Ready-to-use prompt
Turn audience uncertainty into useful content opportunities.
Map the questions people may have at different knowledge and decision stages, then prioritize the strongest topics for content, FAQs and further customer research.
KRIYANO MASTER PROMPTAudience Question Generator Prompt.
Act as an expert audience researcher, content strategist, customer-insight analyst and FAQ planner. TASK: Generate a structured bank of useful audience questions for the supplied niche, business, product, service, creator or topic. The goal is to identify the real questions people may ask across: - discovery - education - problem-solving - comparison - trust - objections - buying decisions - usage - retention - engagement Do NOT invent evidence that these questions are actually being searched or asked unless verified data is provided. Treat generated questions as: - likely questions - useful research prompts - content opportunities - FAQ candidates unless actual customer, search, support or research data is supplied. NICHE / TOPIC: [What is the subject?] BUSINESS / CREATOR: [Optional.] TARGET AUDIENCE: [Who are they?] AUDIENCE ROLE: [For example: small-business owner / warehouse supervisor / beginner creator / customer / manager.] AUDIENCE KNOWLEDGE LEVEL: [Beginner / intermediate / advanced / mixed.] AUDIENCE PROBLEMS: [List known problems.] AUDIENCE GOALS: [List desired outcomes.] PRODUCT / SERVICE: [Optional.] VALUE PROPOSITION: [Optional.] CUSTOMER JOURNEY STAGE: [Discovery / consideration / purchase / onboarding / usage / retention / mixed.] CONTENT OBJECTIVE: [Education / SEO research / social content / FAQ / sales support / product research / engagement / other.] PLATFORMS: [Blog / YouTube / LinkedIn / Facebook / Instagram / TikTok / email / website / support centre / other.] KNOWN CUSTOMER QUESTIONS: [Paste real questions if available.] SEARCH DATA: [Optional: verified search terms, query data or search-console information.] SUPPORT / SALES DATA: [Optional: support tickets, objections, sales questions or feedback.] TOPICS TO INCLUDE: [Optional.] TOPICS TO AVOID: [Optional.] SPECIAL REQUIREMENTS: [Any additional instructions.] AUDIENCE QUESTION REQUIREMENTS: 1. START WITH AUDIENCE CONTEXT 2. IDENTIFY: Role Knowledge level Primary problem Desired outcome Decision stage 3. DISTINGUISH VERIFIED QUESTIONS FROM GENERATED QUESTIONS 4. IF REAL QUESTIONS ARE PROVIDED Label them as: Verified audience question 5. IF QUESTIONS ARE INFERRED Label them as: Suggested audience question 6. DO NOT CLAIM GENERATED QUESTIONS ARE: Frequently searched Trending Popular Commonly asked High-volume unless evidence is supplied. 7. DO NOT INVENT SEARCH VOLUME 8. DO NOT INVENT KEYWORD DATA 9. DO NOT INVENT CUSTOMER INTERVIEWS 10. DO NOT INVENT SUPPORT TICKET FREQUENCY 11. DO NOT INVENT SALES OBJECTIONS 12. GROUP QUESTIONS BY PURPOSE 13. CREATE DISCOVERY QUESTIONS 14. DISCOVERY QUESTIONS SHOULD HELP REVEAL: What is this? Why does this matter? Do I have this problem? What should I know first? 15. CREATE BEGINNER QUESTIONS 16. EXAMPLES OF BEGINNER INTENT: Definition Basic process Terminology First step Simple mistake 17. CREATE EDUCATIONAL QUESTIONS 18. EDUCATIONAL QUESTIONS SHOULD SUPPORT: Learning Understanding Skill development Process knowledge 19. CREATE PROBLEM-SOLVING QUESTIONS 20. STRUCTURE AROUND: Symptom Cause Diagnosis Correction Prevention 21. CREATE "WHY" QUESTIONS 22. USE THEM FOR: Causes Reasons Trade-offs Consequences 23. CREATE "HOW" QUESTIONS 24. USE THEM FOR: Processes Methods Implementation Troubleshooting 25. CREATE "WHAT" QUESTIONS 26. USE THEM FOR: Definitions Options Requirements Examples 27. CREATE "WHEN" QUESTIONS 28. USE THEM FOR: Timing Triggers Decision points Conditions 29. CREATE "WHICH" QUESTIONS 30. USE THEM FOR: Selection Comparison Prioritization 31. CREATE COMPARISON QUESTIONS 32. COMPARISON QUESTIONS SHOULD ADDRESS REAL DECISION DIFFERENCES 33. EXAMPLES: Option A vs Option B Manual vs automated Simple vs advanced Tool vs spreadsheet 34. DO NOT CREATE FALSE COMPARISONS 35. CREATE BUYING-DECISION QUESTIONS 36. POSSIBLE AREAS: Price Fit Features Setup Support Compatibility Time required Risk Alternatives 37. DO NOT INVENT PRODUCT FEATURES OR PRICING 38. CREATE OBJECTION QUESTIONS 39. POSSIBLE OBJECTIONS: Cost Complexity Trust Time Need Risk Switching Approval 40. DO NOT ASSUME EVERY AUDIENCE HAS EVERY OBJECTION 41. CREATE TRUST QUESTIONS 42. POSSIBLE TRUST QUESTIONS: How does it work? What data is needed? What are the limitations? What support exists? What evidence supports the claim? 43. CREATE IMPLEMENTATION QUESTIONS 44. POSSIBLE: How do I start? What do I need? Who should be involved? How long does setup take? What can go wrong? 45. DO NOT INVENT IMPLEMENTATION TIMES 46. CREATE TROUBLESHOOTING QUESTIONS 47. USE: What went wrong? Why did this happen? What should I check? How can I correct it? How can I prevent recurrence? 48. CREATE USAGE QUESTIONS 49. POSSIBLE: How often? How much? Which setting? Which workflow? What should I monitor? 50. CREATE ADVANCED QUESTIONS 51. ADVANCED QUESTIONS MAY COVER: Trade-offs Optimization Exceptions Integration Measurement Decision-making 52. DO NOT MAKE ADVANCED QUESTIONS COMPLEX JUST FOR APPEARANCE 53. CREATE STRATEGIC QUESTIONS 54. STRATEGIC QUESTIONS MAY COVER: Prioritization ROI Risk Scaling Process design Resource allocation 55. DO NOT INVENT ROI 56. CREATE FAQ QUESTIONS 57. FAQ QUESTIONS SHOULD BE ANSWERABLE CLEARLY 58. AVOID VAGUE FAQS SUCH AS: "Why are we the best?" 59. CREATE CONTENT QUESTIONS 60. TURN AUDIENCE QUESTIONS INTO: Article ideas Video ideas Short-form topics Carousel ideas Email topics 61. DO NOT ASSUME EVERY QUESTION NEEDS A FULL ARTICLE 62. CREATE SHORT-FORM-FRIENDLY QUESTIONS 63. SHORT-FORM QUESTIONS SHOULD: Focus on one issue Have a clear answer Be understandable quickly 64. CREATE LONG-FORM QUESTIONS 65. LONG-FORM QUESTIONS MAY: Require explanation Compare multiple options Need a process Need examples 66. CREATE SOCIAL ENGAGEMENT QUESTIONS 67. ENGAGEMENT QUESTIONS SHOULD INVITE: Experience Preference Opinion Problem sharing Decision reasoning 68. DO NOT USE EMPTY ENGAGEMENT BAIT 69. AVOID: "Agree?" "Yes or no?" "Who else?" unless the context makes them useful. 70. CREATE CUSTOMER-RESEARCH QUESTIONS 71. RESEARCH QUESTIONS SHOULD HELP LEARN: Context Current process Pain Workaround Impact Desired outcome Decision criteria 72. DO NOT LEAD THE RESPONDENT 73. BAD: "How frustrating is your terrible inventory system?" 74. BETTER: "What happens when the stock shown in the system does not match the physical quantity?" 75. CREATE INTERVIEW QUESTIONS 76. OPEN-ENDED QUESTIONS SHOULD BE USED FOR DISCOVERY 77. EXAMPLE: "Walk me through what you normally do when this happens." 78. CREATE SURVEY QUESTIONS CAREFULLY 79. KEEP SURVEY QUESTIONS NEUTRAL 80. DO NOT COMBINE TWO QUESTIONS INTO ONE WHEN POSSIBLE 81. CREATE SALES-DISCOVERY QUESTIONS WHEN RELEVANT 82. POSSIBLE: What process do you use today? What is not working? What happens when the issue occurs? Who is affected? What matters most in a solution? 83. DO NOT MANIPULATE THE USER TOWARD A SALE 84. CREATE SUPPORT-FAQ QUESTIONS WHEN RELEVANT 85. POSSIBLE: How do I set this up? Why am I seeing this? Can I change this? What data is required? How do I correct this? 86. CREATE POST-PURCHASE QUESTIONS 87. POSSIBLE: How do I get started? What should I do first? How do I get more value? What mistakes should I avoid? 88. CREATE RETENTION QUESTIONS 89. POSSIBLE: What should I review regularly? What advanced feature should I try next? How do I improve results? 90. DO NOT CREATE FAKE CUSTOMER SUCCESS QUESTIONS 91. CREATE QUESTION CLUSTERS 92. GROUP RELATED QUESTIONS UNDER A MAIN TOPIC 93. EXAMPLE: Inventory discrepancy → Why does it happen? → What should I check first? → When should I adjust stock? → How do I prevent recurrence? 94. IDENTIFY PARENT QUESTIONS 95. IDENTIFY SUPPORTING QUESTIONS 96. CREATE A QUESTION JOURNEY 97. EXAMPLE: What is it? Why does it matter? How does it work? Which option should I choose? How do I implement it? How do I troubleshoot it? 98. CREATE QUESTIONS BY AWARENESS STAGE 99. UNAWARE: Questions around situations and symptoms. 100. PROBLEM-AWARE: Questions around causes and solutions. 101. SOLUTION-AWARE: Questions around approaches and comparisons. 102. PRODUCT-AWARE: Questions around fit, features, usage and objections. 103. MOST-AWARE: Questions around next steps, pricing, availability and implementation when verified. 104. DO NOT INVENT OFFERS OR AVAILABILITY 105. CREATE QUESTIONS BY FUNNEL STAGE 106. TOP OF FUNNEL: Educational and discovery. 107. MIDDLE OF FUNNEL: Comparison, process, trust and objections. 108. BOTTOM OF FUNNEL: Fit, implementation and purchase decision. 109. POST-PURCHASE: Usage, optimization and troubleshooting. 110. CREATE QUESTIONS BY KNOWLEDGE LEVEL 111. BEGINNER: Plain language. 112. INTERMEDIATE: Process and decision questions. 113. ADVANCED: Trade-offs, exceptions and optimization. 114. REMOVE DUPLICATES 115. MERGE QUESTIONS WITH THE SAME INTENT 116. DO NOT KEEP NEAR-IDENTICAL QUESTIONS JUST TO INCREASE THE COUNT 117. IDENTIFY HIGH-VALUE QUESTIONS 118. PRIORITIZE USING: Audience relevance Problem severity Decision importance Content usefulness Business relevance 119. USE: High Medium Low 120. DO NOT CREATE FALSE NUMERICAL SCORES 121. IDENTIFY QUESTIONS NEEDING FACT CHECKING 122. FLAG QUESTIONS INVOLVING: Current statistics Laws Regulations Health Finance Safety Product specifications Current platform features Prices 123. IDENTIFY QUESTIONS REQUIRING REAL CUSTOMER RESEARCH 124. EXAMPLES: Why do customers choose competitor A? What is the most common objection? Which feature matters most? 125. DO NOT ANSWER THESE AS FACT WITHOUT DATA 126. MARK: Research required 127. CREATE QUESTION-TO-CONTENT MAPPING 128. FOR EACH HIGH-VALUE QUESTION RECOMMEND: Short video Article FAQ Carousel Post Email Guide Tool 129. MATCH FORMAT TO QUESTION DEPTH 130. SIMPLE QUESTIONS MAY NEED SHORT CONTENT 131. COMPLEX QUESTIONS MAY NEED LONG-FORM CONTENT 132. CREATE SEO RESEARCH STARTING POINTS 133. TURN QUESTIONS INTO NATURAL SEARCH-STYLE PHRASES 134. DO NOT CLAIM SEARCH DEMAND 135. LABEL THEM: Keyword / search-query candidates 136. CREATE YOUTUBE QUESTION IDEAS 137. CREATE SOCIAL QUESTION IDEAS 138. CREATE FAQ PAGE QUESTIONS 139. CREATE EMAIL TOPIC QUESTIONS 140. CREATE PRODUCT-RESEARCH QUESTIONS 141. IDENTIFY CONTENT GAPS 142. ASK: Which important audience problem has no useful question coverage? 143. IDENTIFY QUESTION GAPS BY: Problem Journey stage Knowledge level Format 144. CREATE VALIDATION METHODS 145. RECOMMEND VALIDATING QUESTIONS THROUGH: Customer interviews Support tickets Sales calls On-site search Search Console Keyword research tools Comments Community discussions Surveys 146. DO NOT CLAIM VALIDATION HAS OCCURRED 147. CREATE A MINIMUM RESEARCH PLAN 148. IDENTIFY THE 5–10 QUESTIONS THAT SHOULD BE validated first. 149. CREATE AN UPDATE PROCESS 150. AUDIENCE QUESTIONS SHOULD EVOLVE BASED ON: New customer feedback Search data Support patterns Sales objections Product changes 151. FINAL QUALITY CHECK Before finalizing verify: - questions match the target audience - knowledge level is considered - journey stage is considered - generated questions are not presented as verified demand - real questions are distinguished from suggested questions - search volume is not invented - customer frequency is not invented - questions are specific - duplicate intent is removed - beginner and advanced needs are balanced - problem-solving questions are included - comparison questions are included when relevant - objections are included when relevant - FAQ questions are useful - research questions are neutral - content opportunities are mapped - high-value questions are prioritized - fact-sensitive questions are flagged - research gaps are clearly identified OUTPUT FORMAT: 1. AUDIENCE SNAPSHOT Provide: Audience Role Knowledge level Primary problems Desired outcomes Journey stage 2. VERIFIED QUESTION INPUTS List any actual supplied audience questions separately. 3. QUESTION THEMES Identify the main question clusters. 4. MASTER QUESTION BANK For each question provide: Question Category Audience stage Knowledge level Intent Source status Priority Use source status: Verified audience question Suggested audience question 5. DISCOVERY QUESTIONS 6. EDUCATIONAL QUESTIONS 7. PROBLEM-SOLVING QUESTIONS 8. HOW-TO QUESTIONS 9. FAQ QUESTIONS 10. COMPARISON QUESTIONS 11. OBJECTION QUESTIONS 12. BUYING-DECISION QUESTIONS 13. IMPLEMENTATION QUESTIONS 14. TROUBLESHOOTING QUESTIONS 15. ADVANCED / STRATEGIC QUESTIONS 16. ENGAGEMENT QUESTIONS 17. CUSTOMER INTERVIEW QUESTIONS 18. SALES-DISCOVERY QUESTIONS When relevant. 19. QUESTION CLUSTERS Show: Parent question Supporting questions 20. QUESTION JOURNEY Map useful questions from discovery through post-purchase. 21. TOP 20 PRIORITY QUESTIONS Rank the strongest questions. 22. QUESTION-TO-CONTENT MAP For each priority question provide: Recommended format Platform Content angle 23. SHORT-FORM VIDEO QUESTIONS Identify questions suitable for Reels, TikTok or Shorts. 24. LONG-FORM CONTENT QUESTIONS Identify questions suitable for articles, YouTube or guides. 25. FAQ PAGE SET Create a clean FAQ shortlist. 26. SEARCH-QUERY CANDIDATES Create natural search-style versions without claiming search volume. 27. RESEARCH-REQUIRED QUESTIONS Identify questions that cannot be responsibly answered without real customer or market data. 28. FACT-CHECK QUESTIONS Identify topics needing up-to-date or expert verification. 29. CONTENT GAPS Identify important audience needs not yet covered. 30. VALIDATION PLAN Recommend how to verify which questions matter most. 31. FINAL RECOMMENDATION Provide: Best discovery question Best educational question Best problem-solving question Best engagement question Best conversion-support question Best long-form topic Best short-form topic IMPORTANT: - Never present invented questions as verified audience demand. - Never fabricate search volume or customer-frequency data. - Separate supplied evidence from inference. - Remove duplicate question intent. - Prioritize questions that help the audience make progress. - Flag questions that require current, expert or customer-specific evidence.
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How to use it
Use the prompt effectively.
01
Separate evidence from inference
Keep real customer, search, support or sales questions distinct from AI-generated suggestions so likely audience interests are not mistaken for verified demand.
02
Cover the full customer journey
Generate questions from initial problem awareness through comparison, implementation, troubleshooting and ongoing usage instead of focusing only on beginner FAQs.
03
Group questions by intent
Cluster related questions around problems, processes, objections and decisions so they can become useful content series, FAQ structures and research themes.
04
Validate the highest-value questions
Use customer conversations, support tickets, comments, search data and other real evidence to determine which suggested questions deserve the greatest content investment.
Example
Turn one inventory problem into a structured audience-question bank.
Example input
Niche: Inventory and warehouse operations.
Audience: Inventory controllers, storekeepers, supervisors and small-business owners.
Problem: Physical stock does not match the system.
Objective: Generate educational content and FAQ topics.
Knowledge level: Beginner to intermediate.
Possible output
DISCOVERY: 'Why does physical stock differ from system stock?'
PROBLEM-SOLVING: 'What should I check first when physical stock does not match the system quantity?'
PROCESS: 'Should I adjust the inventory immediately when a discrepancy is found?'
DIAGNOSTIC: 'Can receiving or transfer transactions cause stock discrepancies?'
PREVENTION: 'How can cycle counting help identify inventory errors earlier?'
ADVANCED: 'How should repeated discrepancies be separated into transaction, process and control failures?'
CONTENT MAP: The first-check question fits a short video or checklist; repeated-discrepancy root causes are better suited to a detailed article or long-form video.
SOURCE STATUS: These are suggested audience questions unless actual search, customer or support data confirms them.
Improve the result
Useful questions are research inputs, not invented evidence.
A generated question is not proof of demand
AI can help identify plausible questions, but search volume, frequency and real customer importance should come from actual research data.
Questions reveal content structure
A strong cluster of related questions can become a Reel series, FAQ page, guide, email sequence or long-form content plan.
Prioritize progress, not just curiosity
The most useful questions usually help the audience understand a problem, make a decision, complete a task or avoid a meaningful mistake.