How to Leverage Multi-Touch Attribution & Marketing Mix Modeling through UMM
Many marketers today rely on outdated marketing measurements to target their campaign audiences. Across digital, print and broadcast channels, they are leveraging traditional marketing mix models (MMM) and multi-touch attribution (MTA) in order to optimize their campaigns and reach consumers.
Relying on MMM and MTA alone can’t provide the depth of insight required to meet today’s consumer demands. However, marketers can combine these methods into a unified marketing measurement (UMM) to achieve the in-campaign insights they need for optimal performance.
What Are Marketing Mix Modeling & Multi-Touch Attribution?
Marketing Mix Modeling has been a part of the marketer’s toolbox for decades. By collecting aggregate, long-term data, marketers could understand how consumer needs and responses changed over time.
These insights provided a high-level, “top down” overview of campaign performance. However, marketing mix modeling came to be in a simpler marketing ecosystem, where consumers had far less choice in the ways they could engage with brands.
To understand how marketing efforts were performing across these limited number of channels, marketers leveraged antiquated “spray and pray” methods, sending out as much marketing material as possible. This provided marketers with a larger scope of touchpoints from which to draw their data. Given the small number of channels these touchpoints were delivered within, marketers could easily determine which channels to prioritize for campaign optimization.
However, as the marketing landscape evolved, more channels came to life. From an increase in television and radio stations to the emergence of digital media, the overwhelming number of avenues to engage consumers meant high-level insights could no longer provide clarity into what was driving the return on marketing investment. Soon, marketers found themselves needing insights that effectively attributed value for each individual channel across a wider marketing mix.
Enter multi-touch attribution. MTA revolutionized the way marketers could understand their campaign efforts. By looking at each individual channel along the marketing mix, MTA assigns value to those channels based on their individual impact toward driving consumers to purchase. These insights allowed marketers to better understand the relationship between channels, and their impact on ROI.
Why MMM and MTA Alone Aren’t Enough
While both marketing mix modeling and multi-touch attribution provide important insights into campaign effectiveness, relying on either method alone can’t provide the insights that help marketers reach consumers at the person-level.
By leveraging MMM, marketers can understand the overall consumer trends that impact effectiveness across the media mix thanks to the long-term data collection the model uses to generate insights.
However, marketers can’t rely on data collected months ago to influence their campaigns. By utilizing multi-touch attribution, marketers can gather insights into the effectiveness of individual channels across the media mix but can’t account for the consumer patterns, external factors, or changes in marketing capabilities that are identified using long-term marketing measurement.
To leverage both marketing mix modeling and multi-touch attribution to their full extents, marketers need to combine the two into a unified measurement model that can use the unique insights they both provide together.
Leveraging Unified Marketing Measurement for Better ROI
Unified marketing measurement allows marketers to combine their analytics efforts from a variety of models across print, broadcast, and digital—plotting the insights into a single view of marketing impact that can be used to better optimize campaign efforts. With UMM, marketers can more efficiently leverage marketing mix modeling, multi-touch attribution, and additional measurement methods. This helps to:
Fill marketing measurement gaps
When marketers leverage marketing measurement methods like MMM or MTA individually, they’re limiting the impact those measurements can provide and the opportunities that marketers have to use those insights for campaign optimization. Today’s consumer trends change too fast to work on MTA measurement for one campaign then, MMM the next, and expect those insights to remain relevant long enough to use later on
By combining measurement models at the same time, marketers can gain visibility into all modeling efforts together, as they become available. This helps prevent overreliance on a single model, which could result in poor coverage of areas not accounted for in that particular measurement.
Provide in-campaign insights
Marketers need the ability to rapidly recognize shifts in their audiences’ behaviors that can impact campaign effectiveness and apply changes to their campaigns that ensure efforts are consistently optimized to best meet consumer demand and generate ROI. With unified marketing measurement, measurement efforts are combined for greater analytics synergy that can provide the insights each method brings to the table when marketers need them most.
Gain comprehensive insights across marketing efforts
Marketers today are engaging consumers across more touchpoints and channels at a faster pace than they did even five years ago. In order to ensure that each marketing effort across a campaign is backed by quality analytics, marketers need the capability of UMM to leverage a variety of measurement models at once.
In this effort, unified marketing measurement helps distill the insights generated from individual measurement models, like marketing mix modeling and multi-touch attribution, and coordinates them into one comprehensive view of marketing effectiveness across the entire campaign.
Modern marketers need to leverage a variety of measurement models to generate the insights needed for campaign optimization. However, in order to get the most from measurements like MMM and MTA, marketers need to combine these measurements into a unified marketing measurement model that can provide the unique insights of each method and apply those insights into one comprehensive campaign measurement. This ultimately enables efficient marketing decisions and rapid in-campaign optimization.