Consumers have changed the way they buy, what they buy, and how they research products because of the COVID-19 pandemic.

For instance, loyal customers of a certain brand of smart devices may switch to a different company because the brand’s smart watches have been out of stock due to supply chain issues. Changes like this in customer loyalty and behavior are having major impacts on the relevance of consumer data collected before the pandemic that marketers are using to make business decisions today.

That’s why marketers need to collect new data in a post-pandemic consumer landscape, using new approaches and technologies, according to two marketing experts at Penn State.

J. Andrew Petersen
Chelsea Hammond

Drs. J. Andrew Petersen and Chelsea Hammond, who are on the marketing faculty of the Penn State Smeal College of Business, shared their insights about post-pandemic customer data and analytics during a webinar, Marketing Analytics in the Post-Pandemic World. The webinar, which requires registration before viewing it on-demand, is aimed at anyone who is working with market research or making business decisions from data. 

“We can’t just do business as usual with analytics, and our forecasts aren’t going to be as good as they used to be if we use the same old approach and data,” said Petersen, an associate professor of marketing. “This post-pandemic world is going to make us get to know our customers again, understand them through primary, survey-based research or secondary research that’s current and relevant.”

Petersen and Hammond teach in the Master’s in Marketing Analytics and Insights program that is offered by the Smeal College of Business exclusively online through Penn State World Campus. The two talked about how marketers should collect new data and use innovative tools, like machine learning, to gain fresh insights into the post-pandemic consumer landscape.

Changes in the consumer landscape

Petersen said that before the pandemic, the historical data about consumers could reliably help marketers predict what would happen in the future. But the predictive analytics are not so predictive anymore, because of a broad array of changes caused by the pandemic.

The changes in business processes, such as investments in e-commerce, and the disruptions to supply chains have forced consumers into new habits when they are researching products and when they are buying and changed their overall expectations of the experience.

“You need to go back to and think about what people are doing right now and why people are doing those things, and that’s going to involve capturing new data that’s relevant to today,” Petersen said.

Today’s predictive models need new data

A way that businesses can begin to replace their pre-pandemic predictive data is by focusing on collecting data about key areas but with new lenses. 

Businesses need to understand how post-pandemic issues and changes are impacting consumer attitudes and behaviors. Marketers should capture data on these impacts, such as how lagging product availability is influencing consumer switching behaviors. Businesses need new descriptive and prescriptive data to make predictive models more accurate.

“Ultimately we can take these descriptive and prescriptive measurements and use them to recalibrate our predictive analytics,” said Hammond, an assistant clinical professor of marketing.

Machine learning and marketing analytics

Some marketers may not be in a position to pay for time-consuming and expensive research studies to get descriptive and prescriptive data, and Petersen and Hammond described in the webinar how machine learning can provide a solution to that.

An example that Petersen discussed is using machine learning to analyze the text of online customer reviews to understand current consumer needs and sentiments. Machine learning can parse the text and identify topics and associated words, and marketers can draw insights from the tool’s analysis.

“This helps you get good descriptive analytics but with minimal cost,” Andersen said.

The online Master’s in Marketing Analytics and Insights at Penn State

Prescriptive and descriptive analytics and the other topics explored in the webinar are included in the curriculum of the Master’s in Marketing Analytics and Insights program. 

The 30-credit degree program can help marketers learn to leverage their company’s data to gain meaningful insight into marketing communications, customer experience, and brand management.

Register to watch the on-demand recording of the webinar on the On24 website for Penn State World Campus to learn more about capturing new customer data in a post-pandemic consumer landscape.