Decisagent working decision ontology

Pricing

Choose a price, price floor, discount, or pricing policy for a product, customer, or market context.

Decision anatomy

Accountable owner

Chief Revenue Officer, pricing leader, or delegated commercial owner

Recurrence

Continuous or campaign/event-driven

Reversibility

High for future offers, low for completed transactions or publicly anchored prices.

Cost of error

High at scale through margin leakage, lost demand, unfair treatment, or brand damage.

Evidence

  • unit economics
  • demand and elasticity
  • competitive context
  • customer and segment context
  • inventory, capacity, and contractual commitments

Alternatives

  • candidate price points
  • discount levels
  • bundles
  • hold current price
  • decline transaction

Objectives

  • margin
  • revenue
  • conversion
  • retention
  • strategic positioning

Constraints

  • price floors
  • contracts
  • fairness and regulation
  • inventory
  • channel policy

Uncertainty

  • elasticity
  • competitive response
  • causal attribution
  • long-term customer impact

How AI may participate

This is design guidance for the archetype, not a universal maturity requirement or a claim about a particular product.

  • Assemble demand, cost, inventory, competitive, contractual, and segment evidence with provenance and effective time.
  • Evaluate explicit price alternatives and non-price alternatives against margin, demand, service, and strategic objectives.
  • Provide sensitivity ranges rather than hiding elasticity, competitor-response, or attribution uncertainty.

Authority and retained human judgment

Use recommendation or human-approved proposal by default. A price change should become effectful only inside explicit product, geography, duration, magnitude, eligibility, and review limits.

What accountable people still decide

  • Whether the price is consistent with customer commitments, market strategy, and applicable policy or law.
  • How to balance short-term margin against trust, fairness, adoption, and long-term value.
  • Whether exceptional market conditions make historical response evidence unreliable.

Outcome observability

Conversion and margin are fast; retention and market response take longer and require attribution.

Evaluation and trace

  • Predefine the comparator, affected population, expected demand and margin response, and review horizon.
  • Measure realized demand, margin, churn, complaints, and distributional effects without claiming causality the design cannot support.
  • Record overrides and concurrent promotions or market shocks that weaken attribution.

Failure and abstention conditions

  • Abstain when cost, availability, eligibility, or contractual evidence is incomplete.
  • Do not infer willingness to pay from sensitive or prohibited proxies.
  • Escalate large, hard-to-reverse, novel, or high-impact changes for domain and accountable-owner review.

Assess your version of this decision

An archetype cannot determine the right authority boundary by itself. Decisagent Fit separately assesses useful AI participation and supportable action authority from your decision context.

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Reviewed relevant products

No product relationship has crossed human review for this decision. Candidate seed links are intentionally excluded.