The Marriage of Lifetime Value & Likelihood to Buy
In my last post, I discussed the importance of LifeTime Value (LTV) along with the missing piece many data-driven marketers forget, returns. For this follow up piece, I wanted to take a moment and discuss how marketers can take direct action by levering LTV and a customer’s likelihood to buy.
Since we’ve already discussed LTV, let’s take a moment to discuss propensity models, also known as a customer’s likelihood to buy. While we can never know for sure who is going to buy next, in the last few years there have been big improvements in RFM data in predicting the likelihood of purchase. However, Predictive Analytics solutions like AgilOne have been pushing the envelope by using ‘look-a-like’ modeling to predict propensity to purchase, often with game changing results.
With this model in place, you can categorize your customers from high to low deciles in regards to their propensity to buy. Pretty fantastic stuff, I know!
Now let’s take a look at a simple way we can actually put LTV & Likelihood to Buy in action.
We’ve all read fantastic blogs from email marketing evangelists like Loren McDonald discussing the benefits of an “onboarding program” vs. a simple welcome email. It’s all about leveraging rich customer behavior to guide multi-touch campaigns.
Similarly, we can leverage LTV and propensity models for just about any type of campaign. Some of my favorites are intelligent new customer welcome programs and preventative at-risk campaigns. In both of these campaigns, we are leveraging not just a customer’s LTV, but also their high or low propensity to buy along with recent web/email behavior (such as last product browsed).
If we know someone has a low propensity to buy, we can assume that they may need a higher discount rate than an active customer with a very high propensity to buy.
As you can see from the images below, by having a 360 view of my customer in one location, and having the ability to drive direct marketing action, I can create a much more data-driven message leveraging LTV and Likelihood to buy.
On average, we’re seeing these data-driven campaigns increase rebuy rate by up to 15%. This type of campaign is just one of many data-driven marketers are using to improve acquisition, growth, and retention. Traeger Grills is a great example of a data-driven team leveraging LTV in their marketing approach.
So how are you leveraging your customer data to drive your business forward?