Exit Intent

This skill designs end-to-end exit-intent popup strategies for ecommerce stores — deciding when to fire, what to offer, what copy and creative to show, and how to measure lift — so that recovery offers catch abandoning visitors without interrupting the ones who are still shopping or ready to check out.

Use when

• The user runs a Shopify, WooCommerce, BigCommerce, or custom ecommerce storefront and is seeing desktop bounce rates above 55% or abandoning cart rates climbing week over week.
• The user asks for help writing exit popup copy, picking an incentive (discount vs free shipping vs sample), or deciding whether a popup should appear on product, cart, or checkout pages.
• The user wants a structured A/B testing plan for exit-intent variants (trigger sensitivity, offer size, headline tone, visual layout) with a clear primary metric and guardrails.
• The user is concerned that popups are hurting SEO Core Web Vitals, harming mobile UX, or creating a brand perception problem, and wants rules for when not to fire.

What this skill does

Analyzes the store type, traffic composition (paid vs organic, new vs returning), and conversion funnel stage to recommend a layered exit-intent strategy. Produces trigger logic (mouse leave threshold, scroll depth gate, time on page minimum, page-type filters, frequency caps per visitor), offer tiering (soft ask like newsletter vs hard ask like 10% off vs urgency-based like countdown), and at least three headline and CTA copy variants mapped to customer intent. Recommends suppression rules for returning buyers, logged-in accounts, and checkout pages. Includes an A/B test plan with sample size math and statistical stopping rules.

Inputs required

• Store URL or platform (required): Platform matters because trigger implementation differs between Shopify apps, Klaviyo flows, Privy, OptinMonster, or custom JS.
• Primary goal (required): Email capture, first-order discount redemption, cart recovery, or survey collection — each pulls the design in a different direction.
• Average order value and gross margin (required): Dictates how generous the incentive can be without destroying contribution margin.
• Monthly unique visitors and current conversion rate (optional): Improves A/B sample-size recommendations and lift expectations.
• Brand voice examples or past popup copy (optional): Helps match tone so recovery offers sound native rather than generic.

Output format

Four sections. (1) Strategy summary — one paragraph explaining the recommended approach and why it fits the store. (2) Trigger configuration table — trigger type, threshold, page filters, frequency cap, suppression rules, and a short rationale for each row. (3) Offer and creative matrix — three to five variants, each with headline, subheadline, CTA button text, offer value, and intended audience segment. (4) A/B test plan — primary metric, minimum detectable effect, required sample size per variant, estimated test duration, and guardrail metrics (bounce rate, checkout completion, unsubscribe rate) to monitor.

Scope

• Designed for: ecommerce operators, growth marketers, CRO specialists, and DTC brand teams
• Platform context: platform-agnostic, with implementation notes for Shopify, WooCommerce, Klaviyo, and OptinMonster
• Language: English

Limitations

• Does not pull live analytics data — recommendations are based on the numbers you provide.
• Does not generate the actual popup code or design files; output is a strategy specification that your developer, designer, or popup platform can implement.
• Sample-size math assumes roughly normal conversion distributions; very low-volume stores may need longer test windows than the estimate suggests.