Sports betting company that stands out among other online bookmakers as a reliable company that strives to create a long-term association with each customer. Although the company is relatively young, it is already trusted by almost one million active fans.
Hundreds of betting websites offer their services to millions of fans who like to bet on sports online. The client spends large amounts of money to acquire new customers, that’s why it is more important than ever to prevent customer churn and turn new customers into loyal ones.
The rate of customer churn directly affects the growth of the company. To keep that rate low marketing and IT department leaders are looking for a solution that can predict customer churn.
InData Labs was chosen for 3 main reasons:
InData Labs starts to work closely with client’s business analysts and marketing team to get familiar with the business, processes and industry specifics.
Customers in the betting industry appeared to be very dynamic, new players come and go very fast. Churn rates in this industry are much higher than in telecom or gaming.
The betting company saw 40% of their customers churning just after submitting a registration form, even before placing the first bet. Marketing team believes that retaining these new customers is essential for the future growth of the company. For that reason, our data science team builds a special model that can predict churn for that segment of new customers with very limited information. As a result, they were able to see that the model can successfully identify active and passive users based on the information they’ve provided with a registration form. InData Labs also helped to identify motivational bonuses for different customer groups. Within a couple of months, the client runs numerous tests to define which bonuses work better for different customer segments.
Other models in InData Labs solution aim to make predictions for players ‘with a history’. The inputs for these churn prediction models are:
InData Labs’ solution transforms the raw customer data into features for churn prediction models. The outputs of the models are probabilities of churn in the course of 3 weeks. It’s easy for the client’s marketing team to interpret outputs of the machine learning system and to operationalize the insights.
The final solution for the betting company includes three predictive models, allowing the company stay data-driven at different stages of customer lifecycle:
InData Labs solution allows its customer to predict customer churn and take up necessary measures to prevent it. The company saw a 20% higher customer retention rate within the first three months after deployment of InData Labs solution.