In today's digital-first retail landscape, accurate and comprehensive product data is more critical than ever. Yet many companies struggle to effectively manage their product information across channels. Here are the 5 biggest challenges organizations face when it comes to product data:
1. Poor Data Quality
Inaccurate, incomplete, or inconsistent product data can wreak havoc on the customer experience and a company's bottom line. Common issues include:
- Missing or incorrect product attributes
- Outdated pricing information
- Low-quality or missing product images
- Inconsistent data across channels
As Gartner estimates, poor data quality costs organizations an average of $15 million per year.
2. Slow Time-to-Market
Getting new products listed online quickly is crucial in today's fast-paced retail environment. Yet many companies struggle with manual, time-consuming processes to onboard new products, lengthy approval workflows, difficulty collecting complete data from suppliers, and inability to quickly update product information across channels. These inefficiencies can delay product launches by weeks or even months.
3. Inconsistent Customer Experiences
As consumers interact with brands across multiple touchpoints, maintaining consistent product information is key. However, many organizations face siloed data across different systems and departments, difficulty syncing product updates across channels, and inconsistent product descriptions, pricing, and availability information. This lack of consistency confuses customers and erodes their trust in the brand.
4. Limited Product Visibility Online
With the rise of digital commerce, ensuring products are discoverable across channels is critical. Yet companies often struggle with:
- Inability to optimize product data for search engines and marketplaces
- Limited product listings due to incomplete data
- Difficulty managing data feeds for multiple sales channels
- Low-quality product content that fails to convert browsers to buyers
5. Inefficient Manual Processes
Many organizations still rely on spreadsheets and manual data entry to manage product information. This leads to time wasted on repetitive data entry tasks, human errors and inconsistencies, difficulty scaling product catalogs, and lack of centralized data governance. These manual processes simply can't keep up with the demands of modern omnichannel retail.
Management Is the Starting Point. Orchestration Is What Comes Next.
Product Information Management is still an important foundation. A PIM gives teams a structured place to organize product attributes, content, and digital assets—an essential step beyond spreadsheets and disconnected files.
But a PIM alone does not solve the full commercial problem. It does not continuously connect the systems where product data originates, resolve conflicts across those sources, enrich incomplete records with AI, validate every product against each channel's requirements, execute the data and transactions downstream, or bring channel feedback back into the record.
That is where Product Data Orchestration comes in: management plus orchestration. It takes the trusted product record a PIM helps establish and makes it commercially executable across the teams, partners, systems, and channels that depend on it.
nutrād's Intelligent Product Data Fabric™ connects, harmonizes, executes, and monitors product data as one continuous workflow. It works alongside an existing PIM, ERP, DAM, supplier feed, or spreadsheet—adding the intelligence and commercial execution layer that turns organized product information into channel-ready, transaction-ready, and AI-ready product data.
By combining strong product information management with Product Data Orchestration, companies can address the five headaches at their source: less rework, fewer channel failures, faster launches, more trusted information, and a product data operation that can keep up with modern commerce.