platform provider and b) the age of the existing tech stack?
When it comes to the operator side and the data source, it is always the same. We ask what you have and then adopt our ingestion structure to whatever is there. Now we have 300-plus integrations under our belt across more than 30 jurisdictions it's very easy for us to foresee how to find the route of least resistance with a partner. We find competent and complex systems inside our partner’s operations, and we know that we must adopt the structure to the source of the data that we work with.
What's the main driver for new business?
It's very diverse. Te main driver is results. We can demonstrate how we outperform campaigns at 50-100 per cent better than the legacy systems in the market. In-house teams profit from that on the CRM and engagement side. Tey also benefit on the user acquisition side whilst the C-level executives profit because they can run their operations at a far higher level of optimisation with the same team headcount.
What are the advantages of offering gaming specific solutions compared to external software provider offerings?
Tere are a lot of areas where specialisation helps. Understanding data, data structure, the business of gaming, the needs of bettors, how you define this in systems, and setting up on top of existing infrastructure.
Because you might have a large legacy system in place or certain elements that are monolithic. You can't rip these systems apart easily. But what we can now do is circumvent certain parts of this legacy infrastructure. Tis cannot be achieved with an external, monolithic solution where you're in danger of creating a Netscape moment where you're interchanging big chunks of software and not learning fast enough how to use the new one. We can be incremental and take things use case by use case. Tis is why we call them modules because they can be applied to existing structures.
Can you walk us through the AI/ML modules that Golden Whale is regularly implementing into gaming platforms?
Well, the most straightforward are the prediction models that almost everybody wants to have. Value prediction, VIP prediction and bonus usage prediction goes a long way. From there you get into churn prediction and in-session churn prediction - all are popular models. Now we have two layers on top of that. Another is incentive guidance, bet and game recommendation systems from where, going a step further, you can integrate more campaign and interaction types into the models and orchestrate those things with each other.
Tese are things that hugely reduce the need for head count in operational teams whilst addressing the complexity of user journey data far more than any human brain could. Te productivity gains are huge.
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