Read thought provoking articles on the use of machine learning for improving mobile app marketing performance.

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Achieving Post-Install Optimization with Real-Time Bidding (RTB) and Deep Tracking

In recent years, social media has become a popular choice for mobile app marketing. Facebook, in particular, has been growing significantly in terms of its advertising footprint. With over a billion users, it’s not hard to see why an increasing number of advertisers gravitate toward this social media platform. And in many instances, Facebook does offer a scalable and cost effective app marketing solution. However, for app marketers looking to optimize any metrics beyond app install, Facebook might not be the best answer.

Several clients have mentioned to us that they’ve been frustrated with Facebook’s inability to assist them with optimization of post-install metrics. Through the social media platform, our clients have been able to tweak budgets and target ads to drive app installs at scale. However, when it comes to driving post-install key performance indicators (KPIs) such as registrations, bookings, retention rate, cost per returning user (CPRU) and return on investment (ROI), clients find Facebook’s app marketing capabilities to be limited. Platforms such as Aarki Encore, on the other hand, offer effective ways of conducting post-install optimization.

Leverage Big Data

Streamlined big data architecture plays an important role in optimizing for post-install goals.  As different advertisers have their own unique metrics, flexibility in the architecture is needed in order to perform big data analytics and implement optimization for a variety of metrics. Our big data architecture allows us to leverage historical user behavior to dynamically develop a user model geared for post-install optimization within seconds. As more data is gathered, the user model is automatically updated.

This flexibility enables our clients to set any post-install goals that will be automatically picked up by the machine learning algorithms. In turn, the machine learning algorithms in our platform will continually optimize the campaign for the set goals throughout the campaign duration.

Conduct Better Targeting

Machine learning algorithms in Aarki Encore can also help advertiser target users more accurately. With Facebook, the quality of users acquired is often unknown because the platform is mainly optimizing for installs. With Aarki Encore, however, advertisers can leverage their historical data and learning from prior campaigns to develop audience insights. Combined with other relevant user information, these insights can be utilized to make user interests and behavior predictions.

These predictions allow advertisers to target lookalike audiences who are most likely to engage in the post-install action goal. They also help us identify key post-install action drivers. In turn, these key drivers can be utilized to determine what creative or media placement will most likely get the target audience to perform the post-install action.

Optimize the Right Post-Install Metrics

Forecasting the probability of post-install events is also crucial to determining what optimization to implement in real-time bidding situations. The accuracy of the forecast determines both the media placement and consequently, whether advertisers will achieve their post-install goal. In a media-buying platform such as Aarki Encore, Bayesian Logistic Regression algorithm can be utilized to forecast the probability of post-install events. We chose Bayesian algorithm because it takes into consideration both prior knowledge and dynamic changes that occur. The forecast enables us to make data driven campaign decisions and implement necessary optimization in order for advertisers to achieve their post-install goals.

With streamlined big data architecture and machine learning technology, RTB media-buying platforms using deep tracking provide flexibility and advanced capabilities that are necessary for driving post-install metrics. Aarki Encore, in particular, provides a scalable media-buying platform that consists of strong machine learning algorithms as well as a powerful creative design suite.

At Aarki, we realize the importance of post-install optimization in driving the return on mobile app investment. This is why we built a platform that offers the flexibility and capabilities for app developers to optimize their app marketing campaigns for post-install metrics.


Topics: Mobile Advertising, Mobile App Advertising