Customer lifetime value


Customer lifetime value (CLTV or sometimes LTV) is quite simply the value or profit attributed to a customer for their entire customer lifecycle. This can be relatively simple to calculate in some businesses and incredibly complex in others. Either way, one thing is true: there are many factors that influence it and many levers that can be pulled to alter it. Cost per acquisition (CPA) has long been used as a key metric in marketing and especially so in digital marketing due to tracking technology and the transparency of data. However, this has certainly been criticized as too simplistic a view. For example, if you know that a customer spends $100 buying a product from you that has a margin of $50 and it costs you $40 to acquire that customer then you can be happy that you have acquired them profitably.  If that customer then leaves and never comes back then we have a simple model. If, however, the average customer comes back another 3.2 times and phones your call centre twice per purchase then you have additional income and expenditure for this customer that is not taken into consideration. The CPA model continues to be used in channels such as affiliate marketing as it enables businesses to remove the risk of cost-per-click payments where conversions are not guaranteed. It would be far too complicated in most instances to ask affiliates to abide by your CLTV model as so many of the variables would be out of their control. CLTV can be used to determine which customers are the most profitable and to define segments based on this, which can then be targeted appropriately.

Calculating CLTV

There are several different ways to calculate CLTV but we focus on the simple approach. I would recommend understanding the different models in more detail to fully appreciate the complexities of CLTV and ensure you have a model or combination of models that is appropriate for your business. In order to calculate your CLTV using the simple method you need to have an understanding of the following two variables: 1) number of periods that a customer remains with you (customer lifetime); 2) average margin per customer in a period.
In order to help understand these variables there are some common factors that need to be understood and these are therefore also the levers that can be pulled to improve your CLTV:

  • Length of customer lifetime:
  1. CRM programmes
  1. member-get-member schemes
  1.  loyalty schemes
  1. service levels
  • Average margin per customer:
  1. repeat purchases
  1. cross-selling and up-selling
  1.  returns and refunds
  1. pricing and discounts
  1. operating costs
  1. conversion rates
  1. segmentation
The formula in simple terms is therefore as follows:
CLTV = Lifetime × Avg Margin
To give an example of this we can look at a retailer. This particular retailer manages to attract each customer to its store 3.9 times per week on average and those customers spend $21.69 on average during each visit. We therefore know that the customers are spending $21.69 × 3.9 = $84.59 per week. We want to understand our CLTV in terms of years so we can simply multiply by 52 to get an annual customer value of $4,399. We know that each customer has a profit margin of 10 per cent so we know that our profit per customer is actually $439. On average we know that customers stay with us for 15 years and so our CLTV is $439 × 15 = $6,585. That gives us a target figure to acquire customers. We know that we can spend up to $6,585 to acquire a customer over their lifetime.

What does this mean for digital marketing? 

There are many models in digital marketing that are forced upon us. As mentioned above there are cost-per-acquisition and cost-per-click models that are very common. There are also cost-per-impression (sometimes costper-mille), cost-per-action and cost-per-lead models, amongst others. Whilst we are forced to use these as payment methods it is often all too easy to relax into using these as the key performance indicators (KPIs) for running the channels. CLTV is not something that can be implemented purely within one area of your business, but if this model is appropriate then it should be integrated within digital marketing as much as anywhere else. Digital marketers are blessed with exceptional amounts of data so we have the opportunity to understand our customers and the variables involved in greater detail than other areas of the business. This opportunity is golden and should not be wasted.


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