Customer lifetime value (LTV) is increasingly mentioned as one of the most crucial analytical metric for marketers. The LTV of a customer is a more complete picture of a specific customer’s value and profitability than any metrics based on just his/her most recent purchase. LTV analyses can help data-driven marketers understand not just the value of customers, but also the long term success of acquisition channels, products and content strategy.
That's why I find it appalling when I see more and more marketers ignoring the cost of returns from their calculation of a customer's LTV.
Returns are significant to the calculation of Lifetime Value. Excessive returns can significantly alter a customer’s revenue and profitability profile. As mentioned in studies and news segments ranging from Charlotte to Las Vegas, 'return-a-holics' cost companies up to $375 billion each year. Lifetime Value without returns is like… exactly how it sounds!
It’s thinking a customer will spend $1,000 with your brand based on her purchase activity, but not realizing she will be returning half of her purchases. It’s thinking you have a shop-a-holic on your hands when in reality you have a return-a-holic.
Generally, this tunnel vision is due to siloes of data and/or a limitation in Predictive Analytics solutions. Many software solutions attempt to offer deep insights into a company’s products, transactions, and customers. But if the solution cannot successfully tie together ALL relevant data points and layer in the right business intelligence metrics (such as returns) daily, then its LTV calculations will yield incorrect results. This can be worse than not using LTV at all.
So, do your homework! Ask the right questions and know what to look for in your marketing analytics tools. Download our ebook on 3 Common Data Driven Marketing Mistakes below: