As a marketing decision maker, ask yourself, “If I was able to successfully identify which stores and products positively respond to media stimuli by media channel, or which stores don’t respond at all; what would I do with this level of insight?”
At Callahan, we can tell you through leveraging the Intelligence Platform, statistical modeling, threshold pressure testing, and different mathematical techniques, we are able to identify the product, store, or combination thereof—with a high degree of confidence—that are impacted by media, negatively or positively. This in no way in-part or in-whole a media attribution model. You can reference our previous blog posts and podcasts to understand our rationale for why we believe attribution models are inferior and should be avoided.
Now for the part where the rubber meets the road (Hello… road). We set out to uncover the “aha” recently for one of our clients as part of their annual media planning process. We unleashed our data analytics team armed with the Media Impulse Shock Analysis (example at left) to identify which QSR stores were positively impacted by media stimuli, by channel and to what extent.
Once these stores were successfully identified, we were able to start the process of storytelling and filling in the missing pieces by drilling down on commonalities and differences through layering in geographic and economic factors, and consumer demographics and profiles. As the pieces fell into place, we continued to uncover the strategic pullies and levers that operate and drive the business.
This example demonstrates a general media channel system shock. Through threshold pressure testing and various mathematical techniques we can translate signals in the data into insights.
Insights from an analysis like this will help you understand the “true” drivers of your business and shed light on things you once thought were random or a non-factor. We CAN help you identify and understand the signal in the noise.
Learn more about the Callahan Intelligence Platform.