Insights
Head of Data Science
Analytics and Data Science
As businesses continue to optimize toward transaction revenue, eventually, they reach a plateau in performance. Targets become stagnant, and it becomes increasingly difficult to justify increasing media spending to drive business growth. This is often the result of a digital marketing strategy not being aligned with the fundamental growth drivers of the business – new customer acquisition, customer retention, and profit.
Customer Lifetime Value (LTV) is key to solving this performance plateau. LTV enables businesses to pivot their digital marketing strategy to invest in new customers and their most valuable customers to drive long-term growth. This heightened perspective is not visible when optimizing toward transaction revenue alone.
Once LTV has been implemented, you’re no longer restricted to investing based on a singular purchase. It may be that particular products are best suited to loss leaders or have unseen profitable growth value. Moving away from transaction revenue highlights the importance of looking at individual product metrics. Every product has a very different value to a company that cannot be illustrated via transaction revenue and can quickly become exploited when implemented into your wider strategy.
LTV calculations enable businesses to forecast the expected value of a new customer over a chosen period. Many companies often calculate what an average new customer is worth, although struggle to inject this into their marketing strategy. This results in a disconnection between business growth objectives and effectively optimizing their digital strategy.
Fundamentally, your digital marketing team can’t optimize towards LTV if there is no way for them to calculate it in their platform. For example, tracking in Google Analytics (GA) if a sale is via a new or returning customer or dynamically calculating LTV at the point of sale, and pushing that value back through into GA.
While you nurture a greater understanding of your audience, we recommend starting simple so you can work towards more complex and robust modeling solutions. Calculating the average new customer value and what percentage of sales are new customers allows you to instantly input LTV into your digital marketing strategy. You’re then able to sense check if you can invest more and grow through using LTV.
The next crucial step is to determine key factors that impact LTV and exploit them. Generally, we want to avoid sweeping averages because it removes the ability to find opportunities.
KPIs are only valuable when they enable you to segment data and find opportunities. Revenue enables investment into lower-funnel activity but becomes less effective as a KPI as you move up the funnel. The real power of LTV comes when you segment by product and specifically cart composition.
For example, the average 12-month LTV of a customer may be $80, but for customers who bought expensive shirts, it is in fact $140. That same LTV calculation will likely change again if you consider combinations of products bought together. Customers whose average cart value is high may ultimately have a higher LTV.
Your customers give you all the data you need to estimate their future value and score them by:
Determining LTV based on product and cart composition enables your digital marketing strategy to target new customer growth by product and enables targeted investment into your most valuable customers.
By applying machine learning, you can calculate the LTV of every customer based on their individual user journey. Machine learning enables you to value your existing customer pipeline and future customers who have shown interest but yet to purchase. We build these solutions for our most cutting-edge customers and believe this is the future of marketing to stay ahead of your competition.
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Insights
Insights
Insights