
Automated data cleaning for Heinen & Hopman.
Sector
HVAC+R systems
Products
125,000,000+
Employees
28,000+
Managing high-quality product data is crucial for operational efficiency and customer experience. Heinen & Hopman, a global leader in HVAC+R systems, faced significant challenges in centralizing and standardizing its extensive product database. By leveraging Powerimprove.ai, the company streamlined its data management process, improving accuracy and efficiency.
Background
Founded in 1965, Heinen & Hopman has grown into an international market leader in Heating, Ventilation, Air Conditioning, and Refrigeration (HVAC+R) systems. With offices in sixteen countries, the company is committed to innovation and excellence, continuously expanding its global service network to deliver top-tier climate control solutions.
The challenge.
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Unifying a large product database
Heinen & Hopman needed to consolidate its product data into a single Product Information Management (PIM) system. With approximately 28,000 products from multiple suppliers and manufacturers, ensuring data consistency was a complex challenge.
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Lack of standardized product identifiers
Many products were missing unique article numbers, and multiple identification systems were in use, including material codes, supplier numbers, manufacturer codes, and manually entered GTINs—some of which contained errors.
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International expansion & data quality needs
With global ambitions, Heinen & Hopman aimed to implement GTIN article numbers and explore data integration with 2BA, a product data pool. However, the current data quality and structure required significant improvement before integration could be successful.
Our solution.
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Automated product matching
Squadra Machine Learning Company conducted a Proof of Concept (POC) to test the feasibility of automating product matching using Powerimprove.ai. The solution compared the master article file with representative supplier and manufacturer data.
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Intelligent matching algorithms
The Powerimprove.ai software utilized machine learning techniques to match products based on unique identifiers (EAN/GTIN, manufacturer, or supplier codes). When those were unavailable, it matched based on product names, descriptions, or translated data.
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Seamless integration with existing systems
Initially implemented via Excel for ease of use, the solution is also accessible via a REST API, allowing future integration with Heinen & Hopman’s PIM system.
The result
PowerSuite has empowered Heinen & Hopman to...
Accelerate data cleaning
Automated data validation and matching significantly reduced manual effort, saving time and resources.
Improve data accuracy
Enhanced data consistency enabled better internal processes and integration with external platforms like 2BA.
Optimize customer experiences
More accurate and structured product information improved usability for both internal teams and customers.