It should be simple: if you bid higher and spend more, you’ll get more traffic, more installs, and more revenue.
If you work in user acquisition, the increasingly competitive landscape for new customers is a fact of life. Each day you compete with other UA managers to get your ads in front of potentially valuable users across a large network of channels.
But how does the cost of traffic translate into the quality of the users? How do you optimize spend to acquire the highest value users?
“The First Three/Wait and See Option”
One way to understand user value is to assume that users’ early spend informs how much they’ll spend in the their lifetime. Unfortunately, the majority of users acquired through marketing will not make a purchase on the first day, so estimating lifetime spend based on those first three days is not always an option. It can take weeks to see spend and months to determine ROI. In the meantime, you could be wasting thousands of dollars on sources that perform poorly and provide low quality users.
The Early Event Option
This approach requires UA Managers to identify early user events, such as completing the tutorial or reaching a certain level, to indicate a potential high value user. However, this approach is still nothing but a best guess, as customer lifetime values can change daily due to shifts in marketing mix, product changes, and customer demographic profiles.
The Predict and Profit Option
Ultimately our analysis led our data science team to the conclusion that there is a huge competitive advantage for marketers to understand user behavior and forecast spend as quickly as possible once the user has been acquired. So we got down to work. We’ve spent months analyzing user behavior and developing predictive algorithms to remove the uncertainty around a users’ predicted lifetime value.
By analyzing the behavior of every user in an app to understand what outlier markers correlate with high spend or desired action, we’ve built the analysis to be “self-learning”, meaning that it will refine based on changes in user behavior.
UA is difficult and the world of mobile marketing moves fast. To scale confidently and efficiently, having an accurate forecast for lifetime value is the only way to truly justify your marketing budget.
Playnomics is an integrated partner of MobileAppTracking. Read more about this integration here.
Author
Becky is the Senior Content Marketing Manager at TUNE. Before TUNE, she handled content strategy and marketing communications at several tech startups in the Bay Area. Becky received her bachelor's degree in English from Wake Forest University. After a decade in San Francisco and Seattle, she has returned home to Charleston, SC, where you can find her strolling through Hampton Park with her pup and enjoying the simple things between adventures with friends and family.
Unfortunately, John and his team of smart folks can only predict hi value user acquisition with about 70% (company claim) accuracy…again, predict…not guarantee…which is a little less accurate than your nightly, long-range weather forecast. You might learn a little bit more than you knew before…but hardly worth the time, aggravation and cost. He is trying to predict (incorrectly nearly 1 in 3 times) the future based on current data and historical behavior…fools gold in a market that moves as rapidly as mobile.