Customer Lifetime Value, commonly referred to as LTV, CLV or CLTV, is one of the most important metrics for any consumer brand. Bringing in new customers usually requires a lot of investment. By measuring your LTV along with your Customer Acquisition Cost (CAC), you can determine how long it will take to amortize your investment. LTV goes far beyond the initial purchase a customer makes. It measures how valuable a customer is to your brand throughout their lifetime. This article guides you on how to calculate LTV right and where to find different LTV views in RetentionX.
How to Calculate LTV
Before you can maximize your LTV, you need to know how to calculate it accurately. LTV is different from total revenue as it should always include product cost, and has nothing to do with predicted revenue per customer as it's based on historical customer data instead of estimates. Many brands often inadvertently rely on these metrics because they do not have a clear understanding of how LTV is calculated.
LTV tells you how successful you are at retaining customers who buy more than once, and although it does not indicate true profitability (i.e. net profit), it is a necessary profitability metric to guide decisions. LTV reflects profitability at the CM1 (Contribution Margin 1) level, which is calculated as net revenue (after product returns) minus cost of goods sold (COGS).
LTV = ∑ Net Revenue - ∑ COGS
It's all about the timeframe
Brands are often asked "What's your LTV?". This easy sounding question should never be answered with just a single number. LTV is time-dependent! Because there's an inherent time component to the calculation and its tendency to evolve over time, context is key. A correct answer to this question would be something like, "After the first year, the average LTV of our customers is $250".
Why? Let's take the example of Anna and Michael. If we compare the LTVs of both customers, we would quickly agree that Michael is the more valuable customer with an LTV of $1,261 compared to Anna's LTV of $893.
But with this comparison, we miss the context! By assessing their current LTV, we miss factors such as purchase frequency and customer lifetime.
If we compare the first order dates, we would see that Anna placed her first order only 3 months ago, while Michael became a customer 8 months ago. So it might be quite unfair to compare them, as Michael simply had more time to place more orders and thus generate a higher LTV. To solve this problem, it is important to make the data comparable by always looking at the same time frame. For example, if we compare the first 90 days of both customers, we see that Michael had an LTV of $427, while Anna already had an LTV of $893. So even though Anna's current LTV is lower than Michael's, she should be considered a high-value customer.
The same logic should be applied to your overall LTV. By simply averaging all of your customers' individual LTVs, you would be giving the LTVs of new customers the same weight as those of loyal customers, which would likely lower your overall number – especially during scaling periods when you're acquiring a high volume of new customers. Default time frames used by consumer brands to measure LTV are 1, 3, 12, 24 and 60 months. RetentionX provides these exact breakdowns of LTV:
- LTV 30 Days
- LTV 90 Days
- LTV 1 Year
- LTV 2 Years
- LTV 5 Years
Where to Find the LTV in RetentionX
In the first step RetentionX calculates the LTV per customer. Under Customers > All Customers you'll find the LTV per customer and if applicable the LTV breakdown after 1, 3, 12, 24 and 60 months.
Using individual records, RetentionX calculates the average LTV for your entire customer base. Under Customers > Daily LTV, you'll find a breakdown of the average LTV that includes all customers who have completed the lifetime under consideration, e.g. 1 year. This report allows you to answer our starting question of what your LTV is, but time-dependent. As this value evolves over time with changes in customer quality, the report illustrates the development of the LTV since you started using RetentionX. More details about this report can be found here.
Understanding influencing factors
In addition to average customer lifetime value, RetentionX provides other ready-to-use LTV analytics to help you understand the drivers of customer quality, such as:
- Customer Cohorts by LTV: Find out if your more recent customers are better or worse than those you acquired last year. This report is perfect for measuring short-term changes in customer behavior that are impacting your overall LTV. Learn more here.
- LTV Cohorts: Quickly understand if you're able to improve the quality of your newest customers. Learn more here.
- Product LTV: Reveal hidden champions of products that attract better customers by understanding the LTV of customers based on the first product purchased (LTV of New Customers). Learn more here.
- LTV by Location: Identify the locations of your highest LTV customers to optimize ad geo-targeting. Adjust your bids and budgets to focus on the most profitable cities. Learn more here.
- LTV by Marketing Journey: Track which marketing channels convert the most valuable customers, optimize your marketing spend, and align your budget with the channels that deliver the highest return on investment. Learn more here.
- LTV by Incentive: Learn which offers and discount codes work best to retain customers and maintain profitability. Learn more here.
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Revenue Contribution of Top LTV Customers: Understand the importance of your most profitable customers by analyzing the share of total revenue contributed by your top LTV customers. Learn more here.
Bonus: Customer lifetime value vs. customer loyalty
We often hear from brands that if a customer has spent a lot of money with their brand, they must love the products, buy often, and be extremely loyal to the brand. This seems to make sense, but it may not be true. Here is why: A customer may have an incredibly high LTV because they were once a loyal and active customer, but if they hadn't bought from you in a few years, would you still call them a loyal customer? Probably not!
So to understand customer loyalty, you need to consider recency and frequency (in addition to monetary value). This is why we recommend using RFM Analysis to evaluate customer loyalty. Learn more here.
Not using RetentionX yet?
Read our full blog post about LTV analysis for Shopify stores here.
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