In this episode, Brian and Andrew sit down with Dan Entrup, co-founder of AggKnowledge, to talk about one of the most overlooked drivers of the data quality crisis: the respondent experience nobody is actually fixing.

Dan tracked every research outreach he received over 15 months and turned it into a SampleCon presentation. The numbers were brutal. 137 times asked his age. 57 dental requests sent to someone who has never been a dentist. An inbox so flooded with irrelevant surveys that even a motivated expert panelist nearly quit. His point is sharp: bad targeting is not just inefficient, it is actively killing the panels we depend on.

The conversation gets into what AggKnowledge is building to solve it upstream, why free-text profiling and stale data are quietly sabotaging research operations at scale, and why identity verification and workplace verification are not the same thing. There is also a candid take on the M&A and funding landscape, who is well-positioned, where the yellow flags are, and why human knowledge only gets more valuable as AI takes over everything else.

Key Takeaways:

• Why bad targeting is a fraud accelerant, not just a waste of budget

• What 15 months of tracking his own respondent experience revealed about how broken outreach really is

• Why the gap between identity verification and workplace verification is where embellishment hides

• How upstream profiling data can reduce fraud before a screener is ever sent

• Why companies beating on revenue are still seeing their stock drop, and what that signals for the research industry M&A

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• AggKnowledge

• It's Pronounced Data (Newsletter)

This episode is the bonus round to Brian and Andrew's four forces webinar. They ran out of time on the live session, so they saved the best part for here: where all four trends are actually pointing and what it means for how research gets done.

Andrew lays out the clearest version of the webinar's thesis: capital, AI, and the data quality crisis are not three separate things. They are converging forces pushing the industry toward methodologies that are more transparent, more respondent-friendly, and more operationally feasible than what came before.

From there, the conversation gets specific on async qual, AI-led conversational interviewing, and agentic research. Andrew makes a sharp argument that the next step change in automated research will not come from software companies selling AI tools. It will come from agencies building proprietary workflows trained on their own data and methodological history. The agencies that do that work now will have a moat that an off-the-shelf product cannot replicate.

The episode closes with Brian's take on four things the disruption narrative tends to get wrong, including why qual is not dying and why the trust crisis will not be solved by more technology.

Key Takeaways:

• Why the four trends are a single converging story, not four things happening in parallel

• What AI-led async qual does better than scheduled IDIs and why it matters for panel health

• Why agentic research workflows will be built by agencies from the inside, not sold to them as products

• Why qual is not dying and why AI quant cannibalises quant budgets, not qual budgets

• Why the trust crisis is a culture problem, not a technology problem

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In this special episode, Brian and Andrew bring their live webinar to the podcast feed. Drawing from recent conferences, client conversations, and industry reports, they break down four forces reshaping how research gets done: Capital Influx, the Data Quality Crisis, AI Disruption, and Methodology Reframe.

Brian's core argument is that these are not four separate trends. They are one larger story with feedback loops accelerating each other, and the industry does not get to choose whether the shift happens, only whether it leads or follows.

The episode also features a live Q&A, including a sharp exchange on whether there are research categories where AI should not be used yet, and a direct answer to how you sell quality to a client who thinks $12 CEOs are fine.

Key Takeaways:

• Why OpenAI and Anthropic’s launch of deployment consulting firms is a competitive threat the insights industry needs to take seriously

• What the latest GDQ benchmarks reveal, including a 59.6 percent post-survey removal rate in B2B

• Why the biggest fraud risk is not bots but humans using AI to fake qualifications and game incentives

• Why synthetic data still needs proof, and why every credible synthetic platform still anchors to a verified human sample

• Why the qual and quant divide has not just blurred, it has effectively disappeared

If you loved the episode, have comments, or want to appear on the show, connect with us down below!

Connect with us:

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• ROI Rocket