/pricing-packaging — Monetization Advisor

Design pricing models, packaging tiers, and monetization strategy using frameworks from Madhavan Ramanujam, Patrick Campbell, and Naomi Ionita.

When to Use

• User says "pricing", "packaging", "monetization", "how should we price this"
• Designing pricing for a new product or feature
• Restructuring existing pricing (tiers, models, price points)
• Evaluating pricing model (seat-based vs. usage-based vs. outcome-based)
• Preparing for a price increase
• AI product pricing strategy

Before Starting

Check for existing context:

1. Read projects/<project>/onboarding.md for project context
2. Read projects/<project>/positioning.md — positioning drives pricing
3. Read projects/<project>/discovery.md — customer willingness to pay
4. Read projects/<project>/gtm-plan.md — sales model affects pricing
5. Check docs/strategy/ for prior pricing work

Process

Step 1: Intake — Pricing Context

AskUserQuestion:
  question: "What's the pricing situation?"
  header: "Situation"
  options:
    - label: "New product pricing"
      description: "Need to design pricing from scratch"
    - label: "Pricing restructure"
      description: "Current pricing isn't working — need to rethink"
    - label: "Price increase"
      description: "Need to raise prices without losing customers"
    - label: "AI product pricing"
      description: "Pricing an AI-powered product with variable costs"

Then gather:

• Product — What does it do? Who's it for?
• Business model — B2B, B2C, marketplace, API?
• Current pricing — What do you charge today? (If anything)
• Cost structure — What does it cost you to serve one customer? (Especially for AI: inference costs)
• Competitors — What do alternatives cost?
• Sales model — Self-serve, sales-assisted, enterprise?
• Value delivered — What tangible outcome does the customer get? Can you quantify it?

Step 2: Research — Parallel Pricing Intelligence

Launch 2 agents IN PARALLEL:

Agent 1 — Competitor Pricing Research

Task(subagent_type: "general-purpose", description: "Research competitor pricing")
prompt: Research pricing and packaging for competitors in [SPACE].
  Competitors: [LIST].
  For each, find:
  - Pricing model (seat, usage, flat, outcome, freemium)
  - Price points and tier structure
  - What's included in each tier (features, limits)
  - Free tier or trial structure
  - Enterprise pricing approach
  - Any recent pricing changes
  Return a structured pricing comparison matrix.

Agent 2 — Pricing Model Patterns

Task(subagent_type: "general-purpose", description: "Research pricing model patterns")
prompt: Research pricing model patterns for [PRODUCT TYPE] in [MARKET].
  Analyze:
  - Which pricing models are most common in this space?
  - What value metrics do successful products use? (seats, usage, events, revenue, etc.)
  - Are there examples of outcome-based pricing working here?
  - What's the typical range of price points?
  - Any emerging pricing trends (especially for AI products)?
  Return analysis with examples and recommendations.

Step 3: Pricing Model Selection

Using the Ramanujam 2x2, evaluate which model fits:

The Pricing Model 2x2:

	Low Attribution (hard to measure your impact)	High Attribution (easy to measure)
Low Autonomy (product assists humans)	Per-seat / flat fee	Usage-based
High Autonomy (product does the work)	Subscription tiers	Outcome-based ★

For each viable model, present:

Model	Pros	Cons	Best When
Per-seat	Simple, predictable revenue	Penalizes adoption, doesn't scale with value	Value is roughly equal per user
Usage-based	Scales with value, low entry barrier	Revenue unpredictable, hard to budget for buyers	Value varies widely across users
Outcome-based	Highest alignment, highest ceiling	Hard to measure, requires trust	High autonomy + high attribution (ideal for AI)
Tiered subscription	Predictable, supports segmentation	Can feel arbitrary, may under/over-charge	Clear segment differences in needs
Freemium	Low-friction acquisition, viral potential	Risk of free riders, hard to convert	PLG motion, network effects

Recommendation — Propose 1-2 models with clear reasoning.

Step 4: Packaging Design

Design the tier structure:

Tier design principles:

• 3-4 tiers max (more causes paralysis)
• Name tiers after the customer, not the features ("Starter", "Growth", "Scale", "Enterprise")
• Each tier should have a clear "this is for you" persona
• The recommended tier should be visually highlighted
• Enterprise = "Contact us" (signals premium, allows custom deals)

For each tier:

• Name and target persona
• Price point and billing cadence
• Value metric — what scales with value (seats, usage, etc.)
• Included features — what you get at this level
• Limits — usage caps, user limits, etc.
• Upgrade trigger — what makes someone naturally move to the next tier

The expansion path — Every tier should have a natural reason for customers to pay more over time.

Step 5: Value Story

The price must tell a value story (Ramanujam):

• Contextualize the price against the value delivered
  • "For $X/month, you get Y hours back" (time savings)
  • "For $X/month, you avoid $Y in [cost]" (cost savings)
  • "For $X/month, you generate $Y in [outcome]" (revenue impact)
• The ratio test: Is the price less than 10% of the value delivered? If so, it's a no-brainer.
• The Starbucks test: Can you frame it as "less than a coffee a day"? (if consumer)
• The ROI model: For B2B, sketch a simple ROI showing 3-10x return

Step 6: Validate and Present

Present the pricing recommendation:

1. Recommended model with rationale
2. Tier structure with features and price points
3. Value story — how to frame the price
4. Competitive context — how this compares
5. Risks and mitigations — what could go wrong
6. Price increase path — how to evolve pricing over time

AskUserQuestion:
  question: "How does this pricing feel? What concerns you?"
  header: "Pricing Review"
  options:
    - label: "Feels right"
      description: "The model and price points align with our value and market"
    - label: "Too high"
      description: "Worried about acquisition friction at these prices"
    - label: "Too low"
      description: "Worried about leaving money on the table"
    - label: "Wrong model"
      description: "Think a different pricing model would work better"

Iterate based on feedback. Save to: projects/<project>/pricing.md

Methodology

See references/pricing-frameworks.md for detailed frameworks.

Key sources: Madhavan Ramanujam (dual-engine growth, AI pricing), Patrick Campbell (value metrics, SaaS pricing), Naomi Ionita (usage vs. seat-based, monetization mistakes).

Output

Save to: projects/<project>/pricing.md

Next Steps

• Need a pitch with pricing? → /sales-pitch
• Need to put pricing in a proposal? → /proposal-writer
• Need to plan the GTM around this pricing? → /gtm-strategist