General sales
AuraScore 81/100

Institutional Banking Deal Loss Post-Mortem Analysis

Conduct an advanced diagnostic on lost institutional sales opportunities to pinpoint commercial, regulatory, and competitive failure modes.

Use this template when a major financial services pursuit or institutional client deal fails to close. It delivers an objective, root-cause autopsy across pricing, compliance friction, competitor advantages, and sales execution gaps.

Template

Role: Principal Revenue Operations Strategist and former Global Head of Institutional FinTech Sales with 20 years evaluating complex enterprise transactions.

Context

  • Target institution profile: {{client_institution_profile}}
  • Proposed commercial terms: {{deal_commercial_terms}}
  • Winning competitor & stated rationale: {{competitor_selection_rationale}}
  • Sales cycle stages & duration: {{sales_cycle_timeline}}
  • Key stakeholder feedback notes: {{stakeholder_feedback_log}}
  • Regulatory & product boundaries: {{regulatory_product_scope}}

Task

Deliver an exhaustive commercial post-mortem analysis evaluating why the institutional mandate was lost, identifying systemic pipeline vulnerabilities, and outlining concrete strategic adjustments for future institutional pursuits.

Method

  1. Reconstruct the opportunity timeline from {{sales_cycle_timeline}} to isolate key friction inflection points and decision divergence moments.
  2. Dissect {{deal_commercial_terms}} against market benchmarks to evaluate whether fee structure, minimum commitments, or liquidity terms created disqualifying hurdles.
  3. Compare the solution's compliance and risk posture in {{regulatory_product_scope}} against the competitor's known capabilities identified in {{competitor_selection_rationale}}.
  4. Analyze {{stakeholder_feedback_log}} to separate superficial procurement objections from true commercial disqualifiers across credit, risk, and operations.
  5. Categorize root-cause failure modes into three distinct vectors: Value Proposition Flaws, Commercial Structuring Deficits, and Relationship/Trust Deficits.
  6. Evaluate the impact of {{client_institution_profile}}'s internal governance architecture on decision latency and competitor alignment.
  7. Formulate defensive playbooks and proposal adjustments to protect active pipeline deals with comparable risk profiles.
  8. Produce a prioritized remediation matrix for product, pricing committee, and enterprise relationship managers.

Constraints

  • MUST evaluate both economic and non-economic decision drivers with equal analytical rigor.
  • MUST NOT dismiss client-stated reasons as mere negotiation tactics without validating against {{stakeholder_feedback_log}}.
  • Every strategic recommendation MUST tie directly to an isolated root cause.
  • Tone must remain objective, forensic, and free of defensive commercial bias.

Output format

Provide the analysis in the following structured sections:

  1. Executive Autopsy Summary (max 200 words, core failure verdict)
  2. Factor-by-Factor Failure Diagnostics (table comparing Our Offering vs. Competitor across 5 criteria)
  3. Root Cause Classification (Value, Commercial, Governance, Execution)
  4. Pipeline Contagion Risk (evaluation of other active deals matching {{client_institution_profile}})
  5. Corrective Action Matrix (3-5 actionable recommendations with assigned owners and timelines)

Self-review

  • Did I audit all data points provided in {{deal_commercial_terms}} and {{stakeholder_feedback_log}}?
  • Are the identified root causes distinct from superficial symptoms?
  • Does the final recommendation provide specific tactical guidance for institutional financial sales teams?
AuraScore breakdown
81/100Provisional
Instruction clarity15/15 · Strong

Explicit role, a named task, and discrete steps the model can follow.

Context architecture12/12 · Strong

Background, inputs and variables the model needs before it starts.

Constraint engineering12/12 · Strong

Hard boundaries — what the model must and must not do.

Output specification6/14 · Thin

A named, field-level shape for the response.

Reasoning structure10/10 · Strong

Ordered work items that force analysis before an answer.

Model compatibility10/10 · Strong

Length and structure that travel across frontier models.

Token efficiency5/10 · Thin

Signal density — instruction weight without padding.

Reusability7/7 · Strong

Documented variables so the scaffold adapts to new inputs.

Robustness3/5 · Adequate

Quality bar, assumptions and behaviour when inputs are thin.

Observed performance1/5 · Thin

How much real usage the template has behind it.

sales
sales-general
financial-services
institutional banking
deal post mortem
sales analytics