Interactive DATA MANAGEMENT
know plenty about the customer and be able to head off defection to a rival.
Yet while many organisations have set up teams of analysts and believe themselves to be advanc- ing in the right direction, the reality is that the majority still lack the fine-grained data that will give them the capability to, for example, intervene with a telling offer or football tip at an individual customer-level, based on previous behaviour.
What is missing is the advanced use of analytics which gives an organisation the capacity to seg- ment its customers in much finer detail and then to act on the resulting insights in real time.
KNOW THEM INSIDE OUT
Segmentation will reveal which customers are for instance, loyal but infrequent players or those who are frequent players and have multiple applications on their smartphones. Behavioural analytics can then be deployed to reveal individ- ual customers’ patterns of activity and correlated against market information.
Correlation allows a gaming operator to discover when rivals’ odds are more
competitive. If a recurring link
is established, it indicates that the customer always checks other sites’ odds before placing bets
An example of how this works is with individual customers who always linger before placing bets and occasionally fail to wager any money at all. Correlation allows a gaming operator to discover whether its odds prove unattractive at a moment when rivals’ odds are more competitive. If a recurring link is established, it indicates that the customer always checks other sites’ odds before placing bets. This makes it a priority for an opera- tor to secure such a customer’s business with an offer as soon as they go on the website or activate
their app – and before they have looked else- where. The offer can arrive by text message, email or website pop-up.
Having understood individual customers’ habits in this way, operators can also deploy propensity modelling, of the depth and complexity now enjoyed by online retailers, to show where gam- blers’ next pounds are likely to be spent. This gives the operator the chance to make a revenue- boosting intervention, either by offering the cus- tomer more opportunities to bet on a particular sport or team or by heading off a departure to a competitor with a timely deal.
PERSONALISING THE INTERFACES
This greater knowledge about individual cus- tomers also gives an operator the chance to make simple but effective adaptations to its website and mobile apps to match individual preferences. This means that if the analytics show the cus- tomer has a marked preference for reading racing tips or always bets on races at a particular course, or on a specific team or sport, the website and the
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