How Customer Lifetime Value Model Helped an Etailer Make Crucial Decisions Related to Customer Churn and Retention
Examination of Customer Lifetime Value as a Key Marketing Metric About the Client A well-established US-based e-commerce industry player. Being an online fashion brand, the client is well-known for designing and manufacturing accessories and apparel with modern aesthetics, sourced from the world's highest quality materials and crafted to last a lifetime. Business Challenge Customer lifetime [...]READ MORE >>
Examination of Customer Lifetime Value as a Key Marketing Metric
About the Client
A well-established US-based e-commerce industry player. Being an online fashion brand, the client is well-known for designing and manufacturing accessories and apparel with modern aesthetics, sourced from the world’s highest quality materials and crafted to last a lifetime.
Customer lifetime value calculation has been an age-old issue for e-tailers, due to which the industry continues to fall back on click-through rates and conversions. New econometric models such as return on ad spend (ROAS) have played a key role in serving the purpose, however, such models tend to miss one crucial element- ‘the customer’. Today, customer-centricity is key to measuring the impact of marketing initiatives, as such the metrics that put the customer at the heart of the experience should be focused to enhance business value. Business growth is generally measured in two ways- by acquiring new customers and by focusing on retaining your existing customers to increase the customer lifetime value (CLV). The omnichannel nature of shoppers brings about major roadblocks in customer lifetime value calculation. Data collection and segregation is a huge challenge owing to the number of variables and macro influences on the customer’s journey. While customer lifetime value prediction has been the focus of discussion in the retail sector for some time now, implementation has always been a challenge for retailers. As such, customer retention has often become the defacto strategy adopted by players to gain a leading edge. However, with the evolution of technology and the growth of insightful datasets, customer lifetime value prediction has become an increasing priority for e-tailers and retailers alike.
With similar intent, the client a leading ecommerce industry player approached Quantzig to leverage its customer analytics expertise to develop a customer lifetime value model. A high customer churn rate coupled with a stagnant customer acquisition rate for over six months prompted the client to take immediate action. They were looking at developing a customer lifetime value model to replace their existing customer acquisition and churn rate minimization strategy with a holistic framework to tackle the industry challenges.
The client’s challenges were spread across the following three core areas:
Problem Statement 1
Customer lifetime value calculation proved to be challenging owing to the diverse nature of customer datasets. Hence, they wanted to develop a holistic framework to identify customer churn and minimize the overall impact.
Problem Statement 2
Their inability to understand the current customer landscape proved to be costly, leading to a sharp decline in customer retention rate. This prompted them to devise a customer lifetime value model to understand their customer base so that customer groups with a high propensity of improved engagement could be targeted and the potential churners could be retained.
Problem Statement 3
The omnichannel and siloed nature of the organization curtailed their ability to calculate and keep track of key metrics of success. To tackle this channel the client wanted to implement an insight-led approach to marketing which delivers ongoing brand value across a host of touchpoints – particularly among younger demographics with a high propensity for digital behaviors.
Today, retailers are embracing the challenge and moving away from measuring success based on return on ad spend (ROAS) and are focusing on long-term, company-wide growth. One of the key strategic priorities to doing this is implementing a shift towards customer lifetime value calculation. Request a FREE proposal to know more!
Solution Offered and Value Delivered
To tackle the above-mentioned challenges the customer analytics experts at Quantzig adopted a comprehensive three-step approach that helped deliver a holistic framework aimed at customer retention and acquisition through the development of a customer lifetime value model.
The initial phase of this customer lifetime value engagement revolved around the segregation of customer datasets into two categories namely- growth and churned categories. These categories were further sub-divided into different clusters by leveraging past customer data.
The second phase or the customer lifetime value calculation phase involved the clustering of the datasets to calculate the lifetime values of average customers in each segment using various metrics. Customer traits that differentiated a potential churner from a potential growth customer were identified and a statistical customer lifetime value model was developed to gauge the influence of each variable on the behavior of the customers.
Developed a framework to identify potential churners using a customer lifetime value model and leveraged customized campaigns to improve retention. The implementation of a new strategy helped improve the retention rate of potential churn customer segments by over 10%.
As a result, potential churn customers were identified using these variables and strategies were devised to increase engagement with the potential customers and to prevent the potential churners from moving away. In addition to improving the customer retention rate, the customer lifetime value model helped the client to enhance acquistion by identifying new cross-selling and up-selling opportunities.
What is customer lifetime value and why is it important?
Customer lifetime value is a measure of the total value contributed by a customer to a retailer’s business throughout their lifetime. It is a crucial metric that retailers use to evaluate and gauge the performance of their marketing initiatives.
At Quantzig, we firmly believe that the ability to harness maximum insights from the influx of continuous customer data is what drives an organization’s competitive readiness and success. Our objective is to bring together the best combination of customer analytics experts and consultants to complement our clients with a shared need to discover and build capabilities that drive continuous business excellence.
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