Ecommerce Website Audit with AI-Guided Fixes
Run an ecommerce website audit that connects storefront evidence, shopper friction, SEO, accessibility, and checkout findings to reviewable Runner AI fixes.
Your Ecommerce Website Audit, Built Around Your Store
Describe the outcome you need. Runner uses your catalog, brand, and store context to prepare reviewable Ecommerce website audit work, so you can approve it without moving data between tools.
Try Ecommerce website audit with your store context now. Publishing and automation depend on your plan.
Audit the Customer Path, Not Just a Score
Combine automated evidence with human review, then describe the smallest storefront change that addresses a verified problem.
Check Product Clarity
Runner keeps ecommerce Website Audit work connected to your store and ready for review.
Test Mobile and Accessible Use
Inspect responsive layouts, touch targets, keyboard paths, labels, focus, contrast, zoom, and readable content on the devices customers actually use.
Trace Product Discovery
Follow navigation, collection pages, filters, search, internal links, and empty states to see whether shoppers can reach a suitable product without guessing.
Verify Cart and Checkout
Run real test paths across offers, shipping, tax, payment, errors, confirmation, and support handoffs instead of treating a scanner result as proof.
A product principle for Ecommerce Website Audit
Keep Ecommerce website audit work connected to real store context, make each proposed change reviewable, and publish only what the operator approves.
— Runner AI product principle
Turn Audit Evidence into a Prioritized Change Brief
Start with representative pages: the homepage, a collection, a high-value product page, search or navigation, cart, checkout, confirmation, and a policy or support route. Capture the exact URL, device, observed behavior, screenshots or measurements, customer question, and any catalog or operational constraint. Group findings by shopper impact and confidence rather than by whichever tool produced the longest report. Then bring one verified issue into Runner AI with the store context required to understand it. Ask for a narrow proposal, such as clarifying a product comparison, repairing a mobile layout, strengthening a collection introduction, or aligning a landing-page promise with the product page. The AI ecommerce conversion optimization page explains how to frame conversion work without inventing outcomes, while AI ecommerce search optimization covers the discovery path in more depth. Your team should still validate analytics, accessibility, security, privacy, legal, payment, and platform-specific findings with the appropriate tools and specialists.
Explore Conversion Optimization
Inspect the Preview, Then Re-Test the Real Journey
A generated proposal is not a completed audit fix. Review the changed copy, layout, hierarchy, links, product facts, variants, price, inventory, policy language, and responsive behavior in the Runner AI preview. Compare it with the original evidence and reject changes that broaden the scope or hide the problem instead of solving it. Once an approved revision reaches the real store, repeat the same test path on relevant devices and browsers. For checkout findings, confirm shipping, tax, payment, error, and confirmation behavior with safe test orders. For accessibility, combine automated checks with keyboard, zoom, screen-reader, and human evaluation. Record what changed, what passed, what remains uncertain, and who approved it. AI ecommerce checkout optimization provides a focused companion for purchase-path friction. Browse the full Runner AI feature library when the finding belongs to marketing, storefront building, retention, or backend operations rather than CRO.
Product principle
The useful result is Ecommerce website audit work you can review, revise, and connect back to the store — not another disconnected dashboard.
— Runner AI product principle
Ecommerce Website Audit FAQ
What is an ecommerce website audit?
An ecommerce website audit is a structured review of store performance, content, product discovery, usability, accessibility, SEO, and the purchase path. It combines automated measurements with human testing to identify reproducible problems and prioritize appropriate fixes.
Can Runner AI audit an ecommerce website automatically?
Runner AI can help organize the URLs, observations, screenshots, store context, and goals you provide, then support reviewable storefront change requests. It does not replace specialist security, legal, privacy, accessibility, analytics, payment, or platform audits, and people must verify every finding and proposed fix.
Which pages should an ecommerce audit review first?
Start with representative, commercially important paths: the homepage, key collections, high-traffic product pages, search or navigation, cart, checkout, confirmation, and relevant policy or support pages. Include mobile and edge cases rather than checking only the ideal desktop journey.
How should audit findings be prioritized?
Prioritize reproducible issues by shopper impact, affected traffic or revenue path, severity, confidence, implementation risk, and verification effort. Fix broken or unsafe customer journeys before polishing low-impact details, and keep assumptions clearly separate from observed evidence.
Turn One Verified Finding into a Reviewable Fix
Bring the evidence and store context. Keep accessibility, security, legal, payment, analytics, and final approval with qualified people.
- Evidence-led change brief
- Storefront preview before approval
- Clear re-test path
Help me turn this ecommerce website audit finding into a focused storefront change. Use the affected URL, device, screenshots, shopper task, observed behavior, catalog facts, and constraints I provide; propose the smallest useful fix, flag what needs specialist review, and keep the result reviewable before publishing.