100 AI Prompts for Growth Hackers — Complete Guide

Generate 20 growth experiment ideas for a [product type] at [growth stage: early/growth/mature] with the primary bottleneck at [funnel stage: acquisition/activation/retention/referral/revenue]. For each experiment, specify: the hypothesis, the metric it improves, the effort to implement (S/M/L), estimated impact (S/M/H), and which growth lever it targets (more users / more value per user / more users via users).

Help me prioritize the following [N] growth experiments using the ICE framework: [list experiments with brief descriptions]. For each experiment, estimate: Impact (1-10: how much will this move the key metric?), Confidence (1-10: how sure are we it will work, based on evidence?), Ease (1-10: how easy to implement?). Calculate ICE scores, rank them, and flag any experiments with high confidence but low current ICE score that may be undervalued.

Write a growth experiment brief for testing [hypothesis]. Include: problem statement (what pain/opportunity are we addressing?), hypothesis (if we do X, then Y will happen because Z), success metric and minimum detectable effect, secondary metrics to monitor, experiment design (control vs variant), targeting criteria, sample size calculation, duration, risk assessment, and decision criteria for ship/iterate/kill.

Analyze the results of this growth experiment: [describe experiment, control vs variant, metrics]. Results: control: [metrics], variant: [metrics], sample size: [N per variant], duration: [X days]. Assess: statistical significance (provide p-value interpretation), practical significance (is the effect size meaningful?), segment breakdown (does it work differently for [segment A vs B]?), and recommendation: ship, iterate, or kill — with reasoning.

Design a multivariate test for [landing page / email / onboarding flow] to optimize [primary metric]. Identify 3 elements to test simultaneously (e.g., headline, hero image, CTA button). Define all combinations, required sample size for each cell, minimum detectable effect, test duration, and how to analyze results to distinguish individual element effects from interaction effects. Recommend a testing tool.

Build a growth model for [product] showing how the key growth inputs connect to the primary growth metric. Start with the North Star Metric, decompose it into input metrics (e.g., new users, activation rate, retention rate, referral rate, monetization rate), and create a formula that shows how changes in each input affect the NSM. Identify the 2-3 inputs with the highest leverage for current stage.

Help me identify the primary growth constraint (Theory of Constraints applied to growth) for [product/company]. Current funnel metrics: [list acquisition, activation, retention, referral, revenue metrics]. Using the constraint analysis: which stage has the biggest drop-off? What percentage improvement at each stage would produce the most NSM growth? What is the cost per improvement at each stage? Recommend where to focus.

Design a 2-week growth sprint focused on improving [specific metric] from [current value] to [target value]. Define: the sprint goal and hypothesis, 3-5 experiments to run in parallel, resource allocation (who does what), daily metrics to track, mid-sprint check-in criteria (kill or continue), end-of-sprint retrospective format, and how learnings are documented and shared with the broader team.

Help me structure a growth experiment backlog for a [product/team]. Define: the fields each experiment card should have (hypothesis, metric, effort, confidence, channel, funnel stage, owner), the workflow states (idea → prioritized → in progress → analyzing → shipped/killed/learned), how to prevent experiment backlog bloat, and a template for the weekly growth meeting to review and update the backlog.

Write a post-experiment learning document for the following completed growth test: [describe experiment, results, and context]. Structure it as: experiment summary, quantitative results, qualitative observations, why it worked or did not work (root cause analysis), what we learned about our users from this, how this changes our model or assumptions, follow-up experiments to run based on learnings, and the decision made (ship/iterate/kill).

Audit the conversion funnel for [product/flow]. Here is the current funnel data: [list stages with conversion rates]. Identify: the biggest drop-off stage (by both absolute and relative terms), whether each drop-off is a technical, UX, or messaging issue, the 3 highest-leverage optimization opportunities, and quantify the revenue impact of improving each stage by 10%. Provide a prioritized action plan.

Provide a comprehensive optimization plan for a landing page targeting [keyword/traffic source] with current conversion rate of [X%]. The page goal is [desired action]. Review: headline clarity and value proposition strength, hero section above the fold, social proof placement and quality, objection handling, CTA copy and placement, page speed, mobile experience, and exit intent. Provide specific copy and design recommendations.

Help me reduce signup friction for [product] where the current signup conversion rate from [traffic source] is [X%]. Analyze the current signup flow: [describe steps, fields, friction points]. Identify: fields that can be removed or deferred, where social login would help, where to add trust signals, how to reduce perceived time commitment, and test hypotheses ordered by expected impact. Benchmark against best-in-class signup flows.

Optimize the pricing page for [product] with current trial-start rate of [X%]. Describe the current page: [tiers, pricing, CTA, feature comparison]. Identify improvements for: plan naming and positioning, anchoring strategy (most popular badge), feature comparison clarity, social proof placement, FAQ to handle objections, trial vs freemium CTA framing, and money-back guarantee visibility. Provide rewrite recommendations.

Design an activation funnel for [product] to get new users to [Aha Moment: describe first value experience] within [target time: 24 hours / 7 days]. Map: the current path from signup to Aha Moment (steps, drop-offs), the minimum required path (remove unnecessary steps), in-product nudges to guide users (tooltips, empty states, progress indicators), and email/push sequences to bring back users who stall at each step.

Optimize the checkout flow for [e-commerce / subscription product] with [N steps] and [X%] cart abandonment. Current issues: [describe known friction points]. Recommend: steps to combine or remove, trust signal additions (security badges, guarantees), progress indicator design, payment option expansion, address form optimization, error message improvements, and the single highest-impact change to test first.

Build a revenue funnel model for [business model: SaaS / e-commerce / marketplace]. Define all stages from first marketing touch to revenue, with conversion rate benchmarks for [industry/stage]. For the model: [current traffic X], calculate monthly revenue at current conversion rates, show sensitivity analysis (impact of +10% at each stage), and identify the stage with the highest expected return on optimization investment.

Design a freemium-to-paid conversion strategy for [product] with [N free users] and [X%] current conversion rate. Define: the ideal free experience (enough value to stay, enough limitation to upgrade), upgrade trigger moments (in-product walls, usage limits, feature gates), the upgrade flow and pricing page, email sequences for free users who hit upgrade triggers, and how to A/B test different freemium limits.

Optimize the B2B sales funnel for [product] going from [MQL to SQL to Closed Won]. Current conversion rates: [list by stage]. Identify the highest-friction handoffs, recommend: lead scoring improvements, MQL-to-SQL qualification criteria changes, SDR outreach sequence optimization, demo request to demo show-up rate improvements, and proposal-to-close conversion tactics. Provide one test for each stage.

Design the analytics instrumentation for tracking a [product] conversion funnel in [GA4/Mixpanel/Amplitude]. Define: the event tracking plan (event names, properties, when each fires), the funnel analysis setup, how to segment funnels by [acquisition source, user segment, device], cohort analysis configuration, and the dashboard views to build. Provide the event tracking spec sheet.

Design a viral loop for [product]. Identify: the existing action where users naturally create value for others (invite, share, create, collaborate), how to make this action more visible and friction-free, the incentive structure (intrinsic vs extrinsic rewards), how to measure viral coefficient (K-factor), and the cycle time. Calculate what K-factor is needed to achieve viral growth and what changes would get there.

Design a referral program for [product] to acquire new users via existing users. Define: incentive structure for referrer and referee (double-sided vs one-sided), the friction level of the sharing mechanism, which user milestone triggers the referral ask, the referral landing page positioning, tracking and attribution approach, fraud prevention, and success metrics (referral rate, referral conversion rate, referral CAC vs other channels).

Design a content-led growth strategy (SEO + content flywheel) for [product]. Define: the programmatic content opportunity (tool pages, comparison pages, templates, glossary), the editorial content strategy (thought leadership attracting backlinks), how content drives product signups (in-content CTAs, free tools), the flywheel compounding effect model, required investment, and 12-month traffic and signup projections.

Design a product-led growth (PLG) motion for [product]. Define: the free entry point (freemium vs trial), how the product creates acquisition (sharing, virality, network effects), the in-product upgrade triggers, the PLG metrics to track (PQLs, time-to-value, activation rate, expansion revenue), how sales and product motions coexist, and the top 3 PLG experiments to run in the first 90 days.

Analyze and optimize the paid acquisition mix for [brand]. Current channels and CAC: [list channels with spend and CAC]. Target blended CAC: [$X]. LTV: [$Y]. Recommend: which channels to scale (CAC well below LTV:CAC target), which to optimize (CAC near target), which to cut (CAC unsustainable), and what new channels to test. Provide a 3-month budget reallocation plan.

Design a community-led growth strategy for [product/brand]. Define: the community platform and format (Slack, Discord, forum, LinkedIn group), the content and event cadence to maintain engagement, how community membership drives product signups and upgrades, the community-to-product feedback loop, how to measure community contribution to pipeline, and the team resources required to run this motion sustainably.

Help me analyze and reduce Customer Acquisition Cost (CAC) for [company]. Current CAC by channel: [list channels with monthly spend, new customers acquired, and CAC]. Total blended CAC: [$X]. LTV: [$Y]. LTV:CAC ratio: [Z]. Analyze: which channels are efficient, which have CAC payback > [N months], which are scaling with diminishing returns, and provide 5 specific tactics to reduce CAC across the portfolio.

Design a partnership/co-marketing program to drive growth for [product]. Identify: ideal partner profile (complementary product, shared audience, non-competitive), outreach strategy to attract partners, partnership tiers and benefits, co-marketing activities (joint webinars, co-written content, integration marketplace listing), attribution model for partner-sourced growth, and how to manage and measure the program.

Design a free tool strategy to drive acquisition for [paid product]. The free tool idea is [describe concept]. Analyze: how this tool attracts the ideal user (keyword demand, shareability), how it creates natural CTAs to the paid product, SEO opportunity (traffic estimate, competition), development cost vs expected signups, how to launch and distribute the tool, and similar successful free tool examples in [industry].

Design an affiliate/ambassador program for [product]. Define: commission structure (percentage vs flat, one-time vs recurring), qualifying affiliate profile (audience size, niche fit, trust requirements), how to recruit initial affiliates, the affiliate content kit (banners, swipe copy, demo video), tracking technology recommendation, payout schedule, and how to prevent affiliate fraud. Benchmark commission rates for [industry].

Design a retention strategy for [product] with current [Day 30] retention of [X%] and target of [Y%]. Define: key drop-off points in the user journey, behavioral triggers that predict churn [7/14/30] days before it happens, intervention tactics at each drop-off point (in-product, email, push, CSM outreach), the 'reset the clock' moment that best correlates with long-term retention, and a retention experiment roadmap.

Design a churn prediction and prevention system for [SaaS/subscription product]. Define: leading indicators of churn (behavioral signals available in our data), how to build a churn risk score (describe model approach: logistic regression, ML, or heuristic rules), risk tier definitions (high/medium/low), automated intervention by tier, and how to measure the lift from interventions vs a control group.

Help me optimize pricing for [product] to maximize revenue growth. Current state: [price points, plan names, conversion rate, upgrade rate, churn rate by plan]. Analyze: whether our pricing captures value relative to [describe the value we deliver], where to add a higher-tier plan to capture high-willingness-to-pay users, whether a lower entry price would improve top-of-funnel without killing margin, and 3 pricing experiments to run.

Design an expansion revenue motion for [SaaS product] to increase NRR from [current X%] to [target Y%]. Define: expansion triggers (usage approaching limits, team growth signals, new use case adoption), in-product upsell prompts at the right moment, the CSM-led expansion playbook for [qualifying segment], how to track expansion MRR separately from new MRR, and the top 3 experiments to accelerate expansion.

Design a customer loyalty program for [product/brand]. Define: the points or rewards model (points per $ spent, tiered benefits, milestone rewards), the emotional rewards vs transactional rewards balance, how to gamify engagement without feeling manipulative, the communication strategy to keep members engaged, how to measure loyalty program impact on retention and LTV, and the technology to implement it.

Help me calculate and improve LTV (Lifetime Value) for [product]. Current metrics: average contract value [$X], monthly churn rate [Y%], gross margin [Z%], average contract length [N months], expansion revenue (NRR) [W%]. Calculate: LTV using multiple methods (simple, discounted cashflow), LTV:CAC ratio at current CAC [$A], target LTV improvements from 10% churn reduction vs 10% expansion revenue increase.

Identify monetization opportunities for [product] beyond the current [pricing model]. The product serves [describe users and their value derived]. Explore: usage-based pricing components, add-on modules for power users, enterprise tier features, marketplace or ecosystem revenue, data or API monetization, and professional services opportunities. Evaluate each by revenue potential, implementation effort, and strategic fit.

Design a cohort retention analysis for [product]. Define: the cohort definition (users who started in the same month), retention metric (% returning each subsequent period), the periods to track ([Day 1, 7, 14, 30, 60, 90]), how to segment cohorts by [acquisition channel, activation status, plan type], how to create the retention heat map, and what patterns to look for that indicate improving or deteriorating retention.

Help me design a usage-based pricing model for [product]. The current model is [flat fee / seats]. The natural usage metric that correlates with value delivered is [describe metric]. Design: the pricing formula (per unit cost, volume tiers, minimum commitment), overage handling, how to communicate this to customers (estimated bill calculator), how to predict revenue variance, and how to protect ARR predictability with minimums or caps.

Design a win-back campaign for churned [customers/subscribers] of [product] who churned in the past [3-12 months]. Define: segmentation by churn reason (if known: price, product gaps, competition, went out of business), personalized messaging for each segment, the win-back offer (discount, new feature announcement, consultation), the multi-channel sequence (email + LinkedIn + retargeting), and success metrics (win-back rate, reactivated LTV).

Define the contents of a growth team metrics dashboard for [product]. Include: North Star Metric with weekly trend, acquisition funnel (by channel), activation rate trend, D1/D7/D30 retention, revenue metrics (MRR, NRR, CAC, LTV, LTV:CAC), current experiment status, and weekly cohort retention heat map. Specify the data source and update frequency for each metric.

Design the event tracking instrumentation for [product] in [Mixpanel/Amplitude/PostHog]. Define: the 20 most important events to track (covering acquisition, activation, retention, and monetization), the properties each event should carry, user identity resolution strategy (anonymous → authenticated), the top 5 analyses to run with this data, and the implementation priority order for the engineering team.

Design a user segmentation model for growth analysis in [product]. Define: the behavioral segments that matter most for growth decisions (power users, at-risk users, growth-driver users, dormant users), the behavioral criteria that define each segment, how segments should influence product, marketing, and success team actions, and how to visualize segment distribution and movement over time.

Explain how to build a cohort analysis in [Amplitude/Mixpanel/SQL] for [product] to answer: 'Are we retaining users better over time?' Define: cohort definition and grouping method, retention metric to use, time periods to track, how to normalize for cohort size, how to interpret improving vs deteriorating retention curves, and what external factors to account for when comparing cohorts across different time periods.

Design a rigorous A/B testing framework for a team running [N] experiments per month. Define: the experiment tracking system (doc template, status tracking, results storage), statistical testing methodology (frequentist vs Bayesian, significance thresholds), how to prevent p-hacking (pre-registration, fixed stopping rules), shipping criteria beyond statistical significance (practical significance, segment consistency), and how to document and share learnings.

Perform a growth accounting analysis for [product] using the following monthly data: [list new users, resurrected users, churned users, and retained users for the past 6 months]. Calculate: monthly net growth rate, breakdown of growth by new vs retained vs resurrected users, quick ratio (new + resurrected) / churned, and identify the month-over-month trends. What does this tell us about the health of the growth engine?

Design a marketing attribution model for [business] with [describe marketing channels and customer journey complexity]. Compare: last-touch, first-touch, linear, time-decay, and data-driven attribution for our specific customer journey. Recommend the model that best fits our sales cycle length ([N days]) and channel mix. Define the technical implementation in [GA4 / HubSpot / Segment] and how to present attribution data to the growth team.

Design a growth experiment database/wiki structure for a team of [N growth practitioners]. Define: the data schema for each experiment record (hypothesis, design, results, learnings, status), how to tag experiments by channel, funnel stage, and hypothesis category, how to search and filter past experiments to avoid duplicate work, the onboarding process for new team members, and how to surface insights from past experiments for new experiment ideation.

Design a growth reporting cadence for a startup at [stage: seed/Series A/Series B]. Define: daily metrics to monitor (anomaly detection thresholds), weekly growth meeting agenda (metrics review, experiment results, prioritization), monthly growth report structure (for board/leadership), quarterly growth review (strategy assessment), and annual growth planning process. Include who attends each cadence and what decisions each meeting should produce.

Help me define and calculate a North Star Metric for [company/product]. Criteria: the metric must measure value delivered to users (not vanity), correlate with long-term revenue, be understandable by the whole company, and be actionable by the product team. Evaluate 3 NSM candidates for [product], decompose the recommended one into input metrics, and explain how to measure it weekly with [describe available data].