IADES Startup

h1. Price Formation

Pricing - Reflection Guide

*1 · Product & Strategy ⬇️​*

* What single business goal must pricing accelerate right now?

* Why: Price crafted for adoption (freemium) can starve cash if runway is the real need.

* Is the product inherently sticky once adopted?

* Why: Sticky products recoup revenue via expansion; non-sticky products must charge earlier.

* Will we run product-led, sales-led, or hybrid GTM in the next 12 months?

* Why: Each motion sets different list-price and discount expectations.

* Does pricing reinforce our positioning (premium vs. disruptive)?

* Why: Price signals market segment louder than marketing copy.

*2 · Customer & Value ⬇️​*

* Who is the ideal customer profile and which budget line pays?

* Why: CIO budgets tolerate very different prices than hobbyist credit cards.

* What quantified outcome do we deliver (hours saved, \$ gained, risk avoided)?

* Why: Value-based pricing needs a credible ROI anchor.

* Have we run a real Willingness-To-Pay test?

* Why: A 1 % price lift ≈ 12 % profit boost in SaaS; don’t leave money on the table.

* Do different segments show different WTP?

* Why: Drives tiering or usage caps that match value delivered.

*3 · Cost & Unit Economics ⬇️​*

* What is our fully-loaded COGS per unit of the value metric?

* Why: AI / usage products must price to cost anchor to protect margin.

* What gross-margin floor will we defend (≥ 70 %)?

* Why: Ensures cash for R&D and GTM.

* How volatile are those costs over time?

* Why: Volatile costs argue for variable or hybrid pricing over flat subscriptions.

*4 · Market & Competitive Context ⬇️​*

* Which pricing models dominate our segment today?

* Why: Buyers anchor on familiar patterns; swimming upstream needs extra messaging.

* Where do we sit on the price spectrum vs. substitutes?

* Why: A premium can work—if extra value is obvious.

* Are rivals shifting to usage or hybrid because of AI costs?

* Why: Flat pricing may soon look outdated or risky.

*5 · Packaging & Metrics ⬇️​*

* Which value metric best tracks customer success?

* Why: Tight linkage makes upsell feel natural, not punitive.

* Do we keep plan choices ≤ 5 blocks/tiers?

* Why: Too many options hurt conversion; 3–5 captures 95 % of demand.

* Do feature gates create or destroy value for our ICP?

* Why: One-plan models use usage caps; some markets expect classic feature tiers.

*6 · Expansion & Retention ⬇️​*

* What built-in levers let customers spend more as they succeed?

* Why: Without them, Net Revenue Retention caps at 100 %.

* Do we know the target attach-rate for add-ons (e.g., 5–10 %)?

* Why: Add-ons lift margin without complicating core pricing.

* Will annual pre-pay or credit packs smooth cash flow?

* Why: Improves capital efficiency and shortens CAC payback.

*7 · Operational Guard-Rails ⬇️​*

* Can we meter usage in real-time and show it in-product?

* Why: Transparent meters reduce “bill-shock” churn.

* Do we offer budget caps or auto-throttles?

* Why: Gives buyers confidence to experiment with variable pricing.

* Is there a schedule for price experiments (≥ twice a year)?

* Why: Pricing is a product—iterate with data.

*8 · Changes & Messaging ⬇️​*

* Can we state the price in one clear sentence a buyer gets in < 10 s?

* Why: Complexity kills conversion.

* Do we have a grandfather policy for existing users when prices rise?

* Why: Prevents public backlash and churn spikes.

* Is there a playbook for migrating beta/freemium users to paid?

* Why: Smooth upsell preserves goodwill and ARR.

* Do we keep a documented price-increase playbook (timing, notice, refunds/credits)?Why: Being proactive avoids support fire-drills and lost trust.