UM’s Global “Consumer Demand Forecaster” Model Helps Marketers Predict Consumer Demand Levels through COVID-19 Crisis

UM, the global marketing and media agency network of IPG Mediabrands, released the Consumer Demand Forecaster, its proprietary machine learning model that predicts the rise and fall of consumer demand in various markets amidst the COVID-19 crisis. The accompanying series of reports provides a roadmap for brand marketing re-entry strategies across 10 major categories, including Automotive, Consumer Electronics, CPG, Entertainment, Finance, Food, Insurance, Oil & Gas, Retail and Travel.

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The first set of findings predicts consumer trends across highly impacted categories including Automotive, Insurance (automotive, motorcycle, home, life, travel and cyber) and Food Delivery for the U.S. and U.K. markets. In the Automotive and Insurance categories, there are consistent signs that consumer demand in the U.S. will rebound in mid-May and approach pre-COVID-19 levels by early June. In the U.K., however, there are little to no signs of recovery in consumer demand over the same period.

Using online search data as a representation of consumer demand, the Consumer Demand Forecaster leverages advanced analytics to predict the timing, rate and extent of recovery in consumer demand across 15 countries in different stages of the COVID-19 crisis, enabling marketers to plan their re-entry appropriately. Additional insights across categories will be released weekly.

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“Our data-fueled model provides practical, actionable media guidance to help brands respond to and prepare for recovery from the COVID-19 pandemic,” said Huw Griffiths, Global Chief Product Officer, UM. “By predicting the rise and fall of consumer demand across categories, and the magnitude and shape of that demand, we are able to advise brands on when and how to re-enter the market in both the short- and long-term, with the goal of future-proofing their businesses during this uncertain time.”

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COVID-19global marketingInsuranceIPG MediabrandsMedia AgencyNewsUM
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