How murky has COVID-19 made retail data?
COVID-19 has made past purchasing data less relevant, impacting everything from loyalty program strategies to AI-driven product recommendations, personalized emails and merchandising decisions.
A few columns and blogs have explored the challenges marketers are having extrapolating pre-pandemic shopper intelligence to assess purchasing patterns as consumers have sheltered at home. Purchasing behavior amid the pandemic has also been too erratic to offer much future insights.
“In our post-stay-at-home reality, companies need to recognize that their existing predictive models, forecasts, and dashboards may all be unreliable, or even obsolete, and that their analytic tools need recalibrating,” Angel Evan, president at Particle Inc., a data analytics firm, wrote in a column in Harvard Business Review. “Although the objectives of a specific automated system or predictive model may not have changed, the input data and the users certainly have, which should cause companies to re-evaluate how outputs are interpreted and relied upon.”
Bryan Pearson, former CEO of LoyaltyOne and currently a strategic advisor, wrote in a Forbes column, “COVID-19 is causing consumers to change their once-predictable purchasing behaviors dramatically, and in doing so it’s undermining the traditional statistical modeling retailers use to help frame their inventories, merchandising and marketing.”
Will Douglas Heaven, senior editor for AI at MIT Technology Review, wrote, “What’s clear is that the pandemic has revealed how intertwined our lives are with AI, exposing a delicate codependence in which changes to our behavior change how AI works, and changes to how AI works change our behavior.”
Gary Saarenvirta, founder and CEO at Daisy Intelligence, an AI platform, wrote in a blog entry, “COVID-19 has broken customer shopping habits and historical trends. Retailers will not be able to rely on historical trends to understand the current landscape and adapt to ongoing change. Predictive modeling, by extension, will become less and less relevant. However, successful retailers will still need to invest in the ability to scenario plan with agility in order to run their businesses profitably.”
- Retailers Face a Data Deficit in the Wake of the Pandemic – Harvard Business Review
- Is Covid-19 Stymying Retail’s Intelligence – And Making AI More Critical Than Ever?- Forbes
- COVID-19: The End of Predictive Analytics in Retail – Daisy Intelligence
- Our weird behavior during the pandemic is messing with AI models – MIT Technology Review
- Has the pandemic changed shopping behaviors forever? – RetailWire
DISCUSSION QUESTIONS: What challenges have sudden behavior changes caused by COVID-19 put on leveraging shopper data? Can marketers correct accordingly? Do you see long-term implications?