Best prompts for ChatGPT for marketing using CRO A/B test hypotheses

You are an expert CRO analyst. Create an A/B test plan for the homepage hero CTA with the goal of increasing conversion rate for [primary conversion action]. Provide: 1) One clear hypothesis in the format: “If we [change], then [metric] will [direction] because [reason].” 2) Three test variants: Control, Variant A (copy change), Variant B (design change — color/size/icon). Include exact CTA copy and brief design notes. 3) Primary and secondary metrics, recommended segmentation, and success criteria (absolute and relative uplift). 4) Minimum sample size calculation using baseline conversion rate = [current conversion rate], desired minimum detectable effect = [MDE %], alpha = 0.05, power = 0.8. Show math and final sample per variant. 5) Tracking plan: list events, element selectors, GA4 event names, and custom dimensions. 6) QA checklist for implementation and pre-launch smoke tests. Return as a concise, actionable plan ready to hand to dev and analytics teams.

You are a growth marketer. For an email campaign targeting [audience description], generate a test bank of 12 subject-line variants grouped into 3 themes (benefit, urgency, social proof). For each theme provide: 1) Four subject-line variants (exact copy, ≤70 characters). 2) One hypothesis per theme in the format: If we use [theme], then [metric] will [direction] because [reason]. 3) Recommended segmentation (time of day, recent activity, device), sample allocation, and minimum sample per variant using baseline open rate = [current open rate]. 4) Primary and secondary metrics to track, recommended UTM parameters, and how to avoid deliverability/ISP bias. Return the variants and a short implementation checklist.

You are a conversion copywriter and CRO specialist. For a landing page promoting [offer/product], produce: 1) Three headline variants (Control, Variant A: benefit-focused, Variant B: curiosity-emotion). Provide exact headline copy (≤12 words) and a 10-word subheadline for each. 2) Two hero image concepts (product in use, lifestyle) with alt-text and brief creative direction. 3) Hypotheses for headline and image changes with expected directional impact on CTR and conversion rate. 4) Tracking plan: hero-click, scroll depth, form starts, micro-CTAs, and recommended heatmap segments. 5) Expected uplift scenario table: conservative, likely, optimistic with actionable next steps after each outcome. Make the output ready for designers and analytics to implement.

You are a CRO-focused product marketer. For the pricing page of [product], propose a set of A/B tests comparing: 1) monthly vs annual price prominence, 2) price anchoring (strikethrough vs comparison table), and 3) CTA wording (Start free trial vs Start paid plan). For each test provide: 1) A hypothesis. 2) Two actionable variants with exact copy and layout notes. 3) Key metric definitions (conversion rate, ARPU, revenue per visitor), how to track them, and funnel events required. 4) A simple revenue-per-visitor projection table for a 5% conversion uplift scenario and MRR impact for N monthly visitors. 5) Sample-size calculation using baseline conversion = [current conversion], average order value = [AOV], MDE = [MDE %]. Return concise tables and a go/no-go decision rule for rollout.

You are a CRO specialist for ecommerce. Audit the checkout flow for [store type] and propose 6 prioritized microtests aimed to reduce cart abandonment (e.g., progress indicator, guest checkout toggle, coupon entry placement, autofill, shipping costs preview, trust badges). For each microtest provide: 1) Short hypothesis. 2) Exact UI change or copy change to implement (include sample text or HTML/CSS snippet where helpful). 3) Primary event(s) to measure and how to instrument them (selectors and event names). 4) Expected relative impact on cart abandonment and estimated sample size for detecting a 7% relative uplift. 5) Quick QA checklist for checkout-critical tests. Return a prioritized list (High, Medium, Low) and a recommended 6-week test roadmap.

You are a UX copywriter and CRO analyst. For a lead-gen form with [number of fields] fields, craft: 1) Three label + placeholder + error-message sets (Control, Variant A: friendlier tone, Variant B: microcopy that reduces perceived risk). Provide exact strings. 2) A hypothesis for each variant and expected effect on form completion and field abandonment. 3) Instrumentation plan: events for field focus, field completion, validation error, form submit, and time-on-field. Provide recommended selectors and GA4 event names. 4) Minimum detectable effect calc using baseline form completion rate = [baseline %], MDE = [MDE %]. 5) Implementation tips to avoid bias (randomization, caching, sequential exposure) and a pre-launch QA checklist. Return output ready for developers and content team.