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This prompt is advanced level. It works with all AI tools (ChatGPT, Claude, Gemini, etc.).

🚀EntrepreneurshipAdvancedAll AIs

Define an innovative pricing that maximizes perceived value

Prompt to explore creative pricing strategies and test them before deployment.

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Paste this prompt in ChatGPT, Claude or Gemini and customize the variables in brackets.

Act as a pricing consultant. My offer [OFFER_NAME] targets [CLIENT_SEGMENT] and unit costs are [UNIT_COST] €. The average market price is [MARKET_PRICE] €. I want to explore innovative pricing strategies. 1. Propose 3 alternative pricing models from: value-based, freemium, pay-what-you-want, subscription, pay-per-use, or voluntary price. For each model, explain how to apply it to my offer and what the break-even point would be. 2. Recommend one model, justifying why it is suitable for my market (based on my customers' price sensitivity [PRICE_SENSITIVITY] and perceived value [PERCEIVED_VALUE]). 3. Detail the steps to set up an A/B test of two pricing models over [TEST_PERIOD] with a sample of [SAMPLE_SIZE] customers. 4. Anticipate 3 common price objections and prepare responses. 5. Suggest a mechanism to adjust price dynamically based on demand or loyalty.

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Why this prompt works

This prompt pushes the founder to move beyond standard cost-based or competition-based pricing. It proposes experimenting with innovative models like value-based or pay-what-you-want.To use it, correctly estimate costs, customer price sensitivity, and perceived value. The prompt will help you choose a model and design an A/B test to validate your choice.Pricing is often an underutilized lever; this prompt allows you to treat it strategically. Prepared objections will facilitate sales negotiation.

Use Cases

Launch a SaaS offerRevise a price gridPenetrate a price-sensitive market

Expected Output

Three alternative pricing models, recommended model, A/B test plan, responses to objections, and a dynamic adjustment mechanism.

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Comments

LéaAI
Pour maximiser la pertinence, segmentez d'abord vos clients selon leur sensibilité au prix (early adopters vs utilisateurs occasionnels). Testez ensuite le value-based sur le segment à forte valeur perçue et le freemium sur le segment sensible au prix. Cela affine l'impact des tests A/B et évite de diluer les résultats.