Comically-Narrow Bullseye Definition (Inclusion / Exclusion / Triggers)
Narrow your target to ~seven concrete attributes across three buckets so everyone agrees these people will say yes
- Difficulty
- Easy
- Time to result
- ~days to results
- Steps
- 4
- Confidence
- 90%
A method for defining who to research and build for by narrowing to roughly seven measurable attributes grouped into inclusion criteria, exclusion criteria, and triggers. The goal is a segment so specific the whole team agrees these people would want the product — reducing variables so the research reads clearly. This 'bullseye' for learning is deliberately narrower than the eventual go-to-market ICP.
Origin
Michael Margolis' bullseye framework from 'Learn More Faster', refined across 300+ GV sprints. The 'comically narrow' framing is credited in-episode to Andy Johns (via a Lenny newsletter post). Triggers draw on Jobs-to-Be-Done thinking.
Core principles
- 01Narrow the segment to reduce experimental variables, not to size a market
- 02Concrete, measurable attributes beat vague ones ('buys 3x/week', not 'active shopper')
- 03The bullseye for research is narrower than your business's actual ICP
- 04Exclusion is where teams need the most help because setting people aside is uncomfortable
- 05Triggers — specific events that make someone ready to buy — are the most under-appreciated attribute
How to run it
- 1
List inclusion criteria
Name the characteristics that put someone in the group — conditions, behaviors, product usage. Teams find this easy because it's who they already want.
Pro tip Include adjacent-behavior signals (e.g. 'has used Uber Eats') that indicate readiness to accept your model.
- 2
Brainstorm exclusion criteria
Deliberately dwell here: exclude people with too much expert knowledge (not typical), those locked into a competitor, or those with disqualifying personal/professional experience.
Pro tip Exclude domain experts like pharmacists for a consumer medication product — they aren't your typical customer and waste a precious interview slot.
Watch out Teams resist excluding people; force the brainstorm or your five slots fill with atypical or non-representative participants.
- 3
Identify triggers
Name the specific events or situations that make someone ripe for the solution right now — a new CSO revamping security, something going wrong, or a life event like a new baby or marriage for life insurance.
Pro tip A trigger flips someone from 'I should get around to this' to 'this is on my to-do list' — that person is your true bullseye.
- 4
Converge on ~seven attributes and pressure-test findability
Settle on roughly seven concrete attributes the team agrees on, then try to recruit against them. Use the attribute checklist (new vs existing user, industry, org size, competitor usage, disqualifying experience, title/role, geography, buyer vs end-user, budget/income, life/work setting, trigger, VIP value).
Pro tip The 'VIP' attribute = ask 'what makes one customer more valuable to us than another?' to surface a distinguishing pattern.
Watch out If the people are impossible to find or reach, that itself is a red flag about the business, not just the screener.
In the wild
An insurance-tech company targeting Millennials found everyone said 'I should buy life insurance' but only people with a recent trigger — a new baby or a marriage — actually treated it as an active to-do.
→ The trigger event, not the demographic, defined the real bullseye customer in a buying mindset.
Lenny listed early ICPs of Gong, Linear and Vanta as impressively narrow; Margolis argued they're still too broad for research and would go deeper into concrete, measurable attributes to tease people apart for recruiting.
→ Reinforced that the research bullseye must be narrower and more measurable than a company's stated go-to-market ICP.
Common mistakes
Skimping on exclusion criteria
Because it's psychologically hard to set people aside, teams under-specify exclusions and end up interviewing atypical experts or competitor-locked users who muddy the signal.
Using vague, unmeasurable attributes
Attributes like 'active shopper' can't be translated into a screener; without a concrete definition (e.g. purchases 3x/week) you can't reliably identify true bullseyes.
Is it for you?
Best for
Founders or PMs who describe their customer in vague shorthand and need a rigorous, recruitable segment definition before research or launch
Not ideal for
Products with a genuinely undifferentiated mass market, or when you've already validated the segment and need scale rather than focus
From the transcript
“it should feel comically narrow”
“there are inclusion criteria there are exclusion criteria and then there are what we found is very important are triggers”
“these triggers are specific events or situations that somebody's been in that makes them particularly ready or ripe for the solution”
“it's probably gets down to yeah it's more like seven rough”
From the episode
Identify your bullseye customer in one day
Michael Margolis (UX Research Partner at Google Ventures)