# Why You Need to Calculate Customer Lifetime Value for Your Ecommerce Business, and How to Do It

Businesses that make good use of customer data thrive in the market, especially when increasing customer acquisition is a priority for 49% of companies. That means that Customer Lifetime Value is information that can turn out to be very useful when making new strategic plans for the next quarter or the next business year. Let’s see what it’s all about.

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## What customer lifetime value is and why it matters

Customer Lifetime Value (also called, CLV, LTV or CLTV) is a metric to calculate how profitable a customer is to your business. In other words, it tells you a customer’s value.

There are various reasons why CLV is important:

- It helps a business to understand the best customer retention strategy and answer the question: What is the value of retaining customers vs. acquiring new ones?
- It helps you understand which customers are more valuable (e.g. could be a metric to decide who to send special “fidelity” offers or discounts to make those customers feel loved and stay even longer with your business — especially if your business is a SaaS)
- It gives a good indication of how well-targeted your marketing is to your demographic(s).
- It indicates whether there is a relation between recurring customers and a change in marketing. With the help of CLV, you can replicate that asset.

It’s no wonder that customer lifetime value can be, all considered, a critical metric to your business.

## Historic and predictive CLV

### Historic customer lifetime value

Historic CLV is about an individual customer and all their purchases at your business. It is the sum of all their past purchases multiplied by the margin/expenses:

**(Transaction 1 + Transaction 2 + … + Transaction N) x GPM**

`(Transaction 1 + Transaction 2 + … + Transaction N)`

is the total purchase amount`GPM`

is the Gross Profit Margin – the difference between the revenue and the customer acquisition cost, CAC. It is expressed as a value between 0 and 1.

We multiply the sum of transactions by GPM to get the net lifetime value for that customer.

For example, you are a florist, and your customer purchases flowers for six months in a row for a total of $200. This is the sum of transactions made by this specific customer. You spent $10 to acquire this customer, which is 5% or 0.05 of $200. So, the GPM is 1- 0.05 = 0.95. To calculate lifetime value, multiply $200 by 0.95 and find out that the customer is worth $190.

### Predictive customer lifetime value

Predictive CLV instead analyzes transaction history and behavioral patterns to predict how much profit a customer will generate over time.

**=(AMP x APV) x ACL x GPM**

`AMP`

is the average number of purchases per month`APV`

is the average number of all purchases`ACL`

is the average customer lifespan (in months)`GPM`

is the gross profit margin

## How to calculate predictive CLV

While calculating historic CLV per single customer is rather simple, predictive CLV requires some extra calculation. So for the scope of this article (and the example we’ll introduce later), we’ll explain how to use the predictive CLV formula:

**=(AMP x APV) x ACL x GPM**

So to work out the formula you’ll need:

- Your sales data to calculate the average number of purchases per month (
`AMP`

) and the average number of all purchases (`APV`

). You can get this from your CRM or another database that you use. - The average customer lifespan (
`ACL`

) is the number of monthly transactions per customer. Again, your sales data will provide this information. For example, if a customer purchased for 6 months in a row and then stopped over a period of 12 months, then that customer’s lifespan is 6 months. - The gross profit margin (
`GPM`

) is the value that you can get from marketing and sales data. This is a percentage that indicates how much your business earns per customer, minus the average customer acquisition cost, calculated dividing all the expenses to acquire new customers by the number of customers. For example, your 10 customers bring $12k per year and your expenses for advertising are $200 per year. This means that the average customer acquisition cost is`$200/10 = $20`

; the average income per customer is $1,200. Divide your CAC by average income:`20/1,200=0.016`

(or 1.6%) and substract this value from 1 to get your gross profit margin.`1 - 0.016 = 0.984`

.

This calculation can be performed in a spreadsheet app like Google Sheets, which we’ll use in the example.

### How to import sales data into Google Sheets?

Google Sheets is a good tool to calculate CLV because it’s a cloud app and it’s portable. You can have your calculation handy whenever you need it.

To make importing your raw sales data into Google Sheets painless, you can use Coupler.io. Simply install the addon from the Google Workspace Marketplace and use it to import your file into Google Sheets.

Once you have installed Coupler.io, create a new spreadsheet in Google Sheets and go to *Add-Ons* -> *Coupler.io* -> *Open Dashboard.* There you can add and set up your importer, which you can then run from inside the Dashboard.

For our example in the section below, we imported a CSV file because our data is stored as a CSV file. But you can also import data from Airtable, Pipedrive, Jira and other sources.

### CLV calculation on a real-life use case

We finally come to the example of a small ebook retailer who’s been operating for a few months. The business owner wants to calculate customer LTV with 3 months of customer data. The sales data imported to Google Sheet with Coupler.io looks like this:

- Customer ID is a column listing 10 customers
- Three columns for the months (April, May and June) contain total amounts spent by each customer in each of the three months. (Note that in some months, some customers did not spend at all)

Now, to calculate the lifetime value per customer we’ll use the predictive CLV formula:

=sum(B2:D11)/30*F8*0.8

is the (`=sum(B2:D11)/30`

`AMP x APV`

) for 10 clients and 3 months of purchase data. Here we added the content of the 30 cells with purchase data and then divided the result by the number of cells (30). It’s worth noting that in our example, the invoicing system gives only the total of purchases of a customer in a month, so our AMP is either 0 or 1, meaning that the customer did not buy or did buy. A more explicit way to show (AMP x APV) is:`AMP = count(B2:D11)/30`

`APV = sum(B2:D11)/count(B2:D11`

).

- The average customer lifespan (
`ACL`

) is, in our example, anywhere from 1 to 3 months. To calculate it, we add the number of months each customer has purchased and divided it by the number of customers. We introduced this calculation in cell F8. Google Sheets COUNT function helped us count the cells containing numerical values (purchases):

=count(B2:D11)/10

`0.8`

in the formula is the gross profit margin (`GPM`

). It signifies 80% overall revenue against 20% of acquisition costs. As explained earlier, the GPM is calculated by subtracting the costs of acquisition (e.g. advertising) from the total revenue per customer. This calculation wasn’t done in the spreadsheet, as marketing data is external to sales data.

The CLV that results from the example calculation is $43. This means that each customer earns the small ebook retailer an average gross profit of $43.

## Different ways and formulas to calculate LTV

There are different formulas to calculate CLV besides the one we used in the example. Another version of the predictive CLV formula is the following:

`=(CUS X AAP) / TotCUS X ACL X GPM`

`CUS`

is the number of customers who spent a specific amount for their purchases`AAP`

is the average amount spent by all customers`TotCUS`

is the number of all customers`ACL`

is the average customer lifetime`GPM`

is the gross profit margin

This formula is a good option to calculate CLV if you are a SaaS with fixed subscription plans, and you know exactly, from sales data, how many customers you have on each tier.

Another helpful formula comes from Shopify, that provides the following way to calculate their customer value:

`= AOV x PF`

`AOV`

is the average order value`PF`

is the purchase frequency, defined as total orders divided by total customers

This formula is simpler than the predictive CLV formula we used in our example, as it drastically reduces the number of variables to calculate.

If you scour the Web, you’ll find different formulas to calculate LTV. It’s up to you, based on your needs and your computing skills, to choose the one(s) that work best. In any case, the results should be similar.

## Good and bad LTV for ecommerce

Ideally, you’ll want to increase your CLV to make higher profits. However, there’s no specific “good” or “bad” range for your customer value, as this depends on your business and your customers.

### How you can improve your LTV

The general rule of thumb is that added value always works to capture a customer’s attention and increase LTV. For example, the subscriber of a SaaS product would be easily enticed by a 50% off two month subscription in exchange for survey data to improve the product. But discounts aren’t your only option — here are some more:

**Scarcity**: Offer your product or service, or a part of it, to only a limited number of customers, so interested people are incentivized to sign up before it’s too late.**Limited time offers**: This includes perks such as free shipping offered for a limited time, especially if combined with other deals (e.g. Black Friday and Cyber Monday). This can attract customers because they’ll miss the offer if they don’t “act now”.**Subscription models**: These work better for increasing LTV than one-off purchases. They may also look more appealing to a customer than annual purchases, where you have to spend a large amount in one go. Subscription models work extremely well for SaaS and box-based businesses like Scribbler.**Upselling**: You can add more value to your customers by offering premium upgrades to your product or service; this is a way to rapidly increase LTV.

But there’s more that you should use in your ecommerce reporting.

### Improve customer retention to increase LTV

In terms of customer retention best practices, a newsletter is an absolute must-have. In fact, getting customers to sign up when they register for your service (or even later, for existing customers) may give you good chances to retain them and get more purchases/subscriptions if they get the latest news on your offers, discounts and limited-time opportunities. This is even more effective if your list is segmented so that you can blast your email out to interested customers. You will achieve higher open rates and better conversions.

Asking your customers whether they are satisfied with your service or product is also crucial. This will let you identify possible bottlenecks and understand how to improve user experience. For more on this, read our blog post dedicated to the Net Promoter Score calculation.

Certainly, increasing customer retention rates by 5% increases profits between 25% and 95%, so this is something you want to do if you want to increase LTV.

Another best practice, for customer acquisition and retention alike, is to leverage social media, where prospective customers are more likely to respond positively to offers and promotions. Due to effective social media management, you’ll be able to not only improve retention but impact customer satisfaction rates, brand awareness, and customer loyalty.

Last but not least, invest in good customer support. Customers who are well taken care of when they most need it are more likely to keep purchasing or renewing their subscriptions, developing loyalty to your brand.

## Calculating CLV is worth it

You don’t have to be a big company like Starbucks (with a CLV of about 25K) to start calculating CLV. As you can see in this article, the benefits outweigh the hassles and there are many easy ways to increase the lifetime value of your average customer. When you have your LTV data (especially if you’re a SaaS) you can finally take action to increase your sales and better promote your business. Here’s to your success!

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