Predicting Customer Lifetime Value Using ML
27 Jul 2021
Think about the various group of individuals you interact with on a daily basis – friends, family, relatives, colleagues, coaches, educators, and more. Possibly, there would be a methodology, different styles and communication you would adopt while interacting with each of these individuals/groups.
For every business, there are certainly distinct groups of customers – some create value by being loyal to your brand while others could be just one-time buyers. Irrespective of their persona, they all show unique expectations, needs, pain points, characteristics, and more.
Today, customer lifetime value (CLV) has emerged as one such mechanism to understand the customer better and create appropriate segmentation. Recognizing their preferred lifestyle practices, habits, modes of communication & understanding their unique needs, helps not just meet but exceed their expectations.
Through this article, we’ll try to cover the important facets of how to enhance and boost business strategies with CLV. And do not miss out on the video showcase with the powerful use case of estimating customer lifetime value using machine learning techniques.
Let’s dive right in!
What is Customer Lifetime Value (CLV)?
It is a primary metric of gauging a client’s experience. CLV is an estimate of the net profits the customer brings to your company over the span of their entire relationship. With customer lifetime value segmentation one can create sub-clusters of how to maximize the reach for services/products to acquire new customers and retain existing ones. Businesses make it a priority to grow their CLV by leveraging data analytics. Through Machine Learning (ML) models, they can identify the gross monetary value (GMV). It is further used to evaluate the performance of marketing & sales strategies, retention rate, and how much one should spend on acquisition.
Wish To Improve Lifetime Value For Your Business?
We can help build custom data-driven solutions and CLV models to fine-tune your customers’ relationships.
Why Invest in CLV?
It enables organizations to build a long-term strategy to acquire, nurture, inform, and retain clients.
- Spending pattern estimation of service/product offerings, frequency of orders and purchase history analysis helps the enterprises to optimize the sales & marketing efforts
- Brands that spend time to recognize, target & retain highly valuable customers can expect 10-30% revenue growth over the competition
- Helps understand the customer psyche better to predict demand, serve right and improve retention
Customer Lifetime Value Applied (Use Case)
Wondering how? Let’s understand this through a real-life example of how useful is ML in predicting the CLV model.
Here are key steps of how we at Rishabh Software build solutions to predict customer’s lifetime values:
- Define a suitable time frame for CLV calculation
- Identify key features to predict future outcomes by implementing ML algorithms.
- Evaluate lifetime value for training the ML model
- Develop and operate the model
- Evaluate if the model is working as per expected outcomes
One of the simple yet potent techniques majorly used in evaluating customer value over a time frame is RFM analysis where,
- R indicates Recency – How recently a consumer has made a purchase
- F indicates Frequency – How often a consumer makes a purchase
- M indicates Monetary Value – The value of the purchases made
Conclusion
Today’s customers expect a hyper-personalized experience. With a customer lifetime value model in place, you can categorize, customize, and examine user profiles in a highly detailed manner while opening up new avenues for business on profitability and productivity.
We work with clients across domains and varied sizes to create customer segmentation and predict customer lifetime value for every segment based on their requirement. This data can be further used for crafting and driving highly personalized campaigns/offers. Our skilled data scientists work as an extension of your team to develop custom Machine Learning driven solutions by making the most of all the data lying with you and generate measurable results for your enterprise.
Now is the right time to take advantage of this data-driven technology and stay ahead of rivals!
Want To Conduct The Right Customer Segmentation?
Rishabh Software can help you leverage data-driven capabilities to forecast profitability, set client acquisition budgets, and determine goals for business growth
Field Service Management Solution
In today’s dynamic business environment, companies require nimble field service operations to improve service quality & speed. A field service management (FSM) software enables them to streamline processes, effectively utilize assets & resources, and drive efficiency.
Enterprise Mobile Application Development: Guide to Build a Secure App
This guide will give you a clear understanding of the importance of enterprise mobile apps, how they can benefit your business, and how to develop one. So, let's dive in!
Facility Management Software Development [Case Study]
Admin and property managers handle a large number of facilities. And for them getting a 360-degree view of property over a single platform is quintessential. It helps them to streamline the process of tracking, planning and managing operations better.
Data Warehouse Implementation: Plan, Components, Guidelines & More
This post will discuss how to go about data warehouse implementation, its components, benefits, best practices, resources required, and more.