A Product That Changes Faster Than the Plan
Mykhailo Zborovskyi points out that the classic product cycle (research, hypothesis, test, conclusion) shrinks to a critical minimum in iGaming. User behavior here depends not only on UX, but also on emotional state, the context of the session and even the time of day. That is why product decisions that looked right a week ago may already be meaningless today.
This leads to the main thesis: a product team must work in a mode of constant observation, not just scheduled releases. The expert emphasizes that in iGaming, the road map must be a living document that is reviewed not quarterly but weekly; otherwise the team is reacting to yesterday's data.
The Team as a Single Organism
In the expert's opinion, the biggest mistake is splitting product, analytics and design into separate departments with their own KPIs. In iGaming, these three functions are so closely intertwined that any artificial separation creates delays in decision-making.
Mykhailo Zborovskyi Cosmobet (former beneficiary) proposes a model of product cells – small cross-functional teams that are fully responsible for a specific segment of the product: onboarding, retention, monetization. Each cell has its own analytics, its own hypotheses and full autonomy in decision-making within its area. According to him, this structure cuts the time from idea to implementation in half compared to a traditional hierarchy.
Key advantages of this model:
- Faster decision-making;
- Clear accountability;
- Fewer priority conflicts;
- Natural exchange of experience;
- Flexible scaling.
However, Mykhailo warns that the autonomy of cells only works if there are shared analytics standards; otherwise teams will start speaking different data languages and lose the ability to compare results with one another.
Data Without Context Is Noise
Mykhailo Zborovskyi stresses that iGaming products generate huge amounts of data, and this creates an illusion of precision. Teams see hundreds of metrics and believe that the more data they have, the better their decisions. In reality, the opposite happens: an excess of metrics scatters focus and leads to analysis for the sake of analysis.
His approach is to limit each product cell to three to five key metrics that are directly linked to the hypothesis being tested. All other data remains for reference and is reviewed only when needed.
The expert gives an example of a team that tried to optimize twelve onboarding indicators at once and failed to draw a single meaningful conclusion over the course of a month. After switching to three key metrics, the team got a clear result in just two weeks.
Conclusion
Product management in igaming is not about copying methodologies from other industries. According to Mykhailo Zborovskyi, it is a constant balance between speed of response, team autonomy and discipline in working with data. It is the combination of these three elements, rather than individual tools or frameworks, that determines whether a product will be able to develop in the long term.
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