Driving impact for user growth through machine learning
By Ben Jeger, VP EMEA, Moloco
We live in a fast-changing digital world, where mobile advertisers can utilise transformative tools to maximise profitability and Return on Ad Spend (ROAS). Two-thirds of digital ad spend is devoted to the three Big Tech platforms — Google, Meta, and Amazon. And key to their success and what often gives them the edge is their capability to develop and leverage advanced machine learning (ML) to drive measurable outcomes.
Beyond those Big Tech platforms, we’re seeing the application of ML grow on the open internet and, with this, unlocking new possibilities. Mobile marketing is increasingly becoming more performance-based and ML is certainly the driving force behind this shift.
While ML is a game-changer, some mobile advertisers are still in the early stages of truly leveraging its capabilities to maximum effect. This takes more than understanding advanced technology; it’s about activating and connecting the potential to tangible marketing outcomes.
The key benefits of investing in a digital strategy
In the past, manual time-consuming processes have been required to drive performance. Today, the move to automated operations not only makes advertising campaigns more precise, but ensures they reach the right users at the right time. By reimagining mobile marketing with advanced ML technology, marketers can gather, learn from, and ultimately deliver real business outcomes using first-party and real-time data such as contextual signals, user behaviours, and campaign goals.
This is significant. It means mobile app marketers no longer need to rely on rigid targeting based on cohorts, and instead today’s ML-driven strategies enable them to dynamically adapt to user behaviour in real-time. In doing so, they can cater to users’ ever-changing preferences.
Investing in ML is investing in outcome-based results. ML optimises in-app marketing strategies with first-party data inputs, which means app marketing campaigns can remain aligned with goals as they develop. This is crucial when it comes to driving outcomes. These automated processes also enable optimised targeting.
Machine Learning allows mobile marketers to engage users with dynamic pricing tailored to their unique ROAS target. In addition to this, it ensures user engagement is timely and effective. From serving the right streaming ad to promotional posts on a website to driving app installs and in-app actions, leveraging ML helps to meet diverse marketing objectives. In an industry where capturing user attention is at the heart of success, the power of real-time data is crucial. It’s the difference between staying ahead of developments in the mobile app marketing space, and having to play catch up later. The reality is that an account managed by manual processes will lose out to one that is leveraging AI and automation.
How to determine your machine learning-powered solution
While the benefits of machine learning are clear, building an in-house ML solution is not a simple or easy task – in fact it’s quite the opposite. It requires a great deal of investment in terms of time, talent, and resources. As a result, many mobile marketers are looking to outsource to a dedicated ML-driven advertising platform, to deploy solutions quickly. However, mobile app marketers need to ensure partners and solution providers are a good fit based on their capabilities and specific goals.
This presents the question: how do you cut through the buzz around ML and determine if a solution would be truly effective?
For starters, it is important to ensure the platform has the ability to process large amounts of data in real time. Where there’s an inability or lack of demand for real-time data, this can indicate limitations in targeting and bidding capabilities. Transparency in measurement is another key factor. Real-time reporting and analytics are essential elements to help marketers understand performance and track ROAS. As well as this, there needs to be compatibility with performance metrics. ML should leverage user data (such as user behaviours and preferences) and marketing goals (including installs and in-app purchases) to drive real business outcomes.
With ML-driven marketing, platforms that leverage real-time user data, deliver measurable outcomes, and align with clear objectives are crucial to success.
Data as the catalyst
ML is transforming mobile app marketing, and understanding and proactive engagement is crucial for navigating the technology successfully. Utilising ML to deliver real-time campaign targeting creates a tangible business advantage that drives impact and unlocks value for organisations. The evolving app marketing landscape involves a deeper alignment with ML, prioritising clear goal-setting, and integrating real-time data — all aimed toward achieving measurable growth. While there’s still so much more value we can unlock with ML, the benefits already being realised in the mobile app marketing industry are already seismic.