Did you know the business cost of dirty data can be as high as 10-25 percent of a company’s revenue? Not the kind of numbers a CEO or CFO want to see.
As data cleansing specialists, we see the number of problems that dirty, bad data can cause database managers and administrators on a daily basis. While these problems are often due to common habits such as dealing with multiple data sources and human error, it doesn’t excuse the fact that they can cause large headaches, profit loss, and time wasted.
- Understand where the data problems are stemming from. Are they coming from a CRM program, our other customer information system?
- Form a small data governance group to focus on just the task of measuring and tracking data entry, and even set small goals to keep them accountable.
- Once the team is in place, begin the cleansing process through using fuzzy matching and data deduplication tools. Our own data quality tool, DataMatch, is a great, easy to use tool that helps remove duplicates by 90 percent.
- After you’ve gone through the cleansing process, begin creating a single view of the customer. Take the data you currently have gathered from various sources (social media, CRMs, purchasing history) and begin creating a single master profile of your customer’s behavior. This will help your sales and marketing teams immensely.
- Implement a maintenance program that routinely checks and corrects data. Combining the resources of your data governance group along with your data quality tools and you will set up your company for success!
Being proactive is one of the most important things a company can do to stay ahead of the data quality curve. Yes, you can implement a program to take care of issues that exist now, but it’s also about looking ahead and seeing where future quality issues can occur. Managing and maintaining a data quality program doesn’t have to be hard.
Talk to our data cleansing specialists about getting a program started at your company. Need to start getting rid of your dirty data today? Download a free trial of DataMatch.