The client is one of the largest online card games providers in Asia with millions of active users and a revenue stream of approximately $30 million as of 2018.
- The competition is massive in the iGaming industry across the globe, and gaming companies need to allocate heavy budgets to player reinvestment.
- However, without a rigid structure in place, the client could exhaust their marketing budget trying to retain players or could still have high churn rates despite multiple player reinvestments. Detecting highly valuable players early on is a crucial step, which can only be detected when player behaviour is thoroughly analysed.
- The client made their marketing spend allocation decisions based on a limited number of variables. Their model used an ‘average player’ approach where players were incentivized based on average bet amounts, rounds played and so on.
- Such a model was unsustainable. It led to suboptimal allocation of player reinvestments and the wrong set of players being incentivised. This negatively impacts customer loyalty and revenue growth.
- The client was aware that there was potential for high ROIs if better player reinvestment targeting measures were enforced.
- In contrast to the current approach of limited attributes, an exhaustive list of KPIs including customer demographics, gaming history, and client’s revenue at player level were considered for creating 4-5 Player Segments. The process helped understand the players better.
- New segments were then created based on players’ Recency, Frequency & Monetary value. The players were scored based on their RFM values.
- A Set Of Dashboards & Analytical Reports Were Developed And Deployed To Facilitate Better Reporting Mechanisms For The Client. This Enabled Business Users To Traverse Through The Data With Few Mouse Clicks.
- A Single Point Of Truth Across The Business Using Modern Dashboards Enabled The Decision-Makers For Quick And Timely Decision Making.
This resulted in a
increase in revenue for the client
The client through their RFM solution were able to allocate player retention spend almost on a daily basis, based on the player’s
Thus, making optimal use of the marketing budget to maximize their KPIs.
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