High-quality data is the absolute greatest driver of revenue for a modern business. Good data can lead to a drastic boost in lead conversion rates, account-based success, and closed won deals. On the other hand, poor data quality can drastically reduce the ROI of a company’s CRM and marketing automation investment.

So what exactly is ‘bad’ data?

We’ve drafted up a list of seven common data quality issues so you can have a better understanding of what you shouldn’t do when working in a data-driven environment.

7 Common Data Quality Issues

1) Poor Organization

If you’re not able to easily search through your data, you’ll find that it becomes significantly more difficult to make use of. Through different organizational methods and procedures, there are dozens of ways that data can be represented.

2) Too Much Data

40% of people reported that there’s often too much data to properly work off of inside a database. While it might seem like “too much data” can never be a bad thing, more often than not, a good portion of the data simply isn’t usable, which is going to mean that you’re spending more time digging through the bad so they can get to the good. 

3) Inconsistent Data

When dealing with multiple data sources, inconsistency is a big indicator that there’s a data quality problem. In many circumstances, the same records might exist multiple times in a database. Duplicate data is one of the biggest problems that exist for data-driven businesses and can bring down revenue faster than any other data issue.

4) Poor Data Security

20% of people say that they would never consider doing business again with a company that failed to handle their data in a professional and secure manner. When working with customer data, there must always be precautions in place to make sure that it can’t be used for theft, fraud and spam, which will almost guarantee the loss of a future renewal.

5) Poorly Defined Data 

Oftentimes data is poorly defined, which causes great confusion around the proper methodology for management. For example, data that’s sectioned into the wrong category, like a company account being filed as a single person’s contact, is going to really mess things up in your database and make the whole thing more difficult to understand and sort through.

6) Incorrect Data

Data decays at a rate of 2.2% per month. Therefore, it’s almost definitely going to be the case that some of your data is outdated. It’s a massive issue, as anywhere from 10 to 25% of existing data in your system has errors within it.

7) Poor Data Recovery 

People generally spend 30% of their time with data just looking for the data they need. Even worse- in 40% of searches, people never even find the data that they were looking for in the first place.

Throughout all of these data issues is the common theme  that in order to have your data in the best condition possible, proper management is key. Likewise, the best way to keep your data in order is to implement a proactive data solution that can take care of all of the listed common data quality issues.

Luckily, RingLead has all the tools that you’ll need in order to take care of all of these data quality problems. RingLead is the only full stack data solution that can enrich existing/incoming data while getting rid of the duplicate data in a database.

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