Case Study  ·  Catsy PIM + DAM  ·  Q2 2025

PIM for Shopify: Varaluz — From 22-week collection launches to 5 weeks — and 44% fewer returns

Varaluz Lighting · Luxury Decorative Lighting & Home Décor · Las Vegas, NV

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.

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.

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.

Client background

A sustainability pioneer with a scaling data challenge

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.

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.

Shopify Amazon Wayfair 1,200+ Showrooms & Distributors NetSuite ERP

Catalog scope: 42,000 SKUs  |  Team: 5-person digital + merchandising  |  Channels: Ecommerce, marketplace, showroom, trade

Problem statement

Beautiful products trapped in ugly data chaos

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.

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.

Objectives, approach & success criteria

A phased path to structured, scalable product content

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.

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.

Phase 1 · Weeks 1–2

Foundation

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.

Phase 2 · Weeks 3–8

Catalog rollout

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.

Phase 3 · Weeks 9–10

Full deployment

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.

Success criteria: 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.

Solution & implementation: product data management

One golden record from studio to showroom

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.

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.

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.

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.

Results & outcomes

Measurable data quality transformation across every channel

–77% Collection launch time
(22 weeks → 5 weeks)
–44% Returns from bad data
(13.8% → 7.7%)
–95% Showroom catalog errors
(41% → <2%)
  • Collection launch cycle reduced from 22 weeks to 5 weeks, a 77 percent improvement in time to market
  • Product-related return rate dropped from 13.8 percent to 7.7 percent, a 44 percent reduction that directly improved margin
  • Showroom catalog error rate dropped from 41 percent to under 2 percent, restoring confidence across sales channels
  • Manual data work reduced from 70 percent of merch team time to 11 percent, allowing the team to focus on higher-value work
  • Three new marketplaces added across multiple sales channels without increasing team size
  • Structured data governance established across ecommerce and showroom channels, improving data quality and consistency
  • Full deployment completed in 10 weeks, on schedule and within scope
"Catsy didn't just organize our data; it finally let our creative team be creative again instead of chasing dimensions in Google Drive at 11 p.m."
— Kevin Plumb, CEO, Varaluz
Key insights & best practices

Five lessons for multi-channel decorative brands

1

Your return rate is your data quality score. For brands dealing with complex product data like dimensions, wattage, finishes, and compatibility, small gaps in product details can quickly turn into returns. Before chasing conversion gains, look at your product data quality. Improving data accuracy and maintaining consistent product data across sales channels often delivers a bigger impact than paid acquisition.

2

Showrooms are a real sales channel. Varaluz treats its showroom network like any other of its multiple sales channels, not as an afterthought. When partners receive outdated files or incorrect data, it creates data discrepancies and lost sales. A product information management system that supports showrooms alongside ecommerce ensures accurate product data and a better experience for every partner.

3

Data completeness protects revenue. One of the biggest wins came from using data validation tools to block incomplete product data from going live. Instead of fixing data errors later, the team prevented them upfront. That shift improved data quality, reduced incorrect data across channels, and made product data management far more reliable.

4

Small teams can manage complex product catalogs. Varaluz manages complex product catalogs across multiple channels with a lean team because their PIM system handles the heavy lifting. Centralized data management, automation, and structured product data make it possible to manage complex product data without relying on constant manual data entry.

5

ERP and PIM systems work better together. ERP systems like NetSuite handle transactions, while a PIM solution manages product data, digital assets, and distribution. Keeping those roles clear helps eliminate data silos, improves data accuracy, and allows product data to flow cleanly across multiple platforms and sales channels.

Conclusion

From data chaos to a scalable, consistent product data foundation

Varaluz came into the Catsy implementation with strong products and a well-established brand, but a product data setup that could not keep up with the size of its catalog or the pace of its growth. In just 10 weeks, that shifted. Today, they operate with centralized product data, a single validated product record, and a product information management system that supports every sales channel at once. Collection launches now move on a five-week cycle, with improved data quality, stronger data accuracy, and far less manual data entry slowing the team down.

The design has always stood out. Now the product data does too.

Ready to build your own scalable product content foundation?

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Appendix

Before & after: manual data entry workflow comparison

DimensionBefore CatsyAfter Catsy
Product data storageScattered across Google Drive, supplier Excel files, and studio foldersSingle validated record in Catsy PIM, API-synced from NetSuite
Collection launch cycle18–22 weeks due to manual data reconciliation5 weeks — a 77% reduction
Product return rate13.8% driven by inaccurate PDPs7.7% — 44% fewer returns
Showroom documentationOutdated or watermarked PDFs distributed irregularlyLive branded portal, always current, errors <2%
Merch team time on data70% of team time on manual coordination11% — creative team focused on design and content
Channel expansionNew marketplaces impractical without headcount3 new marketplaces added at same team size
Data completeness enforcementNone — incomplete SKUs reached live channelsPre-launch Slack completeness alerts; no incomplete SKU can publish