When it comes to calculating the lifetime value of your customers, we like to say that there is a simple way, and then there’s the right way. Calculating lifetime value can be as simple as finding a 30 day average; but the true value of calculating out the lifetime value of your customers is to make it actionable.
Calculating the lifetime value of your customers is not about just getting a number. The reason that any business wants to know how much their customers are worth is so that they can impact it.
To start, we’ll show you how to calculate lifetime value the simple way, and then we’ll dive more into the ways that you can calculate it for action.
The simple way to calculate lifetime value is to take the average order value (AOV) and multiply it by the average purchases per client.
So, the simple calculation looks like this:
AOV * # of purchases = LTV
The average number of purchases per client can be hard to track down though, so many people break down LTV into 30, 60, and 90 day LTV to make it a little easier to calculate and a little more actionable.
Those calculations look more like this:
AOV * # of purchases (X days) = X-day LTV
This calculation is already more helpful, because it can show you repurchase and drop-off timelines. You can start to see when you need to work on re-engaging and retargeting previous purchasers.
In order to truly impact the lifetime value of your customers, you need to be able to segment out your customer LTV into different groups to figure out what differentiates your highest LTV customers from your lowest LTV customers.
The more granular and specific your calculations for LTV get, the more actionable they get. That’s why we like to break down LTV by a multitude of variables, so that we can examine it from every angle and make sure that we’re not missing out on anything that could help our business.
LTV by first purchase month
In addition to breaking down LTV into 30, 60, and 90 day calculations, we like to segment customer LTV by first purchase month.
This allows us to see the impact that our efforts have over time, as well as to pinpoint areas where we performed exceptionally well or poorly.
With that in mind, we can then drill down into what actions we took during those time periods and either emulate or avoid those tactics.
For example, if we sponsored a podcast, we need to see if there are any other podcasts that target similar audiences that we could sponsor.
LTV by first product purchased
The next way that we segment LTV is by the first product purchased by the customer.
This allows you to see what products are most likely to drive repeat purchases. For example, your 30-day supply may drive much higher repeat purchases than your single serving product.
One of our clients, JavaPresse, used this metric to boost their LTV dramatically:
They were looking for ways to improve the lifetime value of their customers and discovered that customers who bought a coffee mug with their initial purchase had a much higher LTV and repurchase rate than those who just bought coffee.
This led them to update their marketing to drive more customers to purchase a mug with their initial order, and they were able to increase the number of mug purchases and drive up their overall LTV.
LTV by discount code and traffic source
Other ways that we calculate and segment LTV is by discount code used and traffic source.
The benefit of breaking down LTV by discount code is that you can see if a discount strategy drives long-term benefits for the company, or if it just attracts bargain shoppers.
We had one client who decided to offer a free shipping discount code to see if they could migrate some of their Amazon customers to purchase directly on their site. They assumed that they could absorb the up-front costs and break even on the repeat purchases.
By looking at the data over time, they found that they were attracting Amazon customers, but that those customers were not very loyal, had a lower LTV than other customers, and had increased costs because of the shipping discount. As you can imagine they quickly discontinued that discount, and focused on attracting more loyal customers who were willing to pay the extra up-front costs.
Additionally, we like to calculate the lifetime value of customers based on the traffic sources that led to their conversion.
We have had a multitude of clients discover that some of their clients with the best lifetime value came from their lower-tier traffic sources. Oftentimes despite driving fewer orders these forgotten traffic sources can drive some of your most valuable customers.
One of the things that we didn’t touch on in this article, but is important to mention is that when calculating lifetime value, you need to pull data from all of your different ecommerce platforms. We have had many clients come in believing that their clients were repurchasing at a certain cadence, only to discover that the customers were migrating and purchasing from different platforms and sites.
It is vitally important to understand the true lifetime value of your clients so that you can make informed, educated decisions for your business.
In summary, the best way to calculate the lifetime value of your customers is a way that allows you to take action. However you want to segment or slice and dice your lifetime value data in order to have it make the most sense for you is the best way to do it; above are just some ideas on ways that we have calculated LTV in order to scale businesses.
If you are looking for a simple, automated way to calculate your customer lifetime value, you’re in luck! Praxis specializes in building powerful, automated business intelligence dashboards that connect all of your systems and give you accurate, actionable lifetime value calculations.