Measurement at any time is filled with challenges. There are so many different datasets and parameters to use to quantify an increasingly complex consumer journey. Now, during a time where the entire landscape is shifting, the task becomes even more complicated.
Konstantinos Spetsaris, senior vice president, Analytic Partners, believes that we can apply specific methodology at this time to make greater sense for future forecasting.
The following interview has been edited for length and clarity.
Charlene Weisler: What goes into accurate measurement of and during a pandemic?
Konstantinos Spetsaris: With so many forces at play, a holistic econometric model is best suited to accurately measure the impact of COVID-19 and its compounding impact on other business drivers such as media, operations and direct to consumer marketing.
A simplified formulation of an econometric response model where all controllable and non-controllable drivers are included as predictors (independent variables) would look like Response=f(Marketing, Non-Marketing and Macro Factors). The model lends itself to quantification and decomposition of impacts, reporting of core performance metrics (ROI, cost per acquisition, response/unit of support etc.) and scenario planning (simulation and optimization).
Weisler: Does measurement vary by industry, consumer category, etc.? If so, how?
Spetsaris: Measurement varies in the sense of which KPIs are most critical to any given brand within any given vertical, as well as what data is available per industry. For example, there are industries with an immense amount of first-party data, like financial services, which allows for extreme deep dives. Conversely, in industries like CPG there is a lack of first-party data, which calls for a different process to draw out insights.
Weisler: What data is most important?
Spetsaris: That really depends on what business question is being asked. For that reason, it is critical to have a holistic measurement system in place that allows available data to be viewed through different lenses and dimensions, in order to extract the most relevant answer.
A few examples of the most important factors to consider during the COVID-19 crisis may include:
— Macroeconomic Indicators such as consumer sentiment, consumer confidence etc.
— Financial Indicators such as the VIX (Volatility Index) for financial services firms
— Store closings and operational changes in services — e.g., no longer offering dining in for restaurants or adding a service like curbside pick-up, changes in business model B2B to B2C
— Category base sales to capture shifts in consumer demand towards certain product classes, e.g. disinfectants, cleaners, shelf-stable food
— Scaled indicator variables to capture out of stocks and the impact of stockpiling as a result of the initial panic mode buying at the onset of the pandemic.
Weisler: How can we effectively capture the impact of COVID-19 with so many other forces at play?
Spetsaris: We recommend starting with a holistic measurement framework such as commercial mix modeling that incorporates controllable, non-controllable, and macro-factors in order to isolate the impact of COVID-19 on the business.
From a measurement perspective, there are several factors to consider including: time horizon (immediate vs. longer term impact), industry (benefitting or negatively influenced and to what extent) and unique brand / business dynamics (% of sales impacted, geographic footprint, etc.).
As an initial analytical objective, we recommend beginning with descriptive data analysis to help define the impact window in terms of business units, sales channels, consumer segments, and time. The goal is to identify where the impact of COVID-19 may be manifested in the dependent variable and gauge the order of magnitude vs. expectation. This helps refine our search for the right data inputs for COVID-19, as businesses are impacted differently.
Weisler: Can we still leverage historical results to predict outcomes given this unprecedented event?
Spetsaris: In a word, yes. COVID-19 has disrupted every business in some capacity, which has influenced business and marketing plans and forecasted performance. In this chaotic state, data and analytics become even more important, and measurement approaches must adapt.
It’s critical to update existing models to reflect new consumer behavior and continually refresh to assess how these changes impact business performance.
But without an accurate understanding of historical insights and principle-based learning as a foundation for these updates, there is no way to measure progress or success — nor is there a way to understand when and if consumer behavior and other key factors have returned to “normal.”
Weisler: How will we know the lagging impact of COVID-19 as we shift to stabilization / recovery and revitalization phases?
Spetsaris: In the current environment, it is not enough to just know how much a business has been impacted by COVID-19. Brands need to know how the underlying consumer behavior has changed, and how it may continue to change, and better understand the pandemic’s impact on marketing and media channels, shopping habits, competitive actions, and overall business performance. Given the disruptive nature of COVID-19 its epidemic and economic consequences, decisions taken in the short term will have significant ripple effects down the road.