Product Data

Even disciplined distributor environments experience breakdowns when ERP truth fails to propagate consistently across ecommerce, middleware, and order systems. ERP mismatch leads to manual intervention, pricing exposure, and fragile order flow. This post explains the technical patterns behind truth drift and how to reduce it.

Manufacturers already manage SLAs for shipping, quality, and service. In 2026, the bigger risk is information. Product Truth SLAs define how quickly manufacturers can detect changes, approve new truth, and publish it consistently across every channel that represents their brand.

Messy, inconsistent product data slows digital growth. This article shows how AI-driven taxonomy normalization helps manufacturers clean, structure, and monetize their data for scalable digital success.

Learn how Layer One helps clients enhance product data quality, from taxonomy and brand pages to ERP integration, improving eCommerce performance and customer experience.

Manual product data imports waste time and create errors. This guide shows how to auto-sync AD, Syndigo, 1WorldSync, and DDS feeds into PIMs like inriver, with a real client example and config snippets you can adapt.

Product data quality determines how easily customers find, understand, and buy from you. Learn how to improve accuracy, completeness, and findability to boost B2B eCommerce performance.

Poor product data holds back B2B eCommerce. This article explains the differences between MDM and PIM, their roles in product data quality, and how manufacturers and distributors should decide between them.

This technical guide explains how manufacturers implement Product Truth SLAs across ERP, PIM, CPQ, distributor portals, and EDI feeds using AI-assisted event detection, propagation measurement, and channel validation.