Media Mix Modeling

Optimize your marketing spend with AI-driven insights for maximum ROI.

Marketing Mix Modeling (MMM) is a powerful analytical tool for measuring and optimizing marketing activities. With the increasing complexity and privacy-first nature of modern advertising, MMM is becoming an essential component of the marketer’s toolkit. At OneSix, we are helping clients understand and improve their marketing efforts using off-the-shelf solutions and our in-house MMM application. Implementing these as a continuous solution in their BI environments is allowing them to react to frequent changes in their respective markets.

Services

Optimizing your marketing strategy and budget

Exploratory Data Analysis

Collect and understand data for MMM. Identify if MMM is feasible and determine if it meets business requirements. Gain an understanding of the significant factors or structure that MMM will need to capture.

Model Development

Develop the MMM model iteratively, collecting stakeholder input on results of the model at each step to guide necessary improvements.

Integration

Integrate the model into existing infrastructure, configuring the cadence of model refreshes. Create connections to data warehousing and external inputs. Standardize tabular and graphical outputs for BI reporting.

Impact

Driving practical business outcomes

Improved ROI

By measuring the impact of individual marketing activities on sales, MMM helps marketers to optimize their marketing mix for maximum ROI.

Increased Accountability

MMM provides a clear picture of the effectiveness of marketing activities, making it easier for marketers to justify their marketing spend to senior management.

Real-Time Optimization

With the availability of real-time data, marketers can perform MMM on a regular basis and adjust their marketing mix accordingly. This allows them to respond quickly to changes in the market.

Multi-Touch Attribution

In the ever-connected world, users often touch several marketing channels on their way to a purchase or sign-up. MMM can account for these complex causal graphs, giving credit to channels that are typically harder to assess, such as non-digital media.

Privacy Friendly

Changes to tracking in iOS have hindered traditionally more direct and intrusive methods for measuring the effectiveness of digital advertising. Since MMM relies on aggregated sales data, it isn’t reliant on user-level data, such as PII or cookies.