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Decision-grade B2B research for technology, SaaS, cybersecurity, cloud, devtools, fintech, healthtech and vertical software.

What's different about B2B tech research

Three things make B2B tech research different from generic B2B research.

  • Buyer sophistication. Technical buyers will see through marketing positioning faster than buyers in most other sectors. Research has to be sharper or it gets dismissed.
  • The three-layer decision. IT decision-makers, business buyers, and end users frequently disagree. Research has to capture all three or it misses the real reason a deal moved or stalled.
  • The category-creation problem. A lot of B2B tech sells into categories that don't fully exist yet. Standard category research is the wrong tool. We use a different frame for category-creation work.

The questions we settle in B2B tech

  • Is the category real? Especially for AI-native, dev-platform and security categories built in the last 24 months.
  • What's the buying committee actually doing? The committee in the slide vs the committee in the deal.
  • Why are we really losing to the alternative we keep losing to? Almost never the reason in the CRM.
  • Will the buyer pay this much? Willingness-to-pay tested at unit-economic resolution, not benchmarked from comp.
  • Where is the buyer actually getting their information? Channel reads that don't assume tech buyers all live on the same five sites.
Tech buyers will dismiss marketing-grade research in one screen. Decision-grade is the bar.
How we frame B2B tech work.
Frequently asked

B2B tech research, questions.

How is B2B tech research different?

Buyers are sophisticated, often technical, and increasingly cynical about vendor marketing. The research has to be sharper: tighter screening, more technical depth in interviews, more sensitivity to the gap between IT decision-makers, business buyers and end users.

Which categories do you cover?

Enterprise SaaS, cybersecurity, cloud infrastructure, devtools, dataops/analytics, fintech, healthtech, vertical SaaS, AI infrastructure, and the platform layer below them. We screen out vanity coverage in categories where we can't reach decision-makers credibly.

What's your view on synthetic AI audiences in tech research?

Useful for early screening and message testing. Not yet usable as the sole evidence base for decisions where the buyer reasoning matters. We use AI to accelerate the work; we don't use it to replace the buyer.

Do you do PMF research for early-stage tech?

Yes, typically Decision Briefs for Series A/B companies testing message-market fit, ICP and willingness-to-pay. Lighter than a full enterprise engagement but framed the same way.

How do you reach senior tech buyers?

Hand-screening, founder/operator networks, ex-colleagues of buyers, peer introductions, and a long-built recruiter network. We do not panel-tag.

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