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research/PricingResearchRoadmap.md
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# Pricing Research Roadmap
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Status: draft.
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## Purpose
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This document prioritizes adjacent research topics for `adaptive-pricing` into phased workstreams. It assumes the market patterns summarized in `PricingPatternsAndStrategies.md` and the vocabulary in `PricingOntology.md`.
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The roadmap is research-first: each phase should produce inspectable artifacts, scenario tests, and downstream recommendations before implementation hardens.
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---
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## Roadmap Overview
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| Phase | Focus | Primary outputs |
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| --- | --- | --- |
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| 1 | Ontology, lifecycle pricing, value metrics | Stable vocabulary, lifecycle playbooks, value-metric selection guide |
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| 2 | Solver design, comparable customer LTV | Constraint model, optimization objectives, LTV estimation spec |
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| 3 | Stripe/payment-provider abstraction | Provider mapping layer, artifact lifecycle, sync semantics |
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| 4 | Dynamic/adaptive pricing governance | Policy model, explainability rules, fairness and audit patterns |
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| 5 | AI-assisted pricing recommendations | Recommendation interfaces, guardrails, human-in-the-loop workflows |
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---
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## Phase 1: Ontology, Lifecycle Pricing, Value Metrics
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**Goal:** Finish the conceptual foundation and connect it to lifecycle-aware strategy.
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### Workstreams
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#### 1.1 Ontology completion
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- Resolve open questions in `PricingOntology.md`
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- Define primitive composition patterns for hybrid models
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- Produce terminology conflict map for overloaded market terms (`plan`, `price`, `tier`, `package`)
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- Specify canonical parameter classes and validation rules
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- Draft scenario tests for common B2B, B2C, marketplace, and platform-fee models
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#### 1.2 Lifecycle pricing
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- Define lifecycle phase objectives, risks, and acceptable tradeoffs
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- Produce lifecycle playbooks for Exploration through Decline
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- Specify migration patterns: grandfathering, opt-in upgrades, forced migration, sunset pricing
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- Map strategy patterns from `PricingPatternsAndStrategies.md` to lifecycle phases
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- Identify metrics that signal when to change pricing phase
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#### 1.3 Value metrics
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- Research value metric selection criteria: value alignment, legibility, metering cost, gaming risk
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- Compare seat, usage, outcome, and hybrid metrics for AI-heavy products
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- Define anti-gaming mechanisms and abuse detection considerations
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- Document outcome metric attribution requirements
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- Produce a value-metric decision guide tied to offering type and lifecycle phase
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### Exit criteria
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- Ontology terms are stable enough for schema design
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- Lifecycle playbooks cover all six canonical phases
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- Value-metric guide supports at least ten representative offering archetypes
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### Dependencies
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- None. This phase is the foundation.
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---
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## Phase 2: Solver Design, Comparable Customer LTV
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**Goal:** Specify how customer-tunable pricing is solved safely against seller economics.
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### Workstreams
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#### 2.1 Boundary and constraint model
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- Formalize boundary conditions from `INTENT.md` into testable constraints
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- Define hard versus soft constraints and approval escalation paths
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- Model commitment offsets for discounts and concessions
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- Specify invalid-configuration explanations
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#### 2.2 Comparable customer LTV
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- Define `average_comparable_customer_lifetime_value` estimation inputs
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- Specify segment normalization, risk classes, and usage expectations
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- Define the `most_favorable_predefined_model` selection algorithm
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- Specify required improvement factor semantics and seller overrides
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- Identify data requirements and confidence intervals for estimates
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#### 2.3 Solver design
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- Research constraint-solving approaches for customer-tunable parameters
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- Evaluate multi-objective optimization: LTV, margin, predictability, adoption, churn risk
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- Define explainable optimization outputs for sales and customer-facing flows
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- Produce solver scenario suite: valid tuning, rejected tuning, edge cases, abuse attempts
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- Draft simulation interface for pre-activation evaluation
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### Exit criteria
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- LTV comparison spec is sufficient for prototype implementation
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- Solver accepts tunable parameters and returns validated configurations or rejections with reasons
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- Scenario suite covers volume discounts, commitment trades, prepayment trades, and hybrid models
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### Dependencies
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- Phase 1 ontology and lifecycle framing
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---
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## Phase 3: Stripe/Payment-Provider Abstraction
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**Goal:** Keep the internal pricing model as source of truth while executing cleanly on providers.
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### Workstreams
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#### 3.1 Provider abstraction model
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- Define provider-neutral artifacts: product, charge component, meter, subscription, invoice, discount execution
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- Specify mapping from canonical primitives to provider objects
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- Model idempotent create/update/sync semantics and drift detection
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- Define metadata strategy for auditability and reconciliation
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#### 3.2 Stripe reference mapping
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- Map access fees, recurring prices, metered prices, tiers, credits, and coupons to Stripe Billing
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- Research usage record ingestion, billing thresholds, and tax behavior
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- Define customer-specific subscription configuration patterns
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- Document limitations where provider models do not align cleanly with ontology primitives
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#### 3.3 Multi-provider survey
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- Compare Stripe, Paddle, Chargebee, Lago, Orb, Stigg, and m3ter
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- Identify provider capability gaps for outcome fees, complex commitments, and negotiated deals
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- Recommend minimum abstraction surface for future provider adapters
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### Exit criteria
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- Stripe mapping spec covers the primitive set defined in Phase 1
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- Sync and reconciliation rules are documented
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- Provider comparison informs adapter interface design
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### Dependencies
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- Phase 1 primitive definitions
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- Phase 2 validation semantics for publishable configurations
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---
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## Phase 4: Dynamic/Adaptive Pricing Governance
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**Goal:** Enable adaptive pricing without sacrificing trust, fairness, or auditability.
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### Workstreams
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#### 4.1 Governance model
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- Define policies for dynamic price changes, segment changes, and personalized offers
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- Specify approval workflows and exposure limits
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- Model grandfathering, price locks, and renewal behavior
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- Define pricing version history and decision audit trails
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#### 4.2 Trust-preserving adaptation
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- Research transparent dynamic pricing and customer-selected tradeoffs
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- Define explainability requirements for customer-facing price changes
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- Specify fairness constraints for personalized pricing
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- Document regulatory and reputational considerations, including algorithmic pricing scrutiny
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#### 4.3 Experimentation and regulation
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- Research pricing experiments: Van Westendorp, conjoint, Gabor-Granger, live A/B tests
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- Define experiment guardrails tied to lifecycle phase and segment sensitivity
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- Research revenue-recognition implications for discounts, credits, breakage, and bundles
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- Produce compliance checklist for EU and other relevant jurisdictions
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### Exit criteria
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- Governance policy model covers publish, change, rollback, and sunset operations
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- Explainability standard is defined for both seller and customer views
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- Experimentation playbook exists with explicit guardrails
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### Dependencies
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- Phase 1 lifecycle playbooks
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- Phase 2 solver and simulation outputs
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- Phase 3 provider sync for operational enforcement
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---
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## Phase 5: AI-Assisted Pricing Recommendations
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**Goal:** Support human and agent workflows for pricing discovery, tuning, and governance.
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### Workstreams
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#### 5.1 Recommendation surfaces
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- Define seller-facing recommendations: model selection, packaging, migration, discount risk
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- Define customer-facing safe tuning assistance within solver bounds
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- Specify inputs: lifecycle phase, segment, usage forecast, competitive context, boundary conditions
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#### 5.2 Guardrails and evaluation
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- Require recommendations to cite ontology terms, constraints, and comparison metrics
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- Define refusal conditions for under-specified or high-risk requests
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- Evaluate recommendation quality against scenario suite from Phase 2
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- Specify human approval paths for non-self-serve changes
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#### 5.3 Agent integration
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- Define agent-readable interfaces for pricing-model definition, validation, simulation, and publish
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- Map recommendation outputs to workplans, ADRs, and implementation repositories
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- Document prompt and tool boundaries for pricing agents operating on seller data
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### Exit criteria
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- Recommendation contract is machine- and human-readable
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- Guardrails prevent unmanaged discount suggestions
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- Agent integration guide connects research artifacts to implementation repos
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### Dependencies
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- Phases 1–4 artifacts
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- Operational telemetry and simulation data from pilot implementations
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---
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## Cross-Cutting Research Backlog
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These topics span multiple phases and should be revisited as the canon matures:
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| Topic | Primary phase | Notes |
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| --- | --- | --- |
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| Revenue recognition for credits and breakage | 4 | Accounting constraints affect credit and prepayment primitives |
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| Marketplace and take-rate models | 1, 3 | May require extension of ontology |
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| Tax and invoicing semantics | 3, 4 | Provider-specific but policy-driven |
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| Sales-assisted negotiation workflows | 2, 4 | Approval thresholds and deal desk integration |
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| Pricing health checks | 2, 5 | Ongoing monitoring of margin, churn, and discount exposure |
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| Migration tooling | 3, 4 | Operational safety for lifecycle transitions |
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---
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## Suggested Research Artifacts Per Phase
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| Phase | Artifact examples |
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| --- | --- |
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| 1 | `PricingOntology.md` revisions, lifecycle playbooks, value-metric guide, scenario catalog |
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| 2 | LTV spec, solver spec, simulation contract, boundary-condition schema |
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| 3 | Provider abstraction spec, Stripe mapping guide, adapter interface card |
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| 4 | Governance policy spec, explainability standard, experiment playbook |
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| 5 | Recommendation contract, agent integration guide, evaluation rubric |
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---
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## Relationship to Implementation
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This repository remains research-first. Implementation repositories should consume canon outputs as:
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1. Vocabulary and schema definitions from Phase 1
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2. Validation and solver rules from Phase 2
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3. Provider mapping specs from Phase 3
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4. Governance and publish policies from Phase 4
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5. Recommendation interfaces from Phase 5
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See `INTENT.md` for the intended adaptive-pricing engine scope and success criteria.
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