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HayatelinHayatelin/founder-skills/skills/pricing-strategy/SKILL.md

pricing-strategy

Skill0 starsChanged 5 months agoMITView on GitHub

Chooses a pricing model (per-seat, usage, outcome-based, or hybrid), sets tiers, and sanity-checks unit economics. Trigger on "how should I price", "help me price my SaaS", "pricing tiers", "what should I charge", "outcome-based pricing", or "are my unit economics okay".

110 other projects use a version of this.

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Projects with it also use community-led-growth, ph-community-outreach and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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  • +6 more from nicepkg

The file

We split this skill into the rules it gives an agent

2 rules. 0 are common, 2 are distinctive, and 0 are very specific to this project.

  • 0

    Common

    Most of the 103 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 0

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    When a founder must pick a pricing model and tiers, or pressure-test whether the current pricing supports a healthy business.

    line 11
  2. Distinctive:

    Avoid: cost-plus pricing; too many tiers.

    line 45

“Common” is measured: kept by at least 6 in 10 of the 103 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

When to use

When a founder must pick a pricing model and tiers, or pressure-test whether the current pricing supports a healthy business.

Inputs to gather

  1. What value/outcome the product delivers and how it's measured.
  2. ICP and their budget reality (who signs, what they spend today).
  3. Rough cost-to-serve per customer (incl. model/API costs).
  4. Current or guessed CAC and expected retention.

Process

  1. Pick the model by value metric:
    • Per-seat — value scales with users (collaboration tools).
    • Usage — value scales with volume; aligns cost-to-serve.
    • Outcome-based — charge per result delivered (per resolved ticket, per confirmed booking, per agent action). The 2026 shift; NRR 120-150% when it lands. See Intercom Fin (per-resolution), Zendesk (per automated resolution), Salesforce (per agent action).
    • Hybrid — small platform fee + outcome/usage, to floor revenue and de-risk.
  2. Set 3 tiers (entry / pro / enterprise) anchored to value, with a clear reason to upgrade between each. Use price anchoring — make the middle tier the obvious pick.
  3. Sanity-check unit economics: LTV = ARPA × gross margin × avg lifetime. Target LTV:CAC ≥ 3:1 and CAC payback < 12 months. Flag if model costs crush margin.
  4. Stress-test churn: assume B2B 10-20%/yr, B2C 40-60%/yr; if B2C, push toward annual or higher-value use cases.

Output

  • Recommended model + one-line rationale tied to the value metric.
  • Tier table: name, price, who it's for, gating feature, upgrade trigger.
  • Unit economics: LTV, CAC, LTV:CAC, payback months, with assumptions.
  • One pricing experiment to run next (e.g. test outcome vs. seat on 5 deals).

Quality bar & pitfalls

  • Good = price maps to a value metric the customer already counts in their head.
  • Outcome-based requires you can attribute and measure the result — verify that first.
  • Avoid: cost-plus pricing; too many tiers; undercharging "to get started" (anchors low forever); ignoring API/model cost in margin. For vertical AI, outcome + proprietary data is the durable combo.

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