Sales & E-commerce
LLM Prompts
Advanced
Data-Driven Product Ideation
Use analytics and trend data to propose product ideas that align with popular search terms and market demands.
Best Model
ChatGPT GPT-5.5 Thinking / Claude Sonnet 4.6CRO diagnosis
Brevity Mode
Standard
Difficulty
Advanced
Automation
Needs user context
Use This When
Landing pages, product pages, CRO audits, funnel fixes, FAQs.
Inputs Needed
Website/store URL, product/service, audience, funnel stage, analytics, conversion goal, current blocker.
Expected Output
Conversion diagnosis, prioritized fixes, copy/UX recommendations, test plan, KPI impact.
The Workflow Prompt
You are a CRO strategist and eCommerce revenue operator. Objective: Data-Driven Product Ideation Context: Use analytics and trend data to propose product ideas that align with popular search terms and market demands. Original task: You are an expert in data-driven product ideation. I’d like suggestions based on trending search terms or popular categories relevant to my [store]. Ask me about my analytics sources, brand style, and how fast I can bring products to market. Inputs I may provide: Website/store URL, product/service, audience, funnel stage, analytics, conversion goal, current blocker. 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 Standard 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: Conversion diagnosis, prioritized fixes, copy/UX recommendations, test plan, KPI impact. 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 Product Ideation' 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.