Your Customer Lifetime Value will guide you

Understanding your Customer Lifetime Value (CLV) is key to determining a value-driven marketing mix. But how do you calculate it, and how do you apply it to your strategy?

You might know the Pareto principle: 80% of revenue comes from just 20% of customers. Identifying high-value customers helps companies find more of them and avoid over-investing in the others.

How do you calculate the Customer Lifetime Value?

Firstly, determine what the value is based on. For an e-commerce site, use revenue. For lead generation websites, use the conversion rate of leads to paying customers and then the value of a paying customer.

Depending on your available data, there are two different ways to calculate your CLV. Many look at the turnover during a certain period. However, you can also calculate it on the value-add margin, the profit you make after production and operational costs. 

You’ll need to choose a time period with sufficient data so that seasonality and other factors won’t distort the picture. The time period you choose will also depend on the sector.

Measuring CLV with Google Analytics

Google Analytics tracks and analyses visitor behaviour on your platforms and, with some minor tracking setup tweaks, can help calculate your Customer Lifetime Value (CLV). To start, identify unique users using client IDs or user IDs generated by your web platform's backend or by importing IDs from your CRM system.

How will you use the Customer Lifetime Value?

The next step is to determine how you want to use the CLV. Are you going to rely solely on historical data, decipher customer segments or use it to predict the future based on a statistical model?

To decipher customer segments, use the historical CLV to map your customer value with behavioural variables, dimensions or RFM models. This reveals segments and look-alike profiles for targeting and converting.

Once you’ve segmented your customers, you can then personalise content, advertisements, emails, web platforms and in-app experiences to meet them where they are, with the information they need.

You can also use CLV to make predictions for future revenue and margin. An additional variable that can strongly refine these insights is the historical and current churn ratio, the customer loss rate.

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