## Start With the Client Questionnaire

**Purpose:** Understand who they want to target, not the whole market.

**Key inputs extracted:**  
* Priority regions  
* Competitor list  
* Target customer segments

**Explicit non-targets to avoid (important filter)**

**Why this matters:** This defines the scope so we don’t generate prompts for irrelevant verticals (example, pharma, R&D, clinical labs in this case).

## Identify Real Workflow Problems (Not Product Features)

We avoid using the client’s internal terminology because it usually does not reflect how people actually search.

We instead look at:  
* The jobs-to-be-done  
* The pain points that drive software adoption

**Typical categories to explore:**  
* Compliance / documentation friction  
* Operational bottlenecks  
* Data integrity issues  
* Reporting requirements  
* Staffing + workload constraints

## Gather Real Market Language (Not Assumptions)

We search how practitioners talk in the wild.

Use LLMs, Reddit, discussion boards, Q&A threads:  
* Search using workflow pain questions, not product names (example, "how to maintain chain of custody logs" instead of "LIMS software").

**Outcome:**  
* A list of real, verbatim questions showing how people actually describe their problems.

## Group the Real Questions Into Themes

We don’t invent themes. We observe patterns:

**Example resulting themes:**  
1. Chain-of-custody & sample tracking  
2. Instrument data-transfer issues  
3. QA/QC review workflows  
4. State/municipal reporting requirements  
5. Turnaround-time bottlenecks

These themes reflect recurring real-world pain not marketing categories.

## Normalize the Questions Into Neutral Search Prompts

**Goal:** Convert messy human phrasing → clean prompts that AI search engines respond to consistently.

**Normalization rules:**  
* Keep the pain + workflow + constraint  
* Remove local context, emotion, anecdotes  
* Avoid vendor names, solution bias, or insider jargon

This step produces the final prompt list for OptimizeGEO scanning.

## Final Output

A structured topics + prompts set, ready for measurement scans. This set:  
* Reflects actual market pain  
* Avoids branding bias  
* Aligns with target customer segments  
* Is generalized enough for AI platform visibility analysis

## Why This Works

This approach avoids:  
* Guessing  
* Overfitting to client worldview  
* Feature-based prompts that have no real search demand

Instead, we anchor prompts in:  
* Real conversations  
* Real workflows  
* Real regulatory + operational friction

Which produces signal-rich visibility measurement data.

Topics, Prompts & Planning - GEO Strategy Guide | OptimizeGEO  
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