bizacuity

iGaming Churn Analysis

About Client

The client is one of the world’s largest and oldest multi-channel bookmaking and gaming companies from the United Kingdom, operating in over 25 countries with annual revenue exceeding €3 billion as of 2020.

Background

  • To acquire a player, igaming operators need to fight the stiff competition in their industry, ensure their players’ KYC operations are quick and smooth, verify their payment accounts setup and they need to keep them engaged for as long as they can on the internet by providing the best experience possible. Through every step, a significant number of players will choose to never return to the site. Retaining the customer for as long as they can is one of the key indicators an online casino consistently tries to improve.
  • However, this is easier said than done. To keep a player engaged means to study and understand their behaviour, hyper-personalize their gaming experience to retain them for longer and make personalized marketing offers so that they return.
  • Churn analytics is extremely important and online casinos nowadays use machine learning and deep learning algorithms to gain a high-quality perspective of their players in order to reduce churn rates

Challenge

  • The client wanted to reduce their player churn rate and predict most valuable players early on to retain them through personalized offers. Further, they needed the information integrated to their CRM for campaign analysis and measuring efficiency of their marketing efforts.

Our Solution

  • BizAcuity with over 60 years of collective experience in the iGaming industry identified key customer predictor variables that optimizes marketing analytics for the company.
  • With the variables, the team built a machine learning model that was able to predict player behaviour at the individual level. Using a machine learning model ensures that the model gets increasingly accurate over time as data is continuously fed back into the model.
  • The prediction output was then integrated with the client’s CRM workflow for dashboarding the results

Outcome

Within 4 months of implementation of the model developed by BizAcuity,
The player churn rate of the
client was reduced by10%
With A Low Total Cost Of Ownership

The ‘Early identification of VIPs’ feature led to a

5%
increase in average player value after understanding patterns of churn

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