20 Apr

Gambling News

Hub88 on using AI-powered Page Insights to transform data into decisions

Converting data into usable knowledge continues to be a concern for the industry as operators struggle with ever-more complicated datasets. Director of Product at Hub88 Gabriel Kolawale describes how AI-powered solutions like Page Insights are transforming data analysis into "co-pilots" for decision-making.

Although "data-driven decision-making" is frequently discussed in the industry, many operators still have difficulty effectively processing player data. What is preventing them from moving forward?
With operators processing millions of bets annually, the industry has no shortage of data. However, most operators find it difficult to translate this data into strategy and action. Gartner's report predicts that by 2027, 50% of business decisions will be "augmented or automated by AI agents," but many operators are still using fragmented and static data.

Even though more data is being gathered than ever before, a large amount of it is underutilized because it takes too long to understand. That delay can result in a significant competitive disadvantage in online casinos, where player behavior and margins can change rapidly.

The missing component is contextual intelligence. technology that not only gathers data but also comprehends it instantly. Systems that show what matters to them at the right time and allow for quick response are essential for operators.

You've added Page Insights to Hub AI. What issue is resolved by this?
The friction that operators encounter between data and decision-making is intended to be eliminated with Page Insights. In the past, laborious filtering and cross-referencing were necessary for performance analysis, whether by nation, game, or individual player.

That procedure is now instantaneous thanks to Page Insights. The technology creates user-friendly visual dashboards and AI-generated summaries that highlight important trends or movements as soon as a user views a data-rich page in the Operator Backoffice or Supplier Zone.

Anomalies, growth spikes, and underperformance are frequently the most economically significant signals that the AI actively highlights. The immediacy this provides is priceless because even small percentage changes can have a big impact on revenue.

What distinguishes this from conventional analytics or BI tools?
Although they were created for a different rate of decision-making, traditional BI tools are nonetheless very effective. Many rely on specialized users to extract value, sit outside the core platform, and need manual configuration.

Embedded analytics is becoming more popular in several related businesses, including FinTech, e-commerce, and SaaS. The concept is that insights ought to be present in the decision-making process itself, rather than in a different setting that causes conflict.

This is seen in Page Insights. It instantly adjusts to the context of the page that users are on and is completely integrated into the workflow. Setup, report creation, or any other delays are not necessary. When performance varies across several markets and partners, operational teams are able to react more quickly.

Could you give a real-world example of how this operates?
Our country-level performance study in the Supplier Zone is one application of Page Insights. Traditionally, in order to determine which locations are generating revenue, providers may export data into spreadsheets or create custom reports.

That whole procedure is reduced to a single view with Page Insights. Depending on their business requirements, users may quickly view the top-performing nations, determine which markets are gaining traction, and switch between indicators like GGR, turnover, actives, and average bet.

The AI-generated HubAI Insights Sidebar is what really brings value. For example, it can draw attention to a 15% to 20% growth increase in a particular area or indicate a drop that needs further examination. Commercial decisions are influenced by these kinds of information.

What part does Context Mode play in increasing the actionability of data?
The tool transitions from visual analytics to interactivity in Context Mode. Users can ask questions in normal language, and the AI will respond based on the data that is immediately visible, rather than visiting dashboards or creating queries.

This is indicative of a larger trend in the use of AI that we have seen. Natural language querying is "democratizing" data analysis, as we have seen in a number of industries.

Practically speaking, this implies that an account manager or member of the commercial team may ask questions like "who is the top performer" or "what is the total GGR for the top five partners" and receive a prompt, reliable response. By eliminating the need for technical teams to perform routine analysis, it frees up their resources for more difficult tasks.

What does this signify for iGaming decision-making going forward?
AI is changing in this environment from a reporting tool to a co-pilot that reveals insights, predicts trends, and increasingly suggests actions.

Speed of insight will be a crucial distinction in a competitive environment where operators are rapidly entering new markets and managing increasingly complex ecosystems. Whether it's a decreasing segment or a high-performing market, those who can see and respond to trends more quickly will have an advantage.

Over the past 12 months, we have made large investments in our product line, and we are always looking for new solutions that make things easier for our partners. The objective is to minimize the gap between data and action. A significant step in that direction is Page Insights.