affiliate-driven rankings, and internal CRM reports have formed the primary intelligence layer in an industry approaching $150 billion in global revenue. The gap is real: without reliable cross-market data, capital gets misallocated, market entries are misjudged, and regulatory shifts go undetected until they show up in revenue figures.

Blask launched publicly in May 2024 with the proposition that this gap is both significant and closeable. The more important question for any operator, game developer, analyst, or regulator considering the platform is not whether the data would be useful — it clearly would be. It is whether the methodology is robust enough to act on.

What the Platform Shows

For an operator, Blask surfaces rising or falling demand by country, competitor market share, which brands hold local licenses, and which are operating offshore. For a game developer, it tracks the daily visibility of individual titles across casino lobbies. For a regulator, it identifies unlicensed brands and estimates the revenue split between licensed and unlicensed operators.

The platform currently covers 126 countries, with the five largest markets by index size being the United States, United Kingdom, Canada, Turkey, and Italy. In the US, each state carries its own index, reflecting the country’s fragmented regulatory structure. The country-level view also captures emerging markets: in Nigeria, for example, the Blask Index currently describes the market not as a monopoly but as a duopoly — a distinction that matters for any operator assessing entry conditions.

The customer profile feature adds player motivation data: in the United Kingdom, 18% of players surveyed said they gamble “to pass the time when I am bored,” while 12% said they do so “to check my intuition.” For retention teams and product designers, those two motivations imply very different decisions. Profiles are built from questionnaire data and third-party sources, accumulated and synthesized by AI. To validate accuracy, Blask conducted a survey of 8,000 respondents across India, Brazil, and Spain — a meaningful sample, though one that remains internally commissioned rather than independently verified.

The Blask platform gives operators and affiliates a real-time view of brand performance across markets. Image courtesy Blask.

Where the Numbers Come From — and Where They Fall Short

Blask draws from multiple source types: search demand signals, public regulatory filings, operator disclosures, daily computer vision scans of casino lobbies, and third-party research benchmarks. The core brand awareness metric — the Blask Index — is built on AI-processed branded search query data, filtered to remove low-intent noise (complaint traffic, affiliate searches, negative keywords), and combined with computer vision scans of casino lobbies to identify and categorize active brands. The result is a normalized demand signal updated hourly — not raw Google search volumes, but a multi-layer AI-refined indicator of player interest.

Accuracy is self-reported at up to 95% for established brands in regulated markets, validated against regulatory financial data and other third-party benchmarks. That figure drops for newer market entrants without an established search footprint, and in markets where app-store discovery or messaging platforms dominate over Google search, the signal is weaker still. No independent third-party audit of the methodology has been published.
Brand identification involves a three-layer process: computer vision scanning of casino and betting site imagery; NLP models trained to recognise iGaming-specific language across multiple languages; and a final layer of human review. The computer vision model identifies and classifies iGaming-related websites with accuracy of up to 91%, according to Blask’s own published figures.

Against the available alternatives — affiliate-driven rankings with obvious commercial incentives, and traffic tools that independent testing shows carry error rates of around 50% — a daily-updated, multi-source platform with transparent source links represents a different approach to the problem. It is not a replacement for audited financial data, and Blask’s published reports include a disclaimer stating that no warranty is provided as to completeness or correctness. That intellectual honesty is the right posture.

According to Blask data, January 2025 marked a tipping point — for the first time, locally licensed operators matched and began to overtake international grey market brands in audience reach. Image courtesy Blask.

Regulation, Markets, and the Offshore Question

During the interview, Makarochkina demonstrated Brazil’s market data. Prior to regulation, international operators accounted for the majority of measured demand. Following the introduction of regulation in January 2025, the distribution shifted toward locally licensed operators.

Makarochkina demonstrated Blask’s Brazil data during the interview. Before regulation, international operators held approximately 93% of market demand. After regulation took effect in January 2025, that share shifted rapidly, with licensed local operators capturing 94–95% of Blask Index demand within weeks. At the time of interview, 158 of the 559 brands tracked in Brazil held local licenses — figures that are updated daily in the platform.

In the United Kingdom, the platform identifies 134 offshore brands operating without a local Gambling Commission license, with offshore operators accounting for approximately 20% of the total estimated market revenue, according to Blask. A January 2026 peer-reviewed study by Marionneau et al., published in PLOS ONE, found that offshore gambling estimates are frequently non-transparent and methodologically unreliable — a caution that applies to any platform making such estimates, including Blask’s. That 20% figure should be read as indicative rather than definitive.

The UK data also illustrates one of the platform’s more granular features: a local license layer that distinguishes between international brands and those holding Gambling Commission authorisation. At the time of interview, 134 brands were marked as international but operating in the UK market — the kind of detail regulators, as well as operators, would find directly useful. Blask has made regulators an explicit target client segment.

Games, Visibility, and the Seasonal Layer

Beyond market and brand data, Blask tracks individual game titles across casino lobbies through what it calls the Game Visibility Rank. In the UK, for example, Big Bass Bonanza appeared across 133 brands at the time of the interview. For casino operators and game developers, knowing whether a title is gaining or losing placement across competitor lobbies is information that previously required manual auditing.

The platform also allows users to track seasonal gambling peaks — identifying the most active betting days by country — and add them to a marketing calendar. These patterns are country-specific, particularly where sports betting is concerned. In the UK, lottery and football dominate demand; in other markets, the split looks very different.

When the platform was reviewed in March 2025, India’s iGaming market was estimated at $472.8 million USD — a figure that illustrates both the platform’s ambition and the precision questions that accompany any AI-derived market size estimate for a largely unregulated market.

Growth, Clients, and What Comes Next

Since its May 2024 launch, Blask has won five industry trade awards — most recently Best AI Solution at SiGMA Eurasia 2026. By early 2026, the company reported 150+ active customers and over 2,000 companies in its onboarding pipeline, with clients including Flutter, Sportradar, Optimove, Spribe, and EveryMatrix.

One structural question, raised by iGaming marketing strategist Omer Yarkowich, is whether serving operators, affiliates, regulators, and game providers simultaneously risks spreading data depth too thin across use cases. It is a fair challenge for any platform trying to be a single source of truth for stakeholders with different — and sometimes conflicting — interests.

Where Blask is most immediately useful is as a starting point: a structured way to map a market before committing capital or launching a product. An operator considering entry into Nigeria, Brazil, or Indonesia can use the platform to assess demand levels, identify who holds what share, and understand whether the regulatory environment is open, contested, or effectively closed to new entrants. That is intelligence that previously required weeks of manual research and considerable tolerance for contradictory data. Used as a first filter rather than a final answer, the platform has a clear role.
The limits are worth restating plainly. The core demand metric depends on search behaviour, which means it measures interest rather than conversion. Accuracy is self-reported. No independent audit exists. For markets where Google is not the dominant discovery layer, the signal degrades. None of these are reasons to dismiss the platform — they are reasons to use it with calibrated expectations rather than as a substitute for on-the-ground due diligence.

Looking ahead, Blask is developing an API and a natural-language query interface called “Ask Blask” — allowing users to pose direct questions such as “What are the top brands in the UK?” and receive structured answers. A dedicated layer for prediction markets is also in development, a vertical that saw 256% growth in the Blask Index in the US alone through 2025 and is consolidating rapidly around a small number of players. “Due to the rapid pace of change, particularly with prediction markets and AI, we find it difficult to plan more than a few months ahead,” Makarochkina said. In a sector where the competitive landscape can shift within a regulatory cycle, that is less a limitation than a reasonable description of the environment. What Blask has built in its first two years is data infrastructure. Whether it proves robust enough for the use cases being sold to its growing client base is what the next two years will determine.

Further Reading & Key Sources

Marionneau et al. (2026), Uncertainties in measuring offshore gambling: A scoping review of Nordic approaches

Promodo (2024), TComparing Traffic Data Accuracy: Similarweb vs. Ahrefs vs. Semrush

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