AI Prompt
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Act as a senior marketing strategist. Create a comprehensive campaign brief for [PRODUCT/SERVICE] targeting [AUDIENCE]. Include: campaign objectives, key messages, channel strategy, timeline, KPIs, and budget allocation recommendations. The campaign should differentiate us from [COMPETITORS] and leverage our unique value proposition of [UVP].

Analyze the competitive landscape for [INDUSTRY/MARKET]. Create a framework comparing: positioning, pricing strategies, target audiences, marketing channels used, content strategies, and unique differentiators. Identify gaps and opportunities for a new entrant or existing player to capture market share.

Create a detailed buyer persona for [PRODUCT/SERVICE]. Include: demographic details, psychographic profile, pain points, goals, objections to purchase, preferred content formats, media consumption habits, buying triggers, and a day-in-the-life narrative. End with 5 marketing messages that would resonate with this persona.

Develop comprehensive brand voice guidelines for [BRAND]. Include: voice attributes (3-5 adjectives), tone variations by context (social media, customer service, formal communications), words to use vs. avoid, example phrases, and do's/don'ts. Provide before/after examples of copy transformation.

Create a 30-day social media content calendar for [BRAND] on [PLATFORMS]. Include: post themes tied to our goals of [GOALS], optimal posting times, content mix (educational, promotional, engagement, UGC), hashtag strategies, and 2-3 specific post ideas per day with captions. Consider [UPCOMING EVENTS/HOLIDAYS].

Act as a CMO. Given a marketing budget of [AMOUNT] and goals of [GOALS], create a channel allocation framework. Include: recommended spend per channel, expected ROI ranges, testing budget allocation, seasonality adjustments, and KPIs to track. Consider our current performance baselines of [BASELINES].

Develop a content pillar strategy for [BRAND] in [INDUSTRY]. Create 5-7 content pillars that align with our expertise and audience interests. For each pillar, provide: description, example topics (10 each), content formats, SEO keyword clusters, and how it supports business goals. Include a content repurposing framework.

Generate 10 high-impact A/B test hypotheses for [WEBPAGE/CAMPAIGN]. For each test, provide: hypothesis statement (If we change X, then Y will happen because Z), control vs. variation description, primary metric, expected impact range, and sample size recommendation. Prioritize by potential impact and ease of implementation.

Generate 20 headline variations for [PRODUCT/TOPIC] targeting [AUDIENCE]. Include: 5 benefit-driven headlines, 5 curiosity-driven headlines, 5 urgency/scarcity headlines, and 5 social proof headlines. Each headline should be under 60 characters. Explain the psychological trigger behind each.

Write complete landing page copy for [PRODUCT/SERVICE] using the AIDA framework. Include: attention-grabbing headline and subheadline, problem agitation section, solution presentation, 5 key benefits with supporting copy, social proof section, FAQ addressing top objections, and a compelling CTA. Target conversion goal: [GOAL].

Create 10 Facebook ad copy variations for [PRODUCT]. Include: 3 short-form (under 125 chars), 4 medium (125-250 chars), 3 long-form (250-500 chars). Each should have primary text, headline, and CTA. Test different angles: pain point, transformation, social proof, curiosity, and direct offer.

Write a product description for [PRODUCT] that converts browsers to buyers. Include: sensory language that helps readers imagine using it, unique selling points, specifications presented as benefits, ideal use cases, and a mini-story of transformation. Length: [WORD COUNT]. Tone: [TONE]. Include SEO keywords: [KEYWORDS].

Create a brand story for [BRAND] using the StoryBrand framework. Define: the customer as hero, their problem (external, internal, philosophical), position our brand as guide, the plan we offer, the call to action, the stakes of failure, and the transformation/success. Write a 500-word founding story that brings this to life.

Create a value proposition for [PRODUCT/SERVICE]. Define customer jobs (functional, social, emotional), pains (frustrations, obstacles, risks), and gains (desired outcomes). Then map our product's: pain relievers, gain creators, and features. End with 5 value proposition statement variations following the format: "We help [WHO] do [WHAT] by [HOW] so they can [BENEFIT]."

Generate 15 CTA button variations for [ACTION/GOAL]. For each, provide: button text, supporting microcopy (anxiety reducer), and the psychological principle it leverages. Include a mix of: action-oriented, benefit-focused, urgency-based, and conversational CTAs. All should be mobile-friendly (under 25 characters for button text).

Analyze and improve this copy: [PASTE COPY]. Provide: specific issues identified (clarity, persuasion, structure), an improved version with tracked changes explained, readability score improvement, and 3 alternative approaches. Maintain the same word count but increase conversion potential. Keep brand voice of [TONE].

Analyze this marketing performance data: [PASTE DATA]. Provide: executive summary, key trends identified, anomalies or concerns, performance vs. benchmarks, root cause hypotheses for underperformance, top 5 actionable recommendations with expected impact, and suggested next analyses to conduct.

Write a SQL query to [DESCRIBE ANALYSIS]. The database has these tables: [LIST TABLES AND KEY COLUMNS]. Include: the query with comments explaining each part, sample output structure, edge cases handled, performance optimization notes, and 2 variations for related analyses.

Design a [TYPE] dashboard for [AUDIENCE]. Include: dashboard objective, 8-12 KPIs with definitions and formulas, recommended visualizations for each metric, filter/drill-down capabilities needed, data refresh frequency, alert thresholds, and a wireframe layout description. Consider the decisions this dashboard should enable.

Write an executive summary for this data analysis: [PASTE FINDINGS]. Structure it for [C-SUITE/MANAGER] audience. Include: headline insight (1 sentence), key metrics with context, what's working, what's concerning, recommended actions with business impact, and next steps. Keep it under 300 words. Use confident, decisive language.

Analyze trends in this time-series data: [PASTE DATA]. Identify: overall direction (growth/decline rate), seasonality patterns, cyclical patterns, notable inflection points with potential causes, leading indicators, and forecast for next [TIME PERIOD] with confidence intervals. Recommend actions based on trend trajectory.

Create a KPI framework for [BUSINESS FUNCTION/GOAL]. Define 10-15 KPIs organized by: leading vs. lagging indicators, strategic vs. operational metrics. For each KPI include: definition, formula, data source, measurement frequency, benchmark/target, owner, and actions triggered by different performance levels.

Design a cohort analysis for [BUSINESS QUESTION]. Define: cohort segmentation criteria (time-based, behavior-based), metrics to track per cohort, analysis time frame, visualization approach, statistical significance considerations, and expected insights. Provide SQL pseudocode for the analysis structure.

I noticed [ANOMALY] in our data. Help me investigate: create a hypothesis tree of possible causes (technical, external, behavioral), suggest data points to examine for each hypothesis, recommend validation steps, provide a template for documenting findings, and outline the communication plan if the anomaly is significant.

Write a Python data cleaning pipeline for a dataset with: [DESCRIBE DATA]. Include: loading data, handling missing values (with multiple strategies), outlier detection and treatment, data type conversions, feature engineering suggestions, validation checks, and logging. Use pandas best practices and include docstrings.

I need to predict [TARGET] using [FEATURES] with [DATA SIZE] records. Help me: compare 4-5 suitable algorithms with pros/cons, recommend preprocessing steps for each, suggest hyperparameter tuning approaches, define evaluation metrics and why, outline a validation strategy, and identify potential pitfalls.

Create Python visualization code to show [INSIGHT] from this data structure: [DESCRIBE]. Use matplotlib/seaborn. Include: publication-quality formatting, clear labels and titles, color palette for accessibility, multiple subplot layout if needed, annotations for key points, and export settings for presentations.

I want to test if [HYPOTHESIS]. My data: [DESCRIBE DATA TYPE, SAMPLE SIZE, DISTRIBUTION]. Recommend: the appropriate statistical test with justification, assumptions to verify, Python code using scipy/statsmodels, how to interpret results, effect size calculation, and how to report findings in a business context.

Given these raw features for predicting [TARGET]: [LIST FEATURES], suggest 20+ engineered features. For each: name, calculation logic, intuition for why it might be predictive, Python implementation, and feature importance testing approach. Group by feature type (interaction, aggregation, time-based, etc.).

Explain this [MODEL TYPE] model results to non-technical stakeholders. Model predicts [TARGET] with [ACCURACY]. Top features: [LIST]. Create: an executive summary, analogy-based explanation, visual description suggestions, business implications, limitations and caveats, and recommended next steps. Avoid jargon.

Generate 20 subject line variations for an email about [TOPIC] to [AUDIENCE]. Create 4 variations each of: curiosity-driven, benefit-focused, urgency/scarcity, personalization-based, and question format. Each under 50 characters. Include preview text suggestions. Rate each for spam risk (low/medium/high).

Create a 5-email welcome sequence for new [PRODUCT/SERVICE] subscribers. For each email: subject line + preview text, send timing (day/hour), goal of the email, full copy, CTA, and success metrics. Progress from welcome → value delivery → social proof → engagement → conversion. Include personalization tokens.

Create a win-back email sequence for customers who haven't [ENGAGED/PURCHASED] in [TIME PERIOD]. Design 4 emails with: emotional hook (we miss you), value reminder, special offer, and final attempt. Include subject lines, timing, copy, and criteria for suppressing non-responders. Consider why they may have disengaged.

Create personalized email content blocks for [EMAIL TYPE] based on these segments: [LIST SEGMENTS]. For each segment, provide: personalized headline, body copy variation, product recommendations logic, CTA variation, and image suggestions. Show the default version and 3+ segment-specific versions.

Design a 3-email abandoned cart sequence for [PRODUCT TYPE]. Email 1: Reminder (1 hour), Email 2: Overcome objections (24 hours), Email 3: Incentive (48 hours). For each: subject line, copy, product block suggestions, trust elements to include, and A/B test recommendations. Include SMS follow-up option.

Create a newsletter template and 4 weeks of content for [BRAND/TOPIC]. Include: recurring sections (define 4-5), content mix ratio, optimal length, subject line formulas, send time recommendations, engagement hooks, and growth tactics. For each week, provide specific content ideas with headlines.

Create a PRD for [FEATURE]. Include: problem statement with data, user personas affected, jobs to be done, success metrics, requirements (must have, should have, nice to have), user flows, edge cases, technical considerations, dependencies, risks, and launch checklist. Format for engineering handoff.

Generate user stories for [FEATURE/EPIC]. Create 10-15 stories following: "As a [user type], I want [action] so that [benefit]." For each story include: acceptance criteria (3-5 specific conditions), story points estimate, dependencies, and potential edge cases. Group by user type and prioritize by value/effort.

Analyze these user interview notes: [PASTE NOTES]. Extract: key themes (group related insights), user pain points ranked by frequency and severity, desired outcomes, surprising findings, quotes that capture sentiment, and recommended actions. Create an affinity map structure and suggest follow-up questions.

Help plan Q[X] roadmap for [PRODUCT]. Given these inputs: company goals [GOALS], current metrics [METRICS], user feedback themes [THEMES], and tech debt items [ITEMS]. Create: theme-based roadmap, prioritization rationale (RICE scores), resource allocation suggestions, dependencies map, and risk assessment. Include "not doing" list with reasoning.

Apply RICE scoring to these feature ideas: [LIST FEATURES]. For each feature, estimate: Reach (users/quarter), Impact (0.25-3x scale), Confidence (%), Effort (person-weeks). Calculate RICE scores, rank features, and provide reasoning for estimates. Identify any features that need more data before scoring.

Create a competitive analysis for [PRODUCT] vs [COMPETITORS]. Compare: feature parity matrix, pricing models, target user segments, UX strengths/weaknesses, market positioning, recent product updates, and user review sentiment. Identify: competitive moats, vulnerability areas, and differentiation opportunities.

Create a detailed customer journey map for [PERSONA] using [PRODUCT/SERVICE]. Map stages: Awareness → Consideration → Purchase → Onboarding → Usage → Advocacy. For each stage include: user goals, touchpoints, actions, thoughts, emotions (high/low), pain points, and opportunities for improvement. Add moments of truth.

Audit customer touchpoints for [BUSINESS]. List all touchpoints across channels (digital, physical, human). For each: rate current experience (1-5), identify friction points, benchmark against expectations, suggest quick wins and longer-term improvements. Prioritize by impact on satisfaction and feasibility.

Design an onboarding flow for [PRODUCT] targeting [USER TYPE]. Define: the "aha moment" to reach, steps to get there (max 5), information to collect, features to highlight, gamification elements, progress indicators, and re-engagement triggers for drop-offs. Include copy for each step and success metrics.

Create a churn prevention framework for [PRODUCT/SERVICE]. Define: early warning signals (behavioral triggers), health score components, intervention points, retention plays for each risk level, win-back strategies, and exit interview questions. Include automation rules for triggering interventions.

Help me prepare for a meeting about [TOPIC] with [ATTENDEES]. Create: agenda suggestion, key talking points, potential questions I'll face with suggested answers, data/examples I should bring, decisions to drive, and follow-up items to propose. Meeting goal: [GOAL].

Create a presentation outline for [TOPIC] targeting [AUDIENCE]. Include: hook opening (story/statistic), problem framing, solution/recommendation, supporting evidence (3 pillars), objection handling, call to action, and closing. Suggest visuals for each slide. Time: [DURATION]. Goal: [ACTION YOU WANT].

Help me solve this problem: [DESCRIBE PROBLEM]. Walk me through: problem definition (5 Whys), stakeholder map, constraint identification, solution brainstorm (10+ ideas), evaluation criteria, top 3 solutions with pros/cons, recommended approach, implementation plan, and success metrics.

Help me prepare for a difficult conversation about [SITUATION] with [PERSON/ROLE]. Provide: opening script that's direct but empathetic, key points to make, anticipated responses and how to handle each, de-escalation phrases, desired outcome, and follow-up steps. Tone should be professional and constructive.