Making the Case For Using Data Quality Tools Within Retail

By now, most people have become very familiar with the term big data. Whether that applies to culling data from social media or its use in business, big data is certainly here to stay. In business, it is becoming a vital part of running a profitable operation. From those companies servicing a large amount of customers to those dealing with complex supply chains, the case to using big data and managing it effectively becomes very strong.

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The case for using big data within retail companies is critical. Even more so, the ability to manage it effectively with data quality tools is even more important. The ability to use it to drive sales and optimize processes provides a value unmatched by other types of services. In retail, using big data to drive customer loyalty and provide a benefit for customers is a good enough reason for many retailers to implement a data quality program.

Using big data on the retail front has also helped many retailers work through much of the impact of the recent recession, by being able to use the information gathered from data in order to maximize efficiency in many areas, from the supply chain to marketing efforts.

Recently, Data Ladder had the opportunity to work with denim retailer Buckle on their data quality needs. The company was refocusing their initiatives on personalized customer service, and had taken the time to gather customer profile data at the store level. Their main concern was removing duplicates that had been loaded into their current systems.

While many believe that only larger retailers can benefit from the use of data quality tools, smaller retailers can also greatly benefit, and need to realize that embracing these new technologies can help them as they strategically grow their business.

Learn more about how Buckle used Data Ladder’s data quality tools in this case study.