Sports Betting Focus 2017
PERSONALISING A MOBILE OFFER
Recommendation engines and machine learning will defi ne the winners in the developing app ecosystem , and that applies as much in sports betting as it does in the mass-consumer universe of Amazon , Spotify and Netfl ix , writes Sabrina Solda of BtoBet .
True personalisation in sports-betting mobile apps involves providing a layout designed around the individual user , yet getting to the point of being able to offer this type of service is about more than just a navigational design issue .
Responsive design has previously been about enabling any given site to work regardless of the device it will be viewed on ; but making it responsive to each individual user is a far harder task .
Indeed , the whole process of building a suitably tech-enabled yet personalised mobile sports-betting offering is no simple mission . A system needs to be able to collect large amounts of information about any given player , analyse and learn from that data , identify player behaviours , categorise players by their similarities , predict what they are likely to want to bet on next and subsequently offer one-to-one marketing messages .
The new standard It is a task which has been tackled by many of the most popular apps out there . Whether it is Amazon , or any of the other giants of the consumer-facing mobile app space such as Facebook , Uber , Spotify and Netflix , personalisation 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 , massmarket 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 customisation , and given the correct rewards – and without having to rely on possibly intrusive blind bonusing and push notifications - it will see players coming back time and again to your offering .
The appliance of science Machine-learning technology – as part of an artificial intelligence-led offering - holds the key in mobile sports betting as much is it does with the likes of Amazon , Spotify and Netflix , 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 ( utilising user metadata ).
In 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 analyse a large amount of information on the players ’ behaviours and then feed that information back to predict what preferences will work for a new player to the system .
Engine of change 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 enginedriven 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 personalised .
As BtoBet chief marketing offi cer , Sabrina Solda plans and implements BtoBet ’ s inbound marketing strategy to drive awareness and demand in the global market . She has over 15 years of experience working closely with multinational advertising agencies and has enjoyed a successful career as a marketing and communications manager for many companies in the igaming industry .
66 | iGamingBusiness | Issue 105 | July / August 2017