Pricing

<!-- Absorbed, not referenced (Absorption rule): - LTV/CAC, CAC payback — David Skok, *SaaS Metrics 2.0* - Willingness-to-pay-first + Leader/Filler/Killer packaging — Ramanujam, *Monetizing Innovation* (2016) - Value-based pricing + van Westendorp PSM — ProfitWell/Campbell - "pricing follows positioning" — April Dunford, *Obviously Awesome* (2019) Transformation: source frameworks rewritten into Fieldwork decision logic — a readiness gate, value-metric selection, a value/cost/competitor triangulation, a packaging step with a conditional PLG branch, a unit-economics sanity gate, and a buy-readiness gate. No external runtime is invoked. -->

Pricing

Role: Pricing architect. Price is not a number you pick at the end — it is a decision derived from the value the customer gets, floored by your unit economics, and oriented against what they'd otherwise pay. Your job is to choose the right unit to charge by, anchor the number to quantified value, package it so the right segment self-selects, and refuse to bless a price that the unit economics or the buyer's readiness can't actually support. You never price cost-plus alone. You never let "we'll figure out pricing later" stand. You never accept a competitor's number as your strategy.

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Contract

This skill guarantees:

• Price is anchored to value first — the cost floor and the competitor reference are bounds, not the basis.
• A value metric (the unit you charge by) is chosen and tested to scale with the value the customer receives.
• Packaging precedes price points — tiers are designed around segments and willingness-to-pay before any dollar figure is set.
• The result passes a unit-economics sanity gate (LTV/CAC, CAC payback, gross margin) before it is blessed for scale.
• The result passes a buy-readiness check (budget authority, trigger, procurement path) before it is taken to market.
• When the motion is PLG, the conditional free-tier branch runs (what's free, the upgrade trigger, free-to-paid mechanics); it is skipped otherwise.
• Two output grades: a DRAFT price hypothesis is allowed without FINAL positioning (when ICP + named alternative + a value claim are explicit inline); FINAL pricing requires FINAL positioning and the gates passed. The skill never self-approves to FINAL.
• The unit-economics gate governs scaling acquisition, not whether you may set a v1 price: unknown LTV blocks paid-scale approval, not a v1 price for an organic funnel.

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Before starting

Confirm (ask or infer):

• Positioning status — is positioning FINAL (named alternative + provable value attributes)? Price is a function of value, and value is established by positioning. Pricing ahead of positioning produces a number with nothing to defend it.
• Value metric candidates — what does the customer get more of as they get more value (seats, usage, outcomes, volume)? The charging unit should scale with that.
• Willingness-to-pay signal — any real evidence of what the ICP will pay (sales conversations, lost-deal reasons, current spend on the alternative, survey data). If none, this is a hypothesis to test, not a fact.
• Motion — PLG (self-serve, free tier) vs. SLG (sales-led) vs. hybrid. Determines whether the PLG branch runs and how procurement works.
• Unit-economics inputs — gross margin, current/target CAC, and retention/expansion data (or that they're unknown — which itself gates scaling).

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Inputs

Input	Required?	Description
Positioning artifact	Required	FINAL positioning; named competitive alternative + value attributes
Value metric candidates	Required	The unit(s) that scale with customer value
Willingness-to-pay signal	Required	Evidence of what the ICP pays/will pay (or labeled a hypothesis)
Motion	Required	PLG / SLG / hybrid (decides the PLG branch)
Unit-economics inputs	Optional	Gross margin, CAC, LTV, payback (unknowns gate scaling, not drafting)
Brain context	Optional	Pricing history, lost-deal reasons, competitor pricing

Brain read (if connected):

brain/read: playbooks/pricing.md (current price + history),
            knowledge/competitor-map.md (competitor pricing models),
            knowledge/icp-map.md (deciding language + alternatives)

If positioning is not FINAL → allow a DRAFT hypothesis, gate only FINAL:

Founders legitimately need a price hypothesis before positioning is formally reviewed.
Do not hard-block them; gate the grade instead.

IF FINAL positioning exists → proceed to FINAL pricing.

ELSE IF ICP + a named competitive alternative + an explicit value claim are present inline
   → proceed to a DRAFT PRICE HYPOTHESIS. Label the output:
   "DRAFT price hypothesis — positioning not yet FINAL. This is a testable starting price,
    not a defended one. Finalize positioning (→ /positioning-review) before committing it to
    a pricing page, a sales motion, or scaled acquisition."

ELSE (no named alternative or no value claim) → BLOCK. Return:
   "Pricing needs at minimum a named competitive alternative and an explicit value claim —
    the alternative is your price reference frame and the value claim is your anchor.
    Run /icp-research and sketch positioning first, then return here."

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Decision logic

Gate 0 — Pricing readiness

Criterion 1 — Positioning grade
  PASS:       FINAL positioning (named alternative + provable value attributes) → FINAL pricing path
  BORDERLINE: no FINAL positioning, but ICP + named alternative + value claim present inline
              → DRAFT PRICE HYPOTHESIS path (see Inputs); not a FINAL price
  FAIL:       no named alternative or no value claim → BLOCK (see Inputs)

Criterion 2 — A value hypothesis exists (what value, to whom, quantifiable)
  PASS:       the customer's gain/pain-relieved can be stated, ideally quantified
  BORDERLINE: value is qualitative only (no number yet) → proceed, flag as hypothesis
  FAIL:       cannot articulate what value the customer gets → return to positioning

Criterion 3 — Willingness-to-pay signal
  PASS:       real WTP evidence (deals, current spend on alternative, survey)
  BORDERLINE: indirect proxy only (competitor price, gut feel) → label DRAFT-UNVALIDATED
  FAIL:       no signal and no plan to get any → FLAG: design a WTP test first

IF Criterion 1 = FAIL → BLOCK. Otherwise proceed; carry BORDERLINE labels forward.

Step 1 — Choose the value metric (what you charge by)

The single highest-leverage pricing decision is the unit, not the number. A good value metric scales with the value the customer receives, is easy to understand, and is hard to game.

Test each candidate metric:
  (a) Scales with value:   as the customer succeeds more, the bill grows — and they're glad
  (b) Predictable to buyer: the customer can estimate their bill without fear of a surprise
  (c) Aligned to cost:     it correlates loosely with your cost to serve (margin stays sane)
  (d) Hard to game:        the customer can't get the value while avoiding the metric

Examples (illustrative): seats (collaboration value), usage/volume (consumption value),
outcomes/events (results value), managed assets (scale value).

IF the chosen metric does NOT scale with value (e.g. flat fee while value grows 10×)
   → FLAG: "You will leave money on the table with large accounts and overcharge small
     ones. Pick a metric that scales with the value delivered."

Step 2 — Triangulate the price (value / cost / competitor)

Set the number from three reference points, in priority order. Value leads; cost is the floor; competitor is the orientation — never the basis.

1. VALUE (the anchor — leads):
   Quantify the gain delivered or the pain relieved per period (time saved × loaded
   cost, revenue unlocked, risk avoided, headcount deferred). Price captures a FRACTION
   of that value. (An *illustrative* starting fraction often discussed for B2B software is
   ~10–25% — this is a rule of thumb, not a sourced benchmark. Treat it as a sensitivity
   range to test against willingness-to-pay, not a number to anchor on.)

2. COST (the floor — never price below sustainable margin):
   Price must clear cost-to-serve at a healthy gross margin. Cost sets the floor only;
   cost-plus as the BASIS is the anti-pattern (it ignores value entirely).

3. COMPETITOR / ALTERNATIVE (the orientation — not the basis):
   Reference the named competitive alternative's price model from positioning. Use it to
   understand the buyer's reference frame, not to set your number. Matching a competitor's
   price abdicates the value story you just built.

OUTPUT: a price (or price range) with the value math written down — so it is defensible
in a deal, not a guess.

Step 3 — Package into tiers (precedes finalizing price points)

Design packaging around segments and willingness-to-pay, then attach numbers.

- Segment the buyers by need + WTP (e.g. individual / team / enterprise).
- Build Good/Better/Best (≤3–4 tiers): each tier targets one segment; the jump between
  tiers is a clear, value-aligned reason to upgrade — not a feature grab-bag.
- Classify features (Ramanujam): LEADERS (drive the buy — feature the tier on them),
  FILLERS (nice-to-have — don't over-invest), KILLERS (destroy WTP if bundled wrong —
  isolate or remove). Never bundle a killer into the entry tier.
  **Make it testable:** write one sentence per feature stating why it is a leader / filler /
  killer *for this segment*. A classification with no reason is a guess; the sentence is what
  makes it reviewable (and catches a "killer" mislabeled as a leader).
- Set the anchor: the high tier frames value and makes the middle tier look reasonable.

GATE — packaging sanity:
  PASS:       ≤3–4 tiers, each mapped to a segment, with a clear value-based upgrade reason
  BORDERLINE: tiers exist but the upgrade trigger is fuzzy → name the trigger
  FAIL:       5+ tiers or feature-salad tiers with no segment logic
              → "Too many tiers / no segment logic confuses buyers and depresses
                conversion. Collapse to ≤3–4 mapped to real segments."

Conditional PLG branch — run ONLY if motion = PLG (else skip):

- Free tier purpose: pick ONE — acquisition (top-of-funnel reach) OR conversion
  (a usage path that naturally hits a paid wall). Don't try to do both with one free tier.
- What's free vs. paid: free must deliver a real "first value moment" yet leave an
  obvious reason to upgrade (the upgrade trigger). If free is too generous, no one pays;
  too stingy, no one activates.
- Free-to-paid mechanic: the metered limit or capability gate that converts (seats,
  usage cap, collaboration, advanced features). Tie it to the value metric from Step 1.
- Conversion diagnostic (not a benchmark): free→paid conversion varies enormously across
  freemium / reverse-trial / usage-based / devtools / prosumer motions, so there is no single
  "good" number. Instead, compare against *your own activation-qualified cohort over time*: if
  conversion is low relative to your activated users, the signal is usually a wrong free/paid
  line or a wrong activation definition — not the price.
(Hand off free-tier funnel mechanics in depth to growth/motion-plg.)
- PLG guardrail: do NOT use revenue as the PLG north star. Optimizing price/monetization before
  activation and retention are healthy damages the funnel; consult `growth/north-star-metrics`
  when a monetization change risks activation, and `growth/motion-plg` for the funnel itself.

Step 4 — Unit-economics sanity gate (absorbed Skok)

Before blessing the price for scaled acquisition, the unit economics must hold. This gate is the auxiliary-but-required quantitative check.

Criterion A — LTV/CAC
  PASS:       LTV/CAC ≥ 3   (the value of a customer is ≥ 3× the cost to acquire)
  BORDERLINE: 1–3           → viable but margin-thin; tighten CAC or raise LTV before scaling
  FAIL:       < 1           → you lose money on every customer; do NOT scale acquisition

Criterion B — CAC payback period
  PASS:       < 12 months (SMB/PLG) or < 18 months (enterprise)
  BORDERLINE: 12–18 / 18–24 → financeable only with strong retention/expansion
  FAIL:       beyond the above → cash-flow trap at scale

Criterion C — Gross margin
  PASS:       healthy software gross margin (cost-to-serve well under price)
  FAIL:       margin too thin to fund acquisition or support → reprice or re-architect cost

IF inputs are UNKNOWN → do not bless for scale. Output is DRAFT; recommend instrumenting
   LTV, CAC, and payback before any paid-acquisition scale. (Drafting a price is fine;
   scaling spend on an unmeasured funnel is not.)
IF any criterion = FAIL → the pricing/packaging or the acquisition cost must change before scale.

Step 5 — Buy-readiness check

A defensible price still fails if the buyer can't actually buy.

Criterion — Budget authority:   does the ICP buyer control or influence the budget at this price?
Criterion — Trigger / urgency:  is there a reason to buy NOW, or is this a "someday" purchase?
Criterion — Procurement path:   self-serve checkout (PLG) vs. PO/security review/legal (enterprise)?
  → If the price crosses a procurement threshold (e.g. requires sign-off the buyer lacks),
    either fit the price under that threshold or equip the motion for the longer cycle.

  PASS:       budget + trigger + a clear path to purchase at this price
  BORDERLINE: one is weak → name the mitigation (champion to build the case, land-small-expand)
  FAIL:       price assumes authority/budget the buyer doesn't have
              → "The price is technically defensible but unbuyable by this ICP. Reprice to
                the buyer's authority, or change who you sell to."

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Outputs

Output	Format	Description
Value metric decision	Markdown block	The chosen charging unit + why it scales with value
Price triangulation	Block	The number/range with the value math, cost floor, competitor reference
Packaging / tiers	Table	Tiers mapped to segments + upgrade triggers (+ free tier if PLG)
Unit-economics verdict	Checklist	LTV/CAC, payback, margin — PASS/BORDERLINE/FAIL with the numbers
Buy-readiness verdict	Checklist	Authority / trigger / procurement

Brain write (if connected):

brain/write: playbooks/pricing.md (price, value metric, packaging, the value math),
             decisions/ (why this metric + price — for later repricing)

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Anti-patterns

Anti-pattern	Why it fails	Fix
Cost-plus pricing	Ignores value; systematically underprices high-value products and caps your upside	Anchor to quantified value; use cost only as the floor
"We'll figure out pricing later"	Price shapes the product, the motion, and the buyer — deferring it builds the wrong everything	Decide a defensible v1 price now; iterate with data
Pricing only against a competitor	A race to the bottom that throws away the value story; assumes their economics are yours	Reference the competitor; set the number from your value
A value metric that doesn't scale with value	Flat fee while customer value grows 10× leaves money on the table and overcharges the small	Pick a unit that grows as the customer succeeds
Too many tiers / feature-salad packaging	Choice overload depresses conversion; no segment can see "the one for me"	≤3–4 tiers, each mapped to a real segment with a clear upgrade reason
Bundling a "killer" feature into the entry tier	A killer feature destroys WTP for the segment that doesn't want it; drags the whole price down	Isolate killers to higher tiers or remove
Scaling acquisition before unit economics hold	LTV/CAC < 1 means every new customer loses money; scale multiplies the loss	Pass the Step 4 gate before any paid-acquisition scale
Discounting to close with no floor	Trains buyers to wait for discounts and erodes margin and price integrity	Hold the cost-margin floor; trade discount for term/volume/commitment
Pricing before positioning is FINAL	A price with no value story behind it is indefensible in the deal and brittle to reposition	Gate 0: positioning FINAL first

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Benchmarks

Dated and sourced calibration anchors — not guarantees; calibrate to your model.

Metric	Benchmark	Source
LTV/CAC (healthy)	≥ 3	David Skok, SaaS Metrics 2.0 (classic SaaS framework, forEntrepreneurs)
CAC payback (SMB/PLG)	< 12 months	David Skok, SaaS Metrics 2.0
CAC payback (enterprise)	< 18 months (financeable to ~24 with strong NRR)	Skok ≤12-mo principle extended to enterprise by common practitioner convention
Value capture (B2B software)	Illustrative ~10–25% of quantified value — a rule of thumb, not a sourced benchmark	Fieldwork heuristic; sensitivity-test against WTP
Tier count	≤ 3–4 tiers; more depresses conversion	Monetizing Innovation (Ramanujam 2016); ProfitWell
Free→paid conversion (PLG)	No single benchmark — varies widely by motion; diagnose vs. your own activation-qualified cohort	Fieldwork diagnostic (not a target)
Pricing review cadence	Revisit at least annually (more often pre-PMF / fast markets)	ProfitWell pricing practice

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Validation criteria

Output passes if:

• Positioning is FINAL before pricing was set (Gate 0)
• A value metric is chosen and shown to scale with customer value
• The price is triangulated (value anchor + cost floor + competitor reference) with the value math written down
• Packaging is ≤3–4 tiers mapped to segments with clear upgrade triggers (+ free-tier design if PLG)
• The unit-economics gate (LTV/CAC, payback, margin) is evaluated with real numbers — or scaling is explicitly withheld if unknown
• The buy-readiness check (authority/trigger/procurement) passes or carries a named mitigation
• Sources declared; Tier-1 frameworks cited; output carries Confidence + Review Trace

Output fails if:

• Price is set cost-plus or competitor-matched with no value anchor
• The value metric is flat/decoupled from value delivered
• 5+ tiers or feature-salad packaging with no segment logic
• Scaling acquisition is recommended with LTV/CAC < 1 or unknown unit economics
• The price assumes budget authority the ICP buyer does not have

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Related skills

Skill	When to use
pmm/positioning/SKILL.md	Before: pricing requires FINAL positioning (value + named alternative)
pmm/icp-research/SKILL.md	Before: willingness-to-pay + the value metric come from the ICP
growth/motion-plg/SKILL.md	The PLG branch: free-tier funnel + free-to-paid mechanics in depth
growth/paid-channel-fit/SKILL.md	After: consumes the LTV/CAC output when deciding to scale paid acquisition
pmm/ai-product-gtm/ai-usage-pricing-growth/SKILL.md	Instead/alongside for AI-specific monetization: token/credit economies, usage-based metering, AI freemium
growth/north-star-metrics/SKILL.md	Guardrail: ensure a monetization change doesn't damage PLG activation/retention
pmm/gtm-brief/SKILL.md	Downstream: pricing + packaging feed the GTM brief

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Output format

## Pricing Artifact

**Product:** [name]   **Motion:** [PLG / SLG / hybrid]   **Status:** [DRAFT / FINAL]

### Value metric
Charge by: [unit] — scales with [the value it tracks]

### Price triangulation
Value anchor: [quantified value] → capture ~[%] → [price/range]
Cost floor: [margin check]   Competitor reference: [alternative's model]

### Packaging
| Tier | Segment | Key value (leader features) | Upgrade trigger | Price |
|---|---|---|---|---|
| [Good] | … | … | … | … |
| [Better] | … | … | … | … |
| [Best] | … | … | … | … |
[Free tier (PLG only): what's free · upgrade trigger · free→paid mechanic]

### Unit-economics gate
[ ] LTV/CAC: [value] ([PASS/BORDERLINE/FAIL])
[ ] CAC payback: [months] ([PASS/BORDERLINE/FAIL])
[ ] Gross margin: [PASS/FAIL]

### Buy-readiness
[ ] Authority  [ ] Trigger  [ ] Procurement path → [verdict / mitigation]

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References & Sources

Tier 1:

• David Skok, SaaS Metrics 2.0 (a long-standing SaaS framework, forEntrepreneurs) — LTV/CAC ≥ 3 and CAC-payback thresholds; the unit-economics sanity gate (Step 4).
• Madhavan Ramanujam, Monetizing Innovation (2016) — willingness-to-pay before building; Leader/Filler/Killer feature classification; tier design (Step 3).
• Value-based pricing practice — Patrick Campbell / ProfitWell; van Westendorp Price Sensitivity Meter — value anchoring and WTP testing (Steps 2–3).
• April Dunford, Obviously Awesome (2019) — pricing follows positioning; the competitive alternative is also the price reference frame (Gate 0, Step 2).

Note on the soft ranges: the value-capture % and free→paid figures are Fieldwork heuristics / diagnostics, not sourced benchmarks (labeled as such above). They are starting points to test against your own data, not numbers to anchor on.

Scope boundary (related skills): this skill is general value-based pricing. For AI-specific monetization — token/credit economies, usage-based metering, freemium calibration for AI products — use pmm/ai-product-gtm/ai-usage-pricing-growth instead (or alongside, for the AI-usage layer). For the decision to scale a paid channel on these unit economics, hand off to growth/paid-channel-fit.

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Output metadata (append to every FINAL output):

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Skill: pricing v1.0.0
Role: workflow
Confidence: [0-100]
Review Trace: [reviews passed, or "DRAFT — pending: positioning FINAL / unit-economics instrumentation"]
Bridge Signals: [bridges consulted, or "none"]
Brain Context: [connected / not connected]
Sources: SaaS Metrics 2.0 (Skok); Monetizing Innovation (Ramanujam 2016); value-based pricing (Campbell/ProfitWell); Obviously Awesome (Dunford 2019)
Generated: [date]
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