Gtm-Technical-Product-Pricing

# Technical Product Pricing

Initial Assessment

Before recommending pricing, understand:

1. **Product type**: API/platform, developer tool, SaaS application, infrastructure?

2. **Current pricing**: What do you charge now? How long has it been this way?

3. **GTM motion**: Self-serve, sales-assisted, enterprise, or hybrid?

4. **Cost structure**: What's your marginal cost per customer/user/unit?

5. **Competitive landscape**: What do alternatives cost? (Including "do nothing")

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Core Frameworks

1. The Price Increase Nobody Noticed (You're Probably Underpriced)

**The Pattern:**

Platform company, growth stage. Pricing hadn't changed since launch. Enterprise customers paying $15K/year for a product saving them $200K+ in engineering time.

Leadership debate: "If we raise prices, we'll lose customers."

**What actually happened:**

Raised enterprise tier from $15K to $45K/year. Added dedicated support, SSO, audit logs to justify the jump.

Lost: 0 enterprise customers. Zero.

Gained: 3x revenue per enterprise account. Plus the customers who stayed started taking the product more seriously — higher adoption, more internal champions, more expansion.

**Why This Happens:**

Technical founders anchor pricing to cost ("it costs us $X to serve them, so we charge $2X"). Enterprise buyers anchor pricing to value ("this saves us $200K, so $45K is cheap").

**The Pricing Sanity Check:**

For every customer segment, calculate:

Value Ratio = Customer's alternative cost / Your price

If Value Ratio > 10x → You're massively underpriced
If Value Ratio > 5x  → You're underpriced (most startups are here)
If Value Ratio 3-5x  → Healthy pricing
If Value Ratio < 3x  → Approaching ceiling
If Value Ratio < 2x  → You're expensive (need strong differentiation)

**How to Calculate Alternative Cost:**

- Hours spent on manual process × hourly rate × frequency

- Cost of building in-house (engineers × months × loaded cost)

- Cost of existing tool + switching cost + productivity loss during transition

- Cost of *not solving the problem* (incidents, downtime, churn)

**Common Mistake:**

Comparing your price to competitors instead of to customer's alternative cost. Competitors anchor you to a race to the bottom. Value anchors you to what the customer actually saves.

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2. The Three Pricing Models (And When Each Breaks)

**Model 1: Seat-Based ($X/user/month)**

**Works when:**

- Value scales with number of users (collaboration tools, communication)

- Usage is relatively uniform across users

- You want predictable revenue

**Breaks when:**

- Power users and casual users get same price (casual users churn)

- Product value doesn't scale with seats (one admin configures for 1,000 users)

- Customers consolidate seats to reduce cost (usage goes up, revenue doesn't)

**Model 2: Usage-Based ($X/unit)**

**Works when:**

- Usage varies significantly by customer (API calls, compute, storage)

- Marginal cost is meaningful (you need usage to track with revenue)

- Value directly correlates with usage

**Breaks when:**

- Customers can't predict bills (sticker shock at month-end)

- Low-usage customers aren't worth supporting

- High-usage customers negotiate volume discounts that compress margins

**Model 3: Outcome-Based ($X/result)**

**Works when:**

- You can measure outcomes reliably (leads generated, tickets resolved, code deployed)

- Outcomes directly create customer value

- You have confidence in your product's effectiveness

**Breaks when:**

- Outcomes depend on factors outside your control

- Measurement is disputed ("that lead wasn't from your tool")

- Customers game the metric

**The Hybrid That Usually Wins:**

Platform fee (covers your fixed costs) + usage/outcome variable (scales with value).

Example: $500/month base + $0.05 per transaction (or API call, task completed, record processed — whatever your unit of value is).

Why this works:

- Base fee ensures every customer covers cost to serve

- Variable fee aligns price with value

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