Media Mix Modelling & It’s Impact

As assigning value and investment return become more challenging as cookies continue to be less viable, we believe that more marketers should turn towards more empirical methods of valuing the impact of advertising like Media Mix Modelling.

In this week’s article, Jerome Velasquez, Product & Solutions Director, delves into MMM & it’s pivotal role in assessing the comprehensive impact of media investments and the ensuing returns.

Media Mix Modelling is about optimizing for return

Media Mix Modelling is a statistical analysis technique used to determine the optimal allocation of resources across various advertising channels to maximize the return on investment (ROI) of the advertising budget. By scrutinizing historical data on advertising expenditure and its influence on sales or other Key Performance Indicators (KPIs), MMM identifies the most effective blend of media channels to engage the target audience. It encompasses various external factors affecting media investments, including competitor activities, economic conditions, historical performance, and consumer confidence.

Media Mix Modelling presents a future-proofed alternative

MMM emerges as a future-proofed alternative amidst the challenges faced by advertisers with attribution modelling, particularly due to the dwindling reliance on cookies. Moreover, while attribution modelling traditionally measures ROI by attributing value based on predefined rules, such as the last touchpoint in the customer journey, it grapples with limitations related to digital channel focus and the overvaluation of recency in user journeys. Conversely, MMM offers a bespoke solution adaptable to brand dynamics and benefits from evolving technology landscapes, making it less reliant on cookie-based technology.

Media Mix Modelling implementation challenges

Despite its potential, implementing a Media Mix Modeling system presents challenges. The reliability of modeling results hinges on the completeness, accuracy, and representativeness of data. Thus, meticulous attention must be paid to data collection, organization, and understanding. Advertisers must recognize MMM’s propensity for providing aggregate-level insights rather than granular ones, necessitating strategic planning of data sources and alignment with business objectives.

Confidence in ROAS

While developing an MMM model may entail navigating a complex landscape of data volume, perseverance yields holistic insights that instill confidence in Return on Advertising Spend (ROAS) across the business. Despite the inability to drill down into individual tactics, MMM empowers marketers with overarching support for channel allocation and comprehensive measures of channel efficacy and efficiency within marketing investments.

As marketers confront the evolving challenges of the digital advertising ecosystem, embracing Media Mix Modeling offers a robust solution for optimizing advertising strategies and enhancing ROI in an ever-changing landscape. To Learn more & Imply MMM to your business, get in touch with an ADMATICian today!