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

Needs more than a quick edit6 of 13 checks passed

A PM would need to shorten it, reconcile the account plan with the 12-call constraint, and remove or relabel unsupported portfolio claims before using it.

Output

Research Guide: Root Cause Analysis for H2 Squad Allocation

Prepared by: Staff Product Manager Target Audience: Executive Team (CEO, CPO, VP CS, Head of Product) Timeline: 3 weeks of interviews; executive decision in Week 4 Scope: 12 calls (45 minutes each)

---

1. Executive Summary & Recommended Changes to the Call Plan

Before executing this sprint, we must adjust three structural flaws in the proposed plan to protect data integrity:

  1. Resolve the Account-to-Call Ratio: 12 calls cannot cover two separate stakeholders across 12 accounts. We will target 6 accounts total (3 churned, 3 at-risk) and conduct 2 distinct calls per account: one with the Warehouse Operations Manager (day-to-day user) and one with the VP of Operations/COO (economic buyer). Evaluating both perspectives within the same operational context is essential to determine whether operational failure or strategic misalignment triggered the exit.
  2. Quarantine Active Renewals: 5 of the proposed 6 at-risk accounts are actively negotiating renewals and receiving discounts. Interviewing these buyers creates an immediate incentive for them to exaggerate product flaws to gain commercial leverage. We will swap 3 of these with at-risk accounts that are not currently negotiating pricing.
  3. CEO Interview Protocol: Executive presence introduces severe confirmation and deference bias—especially with personal contacts who already know Ana's passion for robotics. Recommendation: Ana should join her 4 target calls as an executive sponsor for the first 3 minutes, then hand off lead facilitation to a Product Manager, remaining on mute as an observer. If Ana leads, she must strictly follow the non-leading script provided.

---

2. Core Learning Goals

  1. Pinpoint the Churn Decision Window: Did the customer mentally churn during the onboarding/implementation phase (Bet B), or did they leave after reaching steady-state due to technological ceilings (Bet A)?
  2. Assess Real Robotics Demand vs. Narrative: Are customers actively deploying autonomous mobile robots (AMRs) and pick-assist hardware, or is "missing robotics" a convenient, forward-looking justification for leaving an underperforming platform?
  3. Quantify the Cost of Onboarding Drag: Does exceeding the 45-day SLA directly burn operational credibility and destroy ROI, or is delay merely a symptom of customer-side disorganization?
  4. Identify False Dichotomies (Bet Neither): Determine whether churn is driven by factors neither bet solves—such as baseline software unreliability, missing core 3PL billing/EDI features, or macro 3PL volume contraction.

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3. Interviewer Guidance & Rules of Engagement

  • Recording Consent (Mandatory): State verbatim: "Before we begin, do you mind if I record this session purely for internal note-taking? None of this will be shared externally." If declined, proceed with manual notes.
  • The "No Roadmap, No Pricing" Wall: Customers will attempt to trade feedback for commitments. If asked about features or discounting, respond: "I'm on the product research side and have no visibility into commercials or delivery timelines. My sole focus today is understanding how your operations actually run."
  • Past Behavior Over Speculation: Never ask: "Would you use a robotics integration?" (Answer is always yes). Always ask: "What automation equipment do you have physically deployed on the floor today, and how does your team interact with it?"
  • Root-Cause Probing (The "Five Whys"): When a customer says "missing integrations," do not accept the label. Ask: "What specific warehouse task were you trying to execute that stalled? What was the manual workaround?"

---

4. Interview Scripts & Timings (45 Minutes Each)

Track 1: VP of Operations / COO (Economic Buyer)

#### Part 1: Context & Operational Profile (7 mins) * How has your facility footprint and throughput profile shifted over the last 18 months? * When you initially signed with Crate, what core business metric were you held accountable for improving?

#### Part 2: Implementation & Time-to-Value (12 mins) * Walk me back to your onboarding. What was the internal sentiment between signing the contract and processing your first live pallet? * Our contract targets a 45-day go-live; our median across customers is closer to 90. Where did the process stall, and what internal operational cost did that delay create? * At what point did your leadership team feel Crate was fully operational? Did you ever reach that state?

#### Part 3: Strategic Priorities, Automation, & Feature Gaps (16 mins) * Over the past year, what capital investments have you made on your warehouse floor (e.g., conveyor belts, automated guided vehicles, pick-assist carts, manual racking)? * If automation is present: Who manufactures it, what software controls it today, and what specific data must pass between it and your WMS? * If automation is absent: What is on your signed capital expenditure plan for the next 12 months? * When you evaluated the market (or competitors), what specific capability made it clear Crate was no longer the right long-term partner? * Think back to the moment you realized this contract wouldn't renew. When did that conversation happen, and who initiated it?

#### Part 4: Decision Trace & Wrap-up (10 mins) * If Crate had delivered on every promise made during the sales cycle within 45 days, would you still be with us today? Why or why not? * What is the single biggest operational bottleneck your business faces this quarter?

---

Track 2: Warehouse Operations Manager (Daily User)

#### Part 1: Floor Reality & Daily Routine (8 mins) * Walk me through the first two hours of your shift on the floor. Where do supervisors and pickers spend the majority of their time inside Crate? * What daily tasks force your team to leave Crate and use spreadsheets, paper, or secondary systems?

#### Part 2: Go-Live Experience & Transition (12 mins) * How disruptive was the transition to Crate for your floor staff? How long did it take for pick/pack rates to recover to baseline? * During the first three months, how often did you have to escalate systemic issues to leadership? What were those issues? * Did you feel the system was configured correctly for your physical warehouse layout, or did you have to mold your workflows to fit the software?

#### Part 3: Floor Automation & Daily Bottlenecks (15 mins) * How do orders physically move through your facility today? * If pickers are assisted by any mechanical or automated equipment, where does software failure slow them down? * Have you piloted or evaluated autonomous carts or robotics on your floor? * If yes: What was the hardest operational part of that pilot? * If no: What prevents you from automating (e.g., client SKU variability, facility constraints, budget)? * If you could fix one workflow in Crate that causes your floor workers the most frustration, what would it be?

#### Part 4: The Tipping Point (10 mins) * When did your team start discussing alternative systems or workarounds? Was there a specific breaking point or system failure? * If you had a magic wand to improve your team’s pick/pack speed by 20%, what would you change about your physical setup or your software?

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5. Decision Rubric: What We Need to Hear

At the end of Week 3, interview findings will be mapped against this falsification framework:

OutcomeEvidence Required from CallsMetric Signal from Portfolio
:---:---:---
Back Bet A<br>(Robotics Integrations)• $\ge 4$ of the 6 accounts have active capital expenditures or signed contracts with AMR/robotics vendors (e.g., Locus, 6 River).<br>• Buyers explicitly state: "We loved Crate's daily usability and onboarding was fine, but our inability to ingest AMR pick-batches forced us to migrate."<br>• Daily users identify manual cart-pushing and picker transit time as their primary throughput ceiling.CRM shows churn clustered heavily in high-volume, automated accounts; robotics surfaced in competitive losses without prompting.
Back Bet B<br>(Implementation Rebuild)• Churn decisions were made inside the first 6 months, directly traceable to operational paralysis during go-live.<br>• Buyers report: "We burned through our operational budget running parallel systems for 100+ days; our team lost trust before we ever saw value."<br>• Robotics is dismissed as an aspirational 3-year vision, not a current operational requirement.First-year logo churn represents the majority of our 18% churn rate; churn correlates directly with onboarding days exceeding 45.
Back Neither<br>(Pivot to Bet C)• Automation is negligible among these mid-sized 3PLs; go-live delays are considered standard industry friction.<br>• Churn is driven by baseline platform stability (e.g., database timeouts, inventory sync errors), missing table-stakes 3PL multi-client billing, or standard EDI connectors to Shopify/Amazon.<br>• Customers cite price-to-value disconnects: "We left because Crate charges premium rates while basic core features remain broken."Exit survey "Missing features" was a proxy for basic warehouse workflows, not robotics; churn spread evenly across all customer tenure bands.

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6. Next Steps

  1. Day 1-2: Approve adjusted account roster (3 non-renewing at-risk, 3 churned). CS to send intro emails.
  2. Day 3-17: Conduct 12 recorded interviews. Maintain a shared executive synthesis doc updated within 24 hours of each call.
  3. Day 21: Final Decision Meeting. Present thematic evidence and allocation recommendation to Ana and Marcus.

Claims the judge couldn’t find in the brief

  • Customers who went live after 90 days churned at 2.4× the rate of the rest in their first year.
  • CRM shows churn clustered heavily in high-volume, automated accounts.
  • Robotics surfaced in competitive losses without prompting.
  • First-year logo churn represents the majority of the 18% churn rate.
  • Churn correlates directly with onboarding days exceeding 45.
  • Exit survey 'Missing features' was a proxy for basic warehouse workflows, not robotics.
  • Churn is spread evenly across all customer tenure bands.

Grades and run details

Decision model 73 · LLM judge 50
Decision model checks
  • partialUses the supplied evidence correctly13%
  • passAddresses the actual decision73%
  • failRespects explicit constraints20%
  • passIdentifies material uncertainty92%
  • partialAvoids unsupported claims35%
  • passProduces the required deliverable49%
  • passTests both theories fairly77%
  • passDifferent questions for user and signer100%
  • passProtects the calls and the accounts98%
  • passDesigned to falsify76%
  • passAsks what people did, not what they think85%
  • failDoesn't lead the witness45%
  • partialMarks what to cut if the call runs over49%
Run
Run
#1
API response time
37 s
Submitted
1 Oct 2026
Critical failure: Includes questions that promise roadmap items or discuss pricing or discounts with customers in renewal talks. Score capped at 40.

Needs more than a quick edit3 of 13 checks passed

A PM would need to fix the prohibited either/or question, add a pricing/roadmap handling script, remove unsupported claims, and clarify the revised call coverage before using it. The reasoning and evidence also need rechecking.

Output

Customer Research Guide: H2 Strategic Bets (Robotics vs. Implementation)

To: Executive Team From: Staff Product Manager, Crate Date: Today Subject: 3-Week Customer Research Plan for H2 Resource Allocation (12 Calls)

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Executive Summary & Plan Adjustments

In four weeks, the executive team will decide where to allocate both engineering squads for the next half. Ana believes we are losing customers because we lack warehouse robotics integrations (Bet A). Marcus believes we are losing them because our implementation cycle is broken and slow (Bet B).

The exit survey heavily favors Ana’s view (46% cite missing features/integrations), but UX research 101 teaches us that exit surveys are structurally flawed. Listing "missing features" first creates primacy bias, and the survey failed to capture temporal dynamics—specifically, when the decision to leave was made. Meanwhile, our internal data tells a damning story: our median time to go-live is 94 days (vs. 45 promised), and customers crossing 90 days churn at $2.4\times$ the rate.

We have 3 weeks to conduct 12 interviews (45 minutes each) to uncover the truth.

Critical Plan Adjustments (Read Before We Start)

  1. Split the Interviewees by Persona, Not Account: The original plan called for interviewing both the Ops Manager and the VP/COO on the same accounts. In 45 minutes, splitting time between a daily user and a high-level signer dilutes the insight. Instead, we will interview Warehouse Ops Managers to understand day-to-day friction (Implementation, UI, operational bottlenecks) and VPs of Ops / COOs to understand strategic drivers (ROI, contract expectations, robotics, and when the churn decision was actually made).
  2. Revise Ana’s Participation: Ana wants to run 4 calls with former customers she knows personally. We must advise against this. Founder-led interviews with churned customers carry massive politeness bias; customers will pull punches about implementation failures or invent reasons to let Ana down gently. Ana should observe these calls anonymously or listen to the recordings, but an unbiased PM or User Researcher must conduct them.
  3. Guardrails for At-Risk Accounts: Five of our six at-risk accounts are in active renewal talks with CS discounts on the table. Interviewers are strictly prohibited from discussing pricing, commercial concessions, or our product roadmap. We are strictly here to diagnose reality.

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Learning Goals

  1. The Churn Timeline: Determine the exact month the customer mentally decided to leave. Did they decide during a painful 90+ day onboarding (supporting Bet B), or later when evaluating modernizing warehouse automation (supporting Bet A)?
  2. The "Missing Features" Audit: Deconstruct the 46% exit survey metric. When respondents checked "missing features/integrations," were they missing critical WMS functionality (e.g., wave planning, inventory accuracy) or specifically robotics middleware?
  3. Implementation Reality Check: Measure the operational impact of our 94-day median go-live time. Did the delay create cash-flow/trust erosion that doomed the account before day one, regardless of subsequent features?
  4. Robotics Urgency: For customers who mention robotics, are they actively deploying autonomous carts today, or is it a 3-year roadmap item they use as a stick to beat us with during negotiations?

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Interview Guide: Two Personas

Persona 1: The Daily User (Warehouse Operations Manager)

Focus: Implementation friction, daily utility, operational roadblocks.

  • 00:00–03:00 | Intro & Permission:
  • "Thanks for taking the time. I’m [Name] from Crate. We’re doing research to figure out where we failed our customers and how we can improve. I am strictly here to learn about your experience—we won't be talking about pricing, renewals, or selling you anything today. Do I have your permission to record this call for internal notes?"
  • 03:00–12:00 | Day-to-Day Workflow & Reality:
  • "Take me back to your first 30 days using Crate. What did the day-to-day onboarding look like?"
  • "How long did it actually take for your floor team to feel comfortable using Crate without holding their breath?"
  • "What was the most painful workaround your team had to invent during your first three months?"
  • 12:00–25:00 | The Implementation Experience (Bet B Probe):
  • "Our data shows it takes about 90+ days for most warehouses to go live on Crate. What was your experience? How did those delays affect your team's stress levels and your relationship with our implementation team?"
  • "Looking back, did the slow start permanently damage your trust in the software, or did you bounce back once things were running?"
  • 25:00–35:00 | Equipment & Floor Integration (Bet A Probe):
  • "What automated hardware or mobile carts are running on your floor today? How do they talk to Crate, or do they?"
  • "When a pick-assist cart or AGV moves through your warehouse, where does the process break down between the robot and Crate?"
  • 35:00–42:00 | The Breaking Point:
  • "Think about the moment you realized you wanted to leave Crate (or started looking at alternatives). What happened on the warehouse floor that week?"
  • 42:00–45:00 | Wrap-Up:
  • "If you could wave a magic wand and change one thing about your onboarding or your day-one experience with Crate, what would it be?"

---

Persona 2: The Decision Maker (VP of Operations / COO)

Focus: Strategic expectations, ROI timelines, contract promises, and robotics strategy.

  • 00:00–03:00 | Intro & Permission:
  • "Thanks for joining. I’m [Name] from Crate. We’re reviewing why customers leave us to make radical changes to our roadmap and processes. I'm not here to pitch you or talk commercial terms—just to understand your true experience. May I record this call for note-taking purposes?"
  • 03:00–10:00 | The Purchase & Promise:
  • "When you signed with Crate, what was the primary business problem you needed solved in your first 6 months?"
  • "What timeline were you given for go-live during the sales cycle, and how did reality compare?"
  • 10:00–22:00 | Implementation & Time-to-Value (Bet B Probe):
  • "For a mid-size 3PL, cash flow and client onboarding speed are everything. How did Crate's onboarding timeline impact your ability to onboard your own end-clients?"
  • "At what point in your first year did you officially consider the implementation 'failed' or deeply troubled?"
  • 22:00–34:00 | The Robotics Mandate (Bet A Probe):
  • "Let’s talk about warehouse automation. How central are autonomous carts or robotics to your strategy today versus three years from now? Are you actively running them?"
  • "When you evaluated staying vs. leaving Crate, how heavy was the absence of robotics integrations in that final calculus? Was it the straw that broke the camel's back, or a nice-to-have?"
  • 34:00–42:00 | Uncovering the Timeline:
  • "Looking back at the lifecycle of your account, when did you mentally check out and decide you wouldn't renew? Was it during implementation, or months later?"
  • 42:00–45:00 | Wrap-Up:
  • "If Crate could fix only one thing—either our onboarding speed or our hardware/robotics connectivity—which one would have saved your account?"

---

Decision Criteria: What We Need to Hear

To make our final recommendation to Ana and Marcus, we will evaluate the 12 calls against the following thresholds:

Backing Bet A (Robotics Integrations)

We back Bet A only if: 1. VPs/COOs explicitly state that the lack of robotics was the primary, active catalyst for churning (not just a grievance listed in a post-hoc survey). 2. Churned customers are actively utilizing or piloting autonomous hardware today that could not function with Crate, resulting in operational deadlocks. 3. The exit survey's 46% "missing features" bucket is proven via interviews to be overwhelmingly about hardware/robotics connectivity rather than core WMS gaps (e.g., billing, inventory tracking).

Backing Bet B (Implementation Rebuild)

We back Bet B only if: 1. Interviews reveal that the 90+ day onboarding process created an insurmountable trust deficit; customers felt abandoned and never recovered faith in the product, rendering subsequent features irrelevant. 2. Daily users report that the complexity of setup and configuration was the primary driver of operational frustration, overshadowing missing integrations. 3. Churned customers admit they mentally checked out during or immediately after the botched implementation window, long before robotics ever entered the conversation.

Backing Neither (The Pivot Option)

We back Neither if: * The qualitative data shows a split narrative where both bets are symptoms of a deeper root cause—such as core WMS unreliability, pricing/value misalignment (17% in exit survey), or poor account management—meaning that building robots or speeding up a broken implementation will simply churn customers faster down a different path.

Claims the judge couldn’t find in the brief

  • For a mid-size 3PL, cash flow and client onboarding speed are everything.

Grades and run details

Decision model 65 · LLM judge 21
Decision model checks
  • partialUses the supplied evidence correctly28%
  • passAddresses the actual decision67%
  • partialRespects explicit constraints9%
  • passIdentifies material uncertainty92%
  • partialAvoids unsupported claims52%
  • passProduces the required deliverable22%
  • partialTests both theories fairly41%
  • passDifferent questions for user and signer97%
  • partialProtects the calls and the accounts88%
  • partialDesigned to falsify49%
  • passAsks what people did, not what they think59%
  • failDoesn't lead the witness83%
  • partialMarks what to cut if the call runs over45%
Run
Run
#1
Time to output
11 s
Submitted
1 Oct 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 9

Addresses the actual decisionRightMixedRight
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.

Gemini 3.8 Flash · API

It does not commit to Bet A, Bet B, or neither; it defers the decision to the research, even though the supplied evidence is not framed as insufficient to make a call.

Gemini 3.5 Flash-Lite · Gemini

It does not choose a bet now, but the supplied evidence cannot support a final call; it clearly says the research will settle the decision and gives explicit thresholds for Bet A, Bet B, or neither.

Respects explicit constraintsRightWrongWrong
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.

Gemini 3.8 Flash · API

It exceeds the requested 1,500-word limit and its proposed 6-account roster would not cover the 12 accounts specified in the supplied call plan.

Gemini 3.5 Flash-Lite · Gemini

It is under 1,500 words and includes the required sections, but it does not enforce the no-pricing/no-roadmap rule in practice because it lacks a script for when customers raise those topics and even mentions “roadmap” in the executive intro.

Avoids unsupported claimsRightWrongWrong
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.

Gemini 3.8 Flash · API

It presents several interpretations and portfolio signals as established facts or evidence, such as exit-survey meaning, churn distribution, and robotics mentions without prompting.

Gemini 3.5 Flash-Lite · Gemini

It presents several interpretations as established facts, including that the exit survey “heavily favors” Ana’s view, that founder-led interviews carry “massive” politeness bias, and that cash flow/onboarding speed are “everything” for mid-size 3PLs.

Produces the required deliverableRightMixedMixed
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.

Gemini 3.8 Flash · API

Although it is a usable interview guide, it is too long and changes the account scope in a way that does not satisfy the supplied 12-call plan.

Gemini 3.5 Flash-Lite · Gemini

The guide is mostly present, but it is not fully usable because it changes the plan to split personas without specifying how the 12 calls and 6 accounts will be covered, and it omits a required handling script for pricing/roadmap questions.

Tests both theories fairlyRightRightWrong
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.

Gemini 3.8 Flash · API

It gives both robotics and implementation disconfirming questions and explicitly leaves room for neither, including stability, billing/EDI, and macro causes.

Gemini 3.5 Flash-Lite · Gemini

It gives both theories probes, but the daily-user track is weighted toward implementation, the signer track asks about robotics only after implementation, and the wrap-up asks which bet would have saved the account, so it does not test both theories fairly.

Protects the calls and the accountsRightRightWrong
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.

Gemini 3.8 Flash · API

It includes recording consent, a no-pricing/no-roadmap rule with a script, and a concrete protocol for Ana's calls.

Gemini 3.5 Flash-Lite · Gemini

It includes consent to record and a no-pricing/no-roadmap rule, but it provides no script for handling pricing, discount, or roadmap questions and the executive intro mentions roadmap changes.

Designed to falsifyRightRightWrong
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.

Gemini 3.8 Flash · API

Each learning goal has questions that could falsify the relevant hypothesis, such as actual automation deployment, go-live timeline, and alternative causes.

Gemini 3.5 Flash-Lite · Gemini

Not every learning goal has a neutral disconfirming question; for example, the implementation goal asks whether delays “permanently damaged trust,” and the robotics goal asks whether robotics was “the straw that broke the camel's back,” rather than first eliciting the decision story.

Asks what people did, not what they thinkRightRightMixed
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.

Gemini 3.8 Flash · API

The core questions ask for recent concrete behavior, including deployed equipment, go-live experience, decision timing, and workarounds.

Gemini 3.5 Flash-Lite · Gemini

Some questions ask about recent actions, but the core includes many opinions, hypotheticals, and leading prompts such as “magic wand,” “how heavy was the absence of robotics,” and “which one would have saved your account.”

Doesn't lead the witnessRightMixedWrong
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.

Gemini 3.8 Flash · API

The questions are mostly neutral and avoid asking customers to choose between the bets or pitching the ideas.

Gemini 3.5 Flash-Lite · Gemini

Several questions are leading or biased, including “Our data shows it takes about 90+ days,” “did the slow start permanently damage your trust,” “cash flow and client onboarding speed are everything,” and the final either/or bet question.

All got wrong 2

Uses the supplied evidence correctlyWrongWrongWrong
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'.

Gemini 3.8 Flash · API

The guide relies on several unsupported current-situation or portfolio claims, including CRM clustering, robotics surfacing without prompting, first-year churn majority, >45-day correlation, and exit-survey meaning.

Gemini 3.5 Flash-Lite · Gemini

It uses most supplied numbers correctly, but invents or overstates current-situation claims such as “cash flow and client onboarding speed are everything” and “90+ days for most warehouses” when the context only gives a 94-day median.

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.

Gemini 3.8 Flash · API

The timings add up to 45 minutes, but the number of questions is too dense for a realistic 45-minute call and there are no must-ask markers or cut-down instructions.

Gemini 3.5 Flash-Lite · Gemini

Timings add to 45 minutes, but the number of questions is too high for 45 minutes, must-ask questions are not marked, and there is no guidance on what to cut if time runs short.

All got right 2

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.

Gemini 3.8 Flash · API

It names material unknowns such as timing of churn decisions, real robotics deployment, onboarding drag versus customer-side disorganization, and third causes, and proposes calls to resolve them.

Gemini 3.5 Flash-Lite · Gemini

It names the key unknowns—when customers decided to leave, whether “missing features” means robotics or core WMS, and whether slow implementation caused trust loss—and says the calls and decision thresholds would resolve them.

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.

Gemini 3.8 Flash · API

It provides separate tracks for the daily warehouse operations manager and the VP/COO signer, with role-appropriate questions.

Gemini 3.5 Flash-Lite · Gemini

It has distinct tracks: the daily user is asked about onboarding, workarounds, floor equipment, and the breaking point, while the signer is asked about purchase promises, time-to-value, robotics strategy, and renewal decision timing.

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