Customer Segmentation Analytics for an Online Payment Services Provider
"Quantzig's customer segmentation analytics solutions helped us build advanced models to identify customers with high churn risks and reach out to them as part of a focused retention program leading to churn reduction." About the Client The client is a leading online payment services provider based out of North America with a large customer base. [...]
“Quantzig’s customer segmentation analytics solutions helped us build advanced models to identify customers with high churn risks and reach out to them as part of a focused retention program leading to churn reduction.”
About the Client
The client is a leading online payment services provider based out of North America with a large customer base. While the company had rapidly grown, based on an aggressive sales strategy, it had lost connection with its customers and was reeling with a high churn rate.
The Business Challenge
Identifying the right target customers is of utmost importance for companies in the financial services sector. But with dynamic customer preferences and the ever-growing competition, it is indeed quite challenging for companies to identify and target potential customers. In such a scenario, customer segmentation analytics solutions can help organizations to target the right customers and drive greater profits by segmenting the customers into homogenous groups with similar characteristics.
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Our client had a rapidly growing customer base and the volume of transaction data entering the system precluded any analysis using manual spreadsheets. When they realized that they did not have the tools to scrutinize data, they invested in proprietary analysis software to alleviate the problem. However, despite the investment, they were unable to derive the insights that were essential for monitoring and decision making. Subsequently, the client approached us with specific issues related to their customers, which was to be unraveled based on their transaction data.
By leveraging Quantzig’s customer segmentation analytic solutions the client was looking to answer the following questions:
- What metrics need to be monitored to gauge customer engagement?
- Which of my customers are likely to churn and what are the specific indicators for churn?
- Which customer segment should my sales team target to build a healthy customer base?
- How should I monetize my customer base to increase revenue?
- How to provide better value to my customers that will increase customer engagement?
Solutions Offered and Value Delivered
Quantzig’s dedicated ‘Customer Analytics Centre of Excellence’ with a team of 20+ data scientists, domain experts, and analysts designed an innovative three-pronged approach that leveraged various customer segmentation analytics techniques to tackle the challenges faced by the client. The crux of this engagement revolved around the use of advanced customer segmentation analytics techniques such as- clustering algorithms and time-series analysis.
The use of clustering algorithms and time series analysis helped the client to segment their customers into smaller segments and model the behavior of churned customers across different cohorts while offering a better understanding of the segment-wise behavior. The feature set built for this purpose included demographic information collected at the time of registration as well as engagement information derived from transaction data sets.
Identifying these segments provided a clear picture of the entire customer base and the variation in behavior of each segment. This helped our client to build the strategy for better customer engagement in terms of offers, customer reach out programs and so on.
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Quantzig’s customer segmentation analytics experts built a customized solution to meet the client’s requirements which included the following three-phases:
The first phase of this customer segmentation analytics engagement focused on developing a data pipeline to access and process the raw data in a secure manner. The pipeline required that the raw data undergo a cleansing and quality check process before any further action.
In the second phase, the raw data was processed to create multiple new features that were specifically engineered for customer analysis. The new features provided a holistic view of the customer journey throughout the lifecycle of engagement and enabled further analysis.
In the third phase of this customer segmentation analytics engagement our experts devised customized dashboards to help the client flexibly analyze data. The processed data was used to build a separate machine learning pipeline for carrying out customer segmentation and churn prediction.
Based on the insights provided, the client was able to monetize customer data by designing services based on customer needs and preferences. The deployment of advanced analytics dashboards also benefitted the client tremendously by offering a real time view of the global customer base.
The customized analytics solution was deployed in a production environment for the client and has had the following impact:
- The customer churn reduced by over 9% post engagement
- Revised offers being provided the client was able to increase customer engagement by 10%