{"id":28532,"date":"2026-04-22T11:28:11","date_gmt":"2026-04-22T17:28:11","guid":{"rendered":"https:\/\/catsy.com\/blog\/?page_id=28532"},"modified":"2026-04-22T11:28:12","modified_gmt":"2026-04-22T17:28:12","slug":"case-study-varaluz-lighting","status":"publish","type":"page","link":"https:\/\/catsy.com\/blog\/case-study-varaluz-lighting\/","title":{"rendered":"Case Study: VARALUZ"},"content":{"rendered":"\t\t
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Case Study  \u00b7  Catsy PIM + DAM  \u00b7  Q2 2025<\/div>\r\n

PIM for Shopify: Varaluz \u2014 From 22-week<\/span> collection launches to 5 weeks \u2014 and 44% fewer returns<\/h1>\r\n
\r\n Varaluz Lighting<\/span>\r\n \u00b7<\/span>\r\n Luxury Decorative Lighting & Home D\u00e9cor<\/span>\r\n \u00b7<\/span>\r\n Las Vegas, NV<\/span>\r\n <\/div>\r\n<\/div>\r\n\r\n\r\n
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Varaluz is a Las Vegas-based luxury decorative lighting brand known for its use of reclaimed metals, hand-forged steel, and recycled glass across a catalog of more than 42,000 SKUs. As the company grew across Shopify, Amazon, Wayfair, and over 1,200 designer showrooms, product data became fragmented across spreadsheets, shared drives, and supplier folders, making product data management increasingly difficult.<\/p>\r\n

After evaluating five platforms, Varaluz selected Catsy PIM + DAM as its single source of truth. As an information management PIM system, Catsy serves as a centralized platform that ensures accurate product data is available across all sales channels. In just 10 weeks, they centralized structured product data and digital assets, automated product data management and syndication, and added data validation so no SKU could go live with incomplete or incorrect data.<\/p>\r\n

The impact was immediate. By reducing manual data entry and automating updates to product descriptions and pricing, they improved data quality and cut launch timelines from 22 weeks to 5. Product-related returns dropped 44 percent, and showroom catalog data errors fell from 41 percent to under 2 percent, all without adding headcount.<\/p>\r\n <\/div>\r\n\r\n \r\n

Client background<\/div>\r\n

A sustainability pioneer with a scaling data challenge<\/h2>\r\n

Founded in 2006 by aerospace engineer Ron Henderson, Varaluz built its reputation by turning waste into art. Hand-forged in the Philippines by skilled artisans, each fixture uses reclaimed steel, recycled glass, or natural fibers, earning recognition from the American Lighting Association, including a HEARTS Award and placement connected to the ALA Lighting Hall of Fame. A 2025 partnership with CIANA Lighting expanded the brand's manufacturing capabilities and custom lighting expertise.<\/p>\r\n

With permanent showrooms at the Dallas Market Center, Market Square in High Point, North Carolina, and the World Market Center in Las Vegas, Varaluz supports a wide network of independent showrooms, online retailers, and trade partners. Despite managing product data, digital assets, and merchandising across multiple sales channels, the entire operation was handled by a team of just five people.<\/p>\r\n

\r\n Shopify<\/span>\r\n Amazon<\/span>\r\n Wayfair<\/span>\r\n 1,200+ Showrooms & Distributors<\/span>\r\n NetSuite ERP<\/span>\r\n <\/div>\r\n

Catalog scope:<\/strong> 42,000 SKUs  |  Team:<\/strong> 5-person digital + merchandising  |  Channels:<\/strong> Ecommerce, marketplace, showroom, trade<\/p>\r\n\r\n \r\n

Problem statement<\/div>\r\n

Beautiful products trapped in ugly data chaos<\/h2>\r\n

Varaluz's product data was scattered across a 2018 Google Drive, supplier Excel files, and studio shot folders, creating fragmented product data with no single source of truth. Finish descriptions, wattage specs, and dimensional data often didn't match across sales channels, and without proper data validation tools or data governance, there was no way to catch data errors before they reached customers or showroom partners.<\/p>\r\n

The impact showed up fast. Showrooms received outdated or watermarked PDFs, which led to lost orders, while return rates climbed to 13.8 percent due to incorrect data in product details. Every launch turned into a long cleanup process, with 18 to 22 weeks spent reconciling product data, fixing data discrepancies, and preparing accurate product data for different sales channels. For a small team, managing product data like this meant spending more time fixing problems than actually moving the business forward.<\/p>\r\n\r\n \r\n

Objectives, approach & success criteria<\/div>\r\n

A phased path to structured, scalable product content<\/h2>\r\n

Varaluz's goals were clear: centralize product data, eliminate manual reconciliation, reduce return rates caused by inaccurate product data, and shorten collection launch timelines. After reviewing five options, they chose Catsy as their PIM solution for its user friendly interface, built-in data validation tools, and ability to improve data quality without adding complexity.<\/p>\r\n

The spreadsheet-style grid made it easy for marketing teams to start managing product data right away, while features like completeness validation and prebuilt templates helped maintain consistent product data across multiple sales channels. It gave them a centralized platform to manage complex product data, reduce data errors, and keep product details accurate from the start.<\/p>\r\n\r\n \r\n

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Phase 1 \u00b7 Weeks 1\u20132<\/div>\r\n

Foundation<\/h4>\r\n

Product data migration from Google Drive, supplier spreadsheets, and ERP systems into a centralized platform. Digital assets consolidated through a hot-folder setup, with NetSuite API integration established to support clean data management across multiple systems.<\/p>\r\n <\/div>\r\n

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Phase 2 \u00b7 Weeks 3\u20138<\/div>\r\n

Catalog rollout<\/h4>\r\n

Product data structured with defined attributes and team training completed. The first 12,000 SKUs were validated and live, with improved data quality and consistent product data across sales channels. A showroom portal launched with automated PDF generation, reducing manual updates and supporting accurate product details.<\/p>\r\n <\/div>\r\n

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Phase 3 \u00b7 Weeks 9\u201310<\/div>\r\n

Full deployment<\/h4>\r\n

The full 42,000-SKU catalog went live, with automation supporting product descriptions and technical specs. Data validation tools and alerts helped maintain data accuracy, reduce data errors, and ensure structured product data across multiple channels.<\/p>\r\n <\/div>\r\n <\/div>\r\n

Success criteria:<\/strong> Reduce collection launch timelines, lower return rates caused by incorrect data, cut manual data entry and repetitive data management work, and support expansion across multiple sales channels without increasing headcount.<\/p>\r\n\r\n \r\n

Solution & implementation: product data management<\/div>\r\n

One golden record from studio to showroom<\/h2>\r\n

Catsy PIM + DAM became the central hub between Varaluz's NetSuite ERP and every outbound channel, with ERP systems continuing to handle transactional data. Through an API-based setup, product data and inventory management updates flowed into the PIM system automatically each day. From there, the product information management system handled structured product data, product descriptions, technical data, digital assets, and product data syndication across multiple sales channels, all from a centralized platform.<\/p>\r\n

The Catsy digital asset management layer gave the team one place for all digital assets, replacing scattered folders and improving data quality. Built-in data validation tools, paired with Slack alerts, ensured no product data could go live with missing or incorrect data. This helped eliminate data errors early and maintain consistent product data across multiple channels, improving overall data accuracy.<\/p>\r\n

For showroom partners, the platform replaced outdated PDFs with a live portal that delivered accurate product details, technical specs, and finish information on demand. This reduced manual updates, cut down on support requests, and ensured accurate product data was always available across different sales channels.<\/p>\r\n

The AI content engine also helped generate product descriptions and technical specifications, allowing the team to focus on reviewing instead of writing everything from scratch. By centralizing product data management, reducing manual data entry, and improving data governance, the team was able to manage complex product data more efficiently while delivering a better customer experience.<\/p>\r\n\r\n \r\n

Results & outcomes<\/div>\r\n

Measurable data quality transformation across every channel<\/h2>\r\n\r\n \r\n
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\r\n \u201377%<\/span>\r\n Collection launch time
(22 weeks \u2192 5 weeks)<\/span>\r\n <\/div>\r\n
\r\n \u201344%<\/span>\r\n Returns from bad data
(13.8% \u2192 7.7%)<\/span>\r\n <\/div>\r\n
\r\n \u201395%<\/span>\r\n Showroom catalog errors
(41% \u2192 <2%)<\/span>\r\n <\/div>\r\n <\/div>\r\n\r\n \r\n