How New York & Company gained full site visibility before Black Friday by letting AI agents monitor their store end-to-end

Just weeks before Black Friday, New York & Company completed a major migration from Hydrogen to Liquid. The timing was aggressive, but the team was confident.

Then reality set in.

With 100+ SKUs refreshed and thousands of pages updated, the QA burden was massive. The e-commerce team ran their standard checks, but the truth every fashion retailer knows: there's no realistic way to manually browse every page, every collection, every variant.

Issues were out there. They just had no visibility into what customers were actually experiencing.

• Mobile conversion blockers — promotional banners positioned in ways that obscured critical CTAs, directly impacting mobile checkout rates during peak traffic.
• Promo code inconsistencies — advertised discounts that didn't apply automatically at checkout, creating friction exactly when customers were ready to buy
• Technical SEO gaps — robots.txt misconfigurations and accessibility issues silently affecting crawlability and compliance.

For a fashion brand heading into BFCM, these weren't just technical issues. They were revenue risks hiding in plain sight.

Within weeks of deploying Zenyt, New York & Company achieved full visibility heading into their most critical selling period:

• 500+ opportunities identified across mobile UX, promotional integrity, crawlability, and product accuracy — issues the team had no realistic way to catch manually
• 50 priority fixes deployed before Black Friday traffic surged, each tied to customer experience impact
• 90% reduction in QA effort — what would have taken 83+ hours of manual review was surfaced in minutes, letting the team focus on peak-season execution
• Estimated $100k–$300k annual impact from conversion improvements on corrected products

1. Mobile UX Agent — simulated real shopper journeys on mobile devices, flagging conversion-blocking elements like overlapping banners and obscured add-to-cart buttons.
2. Promo Integrity Agent — validated that advertised discounts (GET50, GET75, extra 10% off) applied correctly at checkout across all product categories.
3. Crawlability Agent — audited robots.txt configurations, identified accessibility gaps, and surfaced indexing issues affecting organic visibility.
4. Product Accuracy Agent — cross-checked product attributes against imagery to catch trust-eroding mismatches before customers did.

On mobile product detail pages, a persistent "ENTER THE GIVEAWAY" banner at the bottom of the screen was overlaying the Add to Cart button. Customers couldn't complete purchases without first dismissing the banner—creating unnecessary friction during peak mobile traffic.

Product pages advertised stacked offers ($50 OFF $150 with code GET50, $75 OFF $200 with code GET75). Some carts applied discounts automatically, while others required customers to manually enter the code—an inconsistent experience that created confusion during checkout.

The robots.txt was blocking /policies/ paths completely, preventing Google from indexing shipping, returns, and privacy pages. These policy pages provide critical trust signals for fashion shoppers and support Google Ads compliance.

The product listed "Pocket: No Pocket" in product details, but images clearly showed the model with her hand in a side seam pocket. In fashion, these mismatches erode trust and drive returns.