Price Increase Plan AI Prompt Template

Plan a price increase without losing customers using this AI prompt. Strategy, messaging, grandfathering, and rollout plan. Free to copy and use today.

The prompt

ROLE: You are a pricing consultant who has guided 100+ companies through price increases with under 3% churn impact.

CONTEXT: Product: [PRODUCT]. Current price: [CURRENT_PRICE]. Proposed price: [NEW_PRICE]. Customer base: [CUSTOMERS]. Reason for increase: [REASON]. Contract terms: [CONTRACTS].

TASK: Build a complete price increase plan.

FORMAT: 1. Increase Strategy (who gets the increase when: new vs existing customers, grandfathering options with pros/cons). 2. Justification Narrative (the value story: what improved since the last price, in customer terms). 3. Customer Communication: email draft (under 200 words), FAQ (6 questions), and talking points for sales/support. 4. Rollout Timeline (announce date, effective date, checkpoints). 5. Risk Mitigation (churn estimate, save plays for at-risk segments, escalation path). End with a Go/No-Go checklist of 5 items.

CONSTRAINTS: Tone must be confident, not apologetic; apologize for surprise, never for the price. Grandfathering must have an expiry or it becomes permanent discount. All customer-facing copy in plain, respectful English.

Variables to fill in

Replace each [variable] in the prompt with your own details:

[PRODUCT] [CURRENT_PRICE] [NEW_PRICE] [CUSTOMERS] [REASON] [CONTRACTS]

Example input

PRODUCT=project management SaaS, CURRENT_PRICE=$12/user/mo, NEW_PRICE=$15/user/mo, CUSTOMERS=4,000 SMBs, REASON=shipped AI features, 99.99% uptime, support costs up; CONTRACTS=monthly, cancel anytime

How to use this prompt

Decide the increase amount first, then generate the plan and have support and sales rehearse the talking points before any announcement.

Tips for the best results

Announce 30-60 days ahead; surprise increases feel like betrayal, announced ones feel like business.
Lead with added value, not rising costs; customers pay for value, not your problems.
Watch cancellation reasons daily for two weeks post-launch; the data tells you if messaging needs fixing.