An offer written for the client, not the product
AI Sales 12 min
0/19
Business problem
Offers are 'catalog-like': a product description, features, a price list. They don't refer to what the client said in discovery, don't show ROI, don't answer objections. The client compares prices instead of understanding value — because the offer doesn't let them.
Proven method
The offer structure in 7 sections:
- EXECUTIVE SUMMARY: 1 page — the client's situation (their problem, their discovery context), what we propose (an outcome, not a product),
- UNDERSTANDING: 3-5 bullets 'we understand your situation' (facts from discovery — shows listening),
- SOLUTION: what they get (specifically, by their needs),
- CASE STUDY: 1 example of a similar company with numbers (instead of a feature description),
- ROI: how much they gain — numbers from discovery (lost orders, time, cost),
- TERMS: scope, price, deadlines (clearly, without hidden costs),
- FAQ: answers to the objections that came up in the call. AI: client data + context (transcription, notes, discovery) → AI generates an offer draft with sections, proposes an executive summary and ROI from the numbers you provide; you verify all numbers and add the tone. The rule: an offer has to be so specific that the client sees THEMSELVES, not a 'sample client'.
Market example
- BAD
- Improvised general pitch lacking buyer context or verified data.
- GOOD
- A weak offer: 'Our product has features A, B, C. Price: X/month'. A strong one: 'We understand that at 200 inquiries a month, 24h+ responses cost you about 10 orders a month. With our queue and a 2h SLA you recover part of them — that's ~[amount] a month. Below is a case of an agency that cut responses from 24h to 2h and recovered 10% of conversions. Scope: queue implementation, email integration, training for 2 people, SLA. Price: [X]/month. FAQ: 'Can we start with a smaller scope?' — yes, a starter plan'.
Ready-to-use prompt
You are an offer advisor. Context: I sell [PRODUCT]. Client: [COMPANY + DISCOVERY CONTEXT: problem, needs, numbers, objections]. Price/scope: [WHAT I PLAN]. Task: Generate an offer draft: 1. Executive summary (1 paragraph — the client's situation, the outcome, not our story) 2. 'We understand your situation' (5 bullets from discovery facts) 3. Solution (what they get, by their needs) 4. A case study suggestion (what example to give + what numbers) 5. ROI argumentation (how to calculate the value from discovery numbers) 6. Terms (scope, price, deadlines — a skeleton) 7. FAQ (answers to the objections that came up) Mark which numbers I MUST verify before sending. Format: 7 sections.
Model rekomendowany: Claude 3.5 Sonnet / GPT-4o Copy and paste into ChatGPT, Claude or Perplexity
ALTERNATYWNE SCENARIUSZE
Variations & alternative scenarios
Services version: an offer with a work scope and stages.
SaaS version: an offer with plans, implementation and SLA.
Practical exercise
Write an executive summary of an offer for 1 lead (the client's situation + the outcome). Prepare ROI from discovery numbers. Check whether the offer has an FAQ with objections from the call.
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