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Kalamba calls itself a data-driven company, what does that mean in detail?

In order to remain not only competitive but to be a leading company in the igaming space we need to understand our players. Our industry is rather fortunate in that its products are, by their very nature, online, so there’s a huge amount of data and metrics that we can use to analyse performance and identify areas for improvement.

With each and every release we scrutinise the available data from day one of launch and it has proven invaluable. Such focus allows us to identify potential pain points that players may be experiencing. To give an example, you can have players quitting a game immediately after browsing through the available bets, which can indicate that there is a certain sub-sector that expects to be able to bet below €0.50. You then adapt and benefit.

Close attention is consistently paid to key metrics like retention, session length and average bet for given jurisdictions, meaning we are better able to make conscious and informed choices about targeting our gaming toward specific demographics.

We also experiment a lot with volatility, hit rates and other significant parameters to see what resonates better with our audience. All this work helps us improve what we put out there to players and, ultimately, supports our commercial growth ambitions.

 

How can data collection and analysis help a supplier improve its products?  Is this utilisation of available data currently neglected by developers?

It’s essential to perform this kind of R&D in any enterprise and ours is no different. Understanding your customer base and what their preferences are is a key driver for forward thinking, successful business.

From experience, it seems that a lot of key indices, analysis and experiments in igaming are lagging far behind what some of us saw in social casino, for example, where constantly optimising products to enhance the user experience is a key requirement to stay competitive. I suppose it can only help Kalamba if some of our competition neglects this vital area but as long as we continue to perform our due diligence during development and post-launch, then we’ll continue to thrive.

 

How much more do you think data and AI will be integrated into game development going forward?

From a supplier perspective, demographic classification, identifying possible exploits

in a game or pain points in the player’s conversion funnel are just some of the examples of the practical application of AI and the real data insights it provides. Even though the data is anonymised, we can learn a lot about aggregated player behaviours. Being able to tell what works well and what doesn’t means examining many different aspects of the numbers and feedback at the same time and that’s where AI can greatly help.

 

What can we expect from Kalamba in this area?

Kalamba has always championed a creative, data-informed, experimentation approach to

game design and production. Taking it to the next level, we’ve recently initiated our StarGazer project, which we believe will revolutionise the way data is handled and the results we get from it. We will be revealing more in due course!