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2020 will go down as the year we learned how to predict the unpredictable. Marketers, brands and businesses had to adapt to radical consumer behaviors change as COVID disrupted routines, and locations regularly frequented were all but abandoned. Especially for restaurant brands, the old marketing mix models weren’t going to work, without a reliable baseline against which to predict incremental contributions to sales attributable to media.
We needed a new behavioral variable to optimize marketing performance.
When the pandemic hit hard, our restaurant clients needed a new blueprint for their marketing tactics as waves of lockdowns wiped out the option of indoor dining altogether. Brands who could, pivoted their operations to offer pick-up, drive through and delivery, upending pre-pandemic assumptions on how media spend should be allocated.
Consumers adapted quickly to “working from home” routines around home offices and families, staying local and eating at home. Once consumers were no longer commuted to work, food and retail services were significantly impacted. The breakfast daypart shrunk rapidly, and where restaurants remained open, their business shifted accordingly. Footfall patterns that QSRs and fast casual chains understood and depended upon to plan advertising spend were now in flux and hard to predict.
Data on the Go
As media effectiveness experts, we recognized the need for a smarter baseline measure to better predict how behavior could be modeled, guiding QSRs’ advertising media planning across the various phases of the pandemic.
Working with geo-spatial mobility data (tracking footfall timing and frequency for specific regions), we collated consumer traffic information from restaurants across the country, using well-known brands as reliable benchmarks for econometric analysis.
Building the Behavioral Variable
Fueled by the data, we created the “work-from-home” behavioral variable, a far more effective predictor of marketing mix performance to drive demand patterns in QSR patronage. This made simulation and optimization analytics much more reliable, providing hyper precise metrics, pivoting from store and DMA-level models to ones that were split further by QSR service channels.
We could then attribute most visits before 9am and after 5pm to some residual commuter traffic. But by evaluating the hours around these times we revealed new location visit behaviors evident from the massive shift to remote working.
This behavioral variable enabled us to run a single model over the entire course of the COVID disruptions, with more accurate and precise year-over-year comparisons. It produced a sufficiently stable baseline throughout the pandemic so KPIs (such as return on advertising investment) could be measured without interruption. DMA and even store level insights, enabled advertising planning with much more granularity and tactical actionability, so essential for QSRs in particular.
Our clients now had visibility into pandemic effects on customer behaviors, the impact to different dayparts and service channels and, by extension, how to shape optimal media strategies. Mobility became a critical addition to the marketing mix model, particularly in light of disrupted traditional economic measures and seasonal patterns.
Mark Garratt, in4mation insights Partner and Co-Founder, puts it this way:
“We’re now able to measure these baseline trends in a consistent way. And even though people are starting to move about a lot more than they have in the past year, remote working is likely to be a ‘sticky behavior’ that will outlive the pandemic.”
As a result of COVID, we’ve undergone a fundamental shift in the way we work, shop, feed ourselves and our families, and find our out-of-home entertainment. Now that life is cautiously returning to a “new normal”, will businesses insist we all head back to the office full time? It seems more likely that hybrid modes of working will persist. Mobility metrics will become a new and essential tool for tracking the impact of new working behaviors on restaurant customers.
How new consumer behaviors will impact the restaurant sector long term remains to be seen. Some fast casual brands continue the shift to provide click-and-collect menus where they previously accommodated only on-premise dining, forcing a reconsideration of the marketing and advertising models to drive engagement. Our behavioral variable continues to evolve, fueled with new data, which in turn enables our restaurant clients to optimize growth through sophisticated media modeling and effectiveness measurement.
If you are looking for ways to apply a behavioral framework to your advertising media mix, in4mation insights is ready to help.
Stuart Schwartz is Managing Director, Client Growth. For over 25 years he is proud to have created value for clients in media effectiveness and analytics.