Technology, expertise and high-quality audience matter more in the age of AI

Abstract

The insights trifecta brings together three interconnected pillars of research: technology, research expertise and access to high-quality audiences. By aligning these capabilities, organizations can improve participant engagement, strengthen data quality and use AI more effectively to turn research findings into actionable insights.

Bringing research together

Editor’s note: Jennifer Reid is the co-CEO and chief methodologist at Rival Group, the parent company of Rival Technologies, Reach3 Insights and the Angus Reid Group. A pioneer in online research methodologies, Reid is helping shape the future of insights by leading the change in the development of mobile-first communities and other conversational research approaches. Find Reid on LinkedIn.

The insights trifecta is a useful way to think about three parts of research that have traditionally been treated as separate specialties: technology, research expertise and access to high-quality audiences.

Decisions about respondent recruitment and engagement affect the quality of the data collected. Research expertise shapes how those findings are interpreted and applied. Technology influences every stage of the process, from how research is designed to how people participate. Looking at these capabilities together makes it easier to see how much they influence one another.

For years, the industry largely treated these functions as separate specialties. Technology providers concentrated on building platforms, sample providers managed audience access and consulting teams focused on helping clients interpret findings and make decisions. Each plays an important role, but the connections among them become increasingly important as research becomes more technology-driven.

Why audience relationships matter

Respondent quality has become one of the most discussed topics in research, particularly as the industry continues to address fraud, bots, synthetic responses and survey farms. Those issues deserve attention, but they can sometimes overshadow another reality: the “good” people are easy to lose.

Research now competes with every other digital experience for attention. Participants move between social media, streaming platforms, messaging apps, gaming and countless other forms of content throughout the day. If participating in research feels repetitive, inconvenient or disconnected from the way people normally communicate, engagement drops.

The effects are usually visible in the data. Researchers start seeing shorter open-ended responses, less context and higher dropout rates, while spending more time trying to determine whether the feedback reflects genuine opinions or participants who have mentally checked out of the survey.

This is one reason conversational approaches, mobile-first experiences, video feedback and AI-powered probing have gained so much attention. Better experiences for participants often lead to better information for researchers. When audiences are viewed as a long-term asset rather than simply a source of survey completes, decisions about recruitment, engagement and respondent experience start to look very different.

What changes when technology and consulting sit closer together?

Researchers who work closely with product and engineering teams can help shape tools around real research challenges while gaining a better understanding of where technology can improve the work and where human judgment remains essential.

A program with Weber-Blackstone offers one example. Conversational communities, audience management and consulting expertise helped a small internal insights team support research across four countries while strengthening engagement among younger grillers. The approach brought decisions about research design, participant experience and technology together from the outset rather than addressing each separately.

The same principle can apply to other types of research. A syndicated study, for example, may require researchers to think simultaneously about who should participate, how to engage them, which methods will capture the necessary depth and how technology can make the process more efficient. Treating those as connected decisions can influence both the quality of the research and how quickly teams can act on it.

AI raises the stakes

Much of the discussion around AI focuses on speed. Translation, coding, synthesis and early stage analysis can now happen much faster than they could only a few years ago, allowing researchers to spend less time on repetitive tasks and more time interpreting findings, advising stakeholders and exploring implications.

Across different types of research, the same pattern keeps emerging. Decisions about technology affect audience experience, audience experience affects the quality of the data and research expertise determines how those findings are interpreted and applied. That's the relationship the insights trifecta is intended to describe.

One of the biggest lessons has been that improving any one of those areas in isolation only takes you so far. New technology delivers more value when researchers are closely involved in shaping how it's used. Better audiences become even more valuable when the participant experience encourages thoughtful responses. AI becomes more useful when it's supported by strong research design and data that researchers trust. As more organizations introduce AI into their research workflows, those connections deserve just as much attention as the technology itself.