Winning Diagnosis:
User Onboarding Process
New users from recent channels overwhelmed by unclear onboarding, fixed with guided setup.
Focusing on intuitive onboarding for new distribution users reduces support load and accelerates self-serve adoption, leveraging the team's existing focus and assets.
High-confidence problem identification with a direct path to resolution
- check_circleYou want a structured diagnosis and low-regret remediation path
- warningYou already know the root cause and only need implementation help
READY TO START?
Everything you need to diagnose the issue and implement a real fix.
Root cause diagnosis
→ What is actually causing the issue
Prevention framework
→ How to avoid future issues
Priority order
→ What to fix first and why
Resolution steps
→ Step-by-step fix plan
Why This Won
- check_circleThe affected users are from a new distribution channel, which means the problem is isolated and can be addressed without disrupting existing user flows
- check_circleThe proposed fix uses tooltips and guided steps - both low-cost, high-impact tools the team already has in place
- •Reasonable path to resolution in ~7 days
- warningRedesigning onboarding without validating user frustrations may not address the true cause. Misaligned fixes can waste time and fail to reduce support volume
- warningNew onboarding changes may introduce unexpected friction for other user segments. Improving one segment's experience could degrade another's, leading to new support issues
- +Support tickets from the affected segment increased by over 50% week-over-week. A sharp increase in support volume indicates a breakdown in user experience or clarity
- +User session recordings show confusion around key setup steps or feature discovery. Visual confirmation of user pain points can directly link to onboarding flaws
READY TO START?
Everything you need to diagnose the issue and implement a real fix.
Root cause diagnosis
→ What is actually causing the issue
Prevention framework
→ How to avoid future issues
Priority order
→ What to fix first and why
Resolution steps
→ Step-by-step fix plan
- •Reasonable path to resolution in ~7 days
- warningRedesigning onboarding without validating user frustrations may not address the true cause. Misaligned fixes can waste time and fail to reduce support volume
- warningNew onboarding changes may introduce unexpected friction for other user segments. Improving one segment's experience could degrade another's, leading to new support issues
- +Support tickets from the affected segment increased by over 50% week-over-week. A sharp increase in support volume indicates a breakdown in user experience or clarity
- +User session recordings show confusion around key setup steps or feature discovery. Visual confirmation of user pain points can directly link to onboarding flaws
Survey 20 new users from the referral channel to identify the three most confusing setup steps and test tooltip solutions.
Other viable diagnosis paths
These didn't win — here's where the winner pulled ahead
Self-serve Onboarding Friction
Platform-specific onboarding mismatches requiring streamlined self-service guidance integration.
App Store Review Deluge
The spike stems from reviewers encountering a new submission validation step causing unexpected delays and errors…
How this played out
The story of the run11 unique diagnosis paths generated across multiple root-cause angles to maximize coverage.
Top diagnoses were tested against root-cause strength, remediation clarity, and recurrence prevention.
8 lower-conviction diagnosis paths dropped as signals showed weaker evidence or less reliable remediation.
User Onboarding Process separated on diagnosis strength, fix clarity, and execution confidence.
Technical competition logsView the final arena state and phase-by-phase outcomesexpand_more
Archived technical view of the completed run.
- •7d to resolve — low execution risk
- •The most likely root cause of the support spike is a lack of clarity in the…
- •Confidence: Medium–High
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- •7d to resolve — medium execution risk
- •The sudden support spike is most likely due to new users from the platform app…
- •Confidence: Medium–High
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- •5d to resolve — low execution risk
- •The root cause is likely a mismatch between developer expectations and the opaque…
- •Confidence: Medium–High
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- •5d to resolve — low execution risk
- •The spike in support tickets is likely due to a missing or inconsistent onboarding…
- •Confidence: Medium–High
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- •Holding up under critique
- •The proposed solution assumes the root cause is onboarding without sufficient validation steps...
- •The prevention framework lacks specific metrics or triggers to detect emerging issues before...
- •Still true — The diagnosis clearly links the support spike to onboarding friction, supported by…
- •Confidence high — weak evidence support
- •Diagnosis risk: medium · low execution
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- •Holding up under critique
- •The remediation feasibility claim lacks evidence to support the assertion that a two-person...
- •The prevention framework relies on assumptions about user feedback and automated alerts without...
- •Still true — Clear identification of platform-specific onboarding mismatch as the likely root cause…
- •Confidence medium — weak evidence support
- •Diagnosis risk: medium · medium execution
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- •Holding up under critique
- •The root cause is inferred from correlation with the new feature rollout but not directly...
- •The remediation plan assumes a two-person team can implement automated validation quickly...
- •Still true — The proposed solution aligns with the self-serve growth model and leverages the…
- •Confidence medium — weak evidence support
- •Diagnosis risk: medium · medium execution
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- •The 70% increase in support tickets and 84% app store ticket share are presented as fact without source, weakening the diagnostic evidence base.
- •The prevention framework relies on monitoring and iterative updates but lacks concrete mechanisms to ensure proactive adaptation to new acquisition channels.
Advanced through scout and build, but critique exposed specific weaknesses in diagnosis and remediation assumptions strong enough to eliminate it.
Click for eliminated analysis →
- •The feasibility claim for the policy-check tool lacks supporting evidence, undermining confidence in the solution's viability.
- •The prevention framework relies on external partnerships or APIs for policy updates, which introduces dependency risks not fully mitigated.
Advanced through scout and build, but critique exposed specific weaknesses in diagnosis and remediation assumptions strong enough to eliminate it.
Click for eliminated analysis →
●User Onboarding Process
Redesign onboarding process to reduce support requests, prioritize intuitive navigation and clarity.
- •Finished #1 with final score 87
- •This candidate directly addresses the sudden support spike from a specific user segment with a clear root cause diagnosis and actionable remediation plan. It leverages the operator's self-serve model and two-person team by focusing on onboarding redesign, which is both feasible and impactful. The solution is well-supported by strong evidence and has no red flags, making it the most viable and realistic option.
- •Diagnosis risk ended medium
- •Verification confidence was high
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●Self-serve Onboarding Friction
Platform-specific onboarding mismatches requiring streamlined self-service guidance integration.
- •Finished #2 with final score 74
- •This candidate identifies platform-specific onboarding mismatches as the root cause and proposes a solution, but the evidence supporting the feasibility of the solution for a two-person team is weak. The testability score is lower than others, and the red flag about claim-evidence mismatch reduces confidence in the solution's viability for the operator's constraints.
- •Diagnosis risk ended medium
- •Verification confidence was medium
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●App Store Review Deluge
The spike stems from reviewers encountering a new submission validation step causing unexpected delays and errors…
- •Finished #3 with final score 71
- •This candidate focuses on app store submission validation issues as the cause of the support spike. While the solution is plausible, the evidence quality is lower, and the red flag about claim-evidence mismatch suggests the root cause is not fully substantiated. It is less aligned with the operator's self-serve and two-person team constraints compared to the top candidate.
- •Diagnosis risk ended medium
- •Verification confidence was medium
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Decisive Analysis
Eliminated diagnosis path
System Provenance
AI-generated solution, stress-tested for effectiveness. May contain assumptions, inaccuracies, or incomplete context. Verify before applying.