How MuteSix Used Marketing Mix Modeling To Improve Investment Decisions For Its DTC Clients
An award-winning performance marketing agency, MuteSix leverages data-backed, omnichannel media buying and creative strategies to help disruptive direct-to-consumer (DTC) brands achieve success.
Like many other agencies, MuteSix was acutely feeling the implications of changing data policies and regulations across the advertising landscape on its ability to sustain its clients’ campaign performance. As new regulations give people more options to limit how their data is shared with businesses—and platforms introduce solutions that remove identity—it’s increasingly difficult for businesses to get a complete picture of how people’s actions drive outcomes.
Measurement tools such as standard conversion reporting and multi-touch attribution (MTA), among others, have been impacted by these changes. As a result, the DTC disruptor brands MuteSix serves were seeking alternative measurement options. After researching different approaches, the agency landed on marketing mix modeling (MMM) as a potential solution for its clients, as MMM can provide a holistic view of media effectiveness inclusive of every sale—regardless of a sale’s link to ad exposure.
MMM has been a fixture of advertising measurement for decades. Yet, practical hurdles to adoption still exist: First, MMM is typically more costly and time intensive than conversion reporting and MTA, meaning that companies that use MMM only do so annually or twice a year. Furthermore, insights are typically at the channel level, making it difficult to use MMM to inform decisions about which publishers or media tactics to use. But recent advancements have made MMM more granular, transparent, and automated, which opened up an opportunity for MuteSix to build a lighter weight MMM service that could overcome common client hurdles to adoption.
To build its MMM service, MuteSix opted to use Robyn—MMM code from Meta Open Source—as the service’s foundation. Robyn helps reduce human bias through automated optimization and allows for the analysis of diminishing returns and budget allocation. And, because MMM doesn’t require individual-level data, MuteSix was able to create a service unaffected by changes in data policies and regulations.
During the process of creating its MMM service, MuteSix partnered closely with Meta to calibrate its MMM results using incrementality testing. Calibration is the process of comparing model results with “ground truth” to ensure their accuracy, which can be established by running an experiment or test. This combination of experiments and MMM provides a powerful way to ensure that measurement is accurate and consistent.
Ultimately, MuteSix was able to build its solution in a two-week period and onboard three DTC clients to help them optimize marketing spend, build brand image, and increase awareness of their products. The agency customized the solution for each client so that they could identify the elements of successful campaigns unique to them and divert funds to channels that show a higher return on investment.
Since adopting MuteSix’s MMM service, the DTC clients have uncovered a number of valuable insights, including:
As the industry rides another wave of disruption across the digital ad ecosystem, it’s clear that any brand still clinging to old playbooks will lag behind their competition. That’s because a brand’s readiness for disruption is critical to building a future competitive advantage. Since the first iOS 14 drop, MuteSix has been pioneering advanced measurement solutions to help brands combat the loss of view through in-platform attribution. On the whole, our MMM solution is more agile and cost efficient than historical models, while delivering efficiency and scale.
JuHee Kim, President, MuteSix