Discovery is not one surface anymore. It is a listing, a rich result, and an AI citation, and they all read from the same underlying data. What we did for Moonglow was rebuild that data layer once, so all three surfaces could be earned from the same source of truth.
Danielle Schermerhorn
Founder and CEO, Atelier Commerce
BUILT WITH
Discovery is not one surface anymore. It is a listing, a rich result, and an AI citation, and they all read from the same underlying data. What we did for Moonglow was rebuild that data layer once, so all three surfaces could be earned from the same source of truth.
Danielle Schermerhorn
Founder and CEO, Atelier Commerce
BUILT WITH
It is a Tuesday morning. A shopper types moon phase necklace for a June birthday into a search box on her phone. Three surfaces show her the same answer. A blue link to a Moonglow product page. A star rating rich result underneath it. An AI Overview citation quoting the pendant's material and finish. All three read off the same product data layer, and none of it happened by accident.
It is a Tuesday morning. A shopper types moon phase necklace for a June birthday into a search box on her phone. Three surfaces show her the same answer. A blue link to a Moonglow product page. A star rating rich result underneath it. An AI Overview citation quoting the pendant's material and finish. All three read off the same product data layer, and none of it happened by accident.
The situation, told plainly
Moonglow had years of catalog history and a loyal audience, and the product data underneath was working against discoverability. Titles were generic and duplicative, descriptions were thin, and collection structures did not map to how people actually search for a moon phase pendant or a birth date keepsake. Structured data was inconsistent or missing, which kept the catalog from qualifying for rich results and left visibility on the table in image and shopping surfaces. AI Overviews were already answering moon phase and lunar personality queries. Without enriched, well structured content, the brand risked being summarized by competitors rather than cited itself.
The picture was one enriched data layer that earned three surfaces. Product data rebuilt as a merchandising asset with descriptive, search aligned titles that named material and style, richer descriptions, consistent attributes for metal, style, and occasion, and curated cross aisle collections that matched real search demand. Sitewide SEO cleanup that standardized metadata, fixed heading hierarchy, tightened internal linking and breadcrumbs, mapped collections to real demand, and resolved the technical debt that had been suppressing rich result eligibility. Structured data live for Product, Offer, AggregateRating, BreadcrumbList, and Organization, so the same catalog that ranked the blue link could earn the star rating and feed the AI answer. One investment, three surfaces.
The situation, told plainly
Moonglow had years of catalog history and a loyal audience, and the product data underneath was working against discoverability. Titles were generic and duplicative, descriptions were thin, and collection structures did not map to how people actually search for a moon phase pendant or a birth date keepsake. Structured data was inconsistent or missing, which kept the catalog from qualifying for rich results and left visibility on the table in image and shopping surfaces. AI Overviews were already answering moon phase and lunar personality queries. Without enriched, well structured content, the brand risked being summarized by competitors rather than cited itself.
The picture was one enriched data layer that earned three surfaces. Product data rebuilt as a merchandising asset with descriptive, search aligned titles that named material and style, richer descriptions, consistent attributes for metal, style, and occasion, and curated cross aisle collections that matched real search demand. Sitewide SEO cleanup that standardized metadata, fixed heading hierarchy, tightened internal linking and breadcrumbs, mapped collections to real demand, and resolved the technical debt that had been suppressing rich result eligibility. Structured data live for Product, Offer, AggregateRating, BreadcrumbList, and Organization, so the same catalog that ranked the blue link could earn the star rating and feed the AI answer. One investment, three surfaces.
How the data layer was built
The rebuild ran on Shopify Plus. Merchandising, editorial, and structured data were aligned inside one data layer rather than as three parallel projects.
Product titles were rewritten as descriptive, search aligned strings that named the material and the style at the front, because the way a customer types moon phase silver necklace is not the way a legacy title formatted it. Descriptions were rewritten to carry the story and the specification in the same paragraph, so the page read as well to a person as it did to a crawler. Consistent attributes for metal, style, and occasion were pushed across the catalog so filters and facets could hold together and cross aisle collections could be curated to real demand rather than to internal taxonomy. Metadata and heading hierarchy were standardized, internal links were tightened, breadcrumbs were rewired, and collection to search demand mappings were rebuilt so the site could be crawled the way it was designed to be read. Structured data was published for Product, Offer, AggregateRating, BreadcrumbList, and Organization, which is what the star rating rich result, the shopping surface, and the AI Overview citation each need in different combinations. The same enriched layer that ranked the listing earned the rich result and fed the answer engine, so a single investment earned three surfaces instead of three.
How the data layer was built
The rebuild ran on Shopify Plus. Merchandising, editorial, and structured data were aligned inside one data layer rather than as three parallel projects.
Product titles were rewritten as descriptive, search aligned strings that named the material and the style at the front, because the way a customer types moon phase silver necklace is not the way a legacy title formatted it. Descriptions were rewritten to carry the story and the specification in the same paragraph, so the page read as well to a person as it did to a crawler. Consistent attributes for metal, style, and occasion were pushed across the catalog so filters and facets could hold together and cross aisle collections could be curated to real demand rather than to internal taxonomy. Metadata and heading hierarchy were standardized, internal links were tightened, breadcrumbs were rewired, and collection to search demand mappings were rebuilt so the site could be crawled the way it was designed to be read. Structured data was published for Product, Offer, AggregateRating, BreadcrumbList, and Organization, which is what the star rating rich result, the shopping surface, and the AI Overview citation each need in different combinations. The same enriched layer that ranked the listing earned the rich result and fed the answer engine, so a single investment earned three surfaces instead of three.
Success Stories
Scarlett Gasque: The Open Was Never the Problem
A Klaviyo program with strong opens, clean deliverability, and every flow already live. One number told a quieter story. In ninety days the click to open rate climbed, engagement moved from 39.4 percent to 50.7 percent, revenue rose 78 percent, and sessions fell 32 percent. A better audience, not a bigger one.
Scarlett Gasque: The Open Was Never the Problem
A Klaviyo program with strong opens, clean deliverability, and every flow already live. One number told a quieter story. In ninety days the click to open rate climbed, engagement moved from 39.4 percent to 50.7 percent, revenue rose 78 percent, and sessions fell 32 percent. A better audience, not a bigger one.
PXG × Nosto: 104 Days of Compounding Efficiency
PXG activated a full Nosto personalization stack across every major page type of a mature Shopify storefront. In the 104 days that followed, conversion rate rose nearly 25% and revenue per session nearly 28%, on 20% less seasonal traffic than the window before it.
PXG × Nosto: 104 Days of Compounding Efficiency
PXG activated a full Nosto personalization stack across every major page type of a mature Shopify storefront. In the 104 days that followed, conversion rate rose nearly 25% and revenue per session nearly 28%, on 20% less seasonal traffic than the window before it.
Success Stories
Scarlett Gasque: The Open Was Never the Problem
A Klaviyo program with strong opens, clean deliverability, and every flow already live. One number told a quieter story. In ninety days the click to open rate climbed, engagement moved from 39.4 percent to 50.7 percent, revenue rose 78 percent, and sessions fell 32 percent. A better audience, not a bigger one.
PXG × Nosto: 104 Days of Compounding Efficiency
PXG activated a full Nosto personalization stack across every major page type of a mature Shopify storefront. In the 104 days that followed, conversion rate rose nearly 25% and revenue per session nearly 28%, on 20% less seasonal traffic than the window before it.
