Brands seeking to understand consumers in the recession that is expected to follow the spread of COVID-19 will need to update their research playbooks, the chief executive of Nielsen has argued.

David Kenny, CEO/chief diversity officer at the global research firm, discussed this subject on a webinar held by the Interactive Advertising Bureau (IAB).

The “inevitability” of a recession means that measurement practitioners need to be “a lot smarter about how they plan, and do it more effectively”, he argued.

And that process, he proposed, will require leveraging Census- and panel-based programs that together offer a rich blend of information.

“There’s a lot you can do with Census [data],” said Kenny. (For more, read WARC’s in-depth report: Nielsen chief pins down “new-normal” media-measurement theories with new-life realities.)

“We bring in a lot of big data … but bringing that [information] back to a representative panel is the only way to make sure everybody was counted – [and] to ensure that there aren’t biases in the data.”

Another vital consideration, he suggested, is that measurement solutions which rely on households owning high-end technology will not be sufficient on their own.

“In the post-COVID period … a lot of folks are going to be on the wrong end of the economic pyramid and we don’t want to lose them in the [measurement process],” said Kenny. “We need to make sure that everybody, not just the most tech-enabled, is counted.”

Existing models, he continued, also rely on past behaviour, which may not apply in the new environment. “Patterns are changing so quickly that we can’t rely on those models,” Kenny said.

“And I know, for sure, that what we measure during COVID-19 is not going to be representative of before or after.”

While panels are one of the research industry’s legacy propositions, their importance cannot be underestimated. “The only way we can only get to full people is through a panel,” Kenny said.

To that end, he announced, “We're doubling down on investment in panels. We need big data to actually get to scale, but panels need to interpret that big data.”

Sourced from WARC