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From CRM to CDP: Innovating Customer Management in the Era of Big Data in iGaming

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In my previous article, I discussed how a CRM (Customer Relationship Management) should not be seen merely as software but as a set of corporate policies that guide all customer interactions. CRM software facilitates the implementation of these policies, but in the current context of iGaming, where data flows rapidly from multiple channels, we must incorporate new technologies to enhance customer relationships. This allows companies to be more competitive, increase the customer lifecycle, the customer lifetime value (CLV), and improve both efficiency and profitability.

FROM CRM TO CDP: A NECESSARY CHANGE IN DATA STRATEGY

Traditionally, CRM has been seen as the heart of a customer relationship management strategy. Through clear policies and effective use of CRM software, companies have organized and managed their customer interactions, enhancing loyalty and optimizing the user experience. However, to truly stand out and maximize customer value, iGaming companies must adopt more advanced tools that enable a deeper understanding and management of customer relationships.

The Customer Data Platform (CDP) is one such key tool. A CDP not only collects customer data from various sources -such as social media, website pixels, heat maps, platform databases, transactions, and more-, but also organizes this information into a unified customer profile. Additionally, it allows for three-dimensional data visualization, incorporating a new vertex (Z) alongside the traditional axes (X, Y). This provides a deeper, more detailed perspective of customer behavior, enabling much more advanced segmentation and personalization.

NEW DIMENSIONS OF SEGMENTATION: FROM VERTEX X, Y TO THREE-DIMENSIONAL Z

With the integration of the CDP, iGaming companies can overcome the limitations of traditional segmentations, which were based on basic characteristics like age, gender, or type of game (vertex X). Now, thanks to three-dimensionality, we can incorporate the Z vertex, which allows us to analyze more complex and predictive data such as churn probability, behavior patterns, and potential spending increases.

This enables a much more detailed view of the customer lifecycle. For example, not only can we identify players as Curious, New Customers, Potential Loyalists, Frequent Players, Loyal Customers, High Rollers, VIP Players, Churn Risks, About to Sleep, or Dormant Users, but we can also micro-segment and act on each stage with personalized strategies based on their behavior. This approach allows iGaming companies to optimize their resources and maximize the impact of their marketing strategies.

RFM AND PREDICTIVE METRICS: REDEFINING THE CUSTOMER LIFECYCLE

The segmentation model based on RFM enriches us when we can visualize customers in terms of Recency (the last time they interacted), Frequency (how often they interact), and Monetary (the volume of play or economic value). These metrics provide the possibility not only of segmentation but also of behavior prediction. While RFM remains fundamental for understanding the current value of the customer, integrating a CDP allows us to explore much further, offering a broader and more detailed view of behavioral patterns and growth potential for each customer.

PRACTICAL APPLICATION EXAMPLES

  1. Reactivation of Inactive Players: Using the CDP, we identify players who have not interacted with the platform in recent weeks (low recency) but were previously active in high-frequency games. A personalized campaign with exclusive offers for their favorite games is sent during the times they used to be active, thereby increasing the chances of reactivation.
  2. More Efficient Campaigns: Instead of sending all players a generic $10 sports bonus, the CDP enables sending a specific $5 bonus to a customer who is a Barcelona fan, just minutes before the match begins. This not only increases engagement but also significantly reduces activation costs by being more relevant and personalized.
  3. Optimization of Marketing Campaigns: By analyzing CDP data, it is discovered that a specific group of players shows high interaction during afternoons in strategy games. A targeted marketing campaign is launched for these players, offering special bonuses in those games during the peak activity hours detected, improving campaign effectiveness and engagement.

NEXT PRESENTATION

On August 4th at 5:00 PM, I will be presenting at G&M Events Argentina 2024 in Casino Magic Neuquen, a practical case illustrating how these strategies can be effectively applied in iGaming, using real examples of CDP use, treatments, and marketing strategies. Additionally, in my next article, I will delve deeper into automated treatments, marketing automation using the CDP, and how it allows for more efficient and personalized customer management. I hope to see you there!

AICDPAICRMAICustomer SegmentationAIData StrategyAIiGaming

Risk Warning: All news content is created by users. Please maintain an objective stance and discern the content viewpoint on your own.

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