Business Strategy
LLM Prompts
Intermediate
Data-Driven Business Plan Researcher
Create a data-driven business plan with market statistics, competitive analysis depth, and tailored data sourcing for your sector.
Best Model
ChatGPT GPT-5.5 Thinking / Claude Opus 4.7Deep reasoning
Brevity Mode
Detailed
Difficulty
Intermediate
Automation
Needs user context
Use This When
Planning, analysis, client strategy sessions, decision support.
Inputs Needed
Business model, goal, constraints, market, competitors, budget, timeline, internal capabilities.
Expected Output
Executive summary, diagnosis, options, risks, recommended path, implementation plan, KPIs.
The Workflow Prompt
You are a business strategist and operator. Objective: Data-Driven Business Plan Researcher Context: Create a data-driven business plan with market statistics, competitive analysis depth, and tailored data sourcing for your sector. Original task: You are an expert in business plan research. I want a data-driven plan with relevant market statistics for my [sector]. Ask me about the data sources, the scope of market analysis, and how in-depth the competitive section should be. Inputs I may provide: Business model, goal, constraints, market, competitors, budget, timeline, internal capabilities. Operating instructions: - First, restate the objective in one clear sentence. - If critical information is missing, ask up to 5 focused questions. If there is enough information to proceed, make practical assumptions and label them. - Use a Detailed response style. - Be specific to the business, audience, channel, and constraints provided. - Avoid generic AI advice. Give concrete recommendations, examples, templates, copy, or steps I can use. - When current facts, competitors, laws, prices, policies, or market claims matter, use current research and cite sources. - Do not expose hidden chain-of-thought. Provide a concise rationale or decision summary instead. - End with a short QA checklist that helps me verify the output. Required output: Executive summary, diagnosis, options, risks, recommended path, implementation plan, KPIs. Caution: Avoid generic output; require concrete examples, assumptions, and next steps.
QA Follow-Up Checklist
After the AI returns its output, verify against:
- Output is specific to the provided business/context.
- Assumptions are clearly labeled.
- No unsupported claims without source checks.
- Next actions are clear and usable.
Follow-Up Prompt
Now turn the result for 'Data-Driven Business Plan Researcher' into a client-ready version: tighten wording, remove fluff, add missing assumptions, and provide the next 3 actions.
Avoid / Cautions
Avoid generic output; require concrete examples, assumptions, and next steps.