A breakfast brand used SEM based MMM to estimate direct & indirect impact of marketing on sales.
The client is a Top 5 global breakfast brand having significant marketing budget. They have a significant marketing budget and use market mix modelingto estimate the impact of marketing on sales. They however observed that cross channel effects were not being reflected in their current MMM studies and multi-channel effect was not being captured effectively. The client also wanted to know the directional relationship of channel interactions.
Market Mix for a Multi-channel world
Structural Equation Modeling (SEM) based market mix study measures the direct and indirect impact of marketing on sales, as well as latent variables impacting sales.
- % increase in marketing sales with 2% reduced spend through mix reallocation
- A total indirect impact of 4.4% on sales through cross channel interactions
- Aggregated indirect impact of 1.2% on TV from Weekly Ad, Radio, & Search
The estimation enabled the client to understand cross-channel interactions better and plan well for multi-channel campaigns with the recommended allocation of spend mix.
Measurement challenges in multi-channel interactions
Traditional regression based market mix modeling approaches pose certain challenges to measurement validity. These MMM studies are not designed to account for cross-channel interactions. Any such study tends to underestimate the impact of digital ads (which is generating eyeballs like never before). And the nature of regression models does not allow us to account for latent factors. It is hard to justify investments in channels that do not drive sales directly. The traditional marketing impact measurement methodologies do not capture the impact of digital channels well. Even if interaction variables can be introduced explicitly, the direction of channel interactions is not known. We used Structural equation Modeling (SEM) that estimates both direct and indirect impact of measured as well as latent variables on response.
A more accurate estimation of channel impact
The growth of multi-channel marketing means a touchpoint may not generate sales in isolation, but create a ripple effect that eventually leads to sales. It is important to estimate these cross-channel interactions to understand the true picture of how different channels work in conjunction.
Structural Equation Modeling (SEM) based approach can measure the direct and indirect impact of marketing on sales. It also accounts for the latent variables that are not measured explicitly.
While regression can measure interaction effects by explicit input of channel interactions, it is still not able to measure the direction of the relationship i.e. it is not possible to know if TV impacts Radio or Radio impacts TV or a bi-directional relationship exists. SEM estimates measure the magnitude as well as the direction of impact.