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The Top 5 lessons in Data Management

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The Top 5 lessons in Data Management, You Can’t Afford to Miss.

Corrupting your company’s data can be costly.  Data management of  large (millions of records) and small data projects is important. elevenX has compiled what we consider to be the top 5 lessons learned over the years.  Hopefully, this list will help you avoid costly mistakes. 

1.      Clean and standardize your data BEFORE importing or adding more data.

Has anyone ever said to you, “Just import it, and we’ll clean it later”? Don’t fall for it. You may never get to that data cleaning project and you don’t want to corrupt the good with the bad. It is the opportunity to make the necessary changes early before it gets into the larger data set.

2.      Clean data is a journey, not a destination

Your data will never be perfect.  Things change and records become out-of-date.  It’s O.K. Make data cleansing a continual process and make data integrity part of someone’s job (and everyone’s job).  If nobody is officially responsible, it won’t happen. Implement P&P so that users can validate and correct records any time they use a system.

3.      Let technology help you. 

Your system has a  duplicate detection functionality to prevent duplicate records from being entered. Use data validation to ensure that entries are formatted properly (e.g. proper case for name fields).  Provide option sets rather than open text fields when you know that the possibilities for field data are limited to only a few possibilities.

4.      Set realistic expectations with other departments

Be transparent.  Openly address and discuss data limitations. Have you ever heard, “The data is no good, so I won’t use the system”?  One bad record can become visible and causes embarrassment (and it usually winds up on the boss’ desk).  Talk about the true risk of bad records (it’s not usually that bad), and do not manage by exception (but do address every issue brought to your attention) as they can put a spotlight on a larger issue.

5.   Use the data you have to market. Have a plan to continually make it better.

If you have data accurate to the regional level, market by region.  As you obtain state info, get more granular.  If you can only identify prospects (never bought) from customers, market accordingly.  As you add stages in the customer journey, get more granular to make messaging more relevant.

Final Thoughts on Data Management and Marketing

Having the cleanest data set possible allows you to truly personalize messaging to your customers and prospects.  When people feel that you know and understand them (what happens when you send truly relevant messages), they buy. Think of it this way, your best friend expects you to know his wife and kids’ names.  I’m not suggesting that you need to record your customers’ family’s’ names, but you do need to record and accurately maintain the data that is important to you for your customer relationships.

If you have questions, we are here to help.

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