In the Better data in practice podcast, published today, panellists from The Financial Times, Ipsos and Kantar joined host Liam Kay-McClean to discuss examples of better data in practice and what lessons they could teach the wider insight industry.

The podcast follows on from the recent launch of the MRS Campaign for Better Data to help the sector evolve standards and reinforce public trust in research.

Speaking on the podcast, Jessica McCarthy, senior researcher at The Financial Times, said that new technology in the industry, such  as tools using AI and synthetic data, created a need for new forms of regulation.

“With this technological advance, we also need governance, and we need to agree at an industry level what that means for us, how we are going to implement it and how we are going to communicate it,” McCarthy said.

She added that the market research sector would need to evolve to meet the challenges of new technology, adding: “We’re constantly a work in progress. We’re constantly evaluating where we are at, where we can improve, things that have changes in the past couple of years and where the technology is enabling us to go next.”

You can listen to the podcast here:

Also speaking on the podcast, Eileen Irvin, co-head of Ipsos in the UK’s Survey Research Methods Centre, said that there needed to be a renewed focus on survey design principles in a world where it is easier than ever to build surveys, arguing that “there is something about coming back to good questionnaire design principles; I think to some extent we have lost that a little bit”.

Irvin also referenced changing public attitudes: “People’s expectations of surveys are higher than they used to be because they are doing more of them. They have a greater expectation that the idea of being asked for their opinion doesn’t mean as much as they used to, as it happens all of the time.”

James Lavell, general manager at Kantar Profiles, told the podcast that market research faced a challenge in engaging participants, saying: “The position of competing for eyeballs is getting ever harder, and that’s down to the busy world we now live in.”

He added that while synthetic data had its place in the industry, there was a need for a strong approach to data practices for the technology to be effective.

“You have to have your foundations in good quality data to put synthetic models on top,” Lavell said. “Those models have to be monitored, and as we go through the next few years, I think it’s ‘adopt with caution’. We have seen some players in the market try to do 100% synthetic, and I feel that’s a step too far.”