This October I participated in my third 60 mile walk for breast cancer. The event raises awareness and funds for breast cancer research and screening. As the daughter of a survivor, this event and the cause are very close to my heart. The walk is a life-changing experience, full of inspiration and remembrance. Each year I am most impressed by the support I receive from my community.
What does this have to do with Experian Data Quality? Participation in the walk is not only a large financial commitment (with fundraising minimum of $2,300), but also a huge time commitment, for both training and the actual walk itself (requiring travel this year to Atlanta, GA). I am thankful to work for a company that positions itself in part of my support community. Experian Data Quality allowed for me to take the time off needed to travel to and participate in the event showing their dedication to having socially responsible employees. Additionally, 43 percent of donors to my fundraising efforts came from Experian Data Quality employees, including senior management and peers both on and off my team.
It seems that every time I go into a store today, I am offered a loyalty card. From one of my favorite local restaurants to my shoe store VIP program, I feel like I am getting a host of emails and points at every turn. Statistics support my theory: according to a recent Experian Data Quality study, 91 percent of organizations use loyalty programs.
Why did they become so prevalent? Today’s consumer is more empowered than ever before and driving major change within business. In the era of Yelp, digital channels and a 24/7 shopping cycle, organizations have less control.
Determining what type of data quality tools your organization needs depends upon how sophisticated your data quality strategy is. For some companies, a simple data quality approach may be fine, but other organizations may need a very advanced level of data accuracy and data management.
Regardless of your organization’s specific needs, there are a few key universal data quality considerations that are important for any effective approach. Here are six tools that can help with your data quality strategy.
1. Data cleansing: Data cleansing tools are needed when an organization’s data must meet specific domain restrictions, integrity constraints or other business rules. These types of tools provide accurate information for business use. Examples include address verification, email verification, phone validation, etc.
Data is an increasingly important part of organizations today. It can be leveraged for traditional operations and efficiency, but now is also being used to gain a better understanding of the consumer, prompt personalized marketing messages and determine a host of new product innovations.
The increasing use of data is putting a greater spotlight on information and how it is used. But many companies have issues with their data. In fact, a recent Experian Data Quality study found that U.S. companies believe on average a quarter of the information in their databases is inaccurate.