How do you know whether a customer is never returning to your store or if they’re just taking a break? How much are your customers worth? Future Lifetime Value (FLV) allows us to answer these questions quantitatively.
FLV is a simple model that uses RFM summaries (recency, frequency, and monetary value) to predict the value of a customer. This model applies to any customer purchasing in a non-contractual setting. This means any business with transaction data and non-anonymous customers can quickly leverage predictive analytics in their campaigns on the Clutch platform.
FLV is calculated as follows:
FLV = Expected Future Purchases X Discounted Expected Future Spend
FLV is a measure derived from predictive models that learn from the marketer’s data. Each brand’s FLV values are based on their data, not abstractions. The models build each customer a story by putting the customer’s behavior in context of the brand as a whole. Ultimately, FLV enables brands to run smarter campaigns that anticipate what will happen in the future.
What does FLV tell us?
When used as an actionable metric in reporting, Future Lifetime Value can help identify key trends about a particular set of customers. Here are some examples things we can learn from an FLV analysis:
Quantify the churn status of a customer base
If we know which customers will never purchase again, we can adjust marketing spend accordingly
Understand how customers’ value changes over time
If we understand the point in the customer lifecycle that value begins to diminish, we can change course to try to optimize value
Compare FLV with metrics that we know precisely
If a customer is receiving greater promotion investment than their FLV indicates they will return in revenue, we can modify our strategy
How is FLV different than CLV (Customer Lifetime Value)?
When comparing Future Lifetime Value with a common understanding of Customer Lifetime Value we can see that there are 2 key differences.
- FLV estimates the future – making it an actionable metric
- FLV is specific to the non-contractual setting common to a large subset of verticals, but particularly for retail
Below we compare three common calculations of CLV with FLV.
Calculation #1: CLV = expenditures x visits
This doesn’t help us understand lifetime value at all, unless the customer died the day before we measured. This calculation only looks at the past! FLV estimates the future.
Calculation #2: CLV = expenditures x visits x profit margin
This calculation is pretty much the same as Calculation #1, but looking at profits rather than revenues. But we still can’t anticipate the future with this formula – we can only understand what’s already happened.
Calculation #3 CLV = avg gross margin x (retention rate / (1 + discount rate – retention rate)
This formula is more in line with what you’d see in an mba textbook. It looks much fancier and more complicated than Calculations #1 and #2 – but it is still not a perfect calculation of CLV. Why? Because this formula rests on a huge assumption – that we know the retention rate. How would we determine that value in non-contractual retail settings, where it’s unclear whether customers are between purchases or never coming back? Even if we could determine the retention rate, it’s not constant over a customer’s lifetime as this formula suggests (typically retention rate increases over a customer’s lifetime).
Calculation # 3 has the same problem as Calculations #1 and #2. It’s navel gazing into the past without trying to anticipate the future.
As a bonus, FLV can not only help us anticipate the future, but it also lets us answer the retention rate question by understanding whether a customer has churned or not (FLV = 0)
Bonus round: Calculation #4: CLV = Average (Calculation #1 + Calculation #2 + Calculation #3)
Averaging three bad metrics does not produce a good metric! Or an actionable metric. FLV still comes out ahead.
According to, Peter Fader and Bruce Hardie in their paper titled “What’s Wrong With This CLV Formula?”, there is no universal formula to compute customer lifetime value, FLV leverages the uniqueness of your customers and predictive analytics in order to forecast future behavior.
Short Use Cases
- Optimize Promotion Timing
Increase the frequency of customer’s purchases to drive them through the loyalty flywheel. Use FLV to understand whether a customer has churned or is between purchases, and see at what point on their lifecycle is best to send a promotion that motivates action.
- Firewall Your Promotions
Do not send promotions to customers with FLV of 0. This will optimize your marketing spend, enabling you to better reward customers with greater FLV.
- Optimize Promotion Spend
Tier promotions based on FLV. High value customers are given more incentive to shop than low value ones. Again, spending smarter with those marketing dollars.
Hopefully you agree that Future Lifetime Value is a relevant and powerful tool to identify certain segments of your customer base, understand them a bit better and use that information to optimize your marketing strategy and budget. If you are interested in a Future Lifetime Value analysis, we are here to help. Get in touch with us and we can get to work!