Pricing
AuraScore 81/100

Competitive Willingness-To-Pay and Price Elasticity Audit

Synthesize market willingness-to-pay research and competitor pricing into an elasticity report.

Use this template when planning a price increase or packaging overhaul across existing commercial tiers. It evaluates market elasticity data, competitor price ladders, and renewal impact to identify revenue-maximizing price points without triggering churn.

Template

Role: Strategic Revenue Operations Lead and Pricing Research Analyst.

Context

  • Target Market Segment: {{market_segment_definition}}
  • Willingness-To-Pay Survey Dataset: {{survey_wtp_dataset}}
  • Competitor Feature-Price Matrix: {{competitor_feature_price_matrix}}
  • Baseline Renewal and Retention Rates: {{current_renewal_retention_rates}}
  • Expansion Revenue Objective: {{target_revenue_expansion_goal}}

Task

Deliver an analytical research report synthesizing price elasticity, customer willingness-to-pay thresholds, and competitive positioning to determine the revenue-maximizing price points for the target market.

Method

  1. Process {{survey_wtp_dataset}} using Van Westendorp Price Sensitivity Meter techniques (Point of Marginal Cheapness, Indifference Price, Optimal Price Point, Point of Marginal Expensiveness).
  2. Calculate demand elasticity coefficients across core price intervals based on the empirical willingness-to-pay responses.
  3. Cross-reference the elasticity curves against {{competitor_feature_price_matrix}} to identify uncaptured consumer surplus and feature-value deficits.
  4. Simulate renewal attrition risks by running churn sensitivity models against {{current_renewal_retention_rates}} under +5%, +10%, +15%, and +20% price adjustments.
  5. Model net ARR delta factoring in both expected gross churn and increased expansion yield against {{target_revenue_expansion_goal}}.
  6. Identify product feature fences that justify migration to higher-priced packages without inducing packaging revolt.
  7. Provide phased rollout strategies, grandfathering policies, and sales enablement guidance.

Constraints

  • MUST express price elasticity mathematically with exact delta-revenue modeling across all price steps.
  • MUST NOT suggest price increases that project net-negative ARR outcomes under pessimistic churn models.
  • Competitor comparisons must isolate feature-by-feature parity rather than generic brand positioning.
  • Analysis must strictly ground conclusions in the provided survey dataset.

Output format

  • Executive Summary & Core Elasticity Findings (max 150 words)
  • Van Westendorp & Elasticity Curve Analysis (summary table with OPP, IPP, PME, PMC, and elasticity coefficients)
  • Competitive Positioning Matrix (feature tier vs price points relative to competitors)
  • Financial Impact Modeling Table (Revenue, Churn %, and Net ARR Growth across 4 price change scenarios)
  • Price Execution & Transition Roadmap (concrete timeline and grandfathering rules)

Self-review

  • Is the mathematical elasticity formula explicitly stated and logically consistent?
  • Does the net expansion revenue offset projected churn in every recommended scenario?
  • Are grandfathering and migration rules concrete and operationally feasible?
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-pricing
complex-reasoning-analysis-math
price-elasticity
willingness-to-pay
market-research