Lifetime value is an important KPI for any e-commerce business. This guide outlines how to calculate it, how to improve it, and how to predict future returns using it.
In this piece, we’re going to look at the idea and uses of customer lifetime value (CLV or LTV). The power of looking at LTV is that at its core, it’s an inherently straightforward concept to grasp - everyone intuitively understands that customers themselves have a value to a business, rather than just an accounting of all the transactions in a given period.
From this base, we can use LTV calculations to project future value, identify actions to increase profitability and a number of other actions. It also gives you a basis on which to invest in customer care and is an important metric for assessing the effectiveness of your CRM activities.
The good news is that a lot of platforms and CRM programs will do this for you. If you use Magento, for example, you will find this in the data management part of the platform. Google Analytics has a version, but it’s cookie-based (and thus subject to normal cookie-based inaccuracies) and only takes 90 days of data, so it doesn’t really give you that much insight into the long term value of your customers.
Even if you are able to get a value straight from your e-commerce platform or CRM, it’s still worth knowing how the calculation works as there can be a few variations and you will need to know what is being included and what is not.
The standard way of calculating customer lifetime value is to use the following formula:
This might seem relatively complex on the surface, but once you have it set up in Excel or R, the numbers fall out easily. Some quick points on the terms of the equation:
Lifetime Margin is the average total gross margin generated per customer. It’s better to use margin rather than revenue here, as revenue can hide important information about profitability, including how much it costs to retain customers. If your platform or CRM tool is using revenue rather than margin, then you need to be conscious of this in later calculations, especially when looking at acquisition profitability.
Retention Rate is the share of customers that you retain per month
Discount Rate is the average discount rate (using rate not total value is important here) that you are giving your customers. This ensures that your value calculations take this into account and you’re not just able to juice the lifetime value by offering increasingly large discounts.
This value represents the value at a given point in time - average customer margin, retention rate and discount rate will all vary over time.
Once you have the calculation set up, there are two simple things you can do right away - calculate this value by month going back over a reasonable time span (at least a couple of years, but as it’s fairly trivial to do, it makes sense to use all the data you have that’s easily accessible), and start to track this number going forward.
This immediately gives you a sense of where you are as a business and can provide a valuable warning if you are losing customers or their value is decreasing.
Of course, it makes sense to use this data for more than just passive measurement - you can use it to help guide strategy and investment of time and resources.
Logically, it makes sense that there are two main levers to increasing customer lifetime value - increasing the frequency with which customers make a purchase and / or increasing the amount that they spend each time. Taken together, this captures a greater share of wallet and customers choosing to spend more money with you rather than your competitors, which is always a good thing.
As soon as we start talking about frequency and average spend, another type of analysis springs to mind - a recency, frequency, monetary analysis (RFM) of your customers. You will probably already be familiar with this - most CRM tools and some e-commerce platforms have this as part of their data packages.
Essentially, this allows you to break down your customers into cohorts, splitting out the most active and high value customer groups. You can calculate customer lifetime value for each of these cohorts as well. From this, you can start to identify common features within each cohort, whether that is initial purchase category, geography or demographic, time of year or any other signal that you are able to capture.
The same type of analysis can be done with any other type of segmentation - for instance, you may well have performed a behavioural segmentation of the broader market and be able to identify these groups within your customer database.
Identifying and understanding the lifetime value and trends within these various cohorts is very helpful when making strategic decisions such as:
Where to put your media spend
Which products to push (and when)
Which audiences to use in your social and display advertising
What to prioritise with your onsite personalisation
In all these cases, you are seeking to match investment to the groups and actions that will maximise lifetime value and as such, you should be able to set and track performance against targets as you go through the year.
Lifetime value for acquisition
Being able to put a value to each customer acquired also gives you more scope when it comes to looking at cost per acquisition. Without a view of customer lifetime value, the upper bound of your cost per acquisition is equal to the margin that you make on the transaction - that is, if an activity results in a CPA that is greater than the average transaction margin, then it is unprofitable and is resulting in you losing money. Clearly, this creates a ceiling on all of your channels - they will all have a point at which you have to stop. For example, in paid search, this would limit your bid value.
However, incorporating lifetime value gives you more scope for investment. This is relatively straightforward to explain to the financial control part of your business - you acquire customers at a loss, but you make money on them in the long term. This means that you can invest more and grow more quickly.
There are some things to look out for, however.
You may want to limit your payback window to a year (or two, or three years). This creates a balance between growth and profitability
If you are using the full lifetime value, leave yourself a profit margin. If you spend up to the full lifetime value in acquisition, then you are either resigning yourself to creating zero profit on these customers or hoping that you can increase the lifetime value over what you are currently achieving.
Make sure to account for retention costs somewhere in your calculations. While it is cheaper to retain customers, it isn’t free. If you have performed the LTV calculation yourself, you may well have included this already, but if your number is coming from a platform then it’s likely that it’s not there. This can easily erode your profitability if you’re not careful.
The cohort segmentation work that we talked about in the previous section is also useful for acquisition. If you are able to translate these cohorts into targetable segments, then you can use the variable lifetime value to increase or decrease your target CPA as appropriate. This can get quite complex so it’s worth testing by pulling out one or two key segments to start with. One way of doing this is with lookalike or similar audiences - both Facebook and AdWords allow you to upload customer lists and then market to groups of customers that are acting in similar ways. You should be able to track the results of these in your RFM and LTV analysis over time.
Overall, this type of analysis is fairly straightforward and uses data that is readily accessible, so there’s really no reason not to include it in your weekly and monthly reporting. As you track customer lifetime value over time, you will begin to see the trickle-down effects of business decisions as they are made, which is key in maintaining the health and growth of your company.