PIM ROI as a Business Critical Solution: 9 Ways Product Data Quality Impacts Internal Business Practices

Keeping a whole catalog of product data accurate is a tall order for any brand. Accurate product data is comprehensive: it includes essential information like product names and categories plus enriched data like product images and video. Accurate product data is also consistent, reliable, consumable for customers, easy to navigate for internal teams, and always up-to-date.

While there's no doubt that accurate product data is an asset for manufacturers, managing product data is a big to-do. Brands that use spreadsheets and other manual processes (or a jigsaw puzzle of software) spend far more time on what ends up being much lower-quality of product data.

Businesses with product data that is accurate and accessible give time back to all their internal teams. Whole processes work with fewer steps and produce better results. This compounds into more opportunities for teams to be productive elsewhere and to be successful in everything they do.

These are 9 specific, relatable ways product data quality impacts internal business practices.

1. Product Development

Product development is where product information is first imagined. A brand invests time and talent into expanding products and inventing whole new commodities. As design unfolds in creative discussions and later in CAD, the first product specifications are born.

When product specifications are captured into a shared repository at the same time they're developed, that streamlines multi-departmental processes later. It saves time for product development teams who otherwise have to go back into CAD to dig up the product specs that the marketing team asks for.

After product development is done for new SKUs, it's also that complete and accurate product data that determines realistic product launch timelines.

Product development is where the product cycle first starts, but it doesn't operate in a vacuum.

Product development teams benefit from a single repository for existing product data. New SKUs developed to fit into product families or updated versions of existing products require research into the product data catalog for the foundation the development team needs.

2. Marketing

Perhaps the clearest connection between product data quality and internal business practices is found in marketing. Once a marketing team starts preparing for a product launch, they find themselves rushing around to collect all the product data. Product development contributes to what specs they have, and the marketing team develops then enriched product data like product descriptions, images, and video.

Unlocking teamwork with marketing comes down to storing product data in a "living" data repository with a design flexible enough to fit the attributes each brand—and department—requires. The marketing team will need different product attribute fields than the product development team. The marketing team will also need to quickly sort and filter products to build funnels that cross-sell, upsell, and speak to consumers in memorable ways.

Internal business practices seem to drag most for marketing teams when a product launch is underway. Without accurate product data, the marketing team faces months (in most cases) of product information collection and development before SKUs are ready for market.

3. Web Design

The web design department needs access to similar product data that the marketing team does. After the marketing team does the legwork of developing enriched product data, the web design team is able to build off that to add what additional information they need, including SEO fields and metadata.

Have you noticed how much bigger the single product data repository becomes over the product cycle?

Web design's work is simplified with accurate product data. Product information is available for faster work and data is easily searchable and reliable for heavy manual tasks like adding product categories and tags for searchability. Consistent branding is easier with complete product data.

4. Sales

Sales workflows without access to accurate product data result in frustration for salespeople and customers alike.

Product data quality in the next generation of digital commerce—what we see and live today—requires as much product information as possible. Consumers breeze through browser tabs in search of the exact product they desire. Product data has to be as informative as it is emotive.

Product pages are more engaging than ever, but there will still be work to do by the sales team. Depending on the brand, sales teams might also be the points of contact for business partners.

Accurate product data is fundamental for salespeople to quickly search and access product information. It's access to the right data at the right time that will allow sales teams to cross-sell, upsell, and ultimately delight the end consumer.

5. Logistics

Logistics operations for brand manufacturers include processes to prioritize shipments. Whether through VIP sales partnerships, customer membership programs, or other shipments with required expedited shipping, one of the tasks with the greatest potential for error is prioritizing what shipments need to be filled first.

Logistics departments rely on ERP software to check the status of orders, however, the ERP is not the end-all for product information.

Instead, next-gen product information management (PIM) software acts as the center of a software ecosystem—between the ERP for logistics, CAD for product development, CRM for customer service, and CMS for web development—to ensure that no department operates in a silo.

6. Customer Service

Once a sale is made, customer inquiries are one of the most critical touchpoints with buyers. When customers call or write for product assistance, internal business practices for the customer service team need to provide the highest-quality product data to answer queries quickly and with the best information.

Just like for sales teams, the best product data for customer service will include emotive factors that resonate with customers contacting the brand, like "intended environments" for products, renderings, images, videos, related products, and more. If any of these attributes are missing from the customer service team's quiver, the brand loses credibility (and possibly a customer).

Imagine the perfect world where customer service teams have instant, sortable access to the most complete product data with all these attributes and more. Interactions of that caliber lead to the best customer reviews and, over time, the best brand reputation.

7. IT

The IT department bears the brunt of product data quality. Internal business processes for IT teams are, therefore, the precursor to process improvements for everyone else.

Dirty product data bogs the IT team down with endless clean-up. Especially for brands whose product catalog is sold at multiple end-points (through multiple e-commerce channels or through multiple sales partners), the opportunity for inconsistency is endless.

IT teams can easily control access to product data (by product, by attribute, by the user, or by any requirement) while managing product data quality for the next generation of digital commerce. With the next-gen PIM in place (which the IT team can easily implement), internal data management processes are reduced to a fraction of the time that manual processes require.

8. Decision Making

It goes without saying that decision-making by internal teams and leadership is faster with accurate product data. Leadership teams are able to track key next-gen commerce KPIs based on reliable product information. This removes any doubt about the performance of a given ad, product, or page.

Even the quality of product data is a new KPI in the next-gen PIM offering built-in data quality scores for every SKU.

9. People Get Along Better

Accurate product data improves overall internal business practices as well as team performance. These are two enormous weights lifted off of employees' shoulders, allowing more room for greater efficiency plus better rapport.

The human element of accurate product data is rarely discussed, despite the reality that manual product data management is stressful for everyone involved. Every department has its own spreadsheet floating around. Getting the needed details from other departments creates tension on both ends. Inaccuracies result in finger-pointing, and the disappointment of the bottom-line impact of dirty data at the end of the day diminishes the value of everyone's work.

One of the greatest advantages of implementing the next-gen PIM is that it simultaneously improves all internal processes and unlocks collaboration. Departments work better together, internal business practices are completed in less time and with fewer steps, and brands are better situated to roll with whatever the market punches.