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ChatGPT Prompts

Master ChatGPT with our curated library of professional prompt templates.

ChatGPTIntermediate

Live Chat Optimization Playbook

Use Case: Live chat and messaging support optimization

You are a live chat and messaging strategy specialist. Build a live chat optimization playbook for [e-commerce/SaaS/financial services] support. Current metrics: avg response time: [X], CSAT: [X%], resolution rate: [X%], chat volume: [X/day]. Playbook sections: 1) Chat Routing Logic — rules for auto-assignment vs queue vs skill-based routing, 2) Proactive Chat Triggers — pages/behaviors that should trigger a proactive chat offer (with estimated conversion lift), 3) Canned Response Library Architecture — folder structure, naming conventions, 30 recommended canned responses for this industry, 4) Chat Quality Standards — what differentiates a 5-star chat from a 3-star one (with examples), 5) Multitasking Guidelines — how many simultaneous chats agents should handle by complexity, 6) Chatbot Handoff Design — the exact moment and message when bot hands off to human, 7) After-hours Strategy — chatbot, callback offer, or email capture?, 8) Agent Productivity Metrics — what to measure besides CSAT and response time. Target improvements: [reduce handle time by X%, improve CSAT by X pts].

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ChatGPTIntermediate

Knowledge Base Gap Analysis

Use Case: Self-service improvement and deflection

You are a knowledge management specialist. Perform a knowledge base gap analysis for [company] support team. Analysis inputs: Top 20 ticket topics by volume: [list]. Top 5 topics with highest repeat contact rate: [list]. Articles currently in knowledge base: [list main articles or sections]. Top 5 agent complaints about existing documentation: [list]. Gap analysis deliverables: 1) Coverage map — which high-volume topics have adequate KB articles vs gaps vs outdated content, 2) Impact scoring — gaps ranked by: ticket deflection potential (how many tickets could be avoided), customer effort reduction, and agent time savings, 3) Prioritized article backlog — top 15 articles to write/update with brief, 4) Article quality audit — use the FORD framework (Findability, Originality, Relevance, Depth) to grade existing top 10 articles, 5) KB governance recommendations — how often to review and update, who owns it, metrics to track (deflection rate, helpfulness score). Output: an actionable roadmap to close the top gaps in 90 days.

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ChatGPTIntermediate

Docker Compose Production Stack

Use Case: Containerized application deployment

You are a containerization expert. Create a production-ready Docker Compose stack for [application type: e.g., "MERN stack with Nginx reverse proxy and Redis cache"]. Stack components: [list your services]. For each service: correct image with pinned version tag, resource limits (cpus, memory), health checks with appropriate intervals, restart policy, and dependency ordering. Also include: 1) Nginx reverse proxy config with SSL termination, rate limiting, and security headers, 2) Environment variable management using .env file with a .env.example template, 3) Volume configuration for persistent data with backup labels, 4) Network segmentation (frontend network / backend network), 5) Logging configuration with log rotation, 6) A separate docker-compose.override.yml for local development (with hot-reload, no resource limits, debug ports). Also write a deploy.sh script that: pulls latest images, runs migrations, and performs a zero-downtime rolling update.

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ChatGPTIntermediate

GitHub Actions CI/CD Pipeline

Use Case: Automated CI/CD pipeline setup

You are a DevOps engineer specializing in CI/CD automation. Create a complete GitHub Actions workflow for [project type: Node.js/Python/Go/Java]. The pipeline must: 1) Trigger on: push to main, pull requests, and manual workflow dispatch, 2) Jobs: a) lint-and-test (runs linting, unit tests, coverage report, uploads to Codecov), b) security-scan (runs SAST with appropriate tool for the language), c) build-and-push (builds Docker image, tags with commit SHA and "latest", pushes to [ECR/GCR/Docker Hub]), d) deploy-staging (deploys to staging on every merge to main), e) deploy-prod (deploys to production on tag push, requires manual approval). Include: matrix testing across [list versions], caching for dependencies, environment secrets usage, and a Slack notification on deploy success/failure. Stack specifics: [describe your stack]. Registry: [container registry]. Deploy target: [ECS/EKS/Cloud Run/etc.].

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ChatGPTBeginner

Regex Pattern Builder & Explainer

Use Case: Text parsing and validation

You are a regex expert. I need a regular expression to match: [describe what you need to match, e.g., "all valid email addresses including subdomains" or "ISO 8601 datetime strings"]. Provide: 1) The regex pattern for [target language/engine: JavaScript/Python/Go/etc.], 2) A visual breakdown of each component of the pattern using a table (token | meaning | example match), 3) A list of strings it WILL match, 4) A list of edge cases it will NOT match (and why), 5) Any known caveats or performance concerns with this pattern, 6) A function wrapper in [language] that uses this regex safely (null check, error handling). Also provide a version for any major dialect differences (e.g., PCRE vs RE2).

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ChatGPTIntermediate

Dockerfile & CI/CD Pipeline Builder

Use Case: DevOps automation

You are a DevOps engineer specializing in containerization. For my [language/framework] application, create: 1) An optimized multi-stage Dockerfile — minimize final image size, use non-root user, leverage layer caching correctly, add health check, 2) A Docker Compose file for local development with hot-reload, 3) A GitHub Actions CI/CD pipeline YAML that: runs linting and tests on PR, builds and pushes image to [registry] on merge to main, deploys to [environment: ECS/K8s/Cloud Run], and notifies Slack on failure. App details: [describe app, dependencies, env vars needed]. Environment variables must use GitHub Secrets (list which ones are needed).

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ChatGPTAdvanced

SQL Query Optimizer

Use Case: Database performance tuning

You are a database performance engineer specializing in PostgreSQL. Analyze this slow-running query and optimize it. Step 1: Parse the query and identify anti-patterns (e.g., SELECT *, correlated subqueries, missing indexes, implicit type casts). Step 2: Explain the likely query plan the optimizer is choosing. Step 3: Rewrite the query for performance — show the optimized version with inline comments explaining each change. Step 4: Recommend specific indexes to create (include the CREATE INDEX statement). Step 5: Estimate the performance improvement. Table schemas: [paste schemas]. Query: [paste query]. Current execution time: [X ms]. Row counts: [approximate].

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ChatGPTIntermediate

Bug Root Cause Analysis

Use Case: Debugging complex issues

You are an expert debugger. I have a bug in my [language] application. Symptom: [describe behavior]. Error log: [paste error]. Relevant code: [paste code]. Think step by step: 1) Form 3 hypotheses about the root cause, 2) Evaluate each against the evidence, 3) Identify the most likely cause, 4) Provide a fix, 5) Suggest how to prevent this class of bug. Use chain-of-thought reasoning.

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ChatGPTBeginner

Real Estate Social Media Content Plan

Use Case: Real estate agent marketing and personal brand

You are a real estate social media marketing specialist. Build a 30-day content plan for a real estate agent in [market/city]. Agent specialty: [residential/luxury/first-time buyers/investors]. Platforms: [Instagram/Facebook/LinkedIn/TikTok — choose 2]. Content pillars (rotate across these): 1) Market Education (30%) — statistics, trends, buying/selling tips, 2) Listings & Properties (25%) — just listed, just sold, featured properties, 3) Social Proof (20%) — client testimonials, success stories, milestones, 4) Local Community (15%) — neighborhood spotlights, local business features, 5) Personal Brand (10%) — behind the scenes, values, expertise proof. For each of 30 days: post type, content idea, caption starter, relevant hashtags (mix of local and broad). Also: 5 Reel/TikTok ideas that work well for real estate agents in 2026, and a profile bio formula for real estate agents.

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ChatGPTAdvanced

Rental Property Investment Analysis

Use Case: Real estate investment analysis

You are a real estate investment analyst. Analyze this rental property as an investment. Property details: Purchase price: $[X]. Down payment: [X%]. Loan terms: [X% interest, X years]. Estimated renovation: $[X]. Property type: [SFH/multi-family/short-term rental]. Location: [city/market]. Financial inputs: Monthly rent (gross): $[X]. Property tax: $[X/year]. Insurance: $[X/year]. HOA (if any): $[X/month]. Property management: [X% or self-managed]. Maintenance reserve: [X% of rent or $X/month]. Vacancy rate: [X%]. Capex reserve: $[X/month]. Calculate and explain: 1) Monthly cash flow (gross rent → net operating income → cash flow after debt service), 2) Cap rate, 3) Cash-on-cash return, 4) GRM (Gross Rent Multiplier), 5) Total ROI (including appreciation), 6) Break-even analysis — rent level needed to cover all expenses, 7) Stress test — what happens if rent drops 10%, vacancy increases to 10%, or interest rates increase by 1%. Investment decision: rate this as Strong Buy/Buy/Hold/Avoid with reasoning.

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ChatGPTIntermediate

Comparative Market Analysis (CMA)

Use Case: Real estate pricing and market analysis

You are a licensed real estate agent with deep market expertise. Walk me through creating a Comparative Market Analysis (CMA) for a property I am listing or buying. Subject property: [address/neighborhood]. Type: [single-family/condo]. Bedrooms/Bathrooms: [X/X]. Square footage: [X]. Key features: [describe]. CMA structure: 1) Subject Property Summary — key characteristics and condition assessment, 2) Comparable Selection Criteria — how to select the right comps (proximity, recency, similarity — address common mistakes), 3) Comparable Analysis Table — for each of 3-5 comps: address, sale price, $/sqft, beds/baths, days on market, sale-to-list price ratio, and adjustments for differences with subject, 4) Adjustment Methodology — how to make dollar adjustments for differences in condition, features, lot size, 5) Value Range — derive low, mid, and high estimate with reasoning, 6) List Price Recommendation — recommend a specific price with strategic rationale (pricing psychology, market conditions), 7) Days on Market Estimate — based on absorption rate. Market conditions: [buyer's/seller's/balanced, and specific local data].

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ChatGPTIntermediate

Paid Ad Creative Brief

Use Case: Performance marketing creative

You are a performance creative director. Write a creative brief for a paid social ad campaign for [product] targeting [audience] on [platform: Meta/TikTok/YouTube]. Budget: $[amount]/month. Goal: [awareness/conversions/retargeting]. Brief sections: 1) Campaign Objective & Success Metric, 2) Target Audience — psychographic snapshot in 3 bullet points, 3) Core Message — one sentence the viewer should remember, 4) 3 Ad Concepts: each with a format (UGC, talking head, animation, carousel), hook line, visual description, VO/copy direction, and emotional trigger being activated, 5) Winning Creative Hypothesis — which concept is most likely to perform and why based on platform trends for 2026.

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ChatGPTIntermediate

Referral Program Design

Use Case: Viral and referral growth

You are a viral growth strategist. Design a referral program for [product/service] with a [subscription/one-time purchase] model. Think step by step: 1) Incentive Structure — propose 3 incentive models (e.g., two-sided discount, cash reward, exclusive access) and recommend the best one for our economics, showing CAC vs LTV math, 2) Trigger Moment — identify the 2 best moments in the user journey to prompt a referral, 3) Copy Pack — write the referral invite email, in-app prompt message, and social share text, 4) Fraud Prevention — list 3 common abuse vectors and mitigation tactics, 5) Success Metrics — define the 3 KPIs for the first 90 days. Current CAC: $[amount]. LTV: $[amount]. Monthly active users: [number].

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ChatGPTAdvanced

Growth Experiment Brief

Use Case: Data-driven growth experimentation

You are a growth lead using scientific experimentation. Create a structured growth experiment brief to test whether [hypothesis]. Use this format: 1) Hypothesis: 'We believe that [change] for [segment] will result in [outcome] because [rationale].' 2) Metric: Primary KPI and guardrail metric. 3) Audience & Segmentation: Who is in control vs treatment. 4) Execution Plan: What exactly changes, channel, duration. 5) Sample Size Calculation: Assume [baseline conversion rate]% and desire [minimum detectable effect]% lift at 95% confidence. 6) Decision Rule: Define 'go / no-go' thresholds. 7) Risks & Confounds: List 3. Current funnel stage: [awareness/activation/retention/revenue]. Stack: [tool stack].

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ChatGPTIntermediate

Facebook Ad Copy Generator

Use Case: Social media paid ads

Act as a direct response copywriter. Create 3 versions of a Facebook Ad for [product/service]. Version 1: Short & Punchy. Version 2: Story-based (Problem/Agitation/Solution). Version 3: List/Benefit driven. Each must include: Hook, Body Text, and a CTA. Target Audience: [describe audience]. Pain point: [describe pain point].

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ChatGPTBeginner

Instagram Caption Pack

Use Case: Social media content creation

You are a social media copywriter. Write 5 Instagram captions for a [product/service] post. Each caption should: use a different hook style (question, bold statement, statistic, story, list), be 50-80 words, end with 1 CTA, and include a placeholder for 5 relevant hashtags. Brand voice: [describe voice].

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ChatGPTBeginner

Cold Email for SaaS

Use Case: Cold outreach to prospects

You are a B2B email marketing expert. Write a cold email to a [job title] at a [company size] company in the [industry] sector. Our product [product name] solves [pain point]. Include: a compelling subject line, 1 pain point hook, 1 specific benefit with a number, and a soft CTA. Max 120 words. Tone: professional but conversational.

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ChatGPTBeginner

SWOT Analysis

Use Case: Strategic business planning

You are a McKinsey-trained business strategist. Perform a detailed SWOT analysis for [company/product/idea]. For each quadrant (Strengths, Weaknesses, Opportunities, Threats): provide 4-5 specific, evidence-based points (not generic). Rate each point High/Medium/Low impact. End with: Top 2 strategic priorities based on the analysis. Context: [provide relevant business context].

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ChatGPTAdvanced

Unit Economics Analysis

Use Case: Financial planning and investor readiness

You are a CFO advisor who specializes in SaaS/marketplace/consumer business models. Analyze and improve the unit economics for my [business model] business. Inputs: CAC: $[amount]. LTV: $[amount]. Payback period: [X months]. Gross margin: [X%]. Monthly churn: [X%]. MoM growth: [X%]. Step 1: Calculate the key ratios (LTV:CAC, CAC Payback, Net Revenue Retention, Magic Number) and benchmark them against industry standards for 2026. Step 2: Identify the 2 biggest levers to improve LTV:CAC. Step 3: Build a sensitivity table showing how LTV:CAC changes if we improve churn by 1%, 2%, 3% and decrease CAC by 10%, 20%. Step 4: At what monthly revenue does this business become capital-efficient? Show your math.

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ChatGPTIntermediate

Strategy Framework Selector

Use Case: Strategic problem solving

You are a strategy consultant. I am facing this business challenge: [describe the problem]. Help me: 1) Identify the 3 most relevant strategic frameworks for analyzing this problem (choose from: Porter's Five Forces, BCG Matrix, Blue Ocean, McKinsey 7S, Jobs-to-be-Done, Value Chain, Ansoff Matrix, etc.), 2) Briefly explain why each is relevant and what question it helps answer, 3) Apply the most appropriate framework to my specific situation — not generically, but with real analysis based on my context, 4) Identify the key insight the framework reveals that I might have missed, 5) Recommend the next 3 decisions or actions based on the analysis. Context: [company size, industry, time horizon, key constraints].

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ChatGPTBeginner

Deep Work Schedule Architect

Use Case: Focus and deep work optimization

You are a Cal Newport-style productivity architect. Design a deep work schedule for someone with this profile: Role: [job title]. Biggest cognitively demanding tasks: [list 2-3]. Meetings currently taking up: [X hours/week] per week. Best focus hours: [e.g., 7-10am]. Life constraints: [e.g., school pickup at 3pm, gym 3x/week]. Deliverables: 1) A weekly calendar template with blocked deep work sessions (label each: type of work, output goal), 2) A shutdown ritual (end-of-day procedure to achieve psychological closure), 3) An 'attention residue' audit — which current habits are most destroying my focus and a replacement protocol, 4) A distraction elimination toolkit tailored to my work environment [home/office/hybrid]. Target: achieve at least [X hours] of uninterrupted depth work per week.

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ChatGPTBeginner

Habit System Designer

Use Case: Behavior change and habit building

You are a behavioral science coach drawing on the work of B.J. Fogg, James Clear, and Wendy Wood. Help me build a sustainable habit system around [desired habit or set of habits]. For each habit: 1) Tiny Habit Starter — shrink the habit to 2-minute version, 2) Cue Design — identify the best existing anchor (what I already do) to attach this to, 3) Reward Engineering — design an immediate, meaningful reward, 4) Environment Design — 2 physical environment changes that make the habit easier, 5) Friction Removal — 3 obstacles I will face in week 1 and exactly how to remove them. Also build: a 30-day streak tracker template, a habit stacking sequence for mornings/evenings, and a 'bounce back' protocol for when I miss a day. My current morning routine: [describe]. Goal: [describe the behavior you want].

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ChatGPTBeginner

Weekly Planning System

Use Case: Weekly goal achievement

You are a productivity coach. Help me plan my week. My top 3 goals this week: [list them]. My current obligations: [list them]. Energy patterns: [morning/afternoon person]. I have [X hours] of focused work time. Create: a Monday planning template, daily top-3 task structure, an end-of-day review checklist, and a Friday reflection prompt.

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ChatGPTIntermediate

Midjourney v6 Master Prompt

Use Case: AI Art generation

Act as a professional prompt engineer for Midjourney. Generate a high-detail prompt for [subject/scene]. Include: lighting style (e.g., volumetric, cinematic), camera specs (e.g., 35mm, f/1.8), artistic medium (e.g., oil painting, hyper-realistic photography), and 3 descriptive keywords for atmosphere. Parameters: --ar 16:9 --v 6.0 --stylize 250.

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ChatGPTAdvanced

Statistical Results Interpreter

Use Case: Data analysis interpretation

You are a biostatistician and data scientist. I have run a [type of analysis: regression/ANOVA/t-test/chi-square/etc.] and need help interpreting the results. Think step by step: 1) State what statistical test was run and what it is designed to test, 2) Interpret the key output metrics (coefficient/p-value/F-statistic/etc.) in plain English — what does each number mean?, 3) Is the result statistically significant? Is it practically significant? (Distinguish between these.), 4) What are the key assumptions of this test and should I check if they are violated in my data?, 5) What can I conclude from this analysis? What should I NOT conclude (common misinterpretation)?, 6) What follow-up analysis would strengthen or challenge this finding? Results: [paste your output]. Context: [describe your research question and dataset].

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ChatGPTIntermediate

90-Day Onboarding Plan

Use Case: New employee onboarding

You are an HR specialist. Create a comprehensive 90-day onboarding plan for a new [job title] at [company type]. Phase 1 (Days 1-30): Learn. Phase 2 (Days 31-60): Contribute. Phase 3 (Days 61-90): Lead. For each phase: Weekly goals and 'success looks like' statements, key people to meet (with purpose of each meeting), documents/tools/systems to master, a small project to build confidence and prove value, and a check-in agenda template for the manager. Include: Day 1 schedule (first impressions matter most), a '30-60-90 milestones' template for the new hire to fill in with their manager, and the top 3 reasons employees fail in their first 90 days — and how this plan prevents each. Manager: [describe]. Company size: [X people].

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ChatGPTIntermediate

Feature Prioritization Framework

Use Case: Product backlog prioritization

You are a product strategist. Help me prioritize this backlog of features using multiple frameworks to cross-check the decision. Feature list: [list 8-12 features or opportunities]. Step 1: Apply RICE scoring — score each on Reach (users/quarter), Impact (0.25/0.5/1/2/3), Confidence (%), and Effort (person-weeks). Show the RICE score calculation. Step 2: Apply the Impact vs Effort 2x2 matrix — categorize into: Quick Wins, Big Bets, Fill-ins, Thankless Tasks. Step 3: Check against strategic alignment — which features directly advance [your stated product strategy]? Step 4: Apply MoSCoW tagging (Must / Should / Could / Won't) for the next 90 days. Step 5: Final recommendation — your top 5 priorities and the order you'd tackle them, with 2-sentence rationale for each. Flag where your scores are most uncertain.

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ChatGPTIntermediate

Sprint Story Breakdown

Use Case: Agile sprint planning

You are an Agile coach and product manager. I need to plan our upcoming 2-week sprint. Epic: [describe the larger initiative]. Sprint Goal: [what we want to achieve by end of sprint]. For each user story: 1) Write the story in proper format with acceptance criteria (given/when/then), 2) Identify technical subtasks the engineering team needs to complete it, 3) Estimate complexity using T-shirt sizing (XS/S/M/L/XL) with reasoning, 4) Identify dependencies and blockers. After creating all stories: check if the sprint scope is realistic for a team of [X engineers] (assume 8 points capacity per engineer per sprint using Medium = 3 points), and recommend which stories to push to the backlog if we are over capacity. Features/stories to include: [list them in plain language].

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ChatGPTIntermediate

Exploratory Data Analysis Plan

Use Case: Data exploration and analysis

You are a senior data scientist. I have a dataset described as: [describe columns, row count, time range, source, and the business question]. Create a structured EDA (Exploratory Data Analysis) plan. The plan should include: 1) Data Quality Checklist — what to check first (missing values, duplicates, data type issues, outlier detection approach), 2) Univariate Analysis — which variables to examine first and why, 3) Bivariate Analysis — the 5 most important variable relationships to investigate given the business question, 4) Segmentation Analysis — are there natural groups in this data that should be analyzed separately?, 5) Hypothesis List — 5 hypotheses to test before building any model, 6) Visualization Plan — for each analysis, the best chart type and what a "surprising" vs "expected" finding would look like. Also provide: the Python/R code structure for steps 1-3.

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ChatGPTAdvanced

A/B Test Statistical Design

Use Case: Statistical experimentation

You are a statistician and experimentation platform expert. Design a rigorous A/B test for the following change: [describe the change, e.g., "a new checkout flow"]. Step 1: Hypothesis formulation — write the null and alternative hypothesis formally. Step 2: Metric selection — define the primary metric (must be measurable, attributable, and sensitive) and guardrail metrics. Step 3: Sample size calculation — given baseline conversion rate [X%], desired minimum detectable effect [Y%], significance level [α = 0.05], and power [1-β = 0.80], calculate the required sample size per variant. Show the formula. Step 4: Test duration — given [Z daily visitors], how long should the test run? Account for weekly seasonality. Step 5: Segmentation plan — should this be run on all users or a segment? What are the risks of each? Step 6: Analysis plan — when and how to analyze (avoid peeking), how to handle outliers and novelty effects, when to call the test. Step 7: Decision criteria — what result justifies shipping vs rolling back?

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ChatGPTAdvanced

Lean Process Improvement (DMAIC)

Use Case: Process optimization and operational excellence

You are a Lean Six Sigma Black Belt. Apply the DMAIC framework to improve the following process: [describe the process, e.g., 'customer support ticket resolution']. Current state: [describe pain points, metrics if known]. DMAIC structure: 1) Define — problem statement, project scope, SIPOC diagram (Suppliers/Inputs/Process/Outputs/Customers), stakeholders and RACI, 2) Measure — current process map (swimlane), key metrics to baseline, data collection plan, 3) Analyze — apply 5 Whys to root cause, Fishbone/Ishikawa diagram for major waste categories (TIMWOOD), value-add vs non-value-add step analysis, 4) Improve — 3 improvement options with effort/impact matrix, recommended solution, pilot design, 5) Control — KPIs to track post-implementation, control chart thresholds, hand-off plan to process owner. Target: [specific improvement goal, e.g., reduce resolution time by 30%].

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