The overarching approach to how the product is priced, value-based, cost-plus, competitive, or freemium.
A pricing strategy is the reasoning a product uses to decide what to charge: the basis for the number, the logic that defends it, and the experimentsExperimentValidationA test designed to validate a hypothesisView reference → that confirm it. Three bases compete for that role: cost-plus, value-based, and the measurement methods that test willingness to pay.
For most of the twentieth century, pricing meant cost-plus: tally the unit cost, add a target margin, print the figure. It is simple to defend in an audit and indifferent to whether the customer would have paid double. The discipline that displaced it is value-based pricing, set out most fully in Thomas Nagle's *The Strategy and Tactics of Pricing*, first published in 1987 and now in its seventh edition. Nagle's argument is that price should track the economic value a buyer perceives, with cost as a floor rather than the anchor.
The case for taking price seriously was sharpened by Michael Marn and Robert Rosiello of McKinsey in their 1992 Harvard Business Review article *Managing Price, Gaining Profit*. Studying a basket of large companies, they found that a 1% improvement in price, holding volume flat, raised operating profit by an average of 11.1%, a larger swing than the same move in variable cost, fixed cost, or volume. Price is the most sensitive of the profit levers, and usually the least examined.
Measurement methods evolved alongside the theory. The Dutch economist Peter van Westendorp introduced the Price Sensitivity Meter in 1976, four survey questions that map the range a buyer reads as too cheap, a bargain, fair, and too expensive. It turns willingness-to-pay from a guess into a curve, and it remains a standard probe in market research today.
Ramanujam and Tacke's *Monetizing Innovation* (2016) pushes the measurement logic one step further: willingness to pay should be established before the product is fully designed, not afterwards. Their argument is that most innovation failures — featureFeatureProduct SpecificationA product capability or featureView reference →-bloated launches, products priced too low to recoup development, and products nobody wanted — share a common cause: pricing is treated as a finishing step rather than a design input. By that reading, van Westendorp-style surveys run at the end of development are already late; the willingness-to-pay conversation belongs at the point where feature scope is still open.
A B2B analytics tool costs roughly £4 per active seat to serve. Cost-plus thinking, at a 60% margin, lands the team near £10 a seat. Before committing, they run a van Westendorp survey across 200 trial accounts and find the fair-price band sitting between £22 and £35, with churn riskRiskComplianceA risk to the product or businessView reference → rising sharply only above £40.
They set a value-based price of £29 and treat it as a hypothesisHypothesisValidationA testable belief about a solutionView reference →. A holdout cohortCohortGrowthA group of users sharing a common characteristicView reference → keeps seeing £19 so the team can read the demand curve directly. Three months later, conversion at £29 is within two points of the £19 cohort, and revenue per account is up 47%. The cost-plus number would have left most of that on the table, priced against the wrong reference.
In the Unified Product Graph, Pricing StrategyPricing & PackagingAn overarching pricing strategy is a root of the Business, GTM and Growth region, inside the pricing sub-domain. A product connects to it through pricing_strategyProductpriced viaPricing Strategyhierarchy, and a product_priced_via_pricing_strategyRevenue StreamBusiness ModelA source of revenueView reference → ties back through revenue_streamRevenue Streampriced byPricing Strategycross-domain, so the level and the channel stay distinct yet linked. The strategy can also carry an revenue_stream_priced_by_pricing_strategyExperiment PlanValidationAn experiment plan describing the hypothesis, setup, success criteria, and methodology before a test runs.View reference → via experiment_planPricing StrategytestsExperiment Planhierarchy, which encodes the discipline Nagle and McKinsey both argued for: a price is a claim about value that the graph expects to be tested, not a figure asserted once and frozen.pricing_strategy_tests_experiment_plan
Worked example: Trellis
Trellis's pricing strategy ladders a director from a free first tool to a governed, team-wide deploymentDeploymentEngineeringA deployment eventView reference →, monetising collaboration and agent usage rather than the initial build. The Free tier is the on-ramp; Team unlocks collaborators and automations; Business adds the governance, SSO, and audit that Marcus and Sam require before a tool goes company-wide.
Quarterly Recurs every calendar quarter.
Type-specific fields on BaseNode
strategy_typeenumPricing methodology used
review_cadenceenumHow often pricing is reviewed. Uses the shared `Cadence` scale.
last_changestringDate of the last pricing change (ISO format)
idstringrequiredUnique identifier (UUID)
typeNodeTyperequiredDiscriminator for the entity type
titlestringrequiredDisplay name
descriptionstringOptional detailed description
statusstringLifecycle status
tagsstring[]Freeform tags for filtering
5 phases, initial: planning · template: OPERATIONAL
7 edge types connected to this entity.
product_priced_via_pricing_strategypricing_strategy_tests_experiment_planpricing_strategy_offers_pricing_tierpricing_strategy_discounts_via_discount_strategypricing_strategy_trials_via_trial_configpricing_strategy_gates_via_paywallrevenue_stream_priced_by_pricing_strategy