Machine Learning & AI: App Marketers in the Class of 2020

Recently we were like full service app developer Coffee IT present at an app marketing event at the office of Google Netherlands. This event is an initiative of Team Nijhuis and Google. Several app marketers were invited to discuss the implementation of digital innovations in the app marketing profession. From the lead marketer of the 9292 app to the creative brain behind Candy Crush. A mixed group of experts by experience was invited to discuss the benefits of machine learning for promoting an app. Due to developments in the Internet of Things, the era of next-generation app marketing has arrived. In this article we discuss the most important results.

Machine learning and AI have changed the playing field. First there was television, then the internet, then the mobile phone and now the era of machine learning has arrived. Machine learning is big business. Nowadays you cannot read an article without encountering the concepts of machine learning, artificial intelligence (AI) or deep learning. For some marketers, machine learning is still a distant concept. Other marketers now know no better than this new form of marketing. The fact that machine learning is big business is well emphasized by recent research by the research agency EconSight. EconSight analyzes trends in the tech market and its impact on the economy and society. This research shows that the value created with machine learning in marketing & sales is estimated at approx $2.6 trillion in 2020. That is quite something. How come?

Machine learning adoption is happening at scale in virtually every industry, from self-regulating AI agriculture to autonomous cars. If we look at the app market, we see a huge increase in the number of machine learning integrated projects from the major players such as Apple and Google. Google alone uses machine learning in more than 4000 projects of, for example, Gmail, Google Translate and therefore also app marketing campaigns. This focus is not surprising if you look at the results of onderzoeken related to app usage. For example, users spend 50% more time on apps in 2018 than in 2016 and spending in the app stores has increased by 75% compared to 2016. So it seems that the app market is not yet saturated.

Average becomes more than 80% of apps never used again after the first three months of downloading the app. Often this is not due to the quality of the app, but to the strategy behind it. With some regularity, app marketing campaigns are set up to realize a legion of new users without a solid plan to retain the users or to encourage them to take more action. The challenge is not so much in getting the new downloads, but in retaining the app users and getting more out of it. Often these users are not or not at all targeted based on personal preferences and demographic or social characteristics. As a result, there is no match between the app and the user, which leads to rapid disinterest and the termination or removal of the app. This is where next-generation app marketing comes in. Next-generation app marketing is using machine learning to reach the app users that bring you the most value. Machine learning uses an enormous amount of data and segments that are linked to the Internet of Things. Think of someone's search behavior on Google, the locations someone has recently visited or even someone's sleeping pattern via third-party apps. You can't think of it that crazy.

Now, perhaps more than ever, marketers should seriously consider replacing traditional tools with new, personalized metrics through AI and MC integrations. Companies are increasingly investing in user retention and setting up customer-oriented metrics such as the CLV (customer lifetime value). These metrics are getting more detailed and better with the help of machine learning. For example, with the help of machine learning you can not only identify your most valuable customers, but also measure important behaviors and preferences and then act on them. You then tailor the campaign to the users that yield the most to you. In many cases, this is only 17% to 20% of your total users.

Google App Campaigns is a relatively new app marketing tool that uses machine learning. The service is promising, but will require further development in the coming years. For example, it is now particularly interesting for B2C parties and not for B2B because an enormous amount of data is required for the algorithm. By combining millions of signals, a self-learning campaign is put together that is fully focused on a specific phase of the customer journey. A Google App Campaign is therefore not specific to attracting new users, but attracting the 17% best users with the highest yield. The campaign is optimized towards these users by displaying personalized messages. You can set up assets that use text, images, video, and HTML5. For the SEA marketer, this will somewhat resemble the interface of Google Adwords.

It is also possible to optimize your existing app through machine learning. In some cases we can implement machine learning in pre-existing apps. Think of an app that uses (and learns) from other third-party apps or an app that is linked to another app under its own management. Keep in mind that the code of the app must be of such quality that machine learning or AI can be successfully integrated. Wondering if machine learning can be integrated into your existing app? Then take contact Contact us and we will be happy to look with you without obligation.