Customer Centricity
Not all customers are created equal. At least according to the concept of customer centricity. And if not all customers are created equal, why do many companies insist on treating them as such?
Customer centricity
Align development, products, and services with your customer needs
Not all customers are created equal. At least according to the concept of customer centricity. And if not all customers are created equal, why do many companies insist on treating them as such? Why do so many use the same metrics for their entire customer base, and more importantly, how can a company monetise on customer centricity?
Not all customers are created equal.
Dr Peter Fader
Customer centricity is a strategy that aligns a company’s development and delivery of its products and services around the current and future needs of a select set of customers to maximise their long-term financial value.
The customers to focus your strategy on should be the customers with the highest customer lifetime value, CLV. Understanding CLV at the individual customer level is something every company should strive to do. It is imperative when practising a customer-centric strategy.
So how do you do it? To help you get started, we, together with Wharton professor and global thought leader Peter Fader, share the ultimate toolbox for success. We hope these articles, models and discussions will inspire you to get started and find your future best customers.
on-demand webinar
Customer lifetime value
In this webinar, Dr Peter Fader discusses what's holding companies back from reaching their true potential and maximising the profits from their customer strategy. What is customer lifetime value, and how do you reap the benefits of it?
Watch webinarCustomer centricity
Recommended articles
Customer-base analysis in a discrete-time noncontractual setting
An academic paper laying out the main model used in practice.
Many businesses track repeat transactions on a discrete-time basis. This model has shown an excellent ability to describe and predict the future behaviour of such a customer base. The model is easy to implement in a standard spreadsheet environment and yields relatively simple closed-form expressions for the expected number of future transactions conditional on past observed behaviour (and other quantities of managerial interest).
By Peter S. Fader, Bruce G.S: Hardie and Jen Shang, 2010
Read articleMore than meets the eye
A non-technical paper sets the stage and covers many key conceptual issues.
At a purely conceptual level, the calculation of CLV is a straightforward proposition: It is simply the present value of the future cash flows associated with a customer. However, the reality is more complex, as any analyst given the task of computing CLV will know. The key challenge is forecasting a customer’s future cash flows conditional on his or her past behaviour.
By Peter S. Fader, Bruce G.S: Hardie and Ka Lok Lee, 2006
Read articleCustomer centricity and customer lifetime value as drivers for sustainable growth
All companies should aim to acquire customers with the highest lifetime value. But to fund the marketing efforts needed to find them, revenue from less profitable customers is needed too. It’s a balancing act that’s tough to get right. In this article, we set the records straight on customer lifetime value and what you need to know to profit from it.
By Lauri Eurén, Columbia Road
Read articleA three-step CLV-focused channel strategy for ecommerce
While executing a customer-centric strategy and acquiring and retaining customers, it’s not enough to merely focus on one group of customers. While it’s true that the business should be optimised based on the customers who bring in most of the profit in the long run, there’s more to the rule than it might sound at first.
By Lauri Eurén, Columbia Road
Read articleBook
Free preview of Customer Centricity
Despite what the old adage says, the customer is not always right. Not all customers deserve your best efforts: In the world of customer centricity, there are good customers, and then there is everybody else. In Customer Centricity, Peter Fader helps businesses rethink how they relate to customers. The book is available to purchase through Amazon.
Written by Dr Peter Fader
Read excerptTools
Assets that can help you to become more customer-centric
Implementation library
This library offers a vast array of implementation notes, such as:
- A note on implementing the Fader and Hardie (Interfaces, 2001) "CDNOW Model"
- How not to project customer retention
- Fitting the sBG model to multi-cohort data
- Implementing the BG/BB model for customer base analysis in excel
You'll also find a list of key books for those interested in applied probability modelling.
Model function library
This is an R library covering the basic models that many researchers (academic and commercial) have been using extensively.
It provides functions for data preparation, parameter estimation, scoring, and plotting for
- BG/BB (Fader, Hardie, and Shang 2010)
- BG/NBD (Fader, Hardie, and Lee 2005)
- Pareto/NBD and Gamma/Gamma (Fader, Hardie, and Lee 2005) models.
Tools for CLV estimation
A set of state-of-the-art probabilistic modelling approaches to estimate individual customer lifetime values (CLV).
Currently, the package includes the four latent attrition models to model individuals' attrition and transaction processes. Including an implementation of the Gamma/Gamma model to model the spending process of individuals.
Python library to calculate CLV
As emphasised by Peter Fader and Bruce Hardie, understanding and acting on customer lifetime value is the most important part of your business's sales efforts. Unfortunately, many companies are doing it wrong.
Lifetimes is a Python library to calculate CLV for your business.