How to use data before screening begins
Editor’s note: Rachel Cope is managing director at Business Advantage, a global B2B research and data consultancy, having worked in the B2B sector for several decades. She is a certified member of the Market Research Society, sustaining member of Wire and an industry mentor. Find Cope on LinkedIn.
In a previous article, I looked at why job titles are often a poor guide to who makes B2B decisions, and why that pushes screeners to become longer and more carefully constructed.
Most of the time, that's exactly the right approach. Researchers who know their markets well can write good screening questions and get on with recruitment, and it's what I've done for most of my 20 years in B2B research. Why reinvent the wheel?!
But there's more we can do before a single screening question is even written to help us understand the market we’re researching. Enter the role of data. Used well before screener design begins, business data lets a research team:
- Map the stakeholder ecosystem around a decision, rather than simply searching for people with matching job titles.
- Identify who is likely to influence, evaluate, approve, use or block a decision.
- Validate contacts against company size, industry, reporting structure, technology stack and business function.
- Draw on intent data and behavioral signals to find organizations and individuals actively researching a given topic, technology or business challenge.
- Build a global view of a market and its buying dynamics, even when the research itself only covers a handful of countries because of budget or timing constraints.
This is an invitation to think about the data your own organization, or your clients, already hold and the ways you might use it to understand more about the businesses and industries you're researching before you get anywhere near a screener.
Job titles will keep being an unreliable shorthand for who really matters in a B2B decision. But between careful, well-briefed screening and a stronger data foundation, it's possible to consistently find (and speak to) the people who shape the outcome.
Let’s take a software vendor evaluating a shift to usage-based pricing as an example. "Head of pricing" or "VP finance" may seem to be suitable decision makers to target. But layer in firmographic and technographic data, and a better picture emerges: which companies have recently changed billing systems; who sits across finance, product and customer success in organizations of a similar size; and which of those individuals show intent signals around pricing strategy. That's a materially different, and more defensible, sampling frame than titles alone could ever produce… and all before a single screening question has been written.
Better recruitment, better insight
Identifying and prioritizing the right organizations and stakeholders from the outset can have a direct payoff: shorter recruitment timelines, lower costs, better incidence rates and less risk of interviewing the wrong people altogether. Target the wrong person and you might not be researching the right decision makers for your study, so it’s well worth thinking about.
The result is what every B2B researcher is ultimately after: higher recruitment success rates, more accurate insight and greater confidence that the findings genuinely reflect how decisions are made in the market you're studying.