# How to Measure the Lifetime Value of E-Commerce Customers

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Whether you notice it or not, you spend the better part of your day swimming in a deep pool of acronyms. Advertisers, in particular, have an extensive shorthand that, from a distance, would look like nothing more than alphabet soup to an outsider – ROI, CTA, CPC, and countless others. However, one advertising acronym can be especially insightful if properly utilized – lifetime value or LTV.

In fact, although not as ubiquitous as other metrics, LTV packs more insights into a single number than nearly any other online advertising measure. While it's lack of popularity – at least with respect to Return on Investment (ROI) – might be attributed to its multiple moving parts, LTV is a straightforward metric that can provide significant effects to longer-term conversions and, ultimately, the bottom line.

In other words, a simple and concise guide that takes a peek behind the LTV curtain will hopefully demystify it a bit and, more importantly, demonstrate how powerful the metric is in informing marketing campaigns and maximizing the conversions all brands crave.

### LTV in a Nutshell

In the simplest of terms, LTV is a metric that allows advertisers to calculate the estimated revenue generated by an individual customer or customer segment over a specific amount of time. LTV gives brands an accurate gauge on what each consumer is worth to the brand and, thus, can help those brands steer ad campaigns to hone their message and maximize conversions. Advertisers that regularly use LTV can always keep tabs on where they're getting the most bang for their marketing buck.

### A Simple Formula

Although, like most other digital marketing metrics, LTV can get somewhat complicated depending on how precise and revealing an advertiser wants it to be, a very simple equation will always lie at its root:

Average Order Value x Purchase Frequency x Estimated Customer Lifespan = LTV

For e-commerce businesses, most of the data needed to calculate LTV is readily available through their choice of analytics platform and can be used for individual customers or consumer segments.

Average Order Value is simply the average amount a customer spends per transaction. Obviously, as with any metric, bigger data sets create more accurate results so the more customers used in the formula, the more insightful the resulting data.

Purchase Frequency is calculated as the number of purchases a consumer makes per year. Therefore, if the average customer makes two purchases per month, the Purchase Frequency would be 24.

The Estimated Customer Lifespan is the murkiest of the bunch and can vary widely by industry or even from company to company. Basically, Estimated Customer Lifespan represents the amount of time a customer remains an active part of a company's consumer base. This typically includes customers that browse inventory and make at least semi-frequent purchases. If historical data is lacking, anywhere between one and three years should be a fairly accurate estimate for most newer companies.

### A Basic Example of LTV

The simplest of LTV examples are provided by subscription-based companies. For instance, let's say you run an online photography marketplace that allows users to download and use unlimited digital pictures per month. Each customer spends a flat $20 monthly fee on the subscription and historical data tells you the typical subscription lasts for two years. In this case, the LTV would be calculated as follows:

Average Order Value x Purchase Frequency x Estimated Customer Lifespan = LTV

$20 x 12 per year x 2 years = $480 lifetime value or $240 per year.

### A More Realistic Example

Of course, real-world applications of LTV will usually have a few more moving parts to them than the example above. Let's add a few more of those moving parts to make it a bit more realistic.

Instead of assuming each customer pays a flat subscription fee of $20 per month, let's look at two consumer segments from the same company – one that pays the basic monthly subscription of $20 along with à la carte purchases, against another segment that pays $30 per month for a premium subscription but already includes all of the available à la carte items.

Basic subscribers pay their $20 fee per month as well as, on average, three à la carte purchases per month at $1, $3, and $4 respective price points. The LTV would be calculated as follows:

Average Order Value x Purchase Frequency x Estimated Customer Lifespan = LTV

($20 + ($1+$3+$4)) x 12 months x 2 years = $672 lifetime value or $336 per year

Calculating the LTV for the premium tier customers is extremely straightforward but let's assume this particular segment is a bit more loyal and has a three-year Estimated Customer Lifespan.

Average Order Value x Purchase Frequency x Estimated Customer Lifespan = LTV

$30 x 12 per year x 3 years = $1080 lifetime value or $360 per year

### Interpreting the Results

Whether you compare the lifetime value or the yearly value of the two customer segments, both show that premium subscribers are more valuable to the company. Of course, this could change if margins or other variables are introduced to the calculation but, with all things being equal, this company would be wise to concentrate on engaging their premium customers because they generate more revenue per customer.

In a dynamic marketplace with seemingly infinite customer affinities and segments, LTV can lend a powerful sense of direction in maximizing a digital campaign's impact on a fickle e-commerce customer base with short attention spans and weakening brand loyalties. Using LTV as a guide, campaigns can be better informed, hone in on the segments that exhibit the most loyalty and revenue, and tailor the message to further strengthen bonds. For advertisers, LTV is a win-win with no downside.

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