Pricing Strategy Analyzer

Price on evidence, not on gut feel or a competitor's pricing page.

What this skill is

A structured pricing review that moves from what the company charges today to what it should charge and how to get there. It combines value-based pricing (Patrick Campbell, ProfitWell), usage-based pricing (Kyle Poyar, OpenView), outcome-based pricing (as used by AI support agents such as Intercom Fin and Zendesk), Good-Better-Best packaging, Marcos Rivera's Street Pricing, and Elena Verna's work on Product-Led Growth (PLG) monetization. The output is a recommendation backed by revenue scenarios and a migration plan.

What it solves

• Pricing set by copying competitors, with no link to the value customers receive
• A value metric (per seat, per unit of usage) that grows slower than customer value
• Heavy, inconsistent discounting that signals the list price is wrong
• Too many tiers, or tiers whose feature gates do not trigger upgrades
• Price changes modeled only for new customers, ignoring churn and expansion in the installed base
• Migrations that surprise existing customers and the sales team

When to invoke

• Win rates are falling on price, or deals close with little negotiation (money left on the table)
• Launching new tiers, add-ons, or a new product line
• Annual or post-funding pricing review
• Moving from seat-based to usage-based, outcome-based, or hybrid pricing
• Pricing an AI feature where inference cost scales with use

Phase 1: Document current pricing

Phase 2: Analyze competitive pricing

Map features to price points, then place the company on a price-versus-value chart: premium, parity, or value positioning. Note where the company charges less than competitors for equal or greater value.

Phase 3: Evaluate the pricing model and value metric

A good value metric is easy to understand, grows with customer value, and is predictable enough to budget for.

Phase 4: Assess willingness to pay

Use the evidence available:

• Win-loss data - share of losses citing price, by segment
• Discount frequency - deals closing at list versus discounted
• Upgrade and downgrade patterns - which tier transitions happen and why
• Customer research - Van Westendorp price sensitivity or conjoint results where available

Segment the findings; enterprise and small business willingness to pay rarely match.

Phase 5: Analyze packaging

Phase 6: Model revenue impact

Build scenarios across the installed base and new business.

State the assumption that most drives each scenario and the breakeven value at which it stops paying off.

Phase 7: Plan the migration

• Grandfathering - who keeps current pricing, and for how long
• Timeline - announcement, effective date, and renewal-based transition
• Communication - customer notice, rationale, and value story
• Sales enablement - new price book, discount guardrails, objection handling
• Risk mitigation - churn watch list, escalation path, rollback criteria

Output

• Current pricing baseline
• Competitive pricing map and positioning
• Pricing model and value metric recommendation
• Willingness-to-pay findings by segment
• Packaging recommendation with tier structure and gates
• Revenue scenario model with key assumptions
• Migration plan with timeline and communication

Operating rules

Always

• Anchor price to customer value, then check it against competitors
• Model the effect on existing customers, not just new ones
• Segment willingness-to-pay evidence before drawing conclusions
• State the assumption behind every revenue scenario
• Plan the migration and sales enablement alongside the price change

Never

• Copy a competitor's price without understanding its value metric
• Treat discounting patterns as noise; they are pricing evidence
• Add tiers without a clear upgrade trigger for each
• Price an AI feature without accounting for inference cost
• Change pricing for existing customers without notice and a transition period