Do you lie awake wondering, ‘How valuable is each new user I acquire and will I recoup my CPI?’ No? Then, you’re definitely not working in User Acquisition! For those sleepless souls who often ponder this, we feel your pain. However, we’ve been looking into the situation and have some advice: Stop thinking of your users as average.
Historically, new user acquisition has focused on the notion of an average user value, because other than the “wait and see” approach, there hasn’t been a way to accurately understand new user LTV. As a result, marketers are forced to make blanket acquisition assumptions and assign all users an average LTV. Unfortunately, while you’re forced to assume an average user value, most ad sources supply a mix of user types whose behavior and spend fluctuate wildly.
At Playnomics, we analyze terabytes of user behavior and it’s easy to see all the ways users differ. Some users come back over and over but never spend, others come once and spend big, some spend regularly, and others only spend when prompted. Clearly, not all acquired users are equal and neither are their LTVs. So, now what?
Instead of assuming average LTV, predict it. Here’s how we do it.
By analyzing user behavior on an individual basis, we train our predictive algorithms to identify various behavioral patterns and match these patterns to different levels of spend. To predict new user LTV, our algorithms match a new user’s behavior patterns to their likeliest level of spend. In beta, we’ve been able to predict the actual spend of users with over 75% accuracy within a few days after acquisition.
For a clear example, let’s consider two (hopefully) fictitious ad networks: Super Ads and Duper Ads.
We’re about to buy with Super Ads at $1 CPI, but we run a predicted lifetime value (PLTV) analysis and see that on average each has a PLTV of $.75. Great, they’re spending, but for each acquired user we lose $.25 – not a great long-term business model! We apply the same analysis to users from Duper Ads at $3 CPI and find that they have an average PLTV of $4. While much more expensive to acquire, these are the customers that are going to bring home the ROI.
Let’s assume a $6000 budget. Without PLTV, let’s say we would divide our budget between the two networks and wait 30 days to see how much users actually spent, and would have earned a net $250. With PLTV analysis, we can quickly see users’ PLTV (let’s go ahead and assume we do it in one day) and shift our budget to the higher-ROI Duper network. As a result, our revenue is $2,000, a 700% increase!
Your users aren’t average and you know that, but you’ve also been left with few choices when it comes to determining LTV. By understanding your users’ unique behavior you can determine their predicted spend, calculate ROI by channel, reallocate spend for greater returns, buy with confidence, and finally get some sleep!
Becky is the Senior Content Marketing Manager at TUNE. Before TUNE, she led a variety of marketing and communications projects at San Francisco startups. Becky received her bachelor's degree in English from Wake Forest University. After living nearly a decade in San Francisco and Seattle, she has returned to her home of Charleston, SC, where you can find her enjoying the sun and salt water with her family.