Customer research call guide

Crate customer research guide: why are warehouses leaving?

Purpose: In three weeks, learn whether churn is more plausibly driven by missing robotics integrations (Bet A), slow implementation (Bet B), or something else. These calls are for understanding customers’ experiences—not selling, negotiating renewals, or validating either executive’s theory.

Learning goals

For each account, establish:

• What happened, and when? Separate implementation, go-live, first value, automation needs, and the point when leaving became likely or decided.
• What mattered most? Distinguish a decisive problem from a feature request, contributing frustration, or reason offered after the fact.
• What evidence supports the explanation? Look for actual workflow impact, workarounds, alternatives evaluated, and actions taken—not just opinions or hypotheticals.
• What might change the outcome? Explore credible counterfactuals without promising anything.
• What else explains churn? Surface causes beyond A and B.

Recommended plan changes

The proposed 12 calls cannot cover both the daily user and contract signer on all 12 accounts: that would require 24 interviews. Keep the 12-call cap, but interview two roles separately at each of six accounts: three churned accounts and three red-health accounts, with one warehouse operations manager and one VP of Operations/COO per account. This gives paired perspectives and preserves both customer situations, but is a small, directional sample—not a prevalence estimate. Select accounts for varied implementation times and automation situations where possible; don’t choose only accounts with known robotics issues.

Do not have Ana conduct four calls with former customers she knows personally. Her involvement risks courtesy bias and leading the conversation. Use an independent interviewer; ideally don’t include personal contacts in this small core sample. If one is included, disclose the relationship, and have Ana neither attend nor receive attributable notes.

Because five at-risk accounts are in renewal talks and receiving discount offers, use an interviewer outside the account/renewal team. Tell participants their answers won’t affect service or renewal discussions. Don’t share interview content with the account team in a way that could be used in negotiation. Follow Legal’s recording requirement below.

45-minute guide: churned customers

45-minute guide: red-health customers

Use the same opening and close. Do not imply that Crate can fix an issue or influence renewal terms.

Guidance for interviewers

• Ask the questions as written, but follow the participant’s timeline. Use neutral probes: “What happened next?” “Can you give me an example?” “How do you know?”
• Don’t offer Ana’s or Marcus’s theories, mention the exit-survey results, or ask leading questions such as “Would robots have saved you?” Ask about events before asking for interpretations.
• Separate when an issue occurred from when the participant says it mattered. Probe for specific actions and evidence: evaluations, workarounds, escalations, or a switch decision.
• Don’t discuss pricing, discounts, renewal negotiations, or roadmap. If asked about roadmap, say you can’t speak to future plans. Don’t make promises or relay an interview answer as a renewal signal.
• Interview roles separately. Record role and account context in notes, but distinguish direct experience from second-hand views. Afterward, write a short timeline, leading cause(s), evidence, and uncertainties for each account.
• Treat recordings and notes as confidential; use only with consent and Legal-approved handling. Don’t present anecdotes as representative of all customers.

What would support each bet?

Support Bet A (robotics integrations): In multiple independent accounts, a specific robotics workflow or integration gap caused meaningful operational friction, and that issue arose before the decision to leave or seriously consider leaving. Stronger evidence: an actual robot deployment or concrete plan, a costly workaround, and a competitor selected or evaluated for this capability. A feature mention alone—or robotics cited in a new-logo deal—doesn’t establish that it drove existing-customer churn.

Support Bet B (faster implementation): In multiple accounts, implementation delays or effort materially postponed go-live or first value, caused operational consequences, and preceded the decision to leave or consider leaving. Stronger evidence: specific preventable blockers, an unmet expectation, and a credible account that earlier go-live would have changed the outcome. The 94-day median, 45-day promise, and 2.4× association make this worth testing, but do not prove causation.

Support neither / remain uncertain: The call evidence points more strongly to another cause; A or B appears only after the decision; accounts describe issues without meaningful consequences; or evidence is mixed and no cause consistently precedes churn. Don’t force a winner from 12 interviews. Compare patterns across accounts, not individual interview counts, and triangulate with CRM timelines and other churn evidence. The exit survey’s single-choice format, first-listed feature option, and sparse free text limit what it can establish.

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?"

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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?"

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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.

Crate churn calls: interview guide

Purpose: Decide between Bet A (robotics integrations) and Bet B (faster implementation) by learning why customers actually leave. Neither theory is proven yet.

Why we're not already sure

• Exit survey: "Missing features or integrations" bundles two things, isn't robotics-specific, was listed first, and has only 41 responses. People also tend to name the most recent or most socially easy reason rather than the first cause.
• Robotics: 3 of roughly 60 churned accounts went to a robotics competitor. The 9 lost deals are real but are new-logo losses, not churn.
• Implementation: The 2.4× churn gap after 90+ days is a correlation. Complex sites may be both slow to launch and likely to leave. We also don't know when customers decided to leave.
• Ana's and Marcus's evidence: Each is anecdotal and selected. Ana hears from customers who will talk to the CEO.
• The two theories may be linked. Robotics-heavy sites may be the slow implementations.

Learning goals

1. When and why each account first considered leaving, relative to go-live.
2. Whether automation was a cause, a rationalization, or irrelevant. The test is whether they took action (bought robots, evaluated replacements), not whether they mention it.
3. Whether slow go-live caused the exit, and whether the delay was Crate's doing or the customer's (their data, staffing, customizations).
4. What else drives exits: price, support, core product gaps, or events outside our control, such as a 3PL losing a shipper contract or being acquired.
5. Whether the two causes overlap.

Changes to the plan

• Call math. Two roles per account means 12 calls covers only 6 accounts. I'd use 8 accounts: 4 churned accounts with both roles (8 calls), and 4 at-risk accounts with the operations manager only (4 calls). At-risk executives are the people in renewal negotiations, which is where contamination risk is highest. Comparing what the signer and the daily user each say is itself valuable.
• Recruit on criteria, not convenience. Among churned accounts, aim for 2 that left within 12 months of signing and 2 that left later. Include go-lives both over and under 90 days, at least 2 sites with robots or carts, and at least 1 that chose "price" in the survey. Pull this from CRM and Customer Success notes this week.
• Ana doesn't run calls. Customers who know the CEO will be polite, and she has a stated hypothesis. Her relationships are valuable for introductions, and at most 1–2 of her contacts should be in the churned set. Someone with no stake in either bet runs the calls, with a second person taking notes. Ana and Marcus get recordings and summaries afterward.
• At-risk accounts need Customer Success coordination. CS confirms no discount conversation is happening that week. The invitation states that this is research, separate from renewal. If a customer tries to negotiate, redirect and tell CS afterward. Weight at-risk answers less, since they describe intentions, not decisions.
• Pre-register. Before call one, Ana and Marcus each read the last section and write what would change their mind.
• Run a parallel data pull. Get tenure at churn, go-live days, and robotics on site for all roughly 60 churned accounts. If the calls and the data disagree, the data wins.

Guidance for whoever runs the calls

• Consent first. The first thing you say after your name is a request to record. If they decline, take notes only and continue.
• Off-limits: pricing, discounts, and roadmap. If they raise price, listen and ask what they compared us with and what they got, but no numbers or offers. If asked "will you build X?", say: "I can't speak to plans. I'm here to understand your experience." If they ask for a commercial conversation, point them to their account manager.
• Do not say "robotics" or "implementation" until the prompted section. Record whether each topic came up unprompted or only when asked. These carry very different weight.
• Alternate the order of the two prompted topics from call to call.
• Ask for stories and dates, not opinions: "Tell me about the last time," "What happened next?" Favor actions ("Who did you call? What did you buy?") over stated reasons.
• Don't defend Crate or fix problems. Answer criticism with "Say more about that."
• Use silence. Wait a few seconds after an answer; the real reason often comes next.
• Debrief within 24 hours on a one-page sheet: decision date, tenure, go-live days, robots on site, trigger event, unprompted causes, prompted causes, strongest quote, and anything that contradicts our hypotheses.

Guide: Operations manager (daily user), 45 min

Guide: VP Operations / COO (signer), 45 min

What we'd need to hear

Eight accounts can't produce percentages. We're looking for a pattern strong enough to act on.

Back Bet A (robotics) if, in at least 3 of the 4 churned accounts: - Automation comes up unprompted, or with only light prompting, as a reason. - They acted on it: robots bought, piloted, or contracted before they decided to leave. - They were live and broadly content with Crate beforehand. - They evaluated or moved to something that connects to their robots, and say they'd likely have stayed if we had. - The same story appears in at least 2 of the 4 at-risk accounts.

Back Bet B (implementation) if, in at least 3 of the 4 churned accounts: - Their first serious doubt came during or shortly after a late go-live, typically within the first year. - They describe never reaching value, or losing their internal champion during the delay. - The delay was mainly Crate's doing (process, handoffs, configuration), not their own data or staffing. - They would say faster go-live would probably have kept them.

Neither bet if: - Exits are mainly driven by events such as a lost shipper contract, site closure, acquisition, or price. - Robotics is mentioned but no one acted on it. - Go-live was slow but they were happy afterward. - Reasons scatter with no pattern. - Core product gaps, such as reporting or inventory accuracy, show up repeatedly. That would point to a third bet we haven't framed.

Both: If the same accounts show robotics-heavy sites with long go-lives because integrations took months, that is a third reading. It favors Bet A if the cause is missing integrations, and Bet B if it's our process. Decide by asking what the customer says was the blocker.

Split results: If churned accounts split evenly, or contradict the data pull, say so. Recommend a targeted follow-up, such as segmenting churn by tenure, rather than forcing a choice.