Why data quality matters to retailers

Marketers in the retail industry are working every day to better understand their clientele. As such, analytics strategies have become popular within retail. Companies want to uncover who their customers are, where they come from and what motivates them to spend their money.

However, a lack of quality data is getting in the way for many executives. According to a recent Experian QAS study, retailers believe that on average, over a quarter of their information is inaccurate.

Flora Delaney, a retail business executive with over 20 years of multichannel, cross-functional experience, recently spoke about this need on her personal website. “Years ago, I ran a data warehouse for a multi-brand grocery chain on the East Coast,” Delaney said. “Within weeks, I learned the truth about most retail data warehouses — plenty of data, but very little that was reliable.”

This lack of reliability is hurting analysis and targeted marketing efforts. But, what does it mean for data to be reliable? As Delaney sees it, there are five key elements.


On a basic level, retail companies need to know what they seek to measure and make sure that the data they’re collecting is answering the right questions. Even if information is accurate, it’s nothing if not relevant.


It is important for information to be complete across each element and each consumer. Incomplete data may show inaccuracies or bias in analysis that was not intended.


These days, retail companies are looking to access information in real time. They want to make decisions about the current transaction or offering based on small amounts of data that was just collected. After all, if your knowledge is six months old, what good is it today?


Without accurate information, companies make poor decisions that could present catastrophic circumstances if not corrected.


When retail businesses gather diverse banks of information, spanning multiple demographics or time periods, it’s important to use the same methods for gathering and purifying data each time. Inconsistencies might lead to erroneous conclusions, leading marketers to waste their time and money investing in misinformation.

It is important for marketers to take each of these areas into account before relying on analytics and data-drive intelligence. Without reliable information, marketers are left unable to keep up in today’s cross-channel environment.

To learn more about developing a data quality strategy, download ‘Unlock the Power of Data’.