Multi-Touch Attribution is a very popular marketing science technique in digital marketing. But once you’re there, MMM offers better modeling, better insight and a much softer landing when cookies (and MTA) inevitably disappear.įorbes Agency Council is an invitation-only community for executives in successful public relations, media strategy, creative and advertising agencies.Rule-based Models Rule-based VS. If this sounds like a big leap and a time investment, it is. It’s wonderful to find out how each channel performs, but be sure to ask potential partners what actionable guidance they can provide from the MMM results.įinally, your partner in MMM should be able to tell you where your channel strategy needs adjustments-meaning where to spend more or less-while also helping you determine where to place incremental funds.
Multitouch attribution how to#
The right partner will also be able to tell you how to get started, the timeline to deployment and the value produced by this type of work. The right partner will be able to help you from start to finish. MMM shines a light upon where those deep dives ought to occur, and where there’s room for improvement or additional spending.Ĭollecting and harnessing data for these types of analysis require very specific technical skills in data engineering and data science, which means you may need to find a partner to help you. What you spend is the first decision toward marketing optimization, but you’ll still need a firm grasp of your tactical mix, your targeting parameters and creative assets in use. But it does not capture all the context or levers available to marketers. MMM offers a high-level, channel view of performance, guiding where strategic adjustments could help your performance goals. You also need a solid understanding of the historical context of previous marketing campaigns and creative tactics leveraged. If you want your MMM solution to be automated once it’s in place (and you should), you’ll need to set up data pipelines to catalog historical data for this time-series analysis, setting a foundation to continuously feed the repository with performance and sales data to improve the prediction modeling. You’ll want sales information, order information, subscription data and more. Talk to them (and the data engineers) about data availability, access and the current level of detail you have around marketing expenditures and business key performance indicators. The best way to get started is to make it a team sport with your ad tech team. You also need enough historical data to get a picture of what’s happening, the infrastructure to safely store and share it, and possibly a partner that can be part of your overall media buying workflow. To take advantage of MMM and these new capabilities, you need historical data and a safe place to share it (preferably in the cloud). At AUDIENCEX, we are helping our clients make the move to MMM so they’re ready for a cookieless future now. And when you do that, MMM offers robust analysis that delivers excellent results.Īlthough many companies use both, many forward-looking marketers are starting to use MMM over MTA. It also provides marketers with an adequate understanding of where to place their dollars and optimize their media spend at the highest level. While the methodology is the same, the actual tools available to execute those methods are vastly improved, and the ability to do it more frequently and with more automation makes the technology itself more web positive.
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