Improving Marketing Mix Models
This new MSI report explores the challenges of modern MMM, MMM use-cases and recommendations for successful MMM implementation.
This new MSI report explores the challenges of modern MMM, MMM use-cases and recommendations for successful MMM implementation.
Managing business risk involves having a rational, data-driven view of the future while simultaneously being as prepared as possible for external shocks — from a global pandemic and the ensuing supply-chain disruptions, to inflation, data signal losses, war, and great power competition. At our annual Forecasting event, held virtually on July 18, leading experts shared how businesses can adapt forecasting techniques to manage risk.
Marketing Books – Summer Reading Suggestions Read more »
A podcast series highlights the career paths and achievements of media researchers. Read more »
Managing business risk involves having a rational, data-driven view of the future while simultaneously being as prepared as possible for external shocks — from a global pandemic and the ensuing supply-chain disruptions, to inflation, data signal losses, war, and great power competition. At our annual Forecasting event, held virtually on July 18, leading experts shared how businesses can adapt forecasting techniques to manage risk.
Member Only AccessMark Wilson, Associate VP at Analytic Partners, advocated the value of scenario planning for businesses. Scenario planning is particularly helpful for new product launches, forecasting the impact of price increases, and budget planning. The keys to their success are that they be data-driven, collaborative across functional teams, ongoing, and iterative, with continuous updating of inputs. A successful scenario planning framework defines success criteria, identifies performance drivers — both controllable and non-controllable — and incorporates critical business dynamics. Marketing drives 15% to 30% of sales, more for some businesses, and companies that adopt data-driven simulations can drive much more growth than companies that do not.
Diana Saafi, Data Science Lead at Discovery, built on Cliff Young’s comments about the importance of multiple indicators for forecasting. Saafi forecasts linear television audiences in segments of interest to advertisers (beyond age-sex segments), rather than political outcomes. She and her team have found that their models have benefited from using multiple sources of data. She recommended identifying signals that are most predictive, experimenting with different types of models (such as ARIMA models and AI models), continually refreshing the data in the models, and continually updating the models. While this process is now automated at Discovery, there are people who monitor changes in the predictions, which she referred to as “human-in-the-loop automation.”
Rex Briggs, Founder & Executive Chairman of Marketing Evolution, who had developed forecasts of US COVID infections and deaths early in 2020, before it had been declared a pandemic, talked about the difficulties in “exponential forecasting” of events like a pandemic, compared to “stable state” forecasting of the impact of media, marketing, and creative. Just as companies might not have anticipated the impact of COVID-19 as it spread, they may be caught “flat-footed” in forecasting the exponential decay of the disease as vaccinations spread in 2021. Business forecasts of the impact of COVID in 2021 should take into account vaccination rates by age and surveys on acceptance of the vaccine.
David Dutwin, SVP of Strategic Initiatives at NORC, and a past president of AAPOR and survey research expert, in an interview with ARF CEO & President Scott McDonald, Ph.D., encouraged the advertising and marketing industry to maintain their faith in survey research. Surveys for marketing and advertising do not have to contend with two problems with election forecasting based on polls: