Coverage of the digital advertising industry has dedicated a great deal of focus to the coming deprecation of third party cookies – understandably so, as it stands to significantly shift the way marketers approach their campaigns. Much of this attention so far has focused on how this change will affect advertisers’ abilities to target audiences. However, targeting is not the only aspect of advertising that will be affected by this coming change. Multi-touch attribution (MTA) models, currently used by many marketers to allow for performance tracking across an ever-increasing number of touchpoints and channels, is also facing potential obsolescence.
Over the course of years, brands and agencies have invested a great deal into developing and refining these robust digital attribution models that heavily rely upon third-party cookies. Thanks to these cookies, many multi-touch attribution models have boasted the ability to identify a user and follow them across websites and media channels. This has enabled marketers to track much of a user’s journey leading to conversion, identifying the best-performing channels, platforms and placements. Clearly, this is incredible insight to have when optimizing media planning.
Of course, as our understanding and approach to data privacy continues to evolve, these models stand to lose much of their ability to generate these insights. In fact, while the focus of cookie-less discussions has primarily been on Google’s planned discontinuation of third-party cookies, their efficacy has already been affected by the changing data policies of other platforms, such as Facebook and Apple. Soon, all web traffic will be split between those who are authenticated and those who are anonymous, with 95% of users expected to fall into the latter category. This presents a clear challenge for marketers to better understand their audiences and how to most effectively communicate with them.
Optimization Options
This doesn’t mean that attribution or optimization will be impossible, of course; there are options beyond MTA. One of those options is media mix modeling (MMM), sometimes also referred to as marketing mix modeling, a well-established methodology that has been in use for decades. While its roots trace back to the 1960s, it is currently still utilized for prediction and planning, as well as budgetary allocation.
While it isn’t a direct replacement for multi-touch attribution, this statistical analysis of aggregate sales, marketing, and business driver data can quantify the impact of marketing channels and tactics on financial outcomes over time. With the proper data in place to support MMM, it can effectively provide insights and recommendations that can be used to optimize marketing investment allocations and predict future outcomes.
Gain Deep Insights
By measuring data on an aggregate level, MMM can include marketing tactics that are not addressable such as radio, out-of-home, point of purchase or broadcast TV. This wider pool of data enables it to answer questions about things like ROI on specific ad spend segments, or to project how budget shifts could affect sales numbers.
Historically, MMM was something that would be done only upon occasion, once or twice a year, requiring two years of data to do a proper analysis. This presents a challenge, naturally, as many marketers do not have two years of data available. However, with cloud architecture and contemporary computing power, it’s now possible to get a meaningful signal with less data, and the intelligence that fuels the modeling has improved as well. The foundational, time-tested and proven methodology remains the same, but the tools available to enact this methodology have become far more sophisticated. This enables analysis to be done both more frequently and with more automation.
Overall, this considerable modernization makes MMM a positive technology for the omnichannel ecosystem, providing an adequate understanding to marketers of where to focus their budgets and optimize their media spend at the highest level. With the proper tools, data, and technology in place, MMM offers a robust analysis that delivers excellent results.
The Future of Media Optimization
If you’re interested in hearing more about the future of attribution and media strategy optimization, check out our on-demand webinar. At the first in our series exploring data, analytics and technology to fuel your campaign performance, aX Data Dive: Media Optimization Beyond MTA, AUDIENCEX Director of Analytics & Insight Benji Joachim explores optimization solutions more deeply. You can also reach out to us at any time; we would be happy to explain how all of AUDIENCEX’s analytics solutions can help you gain a deeper understanding and insight into your media planning.