Streamline your product onboarding and keep your catalog aligned with Lowe’s strict retail requirements. Sync enriched product data and images directly to Lowe’s systems, reducing manual work and accelerating time-to-shelf across one of the largest home improvement retailers.

Lowe’s requires detailed and structured product content through its Item Data Management systems and vendor portals. Sales Layer centralizes your product information and maps it directly to Lowe’s required attributes, reducing back-and-forth corrections and speeding up approvals.

From dimensions and specifications to rich media and descriptions, Lowe’s enforces strict content standards. Sales Layer validates your data before submission, helping you avoid incomplete listings and ensuring your products are ready for publication.

Whether you sell through Lowe’s marketplace powered by Mirakl or as a direct vendor, each channel requires different product data structures and validation rules. Sales Layer standardizes your product data and prepares it for each flow, reducing manual adjustments and speeding up onboarding.

Sales Layer is a cloud-native PIM that centralizes product data and prepares it for distribution across retail channels like Lowe’s, ensuring structured, validated, and consistent content delivery.
Deliver accurate, compliant product data to Lowe’s faster and at scale.

Yes. Sales Layer prepares and structures product data to match Mirakl’s requirements, making it easier to onboard and maintain listings on Lowe’s marketplace.
Yes. Lowe’s uses its own category structure and required attributes. Sales Layer helps map your internal data to these specifications.
Yes. Sales Layer centralizes digital assets and ensures they meet Lowe’s format and quality guidelines before submission.
Built-in validation rules check for missing or incorrect data before sending it to Lowe’s, minimizing rejections and revisions.
Initial setup may involve configuration, but once implemented, business users can manage product data and updates without technical complexity.