Like most people, I have a special relationship with my phone. It's always in my hand, but the truth is I mainly use it for email -- with an occasional indulgence in Facebook during rare free moments. Once I come home, we part for an hour when my son steals my phone to play FIFA, after which he goes to sleep and I reclaim my phone to catch up on the latest news.
With smart technology, advertisers have the ability to understand my location and my virtual and physical behavior -- essentially, when to target a particular campaign according to my daily routine and interests. If I receive a push notification at 11 p.m. about a new FIFA game while I am reading the news, then advertisers are missing their chance. My behavioral pattern has clearly indicated that someone plays a sports game on that device in the early evening, so that is exactly when the new FIFA app should be promoted.
Today's tech-driven advertising strategies must focus solely on the individual user -- pinpointing users based on their personal online habitats, profiling them, and analyzing their behavior through a continual process known as behavioral targeting.
Behavioral targeting has changed the way we advertise, giving us a greater ability to classify a user, understand their virtual behavior, and know when and where to target them on specific platforms. Until now, most advertising strategies have concentrated on profiling and targeting users who are most likely to download a product, but in order to optimize behavioral targeting, both advertisers and developers need to take it a step further and consider each stage of the user's journey.
Focusing on initial downloads alone is not enough
Data has proven that current behavioral targeting methods might motivate users to click and download, but this does nothing for retention, reengagement, and consistent monetization. Matomy's February 2016 survey of app developers showed that user retention, and therefore monetization, is lacking across the board. Eighty percent of app developers see less than 20 percent of users engaging with the app a week after installation, with 43 percent of those developers actually seeing less than 10 percent. Clearly, there is room for improvement.
Today, media companies have much greater access to user data analytics, but most of this information is being underutilized. Advertisers should leverage learnings from one channel to another and gain an understanding of app-specific user behavior, especially high-paying users.
This can be done by profiling users based on hundreds of carefully selected parameters for a campaign, varying from age and hobbies, to how they travel. Once you have determined the attributes of your high-paying users, you can then identify "lookalikes" with similar profiles to expand your user base. This is where data and smart technology come into play, enabling advertisers to target each user with a personalized approach. Cutting-edge ad tech can be optimized by considering how users engage with a product, first by analyzing both their virtual and physical behavior and then offering them targeted advertisements (based on their activity) to boost retention.
High yield turnovers through high yield technology
When it comes to advertising, we have already seen the game-changing impact that tech has had on the industry, specifically in maximizing downloads and purchases. By using data to identify high-paying users and their lookalikes, and then utilizing smart technology to retarget those users throughout their journey with timely and engaging promotions, companies can turn every interaction into a revenue-generating opportunity. At the same time, users benefit as they are only being shown relevant offers instead of streams of irrelevant and often annoying ads. Media companies already have the data and the smart technology -- now they need to harness it through behavioral targeting across the user's entire journey.