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Could “Customer Lifetime Value” Be the Metric You’re Ignoring?
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Table of Contents
Your Affiliate Marketing Longevity
In the affiliate marketing industry, cost-per-acquisition is king. It’s the metric that tells an advertiser how much it costs to drive a sale, and how much they’re willing to spend in order to close that sale.
But as affiliate marketing evolves, with the help of machine learning and advanced analytic tools, we now have the option to gain a deeper understanding into the customer journey. Did the customer purchase the upsell offered after the initial purchase? Did they subscribe to receiving your product for months at a time? Did they make a related purchase for a new product?
It’s this analysis of consumers beyond the initial click that’s known as Customer Lifetime Value (CLV), and it could be a key metric you’re not fully paying attention too.
Customer Lifetime Value
A simplified way to think about a customer’s lifetime value is the dollar amount gained from their “lifetime” of engagement with you. Depending on your product, this lifetime could be short or long term – analyzing your data will give you a good idea of what an ideal customer lifetime value is. How many customers made a repeat purchase? How long did a customer continue to stay receptive to your product offerings? Answers to questions like these will help you quantitate the average “lifetime” for your ideal customer.
A tracking platform can help you pull the necessary data on each of your customers by assigning all of a buyer’s purchases to an anonymous ID. Looking at an average of your customers’ behaviors will give you a good idea of what your ideal customer’s lifetime is, and thus make a huge difference in your marketing efforts.
Using CLV to Optimize Across Platforms
If you’re utilizing multiple affiliate platforms to drive traffic to your campaigns, customer lifetime value analysis is a great way to compare compare the performance of each platform. It’s one thing to know the amount of traffic you’re receiving from an affiliate platform, but it’s arguably even more important to know the quality of the traffic. Analyzing this CLV data will help you determine if your expectations are on target, too low, or too high. Whether the outcome is a positive or negative, it is much better to make decisions about your traffic with this evidence than flying blind.
Affiliate managers can see the true value of their entire channel and which affiliate partners drive the most loyal and profitable traffic. CLV can also help with creating promotions to reward those lifetime customers and encourage them to keep returning.
Applying Machine Learning to CLV
Thanks to machine learning advancements in affiliate marketing, customer lifetime value analysis can now be used to discover related products your customers are more likely to purchase. Let’s say a customer has already completed a purchase of one of your products. Based on analysis of an ideal customer’s behavior, you can now identify related items they will be more likely to buy.
This is called association analysis, and it’s a genius way for brands to proactively set themselves up for a greater chance of increased sales. You’ll know exactly what type of products to market together, or in sequence, to lead to the greatest chance of a customer making multiple purchases.
Moving Forward
Over time, your customer lifetime value data becomes a powerful thing. When it’s high, you know where to continue pushing your efforts. If it’s low, perhaps it’s time to reevaluate the products and partners you work with.
With the sheer amount of granular data affiliates and affiliate partners now have access too, there’s no reason not to focus on your business’ big picture.
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