Customer Lifetime Value
Customer lifetime value (a metric of many names, including LTV, CLTV, CTV, and customer LTV) is so important to your eCommerce business that we’ve created this guide to provide you with a comprehensive round-up of what you need to know to understand and leverage this critical—and frequently misunderstood—metric.
Customer lifetime value is the metric to understand where to invest in your business for long-term success. In fact, if you want to remain a viable company over the long term, you must make customer lifetime value a focus area. It can be hard to do initially—we get it. But the reality is, if you don’t have healthy customer lifetime value trends, your business is not going to make it out alive.
Customer lifetime value is important enough that Venture Capitalists use it as a key indicator when evaluating potential investments. They look to LTV to understand a company’s health and answer questions such as: could this currently profitable company be in a slow, nearly undetectable decline? When will this early-stage business be profitable?
You may be thinking: we’ve managed things fine to this point without really caring too much about customer lifetime value—we’re growing, we’re profitable—so, what’s the big deal? Think of it this way: if data is like fuel, customer lifetime value data is like rocket fuel. Brands that focus on tracking and working to increase customer lifetime value see more explosive business growth and accelerated time to profitability.
Here’s what you’ll find in this article:
- Demystifying customer lifetime value (what is customer lifetime value?)
- How to calculate average customer lifetime value
- Customer lifetime value visualizations are your best friends
- What customer lifetime value visualizations tell you about your business
- What is LTV:CAC? Why is it important?
- How to leverage customer lifetime value for your brand
- Predictive customer lifetime value
Demystifying customer lifetime value
What is customer lifetime value? There’s confusion around it because you may see it calculated in a variety of ways. Some are just plain wrong, and some ways are more useful than others. Let’s take a look at some of the issues.
In a nutshell, customer lifetime value tells you how good you are at retaining customers who purchase more than once. It encapsulates what customers do over a period of time that results in profit for your company. Therefore, it is a profitability metric.
Customer lifetime value is not total sales or predicted sales value. Respectively, these metrics are lifetime revenue (LTR) and predicted revenue. Many companies end up relying on these metrics without realizing it because they don’t understand how to calculate customer lifetime value.
Even when people understand that customer lifetime value isn’t the same as lifetime revenue, they still calculate LTV incorrectly. Compounding the confusion is that the incorrect way to calculate LTV is generally accepted in the industry—to the detriment of eCommerce brands everywhere.
Many people calculate customer lifetime value as “revenue minus product cost.” The problem with this approach is that it does not provide an accurate picture, and can be misleading when trying to understand how much you can invest in growth. If you think that you are going to make $100 in profit from the average customer over a 12 month period, when you’re actually only making $75 in profit that greatly impact how much you can afford to invest in marketing.
But what is it, really? Customer lifetime value is gross margin per customer over their lifetime with your brand.
Gross margin is what’s left after you subtract your landed cost, or what it costs you to manufacture (product cost), ship to your warehouse (freight costs, taxes, duties, insurance), and deliver to the customer.
Timeframe is everything with LTV
When someone asks you, “What’s your LTV?” your answer should not be a single number. Because there’s an inherent time component in the calculation, and the answer can change over time, you always need to provide context. A correct counter-response to that question would be, “For which group of people, and at what point in time?”
After that, you can answer the question by saying something like, “Among customers acquired last year, our 1-year LTV is $40, and our 3-year LTV is $90.”
How to calculate (average) customer lifetime value
Customer lifetime value is time dependent. Therefore, you calculate customer lifetime value for a particular time period. The time period you choose should be specific to your business and take into consideration factors like frequency of purchase and seasonality. Standard windows many businesses use to measure customer lifetime value are 6, 12, 24, and 36 months.
We recommend a two-step customer lifetime value formula to calculate average LTV. First, calculate your gross margin for the specified time period (don’t forget to include landed cost!). Second, use gross margin to calculate customer lifetime value, as illustrated below.
However, the number (or numbers) that you end up with should not be the end of the customer lifetime value story. Calculating average customer lifetime value is only a snapshot and slice of the LTV story.
To really dig into it, you need to see trends by way of graphs and other visualizations.
Customer lifetime value visualizations are your best friends
We believe the most useful representation of customer lifetime value is not as a stand-alone number (even with context) but as visualizations: specifically, with graphs. A graph gives you the business-critical information to see how the value changes over time.
Over time, you want to see an increase in customer lifetime value. In the example below, you can see a positive trend for this brand’s LTV.
LTV visualizations allow you to quickly understand what's going on with your business. When you are calculating customer lifetime value manually, you may, for example, assume a standard percentage to calculate gross margin across all your products. While this will give you some useful information, not knowing true gross margin at a product level prevents you from gleaning insights to inform more effective (and scalable) pricing and marketing strategies, such as for promoting higher margin products. This is just one example of how if one portion of this calculation is off it can greatly impact the takeaway.
At Daasity, we aggregate all your eCommerce data in one place, automatically update it every day, and provide these out-of-the-box LTV visualizations for you to assess your brand's performance.
What customer lifetime value visualizations tell you about your business
With a clear understanding of your LTV through visualizations, you can easily answer a number of questions. For example: are our customers profitable? Are they profitable enough compared to their acquisition cost? Is our LTV trending up or down? Are our more recent customers better or worse than customers we acquired last year?
Beyond average customer lifetime value, there are ways to segment on an LTV basis that you can leverage in your business. We recommend using visualizations to look at segments. Visualizations need context to be truly valuable, and for that, you need to compare several curves on a single graph to find the golden nuggets. Below are three LTV visualizations/breakdowns to track (and that Daasity provides):
- LTV by time since first purchase
- LTV by first product (or SKU) purchased
- LTV by marketing channel
LTV by time since first purchase: A great way to segment customer lifetime value is based on how long it has been since customers’ first purchase. For this brand, LTV growth significantly slows down by the 2 year mark.
Insights: Evaluate customer behavior in the three months after acquisition (no matter what month or year they were acquired). For example, what’s the 90 day LTV of customers the business acquired 1 year ago versus 3 years ago? Are you getting better or worse with customer retention? To avoid this type of trend, it’s important to stay on top of repurchase rates and AOV in order to keep customers engaged and buying for as long as possible. That first three months is critical to determining their long term LTV value.
LTV by first product (or SKU) purchased: It’s also useful to break out customer lifetime value at the product level, as you may find that customers who buy certain products or categories of products tend to stick around longer and purchase more than average. If you can understand some of the characteristics these customers share, you can tailor your marketing to acquire similar customers. You also may want to promote those products/product categories more heavily.
Insights: Analyze customers who bought product X compared to those who didn’t to help you determine which products/product categories lead to higher LTV for a specific time period. With this data update your Acquisition funnel to target customers who buy that product first. Acquiring customers that lead to a higher LTV over time gives you more bandwidth to more heavily invest in new customer acquisition and accelerate your growth.
LTV by marketing channel: Breaking down customer lifetime value by marketing channel can be insightful because you may find a trend that may change how you allocate your budget—specifically, to channels that deliver more profitable customers.
Insights: You might find that customers acquired through Channel A actually spend more money throughout their lifetime than customers acquired through Channel B. Therefore, while Revenue and ROAS numbers might make Channel B look more successful it’s actually the Channel A customers that are worth the greater investment. When you identify the product and channel combinations that lead to a higher LTV you can re-architect your acquisition strategy around what will drive the highest long term value for the brand.
You can unearth a wealth of information for your business by using segmented data to calculate customer lifetime value—and you can basically segment customers however you wish to explore different questions around LTV.
Also, no matter how you segment, when analyzing the curves, always be thinking: what did we do differently during this time that may have impacted the customer and increased or decreased their LTV? Did we raise prices? Launch a special email campaign? Launch a successful SMS campaign? These customer lifetime value visualizations can be very powerful in helping you determine what’s working to keep customers coming back to purchase again.
What is LTV:CAC? Why is it important?
The ratio of customer lifetime value to how much you spend to acquire a customer (i.e., customer acquisition cost, or CAC) is a critical metric to know and monitor. It indicates whether your business is earning enough money to offset your acquisition costs over time.
The challenge is that your CAC will keep increasing over time, as advertising costs (along with other costs) go up, so you will have to constantly work to increase customer lifetime value to maintain a healthy LTV:CAC and a profitable business. A young company may not be profitable in its early days. However, with healthy enough numbers, financial partners tend to be more willing to infuse cash to help the company become profitable sooner.
An average benchmark for a healthy ratio is above 3 after three years. This means that customer lifetime value is at least three times greater than CAC. Ideally, the LTV:CAC ratio should improve over time. For more information, here's our LTV:CAC explainer video:
How to leverage customer lifetime value for your brand
Customer lifetime value doesn’t represent the pulse of your business (for more about checking your company’s pulse, read about the Daasity eCommerce Metrics Six-Pack), but you can consider it the health metric. Unlike the six-pack metrics that you want to check daily, customer lifetime value trends typically change slowly over time and you can review them less frequently.
We recommend reviewing customer lifetime value trends on a monthly and quarterly basis. If you do see big changes (i.e., negative ones), it’s time to review your customer retention strategies and determine what changes need to be made. Using data and knowing your numbers can empower you to test new acquisition and retention approaches to see if they positively impact customer lifetime value.
For example, analyzing customer lifetime value can help you explore questions like:
- Should we restructure how we acquire new customers based on which channels, offers, or products attract high LTV customers?
- Should we spend more on retention (e.g., free shipping, VIP events) versus acquisition (e.g., advertising, deep discounts) tactics?
- Should we cut budget for channels that don’t deliver the same quality of customer?
- Can we better optimize our paid media budget, e.g., use characteristics of our high-LTV customers to target look-alike audiences for Facebook ads?
- How can we ensure we’re profitable on first purchases, particularly if our products/services don’t have a high rate of repurchase?
- Does our welcome email series for new customers increase LTV?
- What are we doing for High Value Customers – special incentives, limited additions, experiences – and are they effective?
- Should we launch subscriptions?
To help you understand how to target your most profitable customers, check out this explainer video on RFM—Recency, Frequency, Monetary—scores and how Daasity can help you segment out your best (and worst) customers.
Bonus Section: What is predictive customer lifetime value?
This post so far has discussed calculating customer lifetime value using historical customer data. There’s another way to calculate LTV that you may hear about: predictive customer lifetime value.
Predictive customer lifetime value is a whole separate beast. It uses complex modeling to predict future customer behavior and profitability. Predictive customer lifetime value modeling may come into play for very young companies without a lot of historical customer data, for example, if they need to calculate customer lifetime value in order to get funding.
However, in our experience, for most eCommerce businesses, calculating customer lifetime value based on historical data gives them more actionable data to inform their strategy to optimize for a healthy business over the long term. While Predictive LTV is a great metric to understand how much value customers will create over a given period of time, historical LTV is a better indicator of when to send that next message to customers.
The more historical data you have, i.e., the more times customers have purchased, and the shorter timeframe you’re looking at into the future, the more accurate your LTV estimate will be.
The time to figure out customer lifetime value is now
We can’t overstate the importance of customer lifetime value trends and why you should look at customer lifetime value in different ways to help you find the insights you need to keep your business healthy over time.
The name of the eCommerce game is to acquire and retain your most valuable customers and optimize your efforts and (cut) budget for customers who will not have high LTV. Daasity helps make calculating and monitoring customer lifetime value much more streamlined and understandable, with visualizations that bring the data to life for teams. Interested in seeing your LTV trends? Contact us.