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Cross-Sectional Variation … More Important than Ever

I try not to let the blog turn into a sales pitch. But during a recent discussion on how to encourage clients to invest in Middlegame  services during COVID-19—or once we finally emerge from the pandemic—my business partner Vegard Søhus reminded me that timeliness is a really important component of our approach. .  During this business season, market share analysis is more important than ever. In this blog, we depict the “wide-angle view” as an extension of Lee Cooper’s market share analysis description, but it is really the power of cross-sectional analysis. 

Cross-sectional analysis is at the heart of any choice-based model and the subsequent assessment of market shares. It highlights the correlation in the relative attraction of the competitive SKUs to shoppers with the relative competitive position of the SKUs across the 4Ps including product, price, promotion, and place. Since the correlation is “relative”—or SKU versus SKU—the modelling of shopper response focuses on each individual time period for each geography.    

Vegard’s point was that the wide-angle view means that we can provide the estimated impact of assortment, pricing, merchandising and even media decisions based on a very narrow timeframe.  Segmenting the weeks and months of 2020 into pre-pandemic versus post-pandemic is a quite simple task and produces little to no pressure on model reliability and validity. We continue to have an overwhelming number of SKU observations for the additional time dimension in the Hierarchical Bayesian engine.   

Marketers tend to think of survey-based instruments—like conjoint—for a cross-sectional approach.  Although fellow Irish firms such as Epic Conjoint have significantly cut the time to setup a study and deliver results, there is still a limit to the number of SKUs that can be evaluated. Identifying variation across regions or channels is also rarely possible. Middlegame can easily meet the same turnaround time with all this detail leveraging the immediately available data from our partners at Nielsen.

Although cross-sectional analysis is often described as the opposite of time series analysis, the Competitive Interaction Analysis (CIA)® platform uses the two together in an integrated modelling system. This allows us to simultaneously incorporate lagged effects that may not be immediately apparent in the shopper response metrics but are still important to the allocation of marketing resources and exploit growth opportunities. The takeaway here is that timing is everything and now is a good time for cross-sectional analysis. 

Okay, I guess it was a bit of a sales pitch. : )  

Middlegame is the only ROMI consultancy of its kind that offers a holistic view of the implications of resource allocation and investment in the marketplace. Our approach to scenario-planning differs from other marketing analytics providers by addressing the anticipated outcome for every SKU (your portfolio and your competitors’) in every channel. Similar to the pieces in chess, each stakeholder can now evaluate the trade-offs of potential choices and collectively apply them to create win-win results.