“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Jason Wulfsohn, CEO and co-founder of AUDIENCEX.
Digital media is a blessing and a curse: It offers unlimited ways to reach highly targeted audiences at scale. But how do marketers reach the right people at the right time in the right place without spending a fortune?
Cookies have given marketers a convenient shortcut to understanding what works and why across digital channels. But as cookies are phased out, the way we track what’s promoted and how will dramatically change. And while marketers have spent years perfecting their attribution models, once cookies are gone – and it’s coming sooner than you think – multitouch attribution (MTA) models will be obsolete.
Enter media mix modeling, also called marketing mix modeling, or MMM. MMM is a statistical analysis of aggregate marketing, sales and business data that quantifies the effect of different marketing channels and tactics (the marketing mix) on financial outcomes over time. The result is insights and recommendations that can be used for budget allocation. When used correctly, it’s an astonishingly powerful tool.
MMM tends to produce higher marketing contribution measurements than MTA. This is primarily because it can include more touch points, especially non-addressable digital tactics such as TV, radio, out-of-home (OOH), point-of-purchase (POP) and others. And it provides an understanding of how to improve ROI.
You can even measure activities that do not always sit in the marketing plan, like sales calls and press releases. Even traditionally elusive and hard-to-measure activities like influencer and brand partnerships can be part of the model. The bottom line is MMM is much richer than MTA – and ultimately provides marketers with more insight, data and better results.
Sounds great, right? It is, but implementing it can be tough.
To take advantage of its capabilities, marketers need to have a handful of key elements in place.
Long-term data
Media mix modeling needs a full view of your media spend and media performance, including impressions, clicks and views, video completes and more. You also need first-party CRM data to do any identity analysis. The more data, the more powerful the analysis.
That’s also why it’s important to input at least two years’ worth of data. The ebb and flow of sales across several different media channels over the course of two years provides the most accurate depiction of how each channel contributes to the result.
Reliable storage
MMM requires a central repository for data – a data warehouse that’s going to store information and structure it. The model also calls for computing resources with predictive capabilities to help fill in any blanks in existing data. If you’re serious about MMM, invest in a vendor that can help set up this infrastructure for you.
Flexible data access
Your MMM vendors need to be able to see the data you have across media and add data into the mix to run an analysis. The ideal approach is for your partner to create a templated process that hosts your data in a warehouse, runs analysis on media and performance, then tells you where to place additional funds or dial them back.
MMM is not a silver bullet. And no one has ever called MMM (or any attribution for that matter) inexpensive. But as part of an overall marketing budget, the cost of measurement and attribution is relatively low. Plus, it can pay for itself when it tells you what to spend, where to spend it – and where to cut your losses. And as cookies disappear, that insight is nothing short of invaluable.
Follow AUDIENCEX (@AUDIENCEX) and AdExchanger (@adexchanger) on Twitter.
