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Michael Margolis (UX Research Partner at Google Ventures)01 December 2024

Identify your bullseye customer in one day

5Frameworks
15Insights

Frameworks in this episode

Marketing4 steps

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

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Communication3 steps

Humble Inquiry Interview Mode

Interview to learn, not to sell — lower your status, smile, and weight past behavior over stated intent

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Innovation3 steps

Multi-Prototype Comparison Testing

Show three distinct concepts instead of iterating one, so users can compare and you avoid over-commitment

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Innovation6 steps

The Bullseye Customer Sprint (5 + 3 in 1)

Interview five hand-picked customers against three prototypes in one team-watched day to learn who to build for

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Leadership5 steps

The Team Watch Party

Whole team watches interviews live, predicts first and debriefs after, replacing the research report with instant alignment

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Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Hot Take· 3

Hot Take26:00

Your Bullseye Should Feel 'Comically Narrow'

Teams instinctively resist narrowing because they don't want to exclude a big market. Margolis pushes them the opposite way — the target should feel comically narrow so the whole team is convinced these exact people will want the product. If you can't find anyone thrilled it exists, that itself is a warning sign.

  • Narrowing reduces variables so you actually learn something from interviews
  • Too much variation produces mushy, inconclusive results
  • The narrow group is for research, not necessarily who you ultimately sell to
  • Inability to find thrilled people is a signal the product may not be needed

“comically narrow is exactly what it is”

Michael Margolis · 26:30

“this is your chance to find the most thrilled people the most specifically pained and if you can't find that that's a problem”

Lenny · 37:30
#targeting#customer-research#startups
Hot Take52:00

Learning Mode vs. Selling Mode: The Art of Humble Inquiry

Margolis draws a sharp line between selling and learning. Borrowing Edgar Schein's 'humble inquiry,' he argues research requires vulnerability — asking instead of telling, and giving the other person higher status. This is hard for founders wired to pitch, but it's fundamentally different from a sales conversation.

  • Humble inquiry = the gentle art of asking instead of telling (Edgar Schein)
  • Learning mode requires being vulnerable and admitting you don't know
  • Founders in constant pitch mode find this genuinely difficult
  • Selling and telling is distinct from learning and inquiry

“humble inquiry is the gentle art of asking instead of telling”

Michael Margolis · 52:30

“there's something that's very distinct here about learning mode versus a selling mode selling and telling versus kind of this idea of humble inquiry”

Michael Margolis · 54:00
#interviewing#mindset#customer-research
Hot Take56:30

Use Competitors' Products as Free Prototypes

Margolis is surprised more teams don't test competitors' existing products as ready-made prototypes. Some feel it's cheating or fear copying, but he argues that if you haven't watched real people react to your competitors' products, you're missing critical information. It's a free way to expand the range of value props you compare.

  • Competitor products work as zero-cost prototypes in a comparison test
  • Teams often avoid this out of a sense it's 'cheating'
  • Not just using a competitor — watching how people respond to it
  • Skipping this leaves an obvious knowledge gap

“ideally I can find produ uh competitors products and use those as free prototypes”

Michael Margolis · 56:30

“if you haven't studied your competitor's products and not just gone through it but like seen how people respond to them you're just missing something”

Michael Margolis · 57:00
#prototyping#competitive-research#product

Explainer· 5

Explainer09:00

What a Bullseye Customer Is (and How It Differs from Your ICP)

A bullseye customer is the narrow subset of your target market most likely to adopt first, and it is deliberately more specific than a typical ICP. Margolis frames it as a research construct for learning, not the final market you will sell to. Even huge companies started tiny and focused before expanding.

  • Bullseye = the very specific subset most likely to initially adopt your product
  • It is usually narrower than the ICP or personas founders show up with
  • Focus streamlines what you build, whose feedback you prioritize, and team alignment
  • Amazon started with books, Facebook with college profiles — success starts narrow

“a bullseye customer is the very specific subset of your target market who initially is most likely to adopt your product or service”

Michael Margolis · 09:00

“Amazon started just selling books or Facebook was just profiles for college students”

Michael Margolis · 10:00
#icp#customer-research#startups#product
Explainer17:00

Why You Test Three Prototypes Instead of Iterating One

Margolis compares showing customers multiple prototypes to shopping for a couch — a single option only gets an isolated opinion, but comparing several surfaces sharper reactions and trade-offs. Multiple prototypes also stop teams from over-committing to a single idea they've polished, keeping them neutral and objective.

  • One prototype gets an opinion; comparing several gives reference points
  • Customers aren't asked to imagine alternatives — you present them
  • The goal isn't a winner, it's the best pieces across options
  • Multiple prototypes prevent teams getting too wed to one idea

“let's shop for a couch I like the color the cushions are uncomfortable I like the fabric or not”

Michael Margolis · 17:00

“the other big benefit of having multiple prototypes is it helps teams avoid getting too wed to one specific idea”

Michael Margolis · 18:00
#prototyping#product#customer-research
Explainer39:30

Trigger Events: What Makes Someone Actually Ready to Buy

Beyond inclusion and exclusion criteria, Margolis emphasizes triggers — specific events that make someone ripe for a solution right now. With a life-insurance client targeting millennials, everyone said they 'should' buy it, but the real bullseye were people with a trigger like a new baby or marriage. The trigger flips a vague someday into an active to-do.

  • Triggers are events/situations that make someone ready or ripe to buy
  • Examples: a new CSO revamping tools, or something going wrong
  • Life-insurance: 'I should' buyers vs. those triggered by a baby or marriage
  • The trigger puts the person in a completely different, active mindset

“these triggers are specific events or situations that somebody's been in that makes them particularly ready or ripe for the solution”

Michael Margolis · 40:00

“people who had the trigger was oh you just had a baby or you just got married”

Michael Margolis · 41:00
#targeting#jobs-to-be-done#customer-research
Explainer1:13:30

Have the Team Predict Outcomes to Beat Hindsight Bias

Before the interviews, Margolis makes the whole team write down specific predictions of what they'll learn. Afterward, comparing results to those predictions counters hindsight bias — the tendency to feel 'we already knew that.' It proves how much was actually learned and helps demonstrate the value of doing research.

  • Everyone predicts specific outcomes before interviews start
  • Predictions must be concrete, not vague
  • Hindsight bias makes findings feel obvious after the fact
  • Comparing before/after proves real learning happened

“we do this thing before the watch party where we get everybody to predict what they think they're going to learn”

Michael Margolis · 1:14:00

“there's this hindsight bias that happens which is as you've gone through the process it's very difficult to remember what you didn't you know that…”

Michael Margolis · 1:15:00
#research-methods#cognitive-bias#teams
Explainer1:16:30

The Curse of Knowledge: Expert Teams' Common Blind Spots

Across many businesses, Margolis sees the same mispredictions, which he attributes to the curse of knowledge — deep experts can't imagine others not knowing what they know. This produces recurring blind spots: overestimating how much customers understand, how big a problem they think it is, how much they'll pay, and how ready they are to buy.

  • Curse of knowledge: experts can't imagine others' ignorance
  • Teams overestimate what customers know about the problem
  • They overestimate willingness to pay and readiness to buy
  • These blind spots recur across many expert teams

“when somebody has deep expertise it's very difficult to imagine that other people don't know what you know”

Michael Margolis · 1:17:00

“there's an overestimation of how much your customer knows about the thing”

Michael Margolis · 1:17:30
#cognitive-bias#customer-research#product

Story· 3

Story29:00

The Specialty-Meds Delivery Case: Narrowing to Refrigerated Prescriptions

A company building a delivery service for specialty medications assumed the key need was ASAP delivery. Interviews revealed the real bullseye cared far more about a predictable, narrow delivery window — driven by scenarios like refrigerated 'cold chain' meds or theft risk. Re-running the sprint on that subset produced a much sharper product-need match.

  • Initial assumption was speed/ASAP delivery mattered most
  • Real signal: a predictable, narrow arrival window mattered more
  • Critical scenarios were refrigerated meds and theft-prone situations
  • Re-recruiting on the refrigerated subset revealed the true bullseye

“it's a refrigerated medication this can't be sitting out on my stoop right it's cold chain”

Michael Margolis · 32:30

“there's this very narrow specific group who's much more likely to adopt this than like everybody who has specialty medications because the need is just…”

Michael Margolis · 34:00
#case-study#customer-research#healthtech
Story35:30

Killing a Project and Learning What 'No' Looks Like

A founder ran three rounds of the sprint on a complex hardware-plus-software product and ultimately killed it — which he called hugely valuable for saving time and effort. The second, subtler benefit was learning to recognize polite, neutral 'encouraging' feedback as a real no. Avoiding building something nobody wants is arguably the biggest payoff.

  • Cheap prototypes killed a big, complex build before it wasted resources
  • The founder learned to recognize what a genuine 'no' feels like
  • Neutral, encouraging feedback often masks disinterest
  • Saving a team from a wrong path is huge for everyone

“it killed the project that was super valuable to him he saved a huge amount of time and effort”

Michael Margolis · 36:00

“now I know what no looks like”

Michael Margolis · 36:30
#validation#customer-research#startups
Story1:07:30

Putting On Your 'Listener Character' Before an Interview

Interviewing well is a hard, practiced skill, not just talking to people. Margolis deliberately shifts into a different mode before each interview — a deep breath, a smile, and his 'listener character' of extreme curiosity and focus, quite unlike his normal skeptical self. It's so distinct his kids have overheard and asked who that person even is.

  • Interviewing is a practiced skill, not innate
  • He resets with a breath and a smile before each session
  • Adopts a 'listener character' of curiosity, unlike his cynical default
  • Smiling changes your voice even on the phone; look for a smile back

“before I start an interview I stop I take a deep breath and I kind of put on that smile and I put on my…”

Michael Margolis · 1:08:00

“if my kids like have overheard like who is that dude because that does not sound like Dad”

Michael Margolis · 1:08:00
#interviewing#mindset#customer-research

Tool· 1

Tool45:30

Recruiting Fast with User Interviews and Respondent

For most recruiting, Margolis relies on services like User Interviews (userinterviews.com) and Respondent, posting a screener questionnaire and getting responses in three to four days. He notes they're far more legit and faster than old methods like Craigslist. Hard-to-reach people (e.g. oncologists) need snowball recruiting or targeting forums and conferences instead.

  • User Interviews and Respondent are his go-to panels
  • Can recruit surprisingly specific people in 3-4 days
  • Sometimes 400+ responses roll in to sift through a spreadsheet
  • Very hard-to-reach roles (oncologists) require snowball/forum recruiting

“I Rely pretty heavily actually on user interviews um respondent is another one of these kind of services”

Michael Margolis · 45:30

“no user interviews is much more legit and very fast”

Michael Margolis · 47:30
#recruiting#tools#customer-research

Takeaway· 3

Takeaway54:30

Pay Participants Enough That They Actually Show Up

With five booked sessions and a whole team watching, no-shows are costly, so Margolis compensates generously rather than handing out $20 Starbucks cards. Consumer sessions run about $125/hour (a standard he inherited from Alphabet), and professionals like attorneys get their hourly rate — around $400/hour. He also doesn't use backups; he swaps out anyone who goes unresponsive beforehand.

  • Underpaying invites no-shows when the whole team is queued to watch
  • ~$125/hour for typical consumer participants
  • Up to ~$400/hour for professionals like attorneys
  • No alternates — he swaps out ghosting participants ahead of time

“I'm not giving $20 Starbucks cards because somebody's going to blow you off”

Michael Margolis · 54:30

“I was paying like 400 bucks an hour for them to show up but I I need them to show up”

Michael Margolis · 55:00
#recruiting#incentives#customer-research
Takeaway58:00

Keep Prototypes Flat — Don't Get Seduced by Fancy Builds

The prototypes are just simple PDFs — flat, no functionality — because the exercise is really a writing task: crisply articulating the distinct value prop, brand promise, and problem solved. Even as AI makes rich prototypes easy, Margolis warns against it; building more than you need re-introduces over-commitment and distracts from the actual question.

  • Prototypes are flat PDFs with no functionality
  • It's a writing exercise about value prop, not design polish
  • Build only as much as needed to answer the question
  • Fancy AI prototypes risk over-commitment and distraction

“they're just PDFs really it's very flat there's no functionality”

Michael Margolis · 58:00

“build only as much as you actually need to answer the question you're trying to answer”

Michael Margolis · 59:00
#prototyping#product#value-proposition
Takeaway1:22:00

Trust Past Behavior Over What People Say They'll Do

Margolis weighs people's actual past experiences far more heavily than their predictions of future behavior. When someone enthusiastically says they'd use a prototype but it contradicts their described history, he stays skeptical — everyone is terrible at predicting their own actions. Watch for genuine excitement and guard against confirmation bias in the room.

  • Anchor on demonstrated past behavior, not stated intentions
  • People are unreliable at predicting what they'll do
  • Discount enthusiasm that contradicts a person's actual history
  • Look for real excitement; police confirmation bias on the team

“put more weight on past experiences than on people's predictions of what they would do”

Michael Margolis · 1:22:00

“we're all terrible at this predicting what we're going to do”

Michael Margolis · 1:23:00
#research-methods#cognitive-bias#customer-research