Michael McBride
Founder & CEO, Atelier Commerce
Michael McBride
Founder & CEO, Atelier Commerce
This is the unglamorous half of growth, and it is the half that makes the rest possible. Three years in, the discipline has not lapsed, because at this scale clarity is not something you achieve. It is something you maintain.
This is the unglamorous half of growth, and it is the half that makes the rest possible. Three years in, the discipline has not lapsed, because at this scale clarity is not something you achieve. It is something you maintain.
The Challenge
The technical SEO problem facing a large parts retailer is fundamentally different from the one facing a fashion brand with a few hundred products. The challenge is not finding clever keywords. It is making sure a search engine can crawl, render, and index a complex, filterable database of tens of thousands of pages without exhausting its patience or its crawl budget on the way.
UTV Source carried the structural debt that any large catalog accumulates over years of change. Redirect chains and loops had built up from countless catalog edits, sending crawlers in circles and bleeding authority at every hop. Duplicate title tags spanned hundreds of product and category pages. Structured data was invalid in places, and the blog was not using schema at all, which left its posts invisible in Google Discover. The sitemap was submitting incorrect and outdated pages to Google, actively pointing crawlers at the wrong targets. Pages sat more than three clicks deep, a crawl-depth problem that quietly buries inventory in a catalog this size. On top of all of it, Search Console flagged Cumulative Layout Shift and slow page speed, the kind of performance friction that compounds across thousands of templated pages. This is the work that never makes a highlight reel. It is also the work without which nothing else in search functions. A brilliant content strategy means nothing if Google cannot crawl the page it sits on.
The Challenge
The technical SEO problem facing a large parts retailer is fundamentally different from the one facing a fashion brand with a few hundred products. The challenge is not finding clever keywords. It is making sure a search engine can crawl, render, and index a complex, filterable database of tens of thousands of pages without exhausting its patience or its crawl budget on the way.
UTV Source carried the structural debt that any large catalog accumulates over years of change. Redirect chains and loops had built up from countless catalog edits, sending crawlers in circles and bleeding authority at every hop. Duplicate title tags spanned hundreds of product and category pages. Structured data was invalid in places, and the blog was not using schema at all, which left its posts invisible in Google Discover. The sitemap was submitting incorrect and outdated pages to Google, actively pointing crawlers at the wrong targets. Pages sat more than three clicks deep, a crawl-depth problem that quietly buries inventory in a catalog this size. On top of all of it, Search Console flagged Cumulative Layout Shift and slow page speed, the kind of performance friction that compounds across thousands of templated pages. This is the work that never makes a highlight reel. It is also the work without which nothing else in search functions. A brilliant content strategy means nothing if Google cannot crawl the page it sits on.
The System
We treated the catalog as living infrastructure that needs continuous maintenance, not a one-time cleanup. Recurring Semrush audits run under campaign 10738940, and we coordinate Screaming Frog crawls against Google Search Console data so the picture is always current. The result is a site that is inspected continuously rather than rescued occasionally.
On crawl health, we ran at least six separate passes resolving redirect chains and loops, and performed a full product-level crawl to find and fix redirects SKU by SKU. We corrected the sitemap.xml so Google receives an accurate map instead of outdated pages. We resolved crawl-depth issues where pages sat more than three clicks from the surface, across multiple audit cycles, and ran indexing checks to confirm categories and products were never accidentally blocked. Search Console 404 errors were cleared in multiple rounds, including through an automated Google Colab pipeline built to handle remediation at scale. On the signals that decide ranking and visibility, we remediated duplicate title tags across hundreds of pages over several rounds, fixed invalid structured data in multiple instances, and corrected the blog schema so its posts could finally appear in Google Discover. We implemented llms.txt for answer engine optimization, then fixed the formatting issues that followed, so AI engines read the brand correctly. We added Open Graph and Twitter Card meta tags so shared links render properly, and added alt text to homepage and recommendation imagery for both accessibility and image search. On speed, the work was structural. We audited the site's scripts and migrated off Render to cut page load, removed redundant code that was dragging performance, and addressed the Cumulative Layout Shift and speed issues Search Console had flagged. Supporting conversion at the infrastructure level, we implemented Cloudinary for BigCommerce to automate image transformation, sizing, format, and background fill, which gave the catalog consistent product imagery and faster loads at the same time. We refined the cart flyout with a full-screen scroll, integrated and tuned the extended warranty script, connected Klaviyo email and SMS flows to BigCommerce, and managed the reviews platforms with optimized review requests.
The System
We treated the catalog as living infrastructure that needs continuous maintenance, not a one-time cleanup. Recurring Semrush audits run under campaign 10738940, and we coordinate Screaming Frog crawls against Google Search Console data so the picture is always current. The result is a site that is inspected continuously rather than rescued occasionally.
On crawl health, we ran at least six separate passes resolving redirect chains and loops, and performed a full product-level crawl to find and fix redirects SKU by SKU. We corrected the sitemap.xml so Google receives an accurate map instead of outdated pages. We resolved crawl-depth issues where pages sat more than three clicks from the surface, across multiple audit cycles, and ran indexing checks to confirm categories and products were never accidentally blocked. Search Console 404 errors were cleared in multiple rounds, including through an automated Google Colab pipeline built to handle remediation at scale. On the signals that decide ranking and visibility, we remediated duplicate title tags across hundreds of pages over several rounds, fixed invalid structured data in multiple instances, and corrected the blog schema so its posts could finally appear in Google Discover. We implemented llms.txt for answer engine optimization, then fixed the formatting issues that followed, so AI engines read the brand correctly. We added Open Graph and Twitter Card meta tags so shared links render properly, and added alt text to homepage and recommendation imagery for both accessibility and image search. On speed, the work was structural. We audited the site's scripts and migrated off Render to cut page load, removed redundant code that was dragging performance, and addressed the Cumulative Layout Shift and speed issues Search Console had flagged. Supporting conversion at the infrastructure level, we implemented Cloudinary for BigCommerce to automate image transformation, sizing, format, and background fill, which gave the catalog consistent product imagery and faster loads at the same time. We refined the cart flyout with a full-screen scroll, integrated and tuned the extended warranty script, connected Klaviyo email and SMS flows to BigCommerce, and managed the reviews platforms with optimized review requests.
Latest projects
Social Media Marketing
Alicia Adams Alpaca: Where nine in ten organic social visitors are meeting the brand for the very first time
Alicia Adams Alpaca runs organic social as top-of-funnel discovery, not bottom-funnel conversion. Nearly 90% of visitors it sends are first-timers, the brand's highest new-visitor rate of any channel, arriving curious after seeing a styled throw or editorial content, ready to look closer.
Social Media Marketing
Alicia Adams Alpaca: Where nine in ten organic social visitors are meeting the brand for the very first time
Alicia Adams Alpaca runs organic social as top-of-funnel discovery, not bottom-funnel conversion. Nearly 90% of visitors it sends are first-timers, the brand's highest new-visitor rate of any channel, arriving curious after seeing a styled throw or editorial content, ready to look closer.
Moonglow Jewelry: SEO & AEO, One Data Layer, Three Surfaces
We cleaned up a sprawling Shopify Plus catalog and enriched the product data behind it, structured for search engines and answer engines alike. The result: the blue link, the star-rating rich result, a seat in the AI Overview. Same data. Built to be found. Built to be cited.
Moonglow Jewelry: SEO & AEO, One Data Layer, Three Surfaces
We cleaned up a sprawling Shopify Plus catalog and enriched the product data behind it, structured for search engines and answer engines alike. The result: the blue link, the star-rating rich result, a seat in the AI Overview. Same data. Built to be found. Built to be cited.
Latest projects
Social Media Marketing
Alicia Adams Alpaca: Where nine in ten organic social visitors are meeting the brand for the very first time
Alicia Adams Alpaca runs organic social as top-of-funnel discovery, not bottom-funnel conversion. Nearly 90% of visitors it sends are first-timers, the brand's highest new-visitor rate of any channel, arriving curious after seeing a styled throw or editorial content, ready to look closer.
Moonglow Jewelry: SEO & AEO, One Data Layer, Three Surfaces
We cleaned up a sprawling Shopify Plus catalog and enriched the product data behind it, structured for search engines and answer engines alike. The result: the blue link, the star-rating rich result, a seat in the AI Overview. Same data. Built to be found. Built to be cited.
