How retail CMOs can calculate an accurate Customer Lifetime Value

| February 11, 2020 | By

Customer Lifetime Value Defined

Customer Lifetime Value (CLV) is a metric that predicts the total sum of money that a retailer makes out of a customer over the entire period of their relationship. In short, it’s about the long-term health of a business rather than short term earnings. 

In a highly competitive market, a retailer’s prime concern is to capture as much of their customer’s spend for as long as possible – we’ve all heard the stat: “it’s 5X more expensive to attract a new customer than to keep an existing one.”

More often than not, retailers attempt to achieve this through a loyalty strategy. Rewards are provided to customers in the hope that it will motivate a desired behaviour.

A customer might spend around £100 at their local supermarket in a week. The retailer will want to secure or, better yet, increase this weekly revenue going forward.

They could provide a reward that encourages the customer to repeat this behaviour – maintaining their CLV – or provide offers and incentives that will lead them to spend more next time round – increasing their CLV.

The problem facing retail CMOs

The CLV problem facing retail CMOs

However while Customer Lifetime Value may be a crucial metric for retailers, it has proven to be a major challenge to calculate accurately: 

However while Customer Lifetime Value may be a crucial metric for retailers, it has proven to be a major challenge to calculate accurately. 

How to get around these CLV challenges

Yoyo can identify customer purchasing behaviour, regardless of whether they shop in-store or online.

Not only can we see the individual items your customers buy, we analyse how long ago they first transacted, how many times, how recently, and what their average spend is.

Check out how we utilise this data to find out what your customers want from their retail experience:

How CMOs can identify what their customers want from an in-store experience

When it comes to calculating Customer Lifetime Value, we could simply sum the value of each customer’s historical transactions and call that their lifetime value.

This is a useful statistic and we enable our retail partners to track it within Yoyo’s Campaign Builder as ‘Total Spend’.

However, it does not tell the full story of a customer’s value. Here are two types of customer it misrepresents:

1. Customers who have only just been acquired, but have already made many purchases in their first week.
They don’t have high historical spend, but they are a hugely valuable customer.
We might expect them to spend a lot over the next 12 months, and nurturing them should be a high priority for the retailer.

2. Customers who have a long transaction history, but have since churned.
They do have high historical spend, but we may not expect them to spend anything in the future without a specific marketing intervention, e.g. a
win-back campaign.

Yoyo’s AI-led technology is able to deliver a more accurate and useful mechanism that reveals a customer’s predicted 1-year spend…

Why should CLV be a 1-year prediction?

We use a statistical model of customer behaviour called Pareto/NBD due to its high levels of accuracy and its capability to predict whether a customer has churned.

Based on this model, a newly-acquired customer will have a high CLV if their purchase behaviour gives us reason to believe they will go on to make future purchases and become a loyal customer. 

A customer with a long purchase history, who has since churned, will have zero CLV if we believe they will not transact again.

You’ve now got an accurate CLV metric. What do you do next?

Armed with accurate CLV data, retail CMOs can answer these crucial questions:Armed with accurate CLV data, retail CMOs can answer these crucial questions:With these questions answered, retail marketing teams can make informed decisions, spend budgets more effectively, target the right customers with the right messages, and measure the impact of campaigns more effectively.91% of consumers say they would be more likely to shop with brands who recognise behaviour and provide relevant offers & recommendationsAnd with the above questions answered, a retail CMO could go after their most valuable and engaged customers or target customers viewed as at risk of falling away, or both!:Loyalty Campaign ROI

Customer Lifetime Value best practices

Increase high-value behaviours
CLV enables retailers to find high-value customers, understand who they are and what attributes they have, so that they can design a loyalty strategy around promoting high-value behaviours.

Prevent customer churn
CLV finds customers whose predicted future spend is low relative to their historical spend (i.e. people who are slipping away), which enables retailers to target them with specific win-back campaigns.

Determine acquisition spend
CLV helps a retailer decide how much to spend to acquire a customer, which should be less than they expect to make over the lifetime of the customer relationship. It can also determine which acquisition channel is providing the best ROI.


If you’ve got this far, check out Yoyo’s latest report on why customer loyalty isn’t dead:

Yoyo Report: Customer Loyalty isn't dead