Featurespace was co-founded by Dave Excell and Professor Bill Fitzgerald, Professor of Applied Statistics and Signal Processing at Cambridge University.

It combines machine learning with a new approach to modelling complex systems to create its Adaptive Real-time Individual Change Identification engine.

This delivers real-time behavioral change identification information, something Featurespace believes will be the future of predictive data analysis.

Almost a year ago exactly, King released a game that would quickly alter the face of the social gaming industry.

According to the Daily Mail, only a month after its release the game had over 10 million downloads; it soared past Angry Birds and FarmVille to become number one within six months. And American tech news website The Verge confirmed this month that half a billion people have installed Candy Crush Saga.

Fast data analysis

The good news for all mobile games companies?

With the right data analytics, they can now skyrocket their profits in line with their popularity, retaining customers and increasing revenues with industry-leading customer interaction.

The reason is simple. Mobile gamers are constantly interacting with their devices, and a passionate gamer can play 8-12 hours a day.

That's thousands of data points generated and collected, but organisations can't stop there.

Those companies who seize the opportunity can turn all that customer data into brilliant solutions for retention, monetization, upsell, product improvements and more - empowering them to effectively use customer data to predict behaviour and positively impact associated outcomes, driving growth and simultaneously increasing customer satisfaction.

With half of all UK internet users playing online games, and more and more gamers using their mobiles and tablets as well as their laptops, the intricate footprints created generate data that is far more complex than humans can process.

Luckily, a mathematical revolution taking place in a few rarified academic institutions such as MIT, Stamford, and Cambridge, focused on machine learning and predictive analytics - of which my co-founder, Professor Bill Fitzgerald, is a world leader.

This revolution in understanding data, called Adaptive Behavioural Analytics, allows companies to see an accurate, real-time view of customer interactions, enabling them to develop customer profiles and make decisions based on actual behaviour, not arbitrary rules.

The technology is so sophisticated, and builds customer profiles so rich, that changes in behaviour are detected in as little as 100 milliseconds.

Highlighting bad behavior

Can you imagine the power that gives you when interacting with your users and building a valuable long-term relationship with them?

Understanding individuals' motives and the thought processes driving gaming choices and habits will result in more effective targeting through tailored products, offers and promotions. Not only does this increase both customer loyalty and opportunities to upsell, but it also makes irregular and erratic behaviour easier to detect.

Individual customer views are so accurate that it's a cinch for gaming companies to identify wider threats facing the industry, like increasing amounts of fraud or questions surrounding the negative social impact of gaming.

The uptake of these intuitive, individualised analytics and the corresponding explosion in user data gives organisations a unique ability to follow the customer and spot potentially fraudulent or addictive behaviour before it even happens.

For example, my other half swears I'm addicted to Candy Crush - in truth, I do really enjoy playing.

But clever behavioural analytics allows gaming companies to predict potentially addictive behaviour the moment any significant change in playing pattern occurs, differentiating between truly problematic behaviours that may need addressing, and the behaviours of mildly obsessed fans (like me).

Maximising good behavior

Gaming companies are uniquely poised to take advantage of these advances, given the extensive insights they can glean from user interactions.

Increases in smartphone and tablet use have translated into more people playing games on those mobile devices, enabling mobile companies to become leaders in utilising customer interaction. Using the rich, adaptive behavioural profiles of mobile gamers, organisations can detect everything from gaming preferences to interest broadcast through social media channels.

In-game upsell - one of the key goals of game developers - can be far more effectively encouraged when each customer appears as who he or she is: an individual, with personal tastes and habits that can inform communication and interaction.

Now is the time

Opportunities like Adaptive Behavioural Analytics, which empowers gaming companies to revolutionise the way they make decisions, develop products, and interact with customers, don't come along very often.

In this incredibly competitive market, champion gaming companies will be those that seize the potential offered by clever customer interaction: stamping down on churn, creating unique views of every single individual user, maximising revenues, spotting high value customers, and even combating challenges like fraud and problem gaming.

Best of all, this analytics approach will translate into secure profits: the gaming sector can start to know its customers on such an individual level that encouraging more in-game purchases-safely-will no longer be an industry challenge.

The time is right for the gaming sector to utilise its incredible volume of data, and apply the right kind of analysis to benefit businesses, customers, and ultimately the sector as a whole. How sweet is that?

You can find out more about Featurespace's smarts via its website.