Articles

The near universal response when asked about current trends in MRX is AI, but a deeper dive reveals a host of other emerging topics and trends.

If it can, would such answers be representative of real consumer preferences? Let's find out...

In order to make tracker studies work harder for us, and give us faster insights, we need to be flexible enough to pivot to better ways of doing things.

New research provides insight into incentives and how changes may impact participation rates and response quality.

The first full month of spring brought with it a shiny new federal privacy bill, some developments on AI regulation, a tax win in Nebraska, a new federal ban on noncompetes, advances in preventing the government from competing with the insights industry, legislation moving in Minnesota on exit polling and political opinion research, complicated business payment disputes, and some new developments on competitive sourcing of insights services and the Census Household Panel.

A new rule from the Federal Trade Commission (FTC) prohibits almost all non-compete agreements in employment contracts.

​​​​​​​Legislation that would have taxed advertising, explicitly including ad measurement and effectiveness research, has died in the Nebraska legislature.

​​​​​​​The Insights Association (IA), the leading nonprofit trade association for the market research and analytics industry, had a mixed reaction to new draft comprehensive privacy legislation proposed in the U.S. House and Senate.

The insights industry’s public policy concerns entered March roaring like a lion, but they are not exactly leaving it like a lamb. President Joe Biden’s State of the Union address to Congress touched on a few of them, including privacy, artificial intelligence (AI) and research subjects who receive incentives. Further this month, IA is engaging with legislation and regulation on data privacy, including potential harsh restrictions on data sharing with Chinese-controlled companies and restricti...

Global Insights leaders answer this question: What do you see as the aspects or applications of AI that are overhyped and could really fool users, creating potential issues for the quality and credibility of market research?