Overview
IBM's Cloud, Data, and AI research organization supports more than 30 product teams. For Eric Mahlstedt and his colleagues, the hard part wasn't running studies - it was finding the right people for them. Recruiting niche technical professionals, like robotic process automation developers, took weeks and came with high dropout rates that delayed insight to product teams.
In a competitive market, that lag has a real cost. Slow sourcing means slow findings, and slow findings mean decisions get made without the research that should inform them.
In their words
With Respondent, IBM's researchers screen and recruit specialized participants quickly and interview them throughout the entire product lifecycle - from market sizing and segmentation to ongoing qualitative feedback. A well-built screener turns weeks of sourcing into a couple of days, and incentive processing is handled at enterprise scale.
Why it works
Respondent is built around a panel of verified participants who joined directly - not aggregated or resold. For an enterprise research org, that means reaching hard-to-find technical audiences fast, with less dropout and more time spent on insight. IBM's research team has grown from 5 to 80+ researchers in five years as feedback became continuous across the product lifecycle.
