Your players do want a personalized mobile offer. But how personal do you need to get?



Your players do want a personalized mobile offer.  But how personal do you need to get?


It is becoming more and more obvious that the world has come to the point where recommendation engines and machine learning will define the winners in the developing app ecosystem. Fortunately, that applies as much in sports betting as it does in the mass-consumer universe of Amazon, Spotify and Netflix. That is a great opportunity, as often it is not very clear in which direction the future will go, or how to create the competitive advantage you need to be a leader or even stay afloat.


How personal do you need to get?


Well, it all starts with the layout. Your sports-betting mobile app involves providing a layout designed around the individual user’s needs and wants. However, getting to the point of being able to implement this type of service is about more than just a navigational design issue. It used to be easier when responsive design meant enabling any given site to work regardless of the device it will be viewed on. Now, there is a far greater task at hand, since you need to be making it responsive to each individual user’s needs and preferences. Indeed, the whole process of building a suitable tech-enabled yet personalized mobile sports-betting offering is far from being a simple mission. A system needs to be able to collect large amounts of information about any given player. Collecting might not seem to be such a difficult task in this modern age, however, to analyze and learn from that data, identify player behaviors, categories players by their similarities, predict what they are likely to want to bet on next and subsequently offer one-to-one marketing messages are all far more difficult tasks.






Keeping up with the evolving industry standards


This seemingly difficult task is a task which has been tackled by many of the most popular brands and apps out there in all sorts of industries. Whether it is Amazon, or any of the other giants of the consumer-facing mobile app space such as Facebook, Uber, Spotify and Netflix, personalization is now the standard and helps define what users expect from their online mobile experience. They may be working across diverse fields in social media, music, film, and TV, mass-market retail or private transport, but what all of these have in common is that they all employ recommendation engines that define the service each individual customer receives. Recommendation engines are what will define the winners in the developing app ecosystem, and that applies as much in sports-betting as it does in the wider universe of consumer-facing mobile offerings. The ability to offer the right product at the right time is true customization, and given the correct rewards – and without having to rely on possibly intrusive blind bonuses and push notifications – it will see players coming back time and again to your offering.


The power of the Recommendation Engine


In sports betting the recommendation engine technology performs a very similar function, allowing the operator to suggest bets on preferred events, whether that is in-play or via virtual sports or eSports. The engine acquires and then analyses data on a player’s patterns of engagement according to which sports, the category of bet or the market type. In both instances, the recommended bet or bets is then offered to the player via the mobile interface and within a few clicks the player will have placed their bet or be playing their preferred game. This is managed all without the player having to reference the long list of events or have to take the unnecessary step of clicking through the hamburger menu or sidebar button. Developments along these lines are effective for all markets whether they are developed – such as in Europe – or are in the more formative stages. Indeed, in markets across Africa where mobile is the primary access route to the internet – but where smartphone penetration levels are running at lower levels – a recommendation engine driven app can work even better with less sophisticated devices. These are fundamental moves for the sports-betting industry. As seems obvious to all who watch developments with the hardware, as the mobile devices of the future progress it offers up the prospect of faster offerings, with better and more potent functionality. It also means the apps that accompany these devices will need to be even more robust, easy to use and personalized.


The science behind it all


Machine-learning technology – as part of an artificial intelligence led offering holds the key in mobile sports betting, providing the capability to offer a tailored sports-betting experience. Particularly effective in online gambling is the hybrid recommendation system – the same as is employed by Netflix – whereby collaborative filtering (where information is collected from many other users) is matched with content filtering (utilizing user metadata). In the casino, a recommendation engine can ensure that all games with similar attributes – such as the theme, the volatility, and the category – are grouped together and offered to a customer according to their own preferences. In the instance of a new customer, the hybrid recommendation system comes into play, allowing us to collect and analyze a large amount of information on the players’ behaviors and then feed that information back to predict what preferences will work for a new player to the system.


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