One of Pecan’s customers is a leading gaming platform and full-service white label casino solution that enables partners to launch a dynamic casino experience within weeks. The platform includes a variety of casino games, including slots, scratch, jackpots, table games, and live dealers.
The company provides a real-money gaming platform and offers the ability to manage all the services that go into an online casino such as operations, customer care, and player management in one place.
The company, like any online company, is interested in identifying its customers, building distinct profiles and matching each of them with appropriate marketing offers, content and products. This type of data-driven segmentation is valuable to the business, as it can be used to ensure that players are continuously getting value and as such increase revenues, reduce churn and help to build successful future products.
Prior to using Pecan, the company only managed to partially leverage its data to improve business results despite boasting many unique active players a week and with hundreds of thousands of weekly transactions. Like other online companies, it also suffered from player churn. Other challenges included difficulty to adapt the offering to different player profiles and the inability to identify high-value players (VIPs) early enough in the process.
Before turning to Pecan, the customer used other statistical and manual methods to build distinct profiles and match each of them with appropriate marketing offers, content and products.
The results were less than optimal so the company asked Pecan to build 2 deep learning-based predictive analytics models:
The customer used the Pecan platform to build both models within 8 days, compared with 4-6 months required by alternative solutions, which also consume huge and expensive resources of data scientists.
Using Pecan instead of traditional methods meant that the cost of the project was estimated at ¼X of the alternative solutions.
Furthermore, the AI models were built by one of the customer’s BI managers using the Pecan platform, avoiding the need for trained and expensive data scientists.
“Pecan set our actionable insights free. We experienced an extraordinary business transformation that took place within a week. We can now say that we’ve stopped betting on our business future”.
CEO of the gaming platform
Compared to the standard identification of high rollers (or VIPs), the model identified a population of 30% additional potential high rollers and treating them as such early enough in their lifecycle meant that the company managed to convert the majority of them into highly valuable customers.
In addition, Pecan listed 5 specific factors that contributed most to each customer’s tendency to be a high roller. Some of the most common contributing factors were:
The customer used this information to empower their retention team in identifying incentives that will prevent specific customers from churning. The additional revenue derived from this improved retention is estimated at $3.7 million, which reflects a growth of 7%.
Furthermore, using Pecan, the customer discovered the 5 most impactful factors on churn among its entire customer population. This critical information was used to optimize marketing and channel spend to holistically address the churn challenge and improve customer loyalty.
Most critically the company empowered its BI team with the capability of building state of the art AI predictive analytics models, without having to hire data scientists for the job.