A Leading Payment Gateway Services Provider Leveraged Customer Churn Analysis to Forecast Churn Probability
Minimizing Customer Churn Using Churn Analysis Models About the Client: An American subsidiary of a German banking firm that recently ventured into the online payment processing segment. The client was well-known for offering payment gateway services in over 80 global markets. The Business Challenge: Over the past few years, the ratio of customers switching over [...]READ MORE >>
Minimizing Customer Churn Using Churn Analysis Models
About the Client:
An American subsidiary of a German banking firm that recently ventured into the online payment processing segment. The client was well-known for offering payment gateway services in over 80 global markets.
The Business Challenge:
Over the past few years, the ratio of customers switching over to other financial service providers has increased significantly due to the wide range of alternative financial products and competing providers. As a result, customer churn rates now lie anywhere between 20% to 30%. This has brought to light the importance of churn analysis and its role in customer retention. Also, reports suggest that customer churn has resulted in high costs in the form of lost profits. This not only signifies the loss of income from the customers themselves but also from other value contributors.
Though systematic recovery is still a rarity in today’s banking world, the probability of winning back lost customers looks promising with advanced churn analysis models that are capable of retaining customers. What’s even more interesting is the fact that the cost of recovering a former customer accounts for just one-third of the cost of acquiring a new one. Moreover, banks are generally well-aware of their former customers, their creditworthiness, how they use their products, and their preferences, making it easier for them to retain and recover former customers rather than acquiring new ones. Owing to such factors leading players are now leveraging churn analysis to understand and capitalize on customer behaviors.
This customer churn analysis engagement outlines how we used customer churn models to forecast churn probability of existing customers for a banking services provider. As a leading payments platform service provider, the client faced a number of challenges such as- increasing customer churn rate, fluctuating customer preferences, increasing competitive pressures, and fraud. This customer churn analysis engagement focuses on the ultimate challenge in customer churn management, i.e., preventing customer churn even before it takes place.
Top Challenges Faced by the Client
With the financial services sector being highly saturated, existing players face several challenges in differentiating their service offerings. Though the client had made significant investments in gathering and storing customer data, less than a fraction of the investment had gone into using the data for practical business applications. The complexity of such disparate datasets was the primary reason that prevented the client from devising an extensive data-driven analytics framework. Additionally, the legacy BI tools used by the client further hampered their ability to handle complex data sets.
However, customer churn turned out to be the biggest and immediate problem that they needed to focus on. The banking services provider soon realized that keeping abreast with the numerical churn value alone was not proving helpful. Instead, they wanted to understand the root cause behind customer churn and leverage customer churn analysis to retain customers and explore customer behavioral patterns through analytics. As a result, they were looking at using churn analysis models to analyze payments patterns and to build sophisticated and effective programs to reduce churn.
Problem Statement 1
The client found it challenging to identify the reason behind customer churn owing to the compelxity of datasets and the inability of their BI tools to gauge data at scale. They wanted to leverage churn analysis to address this challenge and improve the effectiveness of their marketing campaigns.
Problem Statement 2
To quickly deliver actionable insights to operational teams to speed the development of new programs aimed at maximizing customer retention. This was a major challenge that prevented them from developing
Problem Statement 3
To devise churn analysis models that will empower them to understand the preference of different customer groups as well as identify the associated churn risk.
Customer churn is a critical business metric and businesses that have endeavored to minimize churn through a variety of marketing and product development programs alone may find it challenging. Request a FREE proposal to know more about our customer churn analysis solutions.
Solution Offered and Value Delivered
To tackle the challenge of customer churn the client chose to partner with Quantzig and leverage the use of churn analysis models to predict churn rates and modify offerings. The banking services provider needed to first redefine key metrics associated with customer churn. This would also help them set KPI’s and better understand the long-term health of the business.
This customer churn analysis engagement was divided into the following three phases:
The initial phase of this churn analysis engagement focused on the development of predictive customer churn models by leveraging existing churn reports and customer datasets.
Phase two of this customer churn analysis engagement revolved around enhancing churn metrics and the accuracy of the delivered insights to both the operational and executive teams.
Phase three of this customer churn analysis engagement revolved around delivering actionable insights to the clients’ operational team. This helped them speed the development of new programs and roll-out initiatives aimed at minimizing customer churn.
After a detailed churn analysis was performed, customers were selected for whom a high churn risk over the next few months was identified in the analysis. This was then followed up with a detailed understanding of their preferences which also paved way for identifying new upselling opportunities. The churn analysis solutions also empowered the client to compare scenarios, anticipate risks, identify new opportunities for churn reduction, forecast resources, balance risks against expected returns and work to meet regulatory requirements. By making analytics widely available they were well-positioned to align tactical and strategic decision-making to achieve business goals.
With the help of churn analysis solutions, the client reduced customer churn rate from 10% to 3% in the first year and improved customer retention rate by a whopping 85%. Their new ability to preempt and identify customer churn furthered delivered a 70% improvement in the overall annual ROI. Also, the churn analysis project paid for itself within seven months and provided an annual net benefit of $1.5 million.
Quantzig is a leading analytics service provider, with 15+ years of experience in offering customer churn analytics solutions to several companies across industries. Our team comprises of highly knowledgeable analysts and churn analysis experts who deliver accurate results and help drive continuous business excellence. Quantzig’s main objective is to bring together the best combination of advanced analytics solutions and industry expertise to complement our clients with a shared need to discover and leverage churn analysis.
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