Pricing Strategy

Pricing Strategy

When to use

Use whenever a price needs to be set or changed and the current approach is cost-plus (price = cost + target margin, ignoring what the customer will actually pay) or competitor-matching (copying a rival's price without checking whether your value proposition is comparable). Also use to test a proposed price change before committing to it.

What it does

Grounds pricing in two independent, complementary methods run through a bundled calculator: Van Westendorp Price Sensitivity (four-question willingness-to-pay survey, giving an acceptable price range and a floor below which customers doubt quality) and price elasticity modeling (revenue and margin at each price point given an estimated or tested elasticity coefficient) — so the recommendation is bounded by real customer behavior, not internal cost structure alone.

Method

1. Run or collect Van Westendorp responses: ask a representative sample four questions per product — at what price is this so cheap you'd doubt the quality; a bargain; starting to feel expensive; so expensive you wouldn't consider it. Minimum ~30 responses for a directional read, 100+ before a launch-critical decision.
2. Run the bundled calculator's Van Westendorp module (scripts/pricing_calculator.py) to get the four crossing points and the acceptable price range — the floor (below which quality is doubted) and ceiling (above which it's rejected outright) bound your pricing options before elasticity is even considered.
3. Estimate or obtain a price elasticity coefficient — from a real price test if you have one, from category benchmarks if you don't (call this out explicitly as an assumption, not a fact, if it's a benchmark).
4. Run the elasticity module across a realistic price-test range to see revenue and margin at each point — these two often peak at different prices, and the choice between them is a real strategic call, not a math problem.
5. Overlay the Van Westendorp range on the elasticity table: discard any price points outside the acceptable range regardless of what the elasticity model says, since a price outside the willingness-to-pay range risks brand/quality perception damage the elasticity model doesn't capture.
6. Check for a Kano-style structure if pricing tiers/packaging: which features are must-haves (expected, don't differentiate price), performance features (linear value, price scales with them), and delighters (disproportionate willingness to pay) — use this to decide what goes in which tier, not just what's cheap to build.
7. Recommend a price with the explicit trade-off named: "recommend $X, which is the revenue-maximizing point within the Van Westendorp acceptable range; margin-maximizing would be $Y but falls outside/inside the range for reason Z."

Inputs

• Van Westendorp survey responses (or a plan to collect them) as arrays of four values per respondent
• Current price, volume, and unit cost
• An elasticity coefficient (measured or benchmarked) and a realistic price-test range
• Config saved as JSON matching the format documented at the top of scripts/pricing_calculator.py

Output format

Van Westendorp acceptable price range with all four crossing points; elasticity table showing volume/revenue/margin at each tested price with the revenue-max and margin-max points flagged; a single recommended price with the trade-off named explicitly; any tier/packaging implications from the Kano check.

Example

A SaaS product currently priced at $29 shows a Van Westendorp acceptable range of $24-$37, and the elasticity table shows revenue peaks at $24 but margin peaks at $29. Since both are inside the acceptable range, the recommendation names the actual choice: hold at $29 for margin, or move to $24 to prioritize growth/market share — a decision for the business, not a number the model can pick alone.

Common pitfalls

• Setting price purely from cost-plus math, ignoring what customers will actually pay.
• Treating an elasticity coefficient pulled from a generic benchmark as if it were measured for this specific product and audience.
• Optimizing for revenue or margin without checking the price against the Van Westendorp range, risking a technically "optimal" price that customers reject on sight.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: Natan-Mohart
• Source: Natan-Mohart/24-strategy-skills-for-claude
• License: MIT

Install and usage instructions live in the source repository linked above.