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87 agent skills for AI coding assistants — marketing, growth, web3, dev, design & operations. Built for OpenClaw, Claude Code, Cursor, and Codex.

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## Contents - A/B Testing Popups - What to Test (Priority Order) - Test Framework - Statistical Significance - Tools for A/B Testing Popups ## A/B Testing Popups ### What to Test (Priority Order) 1. **Offer** — What you're giving (highest impact on conversion) 2. **Trigger** — When/how the popup appears 3. **Headline** — The hook 4. **Design** — Layout, colors, imagery 5. **Copy** — Body text and CTA 6. **Form fields** — Number and type of fields 7. **Timing** — Seconds delay or scroll percentage ### Test Framework ``` TEST 1: Offer (run first — everything else depends on this) ├── A: 10% discount ├── B: Free shipping └── C: Content upgrade (guide/checklist) Winner → Use in all subsequent tests TEST 2: Trigger timing ├── A: 5 seconds ├── B: 15 seconds └── C: 50% scroll Winner → Use going forward TEST 3: Headline ├── A: Benefit-focused ("Get 10% off your first order") ├── B: Curiosity-focused ("Don't miss this") └── C: Social proof ("Join 50K subscribers") Winner → Use going forward TEST 4: Design ├── A: Minimal (text + form) ├── B: Image-rich (product photo or mockup) └── C: Full-screen takeover vs modal ``` ### Statistical Significance - **Sample size depends on baseline + effect size** — there is no universal "1,000 impressions" number. Lower baseline rates and smaller lifts need far more traffic. Use the table below. - **Minimum conversions:** aim for ~100+ conversions per variant (50 is a bare floor for a rough read) before trusting a result. - **Duration:** run at least 1–2 full weeks to capture weekday/weekend and full purchase cycles, even if significance hits sooner. - **Confidence level:** 95% (α = 0.05) minimum; pick power = 80% when sizing. - **Don't peek / no early stopping** on a fixed-horizon test — it inflates false positives. Set the duration and required N up front, or use a sequential/Bayesian method designed for continuous monitoring. **Required sample size per variant** (2-sided, 95% confidence, 80% power), to detect a *relative* lift over a baseline conversion rate: | Baseline conv. rate | Detect +10% rel. | +20% rel. | +50% rel. | |---------------------|------------------|-----------|-----------| | 1% | ~155,000 / variant | ~40,000 | ~7,000 | | 2% | ~77,000 | ~20,000 | ~3,400 | | 5% | ~30,000 | ~7,600 | ~1,300 | | 10% | ~14,000 | ~3,600 | ~620 | Reading it: a popup at a **2% baseline** that you hope to lift to **2.4% (+20% relative)** needs **~20,000 impressions per variant** — not 1,000. (Approximate; use a proper calculator — e.g. Evan Miller's "Sample Size" or your testing tool's built-in — for exact figures and for absolute-lift inputs.) If the math says you can't reach N in a reasonable window, test a **bigger swing** (offer, not button color), test on **higher-traffic pages**, or accept a **directional** read and re-test later. ### Tools for A/B Testing Popups > Pricing and free-tier limits change constantly — **verify current pricing on the vendor's site before recommending** (as of Jun 2026). Choose on fit, not headline price. | Tool | Best fit | Choose it when | |------|----------|----------------| | OptinMonster | WordPress / general web | You want deep trigger + display-rules control without building it; WP-first stack | | BDOW! (formerly Sumo) | Simple / small sites | You need a fast, low-effort setup and a usable free tier | | Privy / Justuno / OptiMonk | Ecommerce (Shopify) | You need cart-value triggers, spin-to-win, and email/SMS list sync to a store | | ConvertFlow | SaaS / personalization | You need on-site personalization, multi-step funnels, and CRM-aware targeting | | Unbounce / Instapage | Landing pages + popups | Popups live alongside built landing pages and you want one builder | | Klaviyo / Mailchimp (built-in forms) | Already on that ESP | You want capture + flows in one tool and don't need advanced display rules | | Custom (JS) | Full control | You need exact behavior, no third-party script weight, and own consent/CWV handling | **Tool-fit criteria, in priority order:** (1) does it integrate with your ESP/CRM and consent platform; (2) display-rule granularity (trigger × segment × frequency cap); (3) built-in A/B testing + significance reporting; (4) script weight / performance (async, lazy-loaded — see Core Web Vitals note); (5) Consent Mode / GPC awareness; (6) price for your traffic volume. ---