Pricing analysis

Pricing & Packaging Analysis

Decode how a company prices and packages — and where they're leaving money on the table or scaring buyers away.

What it does

Breaks down a pricing page into its mechanics — the value metric, tier structure, psychological devices, and gating logic — then evaluates how well the pricing matches the buyer and recommends concrete changes. Works for a single company or a side-by-side comparison of several.

When to use this skill

• "Analyze this pricing page: <url>."
• "Is our pricing right? Here are our plans."
• "Compare pricing for <A> vs <B> vs <C>."
• Designing or auditing packaging, tiers, or a price increase.

Inputs needed

• Required: the pricing page URL(s), or the plans/prices pasted in.
• Helpful: the target customer, the product's main value metric, the user's goal (raise ARPU, reduce friction, move upmarket), and competitor prices.
• If pricing is "contact sales" with nothing public, analyze the strategy that implies and ask for any figures the user has.

Method

1. Inventory — list every plan: name, price, billing cadence, what's included, limits, and the headline benefit of each.
2. Find the value metric — what does price scale on (seats, usage, contacts, revenue, flat)? Is it aligned with the value the customer gets and growth?
3. Read the structure — Good-Better-Best? How many tiers? Is there a clear "most popular" anchor and an enterprise/contact tier as the upper anchor?
4. Spot the psychology — anchoring, decoy tier, charm pricing, annual discount framing, urgency, "save X%", free tier/trial as acquisition.
5. Check gating — are the right features gated to drive upgrades, or are key features locked too early (friction) or given away too freely (left money)?
6. Assess fit — does the entry price match the ICP's willingness to pay? Is there a gap between free and the first paid tier (the "leap")?
7. Recommend — specific changes: re-tiering, value-metric change, anchor additions, gating moves, packaging simplification. Prioritize by impact/effort.

Output format

# Pricing Analysis — <Company>

## TL;DR
- The value metric, the structure, and the single biggest pricing opportunity.

## Plan inventory
| Plan | Price | Billing | Value metric | Key inclusions / limits | Apparent target |
|------|-------|---------|--------------|-------------------------|-----------------|

## Structure & psychology
- Tier model (e.g. Good-Better-Best):
- Anchors (most-popular / enterprise):
- Devices observed (decoy, charm, annual discount, urgency):

## Gating & monetization
- What's gated where, and whether it drives upgrades:
- Free → first paid "leap":

## Fit with the buyer
- Entry price vs ICP willingness-to-pay:
- Where pricing creates friction or leaves money on the table:

## Recommendations
| # | Recommendation | Why (finding) | Impact | Effort |
|---|----------------|---------------|--------|--------|

(For a comparison, add a matrix: rows = companies, columns = entry price, value metric, # tiers, free option, annual discount, enterprise tier.)

Quality bar

• Quote prices exactly as shown, with currency and cadence. Note the capture date.
• Separate observed structure from your recommendations.
• No invented willingness-to-pay or conversion numbers — reason qualitatively.
• Every recommendation references a specific finding.

Common mistakes to avoid

• Saying "too expensive / too cheap" without tying it to the buyer and value.
• Ignoring the value metric (the highest-leverage pricing decision).
• Recommending more tiers when the problem is an unclear anchor.