Facebook has provided some new insights into its evolving approach to Marketing Mix Modelling, which, eventually, could provide more opportunity for marketers to better target specific audiences with the right content mix, and adjust automatically, based on consumer trends, in order to maximize ad performance across its networks.
“Marketing Mix Modeling (MMM) is a data-driven statistical technique which can help marketers quantify the impact of marketing and non-marketing activities on sales. MMM is privacy-friendly and uses scientific methodology to analyze multiple factors and evaluate how they impact the sales. However, it also has some limitations, for example, it is time-consuming for data collection, resource intensive, long lead time for analysis and these make it difficult for MMM to scale and execute.”
The privacy-friendly element is key here, because with Apple recently implementing its new ATT data tracking prompts in iOS, and other platforms looking to provide more transparency on data collection, Facebook may soon have a lot less user data to work with, which will force marketers to look in new directions.
Which is where marketing mix modeling could help – as Facebook notes, it’s worked with analytics solution provider Analytic Edge to establish a new, repeatable MMM framework, which, ideally, will eventually help advertisers accelerate their process, without requiring the full set-up workload of a regular MMM approach.
Facebook has outlined this new process in a summary document, which explains how it was able to apply this system to a recent campaign by ASUS.
The researchers first outline the MMM process, and the benefits they’re seeking through this enhanced model.
Because of the varying factors, MMM is difficult to implement effectively, especially for smaller, less-resourced businesses, and even more so when considering speed of response in optimizing ad performance. But this new process looks to address these key concerns, and provide an established framework for the system.
It’s a fairly complex outline, but the bottom line is that Facebook is working towards creating new, updated, automated processes that will incorporate all of these new elements into a far easier to apply system.
“Further innovations are underway that will make MMM on SaaS platforms simpler, automated and AI-driven. This will enable widespread adoption of MMM for both large and small companies, who couldn’t access MMM before or couldn’t scale MMM across their whole business.”
That could provide a new pathway forward for better ad targeting, without the need for the same levels of personal data insight that Facebook has applied in the past.
It’s an interesting experiment, and one that will still take some time to develop, but eventually, it could mean that you have more response options for your advertising approaches, which could help to maximize ad performance, even with less user data available.
And as noted, that could become even more important over time, as more people opt-out of data tracking as a result of the new Apple prompts, and potentially, similar restrictions that could be launched on Android as well.