Pricing Strategy

Most early products are underpriced. This skill picks the model, designs the tiers, and writes the page, with the bias set to "charge more than feels comfortable."

1. Pick the value metric first

Ask: "What unit grows for the customer as they get more value?" (seats, projects, messages, revenue processed, documents). Price along that axis. If value and price scale together, growth is built in.

Then match the model:

• Flat monthly: value is uniform per customer. Simplest to explain; caps upside.
• Per seat: value scales with team size. Default for B2B collaboration tools.
• Usage-based: value scales with consumption. Best alignment; hardest to forecast, scary for buyers without a cap or committed tier.
• Freemium: only when the free tier feeds the paid tier (network effects, virality, or usage that naturally outgrows limits). Otherwise it is just free support load.

2. Design three tiers

Three is the number. Two gives no anchor; four causes stalls.

• Low tier: solo or starter. Priced to make the middle look reasonable, missing one thing serious users need.
• Middle tier: where 70% of buyers should land. Mark it "Most popular."
• High tier: 3-5x the middle. Exists partly to anchor; the buyers it fits are real but few. This is the decoy structure working as intended.

Rules for the grid:

• Gate tiers by the value metric and 1-2 capability differences, not a 20-row feature matrix.
• Annual pricing shown by default with roughly 2 months free; monthly available.
• Enterprise = "Talk to us" only when there is a real sales motion; otherwise skip it.

3. Write the page

For each tier: name, price, one-line who-it-is-for, 4-6 bullets phrased as outcomes ("Unlimited client projects") not internals ("Postgres row limit raised"). One FAQ section handling the top 4 objections: cancellation, what happens at limits, refunds, security or data ownership.

Rules

• Anchor on the cost of the problem or the tool it replaces, never on your infrastructure costs.
• Recommend a specific price with reasoning. "It depends" is not an output of this skill.
• First-price heuristic when there is no data: pick the number that feels right, then raise until roughly 1 in 4 prospects pushes back. No pushback means too cheap.
• Grandfather existing customers on price raises. Cheap goodwill.
• Never promise revenue outcomes; pricing is a hypothesis to test like any other.