How AI is Redefining the Use of Audience Data

In a hosted by Lenny Murphy from GreenBook, industry experts Sarah Saab, VP of Product at Prolific, and our own Chief Product Officer Jessica Dubin discussed how AI is changing the way we collect and use audience data. They discussed the benefits and risks of AI, the role of synthetic (AI-generated) samples, and the future of research as AI continues to evolve. 

Keep reading for key takeaways, and be sure to watch the full recording for a deeper dive into the topic. 

The Benefits of AI in Audience Data

Undoubtedly, AI has become a game-changer in the world of research. It allows companies to collect and analyze data faster than ever before. 

When it comes to audience data, we’re seeing more AI-generated audiences. AI algorithms create AI-generated audiences by analyzing real individuals' data to produce virtual personas that mimic the characteristics of a target audience. Using an AI-generated audience, researchers can:

• Skip the recruiting process
• Get faster insights
• Gain greater access and scale

The Risks of AI in Audience Data

Altogether, AI offers many benefits, but it also comes with risks. The industry faces a major concern regarding the quality of data used to train AI models. Data scientists who use non-diverse or inaccurate training data create AI models that produce biased or unreliable outputs.

“When you want to ensure or constitutionally check or fine-tune, I think you will always want to return to reliable human beings,” Sarah said. “At the end of the day, quality is king.”

Furthermore, as AI becomes more involved in research, there are growing concerns about privacy and the ethical use of data. Consequently, it’s crucial to ensure that the data collected respects participants’ rights and complies with regulations like GDPR.

How Synthetic (AI-Generated) Sample Can Be Used

Synthetic samples, which are AI-generated responses based on real data, are becoming more common in research. These samples can be used in various ways to enhance the research process.

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Using Synthetic Sample for Practice

Remesh uses AI-generated responses for practice or demo environments. The responses are based on key demographics to make them as realistic as possible. Researchers can use these AI-generated samples to test and refine their surveys before they go live. This allows them to ensure their questions are clear and effective and also preview the conversation with stakeholders without needing to involve real participants in the testing phase.

Using Synthetic Sample to Inform Research

Moreover, synthetic samples can also inform research by providing preliminary insights. Specifically, these AI-generated responses can help researchers explore ideas and hypotheses before embarking on full-scale studies. However, while synthetic samples should not replace real human responses, nevertheless, they can be a valuable tool for this early-stage research.

Using Synthetic Sample to Augment Qualitative Research

Perhaps the most exciting use of synthetic samples is in augmenting qualitative research. By combining real participant data with AI-generated responses, researchers can scale their studies and gain deeper insights. For example, if a study has data from a few hundred participants, synthetic samples can help extend this to thousands, providing richer and more comprehensive results.

Implications for Privacy and Compliance

As AI and synthetic samples become more integrated into research, privacy and compliance are more important than ever. Companies must ensure that the data they use is collected ethically and that participants’ privacy is protected. This includes following strict regulations and being transparent about how data is used.

“Our clients keep a very high bar [for security], so that's where our bar is. We won't adopt anything until we're very sure that it's going to meet our criteria,” Dubin said about Remesh.

How Prolific and Remesh Partner to Bring Speed and Quality to Insights

Prolific finds quality, vetted research participants at scale. Prolific is integrated right within Remesh’s AI insights platform so that Remesh users can recruit, conduct, and analyze all in one easy-to-use platform. 

“With our integration with Prolific, it takes a few minutes to set up, and then it takes just hours to get participants in. It shortcuts the entire time to insights for our customers,” Dubin said. “We don't have to sacrifice speed for quality — with Prolific those two things come hand in hand.”

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What’s Ahead?

It’s an exciting time in the industry. We’re just at the tip of the iceberg when it comes to AI, and it’s already having a big impact. Here’s a look at what’s next.

Representing the entire world’s population using AI 

Looking to the future, Prolific and Remesh are working on an ambitious goal: to create a synthetic sample that represents the entire world’s population. This would allow AI systems to be trained on data that truly reflects global diversity, leading to more accurate and fair outcomes. As AI continues to evolve, this kind of innovation will be key to ensuring that research remains ethical, inclusive, and effective.

Democratizing qualitative data

As we begin to augment data sets with AI outputs, we can make rich, qualitative data faster and more accessible. Dubin said that she hopes this will make qualitative research even more accessible and that we’ll see more researchers and companies diving deeper into their research efforts.

“The mission of Remesh is to empower researchers to do high-quality research and also allow people's voices to really be heard. I think with some of our simple survey tools, you just get the abstraction. If we see qualitative research that's more of a conversation, really diving into people's attitudes and preferences, we're going to get a much richer data set and ultimately make better decisions,” Dubin said.

The Bottom Line

AI offers exciting opportunities for the research industry, but it also presents challenges that need to be carefully managed. By using synthetic samples wisely and prioritizing data quality and privacy, companies can harness the power of AI to gain deeper insights and make better decisions. The future of research is bright, and AI is leading the way.