
Why is this metric so popular?
There is increasing pressure by retail management to make marketing more accountable.
- Management has been getting anecdotal information rather than facts for years.
- Marketing investments that improve sales may cost as much to implement than the results are worth.
Sales revenue and earning do not show the whole picture.
- Not all customers are equally profitable.
Technology makes it easy to query the whole customer base rather than a set of sales and demographic data for a slice of the customer experience.
- Marketing can now tailor campaigns to many types of customers and plan marketing campaigns made for different types of customers.
Business has a finite number of resources to invest in the Customer Experience.
A known truth is the 80/20 rule which states that 80% of profits come from 20 % of the customer base.
The more profitable you are as a customer; the better service you receive/ how you are treated.
Popular Data Points
Historically, retailers tracked Returns- mostly to track and find fraud.This has evolved. The data that is regularly captured now includes:
Married?
Suburban? Large City? Rural?
Usually buys on discount?
# of Returns
# of calls to Customer Service
Gender
Never returns?
Buys high quality goods
Pays full price
Multi-Channel Customer?
Graduate Degree
Shops on weekends
Credit Card brands used
Age
Each data point is weighted on past patterns and perceived levels of predictability.
A Customers Lifetime Value is calculated and updated with regular frequency.
How are businesses using this data?
Telecom services now offer Priority Queues for customers on hold. A retailer sets up their phone system with their customers CLV and the phone system distributes your call to be answered with the CLV priority.
If you buy airline tickets at bottom-tier prices, airlines will earmark you for bumping in the event that your flight is overbooked. Frequent fliers and seat upgrades have been around for a while but now, there is a parameter on the major airlines CLV profile which tracks the number of complaints a customer has lodged. This too lowers your CLV and affects your seat upgrades.
On the flipside, some retailers withhold discounts from high value customers “because they’ll buy anyway,” unless they’re at risk of losing them.
Marketing campaigns now recognize levels of customer loyalty and market specifically to them. You run the risk of branding customers as ‘bad’ and ‘good’.
But you still don’t have all the questions and answers about a customer’s buying habits by mining transactional detail. In some cases Proxy data is purchased by subscription to substitute missing data points such as Demographics.
I can see both the value and the danger of this practice. Business Analysts out there should try to create a data set like the one described in this article and see how easy it is to create a marketing report using this concept.
Let me know what you think of the Customer Lifetime Value metric.