A blue-chip food manufacturer with thousands of SKUs implemented a new Product Information Management (PIM) platform. The PIM integrated data from several internal sources, including their Master Data Management (MDM) system, R&D/Nutrition database, and Digital Asset Management (DAM) platform. During this process it became clear that the data and associated digital assets were incomplete, inaccurate, dated and not helping them make key business decisions.
The missing data was primarily B2C content, for product “eachs”, often used to drive sales at eRetailers, provide a competitive edge on the digital shelf, and provide shoppers with greater product transparency. The challenge was understanding the full extent of the problem, how to identify the root cause, and ultimately how to fix it.
The manufacturer knew the value of comprehensive B2C product data but was challenged by resources and time to properly evaluate the holes. At the same time, they were amidst constant acquisition of small to medium brands. The content from these brands was inconsistent, but had already been entered into the PIM.
Their hope was to secure some sort of data cleanse at the top of the funnel. And, they had just been penalized with a hefty fine by a major retailer for incomplete and inaccurate data.
ItemMaster performed a Data Quality Assessment (DQA), analyzing an extract of the client’s product information against a number of use cases. This included a scorecard for eCommerce readiness, image quality, on-package attributes, and specific requirements from key retailers like Walmart.com and Amazon.
The assessment quantified the current state of the data. Through interactive dashboards which drill into the details, ItemMaster created a level of visibility down to the item and field level, allowing the client’s analysts and product specialists to quickly pinpoint issues. An executive summary was prepared for the manufacturer’s internal stakeholders for enhanced visibility and to ensure other key stakeholders were aware of the problem.
The DQA objectively confirmed many of the data issues the client team had suspected. It also provided specific areas to target for improvement. For example:
- 67% of items were missing the required images for eRetailers.
- 25% of items had suboptimal feature bullets.
- 5% of items were missing consumer-ready product titles.
The DQA results set a benchmark for the manufacturer as they updated their product information. ItemMaster applied its content creation and enrichment capabilities to help the client fill in critical gaps in data and imagery. Working with ItemMaster from DQA through remediation allowed the manufacturer to quickly ensure their content was 100% complete and accurate for the digital shelf.
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