AI Masterclass: Changing perspectives with AI – how a critical customer views your offering (and how you can optimize it)

1️⃣ Getting started: The real problem

You have an offer that "actually" sounds good.
You have benefits, a clean PDF, maybe even case studies. And yet: too few inquiries, too many queries, too many "We'll get back to you".

The reason is often not the quality of your offer - but the perspective.
Because your customer doesn't read like you do. A critical customer looks for risks, ambiguities, cost traps and evidence.

And this is where AI is extremely powerful: it can take your offer apart like a skeptical decision-maker - and show you what you need to improve specifically.

2️⃣ Why the problem remains

Typical misconceptions that you probably know:

• You argue from your expert logic, not from the customer's perspective ("we do X" instead of "you'll get Y for sure").
• You rely on buzzwords ("holistic", "customized", "innovative") instead of clarity.
• Your offer is too nicely worded - but not resilient: no risks addressed, no boundaries, no evidence.
• You optimize the text, but not the Trust (objections, proof, risk reversal, clear next steps).

The critical customer thinks:

"Sounds good - but what's the catch?"

3️⃣ The concrete solution: The "critical customer check" AI framework

Use AI not as a copywriter - but as a simulated buyer with an agenda.

Framework in 4 steps:

1. Set role & context
   AI gets persona + goal + risk level (e.g. CFO skeptical, time pressure, bad experience with service providers).
2. Have the offer broken down
   AI highlights ambiguities: Promises, scope, prices, results, schedule, dependencies.
3. Generate objections & mistrust
   AI formulates tough questions, "red flags", and what it would need to buy.
4. Optimization suggestions as concrete text modules
   AI does not write "better", but provides: new headline, proof elements, risk reversal, scope box, FAQ, guarantees, next step.

Example prompt (universal)

Copy your offer (text or key points) below and use it:

Role: You are a critical, experienced customer (decision-maker) and are looking for reasons not to buy.
Task: Analyze the following offer.
Output:

1. The 10 biggest doubts/objections (hard, realistic).
2. What information is missing to make a purchase decision?
3. Where are empty phrases or unsubstantiated promises?
4. What risks do I see (time, money, result, dependency)?
5. Concrete optimizations: Formulate improved text modules for headline, value proposition, proof, scope, process, FAQ, call-to-action.
   Offer: [INSERT HERE]

4️⃣ Practical example 1: Consulting offer (B2B)

Initial situation (before)

A consulting company offers:
"Strategy workshop + implementation support for AI introduction - individual, holistic, customized."

Critical customer thinks:

• "What exactly do I end up with in my hand?"
• "How are you different from 20 others?"
• "What does it cost - and what does it depend on?"
• "What internal resources do I really need?"
• "What happens if it doesn't work?"

AI analysis: typical "red flags"

• Result unclear: "support" instead of concrete deliverables
• Scope vague: What's in, what's not?
• Process too generic: no phases, no decisions, no milestones
• Proof missing: no key figures, no concrete cases, no reference logic
• Risk is not addressed: "What if you don't deliver internally?"

Optimization (after) - this is what your offer could look like

Instead of: "Holistic support"
New: "In 21 days to an AI roadmap incl. priority list, business case estimate and pilot blueprint."

Concrete building blocks that AI can provide you with:

• Deliverables box:
  • AI use case backlog (20-40 ideas)
  • Quick win matrix (impact x effort)
  • Pilot plan (goals, data, tools, roles, budget framework)
  • Governance light (approvals, guidelines, tool stack)
• Risk clarification: "What we need from you" + "If you don't have this, then..."
• Anticipate objections (FAQ): "Why workshop is not enough", "How do we measure success", "What happens in case of blockades"

Mini prompt specifically for consulting services

Play a skeptical COO. Ask 15 uncomfortable questions about results, effort, responsibilities, risks, scope, alternatives and measuring success. Then answer them yourself from the provider's perspective - but only with reliable, clear statements. Highlight anything that is still too vague.

5️⃣ Practical example 2: Product offering (e.g. SaaS or physical product)

Initial situation (before)

A product provider sells a tool, for example:
"Our software automates your reporting with AI - faster, smarter, better."

Critical customer thinks:

• "What does automate mean in concrete terms? Which reports? Which sources?"
• "How long does setup really take?"
• "What data do I have to release - and how secure is it?"
• "What does it cost after 12 months?"
• "What are the limits?"

AI analysis: typical weaknesses

• Value proposition too broad ("better")
• No clear use cases ("for whom exactly?")
• No proof ("how much time do you really save?")
• No comparability (plan/price/ROI missing)
• No friction reduction (onboarding, migration, security, integration)

Optimization (after) - this is what a "critical customer"-optimized product offering looks like

Instead of: "faster, smarter"
New: "Create monthly reports from DATEV + HubSpot in 3 minutes - incl. comments & variance analysis."

Elements you should add (AI helps with formulation):

• Use case tiles: "For Finance", "For Sales", "For Ops" - each with a specific example
• ROI snippet: "Saves on average X hours/month with team size Y"
• Integration list + restrictions: "Works with..., not suitable for..."
• Security & compliance short part: Data storage, access rights, audit logs
• Price clarity: "From .../month, setup optional, termination, minimum term"
• "What happens if...": Support, SLA, refund/trial, exit/migration

Mini prompt especially for product offers

You are a suspicious buyer. Rate this product offer on: Clarity, Proof, Risk, Price Logic, Implementation Effort, Integration Capability, Support. Give a scorecard (1-10) and then write the better version of the first 200 words of the landing page.

6️⃣ Immediately actionable steps (doable today)

1. Copy your offer (website text, PDF, pitch deck text - doesn't matter) into an AI tool.
2. Use the critical customer check (prompt above).
3. Use it to create 3artifacts that almost always increase conversion:
   • Deliverables-/Scope-Box
   • FAQ with hard objections
   • Proof/evidence elements (figures, cases, procedural evidence)
4. Have AI writetwo versions :
   • Version A: "Short & clear" (for decision-makers)
   • Version B: "Detail & certainty" (for risk avoiders)
5. Test live:
   • Website: A/B headline
   • Sales: new offer PDF with Scope+FAQ
   • Product: Landingpage-Above-the-fold new

7️⃣ Strategic classification

If you don't make this change of perspective, the following will happen:

• You attract more "nice-to-have" prospects instead of ready-to-buy customers.
• Your sales team wastes time on basics ("What's included?").
• You compete on likeability or price - instead of trust and clarity.

When you make it, the structure changes:
You build offers thatanticipate objections, reduce risks and make a decision easier.
This is a real competitive advantage - especially in markets where "everyone promises roughly the same thing".

8️⃣ Conclusion + call-to-action

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🚀 Next step

If you not only want to understand AI, but also use it in a structured way in your company, then:

👉 Find out more about our AI training course:
https://bloo.school

👉 Find out about our Smart Market Fit offers:
https://bloola.com/smf - The Smart Market Fit course
https://bloola.com/smf-system - The Smart Market Fit System for companies

👉 Or find out more about our consulting and automation solutions:
https://bloola.com