Katie is Chief Product Officer at Adjust, a measurement and analytics company that helps marketers grow their apps across platforms.
Last year was one of dramatic transformation across all industries, but as we enter 2024, global businesses are still assessing how they can best utilize the technology that’s taken the world by storm—AI. Marketing is in the same boat as the rest. In a time when marketing teams carefully allocate time and effort to achieve the most bang for their buck, mastering the dynamic interplay of AI and marketing isn’t just a strategic advantage but a business-critical necessity.
Advancements in AI and its subsets, machine learning (ML) and generative AI, have prompted the industry to reassess where this technology can be implemented to drive efficiency, save valuable time and improve return on investment (ROI). At Adjust, we’ve seen firsthand the impact of ML on predictive analytics and campaign measurement and, across the industry, generative AI has been used for the development of written content and creative visuals. The common goal? To reduce time spent on the basics and increase focus on strategic initiatives.
Less Is More
Emphasized by ongoing economic pressures, businesses are continually searching for ways to save time and improve efficiencies. In conversations we have with our customers, we often find that marketers need more time to focus on strategy, creative ideas and tactics to best target their audiences.
To do this, they need to spend less time on day-to-day tasks like campaign management and data collection. As a result, most marketing teams have embraced AI in some form to speed up these processes, either directly through easily accessible tools like ChatGPT or indirectly through partners or by utilizing integrations to existing software.
Along with increasing efficiency by automating mundane activities, AI technology has enabled marketing teams and their tech partners to optimize campaign results. Measurement and analytics tools have always played a crucial role in marketing, delivering valuable insights into performance, user behavior and ROI. These tools establish the foundation for data-driven decision-making, enabling marketers to refine strategies and pinpoint the optimal audience for campaign success. What’s become apparent to our team and customers over the last year is the remarkable enhancements that AI—specifically, ML—can bring to these tools.
Traditional methods of campaign measurement have experienced a resurgence with the help of ML—namely, incrementality and media mix modeling, or MMM. Incrementality allows marketers to understand the true value of their marketing activities by showing the difference between the outcomes of changed and unchanged marketing activities. MMM, on the other hand, measures a wide variety of marketing activities with aggregated data to gain insight into their ROI impact.
As well as improving these traditional methods, the latest ML technology now extracts insights from aggregated campaign data in significantly less time to predict usage patterns and offer recommendations for optimizing campaigns. Previously, measurement focused on bringing together data from a few sources and comparing results to inform future decision-making. Now, with AI and ML, marketers can predict a user’s lifetime value on days three, seven, 14 and 30 of a campaign. This predictive analysis, combined with the modernization of incrementality and MMM, means marketers have a stronger understanding of how to spend their budgets to achieve a higher return on ad spend.
The benefits of this are immediately apparent. For example, when analyzing the effectiveness of out-of-home (OOH) campaigns—which, simply put, is advertising that can be found outside of a consumer’s home—marketers used to wait six months for measurement. Now, ML-enabled measurement delivers results within a matter of weeks, swiftly enabling marketers to see the impact of their OOH advertisements on app usage, as well as predicted success, and act accordingly.
As we expect to see increased investment in AI, embracing this technology in marketing will be vital for staying competitive in the evolving landscape. Right now, AI allows marketers to access data that’s more refined and helps them make smarter, more informed decisions as a result.
However, in 2024 and beyond, we believe the next step is to answer one critical question: How can this new tech actually take all of that data and then help users themselves reach an informed decision and take actionable next steps? Through the ongoing analysis of data, advanced learning models can make strong recommendations to marketers. In less time and with more accuracy, this can help growth marketers figure out how to optimize their spending to reach their audience and drive results.
What’s clear is that there’s no going back to traditional marketing and campaign measurement approaches. While 2023 was a year of transformation, 2024 and the years to follow hold some very exciting potential. So, how do we make the most of this opportunity?
Understanding and leveraging AI in a responsible and considered way to achieve the best possible results is something we can only achieve through effective collaboration and communication. This applies to many aspects of AI—development, regulation, education and much more. But from a marketing perspective, this means being in constant communication with your tech partners.
In recent years, and the mobile marketing industry particularly, we’ve seen a lot of collaboration. Through conversations with our customers and partners, we’re always learning new things from each other, whether that’s trends, demands or solutions.
Moreover, AI is a rapidly evolving field. Marketers must stay informed about the latest trends, technologies and best practices to harness new technology like AI to innovate and remain competitive. By staying informed and communicating with well-versed partners, marketers should feel equipped to take the plunge and embrace new strategies that leverage AI. No one’s getting it right on the first try, but successful teams are the ones that keep experimenting, testing and adapting their AI campaigns.
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