The COVID-19 crisis is sending an extraordinary shockwave through the economy. Not only have there been significant disruptions to business activity and revenues, but stay-at-home orders have upended customers’ purchasing behavior. Which of these changes will be temporary and which will be permanent is still unknown.
This uncertainty creates a major challenge for business leaders who rely on enterprise analytics and predictive models to drive their strategic decision process. As COVID-19 invalidates statistical models that were being used to predict future customer behavior, how can enterprise leaders avoid additional revenue loss and still create personalized targeting that supports key growth strategies?
To build an effective model, you have to start thinking and acting differently. It is essential that underlying data accurately reflects the current population’s perspectives and behaviors. Even in those cases where purchase behavior has not drastically changed, the magnitude of the COVID-19 economic crisis and its impact on our broader society still need to be taken into account when trying to predict future buying behaviors.
Read this paper to discover:
- How to account for the unprecedented situation brought on by COVID-19.
- How to effectively use external data to help contextualize new predictions and forecasts.
- How to understand changes in your models and digital analytics in order to determine what actions will deliver impact for your business.