Tasks / Product Craft

Customer research call guide

Can the model write a guide that uncovers behaviour rather than opinions?

Task type v1.0 · 2 tasksLast changed 6 Oct 2026 · ChangelogDifficulty

What AI gets right here, and what you’ll still have to catch

From 18 graded outputs by 9 models. 33% were usable with at most a quick edit.

Reliably right

  1. Asks what people did, not what they think96% pass
    Core questions ask for specific recent actions and events ('What happened next?', 'Who did you call?'), not opinions or predictions.
    Sonnet 5.5 · API · Why are warehouses leaving? Two execs, two theories
  2. Tests both theories fairly92% pass
    Both theories get questions that could disprove them (e.g., no action on robotics, happiness after slow go-live), and open-ended timeline questions leave room for a third cause.
    Sonnet 5.5 · API · Why are warehouses leaving? Two execs, two theories
  3. Different questions for user and signer92% pass
    The guide has distinct tracks: daily user questions focus on day-to-day experience and workarounds, signer questions on the decision process and alternatives.
    Sonnet 5.5 · API · Why are warehouses leaving? Two execs, two theories

Where it slips

  1. Marks what to cut if the call runs over28% pass
    The guide includes timed sections that add up to 45 minutes but does not say what to cut if time runs short, nor does it mark must-ask questions.
    GPT-6.1 Sol · API · Why are warehouses leaving? Two execs, two theories
  2. Doesn't trust the default reason47% pass
    The plan names the pre-selected default as a bias but does not use the behaviour columns to show that most 'too expensive' cancellers had stopped cooking; it only picks two contrasting individuals without the aggregate pattern.
    GPT-6 Astra · ChatGPT · Too expensive, by default
  3. Uses the supplied evidence correctly61% pass
    The claim 'Customers will say what helps their negotiation' is an unsupported behavioural statement not derived from the context.
    Haiku 5.5 · API · Why are warehouses leaving? Two execs, two theories

How it’s graded

Each check is built on how world-class product and growth leaders do this work, as they’ve described it on Lenny’s Podcast, and names the leader it comes from.

  1. Designed to falsify

    For each learning goal, does the guide include a question whose honest answer could show the team's hypothesis is wrong?

    Passes when Every learning goal has at least one disconfirming, non-leading question, such as asking about the last time they had the problem and what they did instead.

  2. Asks what people did, not what they think

    Are the core questions about specific things the person actually did recently, rather than opinions, predictions or hypotheticals?

    Passes when The core of the guide asks for recent, specific instances (the last time, what happened, what they did) and follows up on them; opinions and predictions are absent or clearly secondary.

  3. Doesn't lead the witness

    Are the questions free of leading wording, of pitching the idea, and of hints at the answer the team hopes for?

    Passes when Questions are neutral and open, and the idea is not described (or only at the very end, after the problem questions).

Plus our standard checks

Uses the supplied evidence correctly · Addresses the actual decision · Respects explicit constraints · Identifies material uncertainty · Avoids unsupported claims · Produces the required deliverable · Marks what to cut if the call runs over · and 3 written for each task, which you’ll see in the tasks below.

The tasks

Read the brief, then compare up to three outputs, each with the LLM judge’s verdict on every check. Highlights mark what a PM had to fix.

The brief

You're a Staff PM at Crate. In four weeks, the exec team decides which of two bets gets our two squads next half, and both bets rest on a theory of why customers are leaving. We have three weeks for 12 customer calls of 45 minutes. Write the guide for them. It should include: the learning goals; the questions, with timings, for the two kinds of people we'll talk to; guidance for whoever runs the calls; any changes you'd make to the plan below; and what we'd need to hear to back each bet, or neither. Keep it under 1,500 words. The exec team will read it before the calls start.

What the model was given8 items: About Crate, The decision, CEO, Ana Ferreira, CPO, Marcus Hill, Exit survey (41 churned customers, last 12 months), Implementation and CRM data, The call plan, Notes from Customer Success and Legal
About CrateWarehouse management software for mid-size third-party logistics companies (3PLs). 340 customers, $22M ARR. Gross logo churn rose from 11% to 18% over the last year.
The decisionBet A: integrations with warehouse robotics (autonomous carts, pick-assist robots). Bet B: rebuild implementation so customers go live faster. Two squads for the next half go to one of them.
CEO, Ana Ferreira“We're losing warehouses because they're automating and we don't talk to their robots. Every lost customer I've spoken to mentions it.”
CPO, Marcus Hill“We lose them in the first year because implementation takes forever. They're gone before they ever see the value.”
Exit survey (41 churned customers, last 12 months)A single-choice question, 'Why are you leaving?'. Missing features or integrations: 46%. Too hard to implement: 22%. Price: 17%. Other: 15% (free-text box, left blank by all but two). 'Missing features or integrations' was the first option in the list.
Implementation and CRM dataMedian time from signing to go-live: 94 days; the contract promises 45. Customers who went live after 90 days churned at 2.4× the rate of the rest in their first year. 3 churned customers moved to a competitor with robotics integrations; robotics was cited in 9 lost new-logo deals. We don't know when in the year churned customers decided to leave.
The call plan12 calls: 6 with customers who churned in the last 9 months, 6 with at-risk customers (health score red). On each account we want to talk to the warehouse operations manager who used Crate every day and, separately, the VP of Operations or COO who signed the contract. Ana wants to run 4 of the calls with former customers she knows personally.
Notes from Customer Success and Legal5 of the 6 at-risk accounts are in renewal talks, and Customer Success is offering them discounts. Interviewers must not discuss pricing, discounts or what's on our roadmap. Every call must start by asking permission to record.
What a strong answer doesThe answer key the graders mark against

A guide that tests both theories fairly and leaves room for a third: the goals ask what actually drove each decision to leave or doubt, when it happened, and who made it, with questions that could disprove robotics (did they automate, did robots come up before they decided, what did they switch to and why) and implementation (how long go-live took, what happened in those months, whether value arrived) alike. It treats the exit survey as weak evidence (single choice, integrations listed first, 'Other' left blank) and the 2.4× figure as a correlation to probe, not a cause. The core is a timeline of the account: the story from signing to the moment they decided to leave or started doubting, with sequential probes. It has separate tracks for the daily user (what went wrong day to day) and the signer (how the decision was made, what alternatives they weighed), fits 45 minutes with timings, and opens with consent to record. It guards the calls: no pitching, pricing, discounts or roadmap promises, with a script for when an at-risk customer asks, and it addresses Ana's bias: she has a public view and personal relationships, so she should observe or take notes rather than lead, or at minimum use the same script and have her calls read separately. It ends with decision signals: what pattern across the 12 would back Bet A, what would back Bet B, and what would back neither (price, a business change, a missing capability that isn't robotics).

Critical failures (cap the score at 40)
  • Includes questions that promise roadmap items or discuss pricing or discounts with customers in renewal talks
  • Asks customers to choose between robotics and implementation as the reason they left
Task

Staff-level · v1.3

The outputs

9 setups answered this brief.

Needs more than a quick edit11 of 13 checks passed

Must-ask questions aren't marked and there's no guidance on what to drop if a 45-minute call runs over. A PM would need to add priority markers and cut instructions before running the calls.

Output

TO: Crate Executive Team FROM: Staff PM DATE: October 24, 2023 SUBJECT: Research Guide: H1 Bet Allocation & Churn Investigation

---

1. Learning Goals

Our existing data is noisy. The exit survey suffers from primacy bias (“Missing features/integrations” is the first option and bundles robotics with basic APIs/ERPs). Meanwhile, our CRM shows a strong correlation between >90-day implementations and churn, and robotics appears more often in lost new-logo deals (9) than confirmed churn (3).

Over the next three weeks, these calls must uncover: 1. The "Point of No Return": When in the lifecycle did the customer mentally commit to leaving, and what specific operational event triggered it? 2. Implementation Reality: What caused the gap between the 45-day promise and the 94-day reality? Is slow implementation a root cause of churn, or a symptom of a deeper product mismatch? 3. The "Missing Integration" Truth: For those who cited integrations, what specific systems failed to connect? How many actually bought or deployed warehouse robotics? 4. Post-Churn Ground Truth: What did churned customers switch to, how long did the replacement take to go live, and are they using robotics today?

---

2. Recommended Changes to the Call Plan

To get unbiased data within 12 calls, we must adjust the proposed plan:

  • Split the persona tracks across 8–10 accounts (Don't double up on 12): If we interview both the VP and the Ops Manager separately on each account, 12 calls only covers 6 accounts (3 churned, 3 at-risk)—too small a sample. Instead, target 8 churned accounts and 4 at-risk accounts, interviewing the VP on 6 and the Ops Manager on 6 (overlapping on 2–3 accounts to cross-verify stories).
  • Drop the 5 at-risk accounts in active renewal negotiations: Interviewing customers while CS is actively negotiating discounts with them is high-risk. Economic buyers will use the call as leverage to complain about price or demand roadmap commitments, skewing the data. Replace them with 1st-year customers who took >90 days to go live (regardless of health score) or churned customers from months 9–12.
  • Ana should not lead calls with personal contacts: Ana, your relationships are invaluable for securing these interviews, so we’d love your warm intros. However, former customers who like you personally will try to spare your feelings (blaming an external trend like "we needed robotics" rather than saying "your onboarding team failed us"). A neutral PM should lead all calls; execs can join as silent observers or listen to the recordings.
  • Sample across implementation times: Ensure the 8 churned accounts include both <60-day and >90-day implementations so we don't pre-validate Bet B.

---

3. Interview Guides (45 Minutes)

#### Track A: Economic Buyer (VP of Ops / COO) — 6 Calls Focus: ROI expectations, contract promises, strategic tech stack, and the switching decision.

  • 0–3m | Intro & Legal: Thank them for their time. Emphasize that this is a product research call, not a sales/renewal call. Ask permission to record.
  • 3–10m | The Buying Thesis:
  • "Take me back to when you signed with Crate. What was broken in your warehouse that you needed us to fix?"
  • "What were your expectations for how quickly Crate would be up and running?"
  • 10–22m | The Implementation Experience:
  • "Our contract promises a 45-day go-live. Walk me through what actually happened during your rollout."
  • If delayed: "What was the single biggest bottleneck? How did that delay impact your business and your team’s trust in Crate?"
  • 22–35m | The Turning Point & Tech Stack:
  • For Churned: "When did you first realize Crate wasn't going to work out long-term? What happened that week?"
  • For At-Risk: "As you look at your operations today, where is Crate falling short of what you signed up for?"
  • "What other software or hardware did you need Crate to talk to?" (Do not mention robotics first; see if they bring it up).
  • 35–42m | The Aftermath & Automation (Probing Bet A):
  • For Churned: "What system did you move to, and how was their implementation by comparison?"
  • "Where does warehouse automation or robotics—like autonomous carts or pick-assist—fit into your current operations or 12-month plan?" (If they have them: "Did Crate's lack of integration factor into your decision to leave?")
  • 42–45m | Wrap-up: "If you were in our shoes and could fix only one thing for mid-size 3PLs over the next six months, what would it be?"

#### Track B: Daily User (Warehouse Operations Manager) — 6 Calls Focus: Day-to-day friction, rollout reality on the floor, and manual workarounds.

  • 0–3m | Intro & Legal: Set a candid, blame-free tone. Ask permission to record.
  • 3–12m | Go-Live on the Floor:
  • "Were you involved in setting up Crate? Walk me through what it took to get your first warehouse workflow live."
  • "At what point did you feel your floor staff actually trusted the system?"
  • 12–27m | Daily Friction & Workarounds:
  • "Walk me through a typical peak day using Crate. Where did the software slow your team down?"
  • "What tasks were you forced to do outside of Crate—in spreadsheets or on paper—because the software couldn't handle it?"
  • 27–38m | Equipment & Integrations:
  • "What other tools, scanners, ERPs, or floor equipment did you use alongside Crate?"
  • "Did you have to manually move data between Crate and other systems? Which ones?"
  • "Are you using any autonomous carts or robotics on the floor today, or testing them?"
  • 38–45m | The Verdict:
  • For Churned: "When leadership decided to replace Crate, was your team relieved or frustrated? Why?"
  • For At-Risk: "If you could wave a magic wand and fix one bottleneck in how Crate runs your floor tomorrow, what would it be?"

---

4. Guidance for Interviewers

1. Legal & CS Guardrails (Strict): * Always get explicit verbal consent to record at the start. * Never discuss pricing, discounts, or commercial terms. If an at-risk customer brings up their renewal, say: "I’m completely firewalled from commercial discussions so I can focus purely on product feedback. I’ll make sure your CS manager follows up on the renewal side." * Never mention our roadmap or hint that we are debating Robotics vs. Implementation. 2. Don't Lead the Witness: Do not use the words "robotics" or "94-day implementation" until the final 10 minutes of the call. Let them name the pain first. If they say "integrations," ask "Which specific tools?" before assuming they mean hardware. 3. Hunt for Past Behavior, Not Future Wishes: Discount hypothetical statements like "We’d love to look at robotics next year." Focus on concrete actions: "Did you sign a vendor contract for robots?" or "How many hours a week did your team spend fixing data imports during onboarding?" 4. Two People Per Call: One interviewer drives; one silent note-taker logs verbatim quotes and timestamps in our research repository immediately after the call.

---

5. Decision Framework: How We Will Score the Evidence

After the 12 calls, we will map the findings against this rubric to allocate the two squads:

#### What we need to hear to back Bet A (Robotics Integrations): * Active Deployment: At least 4 of the 12 accounts either actively use warehouse robotics today, are in a paid pilot, or migrated to a competitor specifically and demonstrably to connect to robotics hardware. * Retention Blocker: At-risk customers state that robotics integration is a hard requirement for their upcoming 12-month operations, not just a "nice to have" for 3 years from now. * Implementation Was Survivable: Customers who took >90 days to go live tell us that while onboarding was painful, they eventually stabilized and only left because they outgrew our automation capabilities.

#### What we need to hear to back Bet B (Rebuild Implementation): * Early "Point of No Return": Churned customers report that executive trust was broken during a drawn-out onboarding (months 2–4), and they began shopping for replacements before month 6—meaning they never reached full adoption. * Software-Fixable Bottlenecks: The reasons for the 94-day median go-live are things engineering squads can actually solve (e.g., broken data migration tools, rigid warehouse configuration, self-serve setup gaps) rather than pure services/staffing issues. * Misattributed Survey Data: When we unpack "Missing features/integrations" from the exit survey, we find customers were actually frustrated that initial setup of standard integrations took months during onboarding.

#### What we need to hear to back NEITHER (Pivot the Roadmap): * Software vs. Services on Bet B: Implementation takes 94 days because customers have messy data or our Implementation Managers are understaffed—problems solved by hiring or process changes, not two engineering squads. * A Hidden Third Driver: "Missing features/integrations" turns out to be a core software gap unrelated to robotics (e.g., 3PL billing, client portals, or basic ERP/WMS syncs like NetSuite or Shopify), while robotics is exposed as a shiny object mainly affecting a small subset of new-logo sales.

Claims the judge couldn’t find in the brief

  • The exit survey option 'Missing features/integrations' bundles robotics with basic APIs/ERPs

Grades and run details

Decision model 85 · LLM judge 79
Decision model checks
  • partialUses the supplied evidence correctly11%
  • passAddresses the actual decision70%
  • passRespects explicit constraints9%
  • passIdentifies material uncertainty98%
  • partialAvoids unsupported claims40%
  • passProduces the required deliverable83%
  • passTests both theories fairly92%
  • passDifferent questions for user and signer100%
  • passProtects the calls and the accounts98%
  • passDesigned to falsify70%
  • passAsks what people did, not what they think92%
  • partialDoesn't lead the witness25%
  • partialMarks what to cut if the call runs over53%
Run
Run
#1
API response time
27 s
Submitted
13 Oct 2026

Usable with a quick edit12 of 13 checks passed

The guide is thorough and evidence-based; a PM could add a note on which questions to prioritize if time is tight and use it immediately.

Output

Crate churn research: executive pre-read and interview guide

Decision: Allocate two squads next half to robotics integrations (A), implementation rebuild (B), or neither if the evidence does not justify either.

Research stance: Test both explanations, not confirm either executive’s account. These interviews can reveal mechanisms and decision timelines; they cannot estimate their prevalence across 340 customers or prove causality.

1. Learning goals

  1. Reconstruct the departure process: When did concerns emerge, when did leaving become likely, and when was the decision effectively made?
  2. Identify consequential problems: Separate reasons volunteered after leaving from problems that materially changed warehouse outcomes and the buying decision.
  3. Test Bet A: Was a specific robotics incompatibility a binding obstacle? Would addressing it have plausibly retained the account?
  4. Test Bet B: Did implementation delay prevent value, damage trust, or trigger departure? What caused the delay, and could Crate control it?
  5. Find alternatives and interactions: Price, service, reliability, business changes, or other missing capabilities may dominate. Robotics work may itself complicate implementation.
  6. Connect learning to an investable scope: What could two squads deliver next half that would address the demonstrated retention mechanism?

What the existing evidence does—and does not—say

  • The exit survey’s broad integration category, single-choice format, first-position placement, and sparse free text do not establish robotics as the cause.
  • The 2.4× churn association makes implementation worth investigating, but complexity, customer readiness, or other factors could drive both delay and churn.
  • Three competitor moves and nine lost deals indicate a robotics opportunity; acquisition losses are not evidence of a retention mechanism.
  • Unknown decision dates make chronology essential.

2. Changes to the call plan

Resolve the arithmetic: Twelve separate interviews cannot cover twelve accounts with two roles each. Use six accounts × two separate role interviews = twelve 45-minute calls.

Recommended mix: Four churned accounts and two at-risk accounts. This reduces reliance on renewal negotiations while retaining a prospective view. Findings will be depth-oriented, not representative.

Select accounts from the full CRM population, not executive contacts or survey answers alone:

  • Across churned accounts, include slow and faster implementations, first-year and later departures, and robotics-exposed and non-exposed customers.
  • Include at least one confirmed move to a robotics-enabled competitor and one slow implementation without an apparent robotics need.
  • For at-risk accounts, prefer one with active automation plans and one with implementation/value-realization problems. Include the non-renewal account if suitable.
  • Seek contrasting retained accounts through existing operational data, even though the call budget does not cover them.

Recruit both the daily warehouse operations manager and the contract-signing VP Operations/COO. If the original signer has left, recruit someone directly involved in the departure or renewal decision and document that substitution.

Ana should not lead calls with her personal contacts. Use a neutral interviewer without renewal responsibility. Ana can help recruit; observing requires explicit customer consent. Her existing conversations are useful leads, not independently verified findings.

CS should introduce research as separate from renewal discussions, then step out. Participation must not affect commercial treatment.

3. Interview guides: 45 minutes each

Use the relevant role column. In every section, distinguish direct experience from hearsay. Ask broad questions before naming either bet.

TimeDaily warehouse operations managerVP Operations / COO
0–3 min: permission and framingFirst ask: “May we record this conversation for internal research?” If declined, continue with notes. Then explain purpose and confidentiality limits.Same opening.
3–7 min: context and expected value“What did your warehouse handle, and what was your role with Crate? What was supposed to improve?”“What led you to buy Crate? What outcomes and deadlines mattered? How would you judge success?”
7–17 min: chronological reconstruction“Walk me from signing through onboarding, first operational use, and the point when problems became serious.” “Describe a particular shift or incident.” Establish dates, workarounds, operational impact, and who knew.“Walk me from purchase to the first concern, evaluating alternatives, and the decision.” “When did staying stop being the default?” Establish dates, decision-makers, triggers, and alternatives.
17–27 min: implementation and value“What had to happen before you could use Crate successfully? Where did work stall? Who owned each step?” “When did you first achieve useful results?” Probe migration, configuration, training, integrations, staffing, and rework after an open answer.“What go-live date did you expect, and what happened? What consequences did that have?” “What other factors accompanied the delay?” “If the same product had gone live in 45 days, what would still have put the relationship at risk?” Ask why.
27–36 min: workflow, automation, and unmet needs“Which workflows did Crate support poorly? Show or describe a recent example.” Then: “Were robots in use or planned? Which systems, what workflow, and what connection was required?” “What happened without it?”“What capabilities influenced staying or switching?” Then probe automation: vendor, deployment date, committed budget, required integration, and alternatives considered. “If that connection had existed, what else would have needed to change for you to stay?”
36–42 min: decision and competing explanations“Which problem mattered most in daily operations? What did you escalate, to whom, and when?” “What worked well?” “What have we missed?”“Which issues were necessary to the decision, and which were secondary?” “What would have had to be different for you to stay?” Ask about business changes, service, reliability, and other alternatives without forcing a category.
42–45 min: verify and closeSummarize the timeline and mechanism: “What have I misunderstood?” Request relevant artifacts and permission for a brief clarification follow-up.Same; verify whether operational problems actually influenced the commercial decision.

Status-specific wording

  • Churned: Ask what the replacement actually delivered, whether it went live, and whether the cited problem improved—not merely what the competitor promised.
  • At-risk: Ask what has already happened, current unresolved consequences, and what would cause escalation or departure. Do not imply a departure decision exists. Distinguish funded plans from aspirations.

4. Guidance for interviewers

  • Begin with recording permission; record only after consent. Explain that this is research, not a support, roadmap, or renewal discussion.
  • Do not discuss prices, discounts, or roadmap commitments. If raised, acknowledge without probing commercial terms: “I can’t discuss that here; your account team handles commercial conversations.” Record volunteered price concerns as an alternative explanation.
  • Avoid “Did missing robotics make you leave?” and “Would faster onboarding have saved you?” Start with events; use counterfactuals only afterward.
  • Ask for concrete examples, dates, artifacts, and consequences. “It was painful” is not yet a mechanism.
  • Do not defend Crate, disclose executive hypotheses, or offer fixes.
  • Interview roles separately before reconciling accounts. Treat disagreement as evidence, not an error to erase.
  • Use a note-taker and common template: timeline, problem, consequence, decision link, alternative explanation, evidence source, and confidence. Count accounts, not two interviewees as independent votes.

5. Evidence required for the decision

Back A: robotics integrations

Look for a repeated chain across independent accounts:

Committed robotics deployment → specific missing connection → material operational/business constraint → documented role in departure or credible near-term risk.

Stronger evidence includes decision-maker confirmation, pre-decision correspondence, and a replacement that solved the problem. Match the implicated vendors/workflows to current customer exposure. Before funding, establish that a feasible integration scope could address meaningful retention risk next half.

Mentions of “automation,” hypothetical plans, or competitor marketing are insufficient.

Back B: implementation rebuild

Look for:

Crate-controllable implementation bottleneck → delayed usable value or broken operational commitments → loss of confidence/avoidable cost → departure decision before value realization.

Seek repeated bottlenecks, role-level corroboration, and contrasts with faster implementations. Validate the mechanism against the full cohort, accounting where possible for complexity and customer readiness. Identify changes two squads could deliver; do not assume a wholesale rebuild is necessary.

Back neither—or declare the result inconclusive

Neither is justified if dominant causes lie elsewhere, robotics demand is narrow or speculative, delays are largely outside Crate’s control, or either intervention arrives too late to affect retention. If interviews remain contradictory or unsupported, report insufficient evidence, not “neither causes churn.”

Compare both bets on reachable ARR at risk, evidence strength, controllability, delivery feasibility, and time to impact—not mention counts.

6. Three-week execution

  • Week 1: Audit cohorts and timelines, recruit, pilot one role pair.
  • Week 2: Complete remaining interviews; synthesize after each pair without changing standards to favor an emerging winner.
  • Week 3: Verify discrepancies, triangulate with records, assess engineering scope, and prepare the decision memo with supporting evidence, counterexamples, uncertainties, and a recommendation.

Do not commit two squads merely because one story sounds more persuasive.

Grades and run details

Decision model 92 · LLM judge 93
Decision model checks
  • passUses the supplied evidence correctly48%
  • passAddresses the actual decision66%
  • partialRespects explicit constraints20%
  • passIdentifies material uncertainty100%
  • passAvoids unsupported claims64%
  • passProduces the required deliverable73%
  • passTests both theories fairly100%
  • passDifferent questions for user and signer100%
  • passProtects the calls and the accounts94%
  • passDesigned to falsify58%
  • passAsks what people did, not what they think97%
  • passDoesn't lead the witness59%
  • partialMarks what to cut if the call runs over67%
Run
Run
#1
API response time
80 s
Submitted
30 Sept 2026

Needs more than a quick edit8 of 13 checks passed

The guide is strong and actionable, but it is over the word limit and contains a few unsupported factual claims that need correction before use.

Output

Churn Discovery Calls: Discussion Guide

For: exec team (read before calls start), interviewers, note-takers Timeline: week 0 for data pull and recruiting, weeks 1–3 for calls, week 4 for synthesis and recommendation

Why we're doing this

Both bets rest on a theory we haven't tested. The data we have can't settle it:

  • The exit survey doesn't separate the theories. "Missing features or integrations" (46%) was listed first, it was a single choice, and it combines robotics with every other feature gap. The free-text box was almost always left blank.
  • The robotics evidence is thin for churn. 3 churned customers moved to a competitor with robotics integrations. That is 3 of roughly 60 churned accounts. The 9 lost new-logo deals are about acquisition, not churn.
  • The implementation evidence is a correlation. Customers who went live after 90 days churned at 2.4× the rate. But complex customers may both take longer to go live and churn more for other reasons.
  • We don't know when or why the leave decision formed. That is the question the calls exist to answer.

Twelve calls can show us how customers decide to leave. They can't show us how many leave for each reason. The CRM pull below fills that gap, and the calls and the data should be read together.

1. Learning goals

  1. When did the leave decision form, and what triggered it? In the first months or later? During implementation, after go-live, or around an automation project?
  2. Does implementation delay cause churn, or just come with it? If delay mattered, was the cause on our side (fixable by Bet B) or on theirs (data readiness, their staffing)?
  3. Is automation a real driver? Are customers actually automating? Did Crate's lack of robot integration block them, or did it come up afterwards as a reason?
  4. Do signers and daily users tell the same story? Executives may cite strategy (automation). Operations managers may cite experience (implementation, usability).
  5. Are the reasons something else entirely? For example: price, support, acquisition, consolidation, or a non-robotics feature gap.

2. Changes to the plan

1. Pull CRM data in week 0, before the first call. For every account that churned in the last 12 months, pull: - tenure at churn - days from signing to go-live - whether they run or were deploying automation (ask CS and account managers) - where they went

Also answer one question: did the rise from 11% to 18% churn come from first-year customers? If it did, that supports Bet B. If the increase is among long-tenured accounts, that points toward Bet A. This may be the most decisive single fact we get, and it costs a day.

2. Replace at-risk accounts that are in renewal talks. Five of the six are negotiating discounts. They have a reason to exaggerate complaints, and a call with them could easily drift into pricing. Use red-health accounts that are not in active renewal. If there aren't enough of those, add churned accounts instead.

3. Fix the call count. The plan says 12 calls, but two people on each of 12 accounts is 24 calls. Within the 12, I propose 8 accounts:

GroupAccountsWho we interviewCalls
Churned, paired4Signer and ops manager, separately8
Churned, signer only2Signer2
At-risk, not in renewal2Signer2
  • Split the churned accounts so that 3 left in their first year and 3 left later.
  • Include at least one account that moved to a competitor with robotics integrations.
  • Signers get priority because they made the decision.
  • The paired accounts let us compare what the signer says with what the daily user saw.
  • If we can fund 24 calls, pair every account.

4. Ana should not interview her own contacts. Anyone will soften or reshape their story when the CEO asks, especially a CEO they know and whose view they may already have heard. Her contacts also aren't a random sample of the people who left.

My suggestion: - Her contacts can enter the pool if they fit the sampling groups, but a neutral interviewer runs those calls. - Ana and Marcus both listen to the recordings. - If Ana wants to speak with former customers personally, those calls are valuable for the relationship. We run them in addition to the 12 and don't count them as research.

The same rule applies to Marcus: neither exec interviews.

5. Offer a thank-you gift to former customers, such as a gift card. It must not be a credit or discount on Crate.

3. Discussion guide: VP Ops / COO (signer), 45 minutes

0–3 min · Opening - Ask permission to record. If they say no, don't record and take notes only. - Say: "This isn't a sales call. I can't discuss pricing or our product plans. I'm here to understand your experience, good and bad."

3–8 min · Context - "Tell me about your business and how it's changed over the last two years." - "What were your biggest operational priorities this past year?"

8–22 min · The decision story (the core of the call) - Churned: "Take me back to the first moment you started to wonder whether Crate was right for you. What was going on?" - At-risk: "Tell me about the last time you seriously questioned renewing." - Build a timeline with follow-ups: - "When was that, relative to signing?" - "What happened next?" - "Who else was involved?" - "What alternatives did you look at?" - "When was the decision final?" - "What finally tipped it?"

22–30 min · Expectations and early months - "When you signed, what did you expect Crate to do for you, and by when?" - "How did going live compare to what you expected?" - "When, if ever, did you first see the value you signed up for?"

30–37 min · Operational direction - "What investments in the warehouse have you made or planned: equipment, systems, staffing?" - "What did you need your WMS to do as part of those?" - If they mention automation: "How did Crate fit, or not? What did you do about it?"

37–42 min · Prompted check - Hand over a card of possible reasons: implementation time, robotics/automation integration, other missing features, ease of use, support, price, business change. - Rotate the order on every call. The survey showed the first option gets picked more. - Ask: "Pick the top three for you." Then: "Which one, if it had been different, would have changed the outcome?"

42–45 min · Close - "What should I have asked?" - "Who else should we talk to?" - Thank them.

4. Discussion guide: Warehouse operations manager, 45 minutes

0–3 min · Opening - Same as the signer call: recording permission and ground rules.

3–10 min · Daily work - "Walk me through a typical day using Crate." - "What other tools or spreadsheets did you use alongside it?"

10–22 min · Implementation story - "Tell me what happened from signing to go-live." - "What took longest?" - "What were you waiting on, and who was it waiting on?" - "When did it start working the way you needed?" - Get specific episodes, not a verdict. Always ask whether a delay came from us, from them, or from a third party.

22–32 min · Gaps and workarounds - "Tell me about the last time Crate got in your way." - "What equipment or automation runs on your floor? How does information move between it and Crate?" - "What manual steps did that create?"

32–37 min · The decision - "Were you part of the decision to leave or renew? What would you have told leadership?"

37–42 min · Prompted check - Same card as the signer call, with a new random order.

42–45 min · Close - Same as the signer call.

5. Guidance for interviewers

Stay neutral - Don't say "robotics," "automation," or "implementation" before the prompted check, unless the interviewee says it first. What people raise unprompted is our strongest evidence. - Ask about specific past events ("the last time…", "walk me through…"), not opinions or hypotheticals. Treat "we'd have stayed if you'd had X" as weak evidence. - Use their words, not ours. Don't correct them or defend Crate. - In paired accounts, use different interviewers where possible. Never tell the second person what the first one said.

Stay within the rules from Legal and CS - Pricing or discounts: "That's outside what I can cover today. I'll let your account team know you'd like to discuss it." Then tell CS. - Roadmap: "I can't speak to product plans, but I'll make sure what you've said reaches the people who make them." Never promise a feature. - If there's no recording consent, don't record. The note-taker writes verbatim quotes where possible.

Process - A note-taker joins every call. - Within 24 hours, fill in the debrief template: - primary reason, in their words - the decision timeline, with the month the doubt started - robotics raised unprompted? (Y/N) - implementation raised unprompted? (Y/N) - was the delay caused by us, them, or both? - top three from the card - the best quote - Hold a 30-minute team review of the debriefs every Friday.

6. What would back each bet

Each account gets classified by its primary cause, meaning the thing that started or tipped the decision. When signer and ops manager disagree, record both views; don't average them.

Back Bet A (robotics) if: - In at least 3 of the 6 churned accounts, automation was raised unprompted and came before the leave decision. - The customer had a live or funded automation project that Crate blocked or made harder. - Ops managers describe concrete workarounds between robots and Crate. - The CRM pull shows churn concentrated in longer-tenured accounts, with meaningfully more automating churners than the 3 we already know about. - Warning sign: robotics only comes up at the card, or appears in the timeline after the decision was already made. That suggests it's a justification, not a cause.

Back Bet B (implementation) if: - In at least 3 of the 6 churned accounts, doubt formed during or soon after a slow implementation, often phrased as "never saw the value" or "lost confidence." - Ops managers put the main delays on our side: our process, staffing, data migration, or configuration. Those are what a rebuild would fix. - The CRM pull shows the rise in churn comes mostly from first-year customers. - Warning sign: delays were mostly on the customer's side (their data wasn't ready, they didn't have staff). A faster process on our end would then help less than the 2.4× figure suggests.

Back neither if: - Primary causes are spread across several reasons with no clear lead, such as price, support, consolidation or acquisition, or a feature gap unrelated to robotics. - Or signers and ops managers consistently tell different stories that neither bet addresses.

In that case, I'd recommend a smaller fix aimed at whichever cause leads, plus a better-designed exit survey, rather than committing two squads on a weak signal.

If both show up: check whether automating customers are also the ones with the slowest implementations. If they are, those customers' problem is really integration work during setup, and the recommendation should address that directly instead of forcing a choice between A and B.

In week 4, I'll bring the exec team a one-page summary that combines the call findings with the CRM figures, a recommendation, and our confidence in it.

Claims the judge couldn’t find in the brief

  • The survey showed the first option gets picked more.

Grades and run details

Decision model 92 · LLM judge 57
Decision model checks
  • passUses the supplied evidence correctly10%
  • passAddresses the actual decision80%
  • partialRespects explicit constraints18%
  • passIdentifies material uncertainty100%
  • passAvoids unsupported claims37%
  • passProduces the required deliverable69%
  • passTests both theories fairly98%
  • passDifferent questions for user and signer100%
  • passProtects the calls and the accounts100%
  • passDesigned to falsify73%
  • passAsks what people did, not what they think98%
  • passDoesn't lead the witness43%
  • partialMarks what to cut if the call runs over45%
Run
Run
#1
Time to output
1.7 min
Submitted
30 Sept 2026

Check by check

Where the outputs differ comes first. Open a check to read the judge’s reasons. “Mixed” means the two graders disagreed.

Where they differ 4

Uses the supplied evidence correctlyWrongRightMixed
Gemini 4 Argon · API

Claims that the exit survey option 'bundles robotics with basic APIs/ERPs' is interpretation presented as fact; the context only gives the label 'Missing features or integrations'.

GPT-6.1 Sol · API

All factual statements about the current situation are taken directly from the supplied context without invention.

Opus 5.5 · Claude

It invents or overstates a few current-situation facts, including 'roughly 60 churned accounts' and 'the survey showed the first option gets picked more'.

Respects explicit constraintsRightRightWrong
Gemini 4 Argon · API

Includes all requested sections, stays under 1,500 words, addresses no-pricing/roadmap rule, recording consent, Ana's calls, and is written for the exec team.

GPT-6.1 Sol · API

The guide is under 1,500 words, includes all requested sections (learning goals, timed questions for two roles, guidance, plan changes, decision signals), and is addressed to the exec team.

Opus 5.5 · Claude

It exceeds the 1,500-word limit and proposes replacing the at-risk cohort in a way that changes the supplied plan beyond the brief's constraints.

Avoids unsupported claimsRightRightMixed
Gemini 4 Argon · API

Most interpretations are framed as hypotheses or things to probe; the primacy-bias point is a reasonable reading of the evidence even if stated confidently.

GPT-6.1 Sol · API

Interpretations are clearly labelled as such (e.g., the exit survey does not establish robotics as the cause), and no cause is presented as established fact.

Opus 5.5 · Claude

It presents the first-option bias and the 'roughly 60 churned accounts' figure as established facts when the supplied evidence does not support them.

Produces the required deliverableRightRightMixed
Gemini 4 Argon · API

A complete research guide memo with learning goals, two timed question tracks, interviewer guidance, plan changes, and decision framework, usable by the exec team.

GPT-6.1 Sol · API

The output is a complete guide with learning goals, timed questions for both roles, interviewer guidance, plan changes, and decision signals; an exec team could act on it.

Opus 5.5 · Claude

The guide is complete and usable, but it is over the requested length.

All got wrong 1

Marks what to cut if the call runs overWrongWrongWrong
Gemini 4 Argon · API

Sections are timed and sum to 45 minutes, but must-ask questions are not marked and there is no guidance on what to cut if the call runs over.

GPT-6.1 Sol · API

The guide includes timed sections that add up to 45 minutes but does not say what to cut if time runs short, nor does it mark must-ask questions.

Opus 5.5 · Claude

It provides timings but does not mark must-ask questions or say what to cut if the call runs over.

All got right 8

Addresses the actual decisionRightRightRight
Gemini 4 Argon · API

Provides a clear framework with specific evidence thresholds that would back Bet A, Bet B, or neither, which is what the brief asked for in a research guide.

GPT-6.1 Sol · API

The output recommends more research before deciding, states the supplied evidence cannot yet support a call, and specifies exactly what evidence would back each bet or neither.

Opus 5.5 · Claude

It gives the exec team a clear decision rule for Bet A, Bet B, or neither, with thresholds and warning signs.

Identifies material uncertaintyRightRightRight
Gemini 4 Argon · API

Explicitly flags the exit survey as noisy, treats the 2.4× implementation-churn correlation as something to probe not assume causal, and names a third-driver possibility with concrete signals.

GPT-6.1 Sol · API

It names key unknowns (decision dates, whether robotics was a binding obstacle, whether delays were Crate-controllable) and says how the interview evidence would resolve them.

Opus 5.5 · Claude

It names the key unknowns—timing of the leave decision, whether delay causes churn, and whether automation is a real driver—and says how calls and CRM pulls would resolve them.

Tests both theories fairlyRightRightRight
Gemini 4 Argon · API

Each theory gets questions that could disprove it—robotics via actual deployment status, implementation via early trust-break timing—and open questions about the leaving decision come before either theory is raised.

GPT-6.1 Sol · API

Questions could disprove robotics (e.g., 'Were robots in use? What happened without it?') and implementation (e.g., 'Where did work stall? If go-live had been 45 days, what would still have put the relationship at risk?'), and open questions leave room for a third cause.

Opus 5.5 · Claude

It gives both robotics and implementation equal chances to be disproved and leaves room for a third cause.

Different questions for user and signerRightRightRight
Gemini 4 Argon · API

Track A targets the economic buyer with decision-process and ROI questions; Track B targets the daily user with floor-level friction and workaround questions, clearly differentiated.

GPT-6.1 Sol · API

The table provides distinct tracks: daily user gets questions about specific shifts, workarounds, and escalations; the signer gets questions about the purchase decision, alternatives, and go-live expectations.

Opus 5.5 · Claude

It provides distinct 45-minute tracks for the signer and the daily operations manager.

Protects the calls and the accountsRightRightRight
Gemini 4 Argon · API

Script for deflecting pricing/roadmap questions, recording consent at start, and concrete plan for Ana to do warm intros only while a neutral PM leads.

GPT-6.1 Sol · API

It forbids discussing pricing/discounts/roadmap, provides a script to deflect, starts with recording consent, and has a concrete plan for Ana (she does not lead, observes with consent, her prior conversations are treated as leads).

Opus 5.5 · Claude

It includes recording consent, scripts for pricing/roadmap, and a concrete plan to keep Ana from leading calls with her contacts.

Designed to falsifyRightRightRight
Gemini 4 Argon · API

Each learning goal has a disconfirming path: e.g. 'Did Crate's lack of integration factor into your decision?' could yield 'no,' and probing actual robot deployment could show it wasn't relevant.

GPT-6.1 Sol · API

Each learning goal has disconfirming questions (e.g., 'What happened without the robot connection?' for Bet A, 'If the same product had gone live in 45 days, what would still have put the relationship at risk?' for Bet B).

Opus 5.5 · Claude

Each learning goal has questions that could falsify the corresponding hypothesis, such as timing, cause of delay, and unprompted automation mentions.

Asks what people did, not what they thinkRightRightRight
Gemini 4 Argon · API

Core questions ask about specific past events—'Walk me through what actually happened during your rollout,' 'When did you first realize,' 'What system did you move to'—not hypotheticals.

GPT-6.1 Sol · API

Core questions ask for a chronological walk-through, specific incidents, dates, and what they did, not opinions or predictions.

Opus 5.5 · Claude

The core questions ask for specific past events, timelines, and actions rather than opinions or hypotheticals.

Doesn't lead the witnessRightRightRight
Gemini 4 Argon · API

Explicitly instructs interviewers not to mention robotics or '94-day implementation' until the final 10 minutes, and to let customers name the pain first; questions are open-ended.

GPT-6.1 Sol · API

Questions are open and neutral; robotics and implementation are not named until after broad problem questions, and no answer is hinted at.

Opus 5.5 · Claude

It explicitly avoids naming robotics or implementation before the prompted check and uses neutral, open questions.

Results

Every setup we’ve tested on this task type, across all its tasks and repeats, graded on the current checklist. Calibrated. Where our PM checked the graders by hand, they agreed on 95% of 42 checks.

#Model · HarnessTask scoreDecision modelLLM judgeRunsCritical failures
1Sonnet 5.5withAPI88.088.52None
2GPT-6.1 SolwithAPI83.784.92None
3Opus 5.5withClaude92.074.72None
4GPT-6 AstrawithChatGPT89.774.52None
5Haiku 5.5withAPI89.770.12None
6GPT-6 LunawithAPI83.773.92None
7Gemini 4 ArgonwithAPI75.670.12None
8Gemini 3.8 FlashwithAPI67.851.92None
9Gemini 3.5 Flash-LitewithGemini63.926.121 capped

What you get for the cost

GPT-6.1 Sol · API scores within 4 points of Sonnet 5.5 · API at a third of the cost.

Task score against relative cost for each setup. The table below has the same figures.304050607080901001×3×10×30×Cost per output, relative to the cheapest setup (log scale) →↑ Task scoreSonnet 5.5 · API: task score 87, 43× the cheapestGPT-6.1 Sol · API: task score 83, 13× the cheapestOpus 5.5 · Claude: task score 82, 71× the cheapestGPT-6 Astra · ChatGPT: task score 81, 66× the cheapestHaiku 5.5 · API: task score 78, 2.3× the cheapestGPT-6 Luna · API: task score 78, the cheapestGemini 4 Argon · API: task score 70, 13× the cheapestGemini 3.8 Flash · API: task score 57, 8.3× the cheapestGemini 3.5 Flash-Lite · Gemini: task score 42, 3.0× the cheapest, 1 critical failureSonnet 5.5 · APIGPT-6.1 Sol · APIOpus 5.5 · ClaudeGPT-6 Astra · ChatGPTHaiku 5.5 · APIGPT-6 Luna · APIGemini 4 Argon · APIGemini 3.8 Flash · APIGemini 3.5 Flash-Lite · Gemini
Best valueNobody beats these on both score and costAt least one critical failure
Task score and relative cost by setup
SetupTask scoreRelative cost (cheapest = 1)
GPT-6 Luna · API781.0×
Haiku 5.5 · API782.3×
Gemini 3.5 Flash-Lite · Gemini423.0×
Gemini 3.8 Flash · API578.3×
GPT-6.1 Sol · API8313×
Gemini 4 Argon · API7013×
Sonnet 5.5 · API8743×
GPT-6 Astra · ChatGPT8166×
Opus 5.5 · Claude8271×

Cost is each output’s tokens at the model’s list price, shown relative to the cheapest setup. Runs done in an app have no usage meter, so theirs are estimated from the same setup’s measured runs. How we compare cost

About the task

The PM job

Preparing for customer calls.

Why it matters

Leading questions produce the answers you wanted. A good guide is designed to prove you wrong.

What good looks like

  • Past-behaviour questions
  • No leading prompts
  • Clear learning goals
  • Could disprove the team's hypothesis

Deliberately not measured

    Capability tested

    Question design

    The failure we’re looking for

    Hypothetical, leading questions

    Grading

    Decision model and LLM judge, calibrated against a blind PM review