Modeling & Testing

Modeling and testing bring together our philosophy of being tech-enabled and human-first. Campaign data alone is valuable but in some cases, incorporating additional data sources or testing methodologies can provide deeper insights that enhance and strengthen marketing performance.

Media Mix Modeling (MMM) is an important tool that we develop for many of our clients. MMMs provide a diagnostic evaluation of data to understand overall impact of media activities and influence strategic planning. This includes examining media performance, KPIs, and business data as well as other marketing tactics (email marketing, retail catalogs drops, PR, organic social, etc.) and relevant external factors. The outcomes can include:

• Channel contribution analysis
• Media spend allocations and optimization
• Adjusting for external factors (seasonality, product introductions, change of service, category/industry shifts)
• Measurement of long-term brand effects (awareness, consideration)

Propensity modeling uses historical data to predict the likelihood of a customer taking a specific action, such as clicking, purchasing, or signing up. This enables more precise targeting, efficient spend, and tailored audience strategies.

Testing can come in many shapes, sizes, and forms (media channels, geographic, multivariant) and provides extensive value for making smarter, data-driven decisions. Testing can allow for innovative or unproven tactics to be quickly evaluated with minimal risk. For example, incrementality testing measures whether paid media drives lift by comparing performance across exposed and unexposed groups, such as the differences in conversion between test and control geographies.