How Quantzig Used Customer Loyalty Analytics to Drive Customer Experience (CX) for a Major Bank in US?

May 23, 2022

Highlights of the Case Study: 

Particulars Description 
Client A major bank headquartered in the US   
Business Challenge The client needed to improve its customer experience and customer relationship management to ensure long-lasting relationships with its clients.  
Impact The end-to-end customer loyalty analytics solution provided by Quantzig helped the client maximize the value of its customer base. 

Game-changing Solutions for Banking & Financial Services: 

The reason for the hype in customer loyalty analytics is because of the fact that the BFSI industry is very competitive as customers have various options available. Therefore, customer experience and customer relationship management have become huge differentiators in the banking industry. A good understanding of customers is imperative to achieving customer loyalty and building long-term relationships with clients. As the banking industry witnesses a shift from product-centricity to customer-centricity, it is crucial to engage with the customer from the moment they sign up. Client life-cycle management has become the key mantra for success in the banking industry. 

The Challenges of the Banking Client: 

Our client sought to consolidate its place as one of the leading players in the banking industry. Hence, it needed to enhance customer loyalty and maintain long-term relationships with its customers. However, our client was facing difficulties in acquiring an in-depth understanding of customer needs, due to which it was unable to engage with and retain customers. The result was high customer acquisition cost and churn rate. Therefore, the client approached Quantzig to get help in understanding the customers’ needs better and optimize its customer engagement process to enhance the customer experience. 

Quantzig’s End-To-End Customer Analytics Solution for Banks: 

Quantzig provided an end-to-end customer loyalty analytics solution that helped our client revamp its entire customer engagement protocol. Qunatzig began by integrating the data from various sources (account, channel, product, and DMA) to create a single analyzable dataset. It then deployed customer loyalty analytics wherein clustering and multivariate regression-based models were used to provide insights, which, in turn, improved customer loyalty and sales.  

The Quantzig team developed a churn probability simulator to estimate the probability of a customer terminating their relationship with the bank based on transaction history, product portfolio, and length of the relationship. Our analysts implemented advanced sentiment analysis to gauge customer sentiment across different feedback channels, such as social media and user experience surveys. This activity helped measure the brand’s reputation and understand the unique needs of its customers. Quantzig’s advanced sentiment analysis solution leveraged machine learning algorithms and natural language processing (NLP) to assign weighted sentiment scores to the entities and analyze datasets in real-time. 

customer loyalty analytics

Impact Analysis of Quantzig’s Customer Analytics Solutions for the Banking Industry 

The end-to-end customer analytics solution developed by Quantzig helped the client maximize its customer base’s value. The insights thus gleaned enabled our client to create targeted solutions for its customers and offer the right solutions in a consistent, professional manner. Below is a synopsis of how our intervention helped the client: 

customer loyalty analytics solutions
  • Enabled the client to have a comprehensive view of customer accounts, account structure, and investment opportunities 
  • Decrease in customer churn by 17% 
  • Achieve higher customer loyalty and centricity 
  • An improved customer tracking system that manages loyalty programs and integrates them with internal systems 
  • Increased profit margins 
  • Reduced customer acquisition cost (CAC) by 10% 
  • Increased customer satisfaction by 3X 
  • Increased repeat customers 

Key Outcomes 

The overall benefit of our interventions was a seventeen percent reduction in customer churn and a ten percent reduction in customer acquisition cost. A significant three-fold increase in customer satisfaction ensures repeat customers, increased profits, and higher customer loyalty, likely to reap the rewards over generations of loyal users.   

Broad Perspective on Customer Analytics in BFSI Sector 

CX has become the holy grail for success in the banking industry. If one can cater to all the customers’ demands, one is likely to win lifelong membership. Banking services need to cater to the demand for personalized services that customers can trust and depend on for financial well-being. In addition, customers seek round-the-clock easy access along with real-time assistance. Financial institutions need to be able to build trust and nurture a long-term healthy relationship with their customers.  Big data analytics is essential in enhancing CX, which will lay the path for future business decisions. The high expectations and variations in customer needs mandate the reliance on analytics to gain valuable insights. 

Key Takeaways 

  • Decreased customer churn by 17% 
  • Reduced customer acquisition cost (CAC) by 10% 
  • Increased customer satisfaction by 3X 
  • Increased number of repeat customers 
  • An improved customer tracking system that manages loyalty programs and integrates them with internal systems 

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