Inaccurate, incomplete data is notorious for triggering costly business disruptions – in fact, dirty data costs companies millions of dollars every year.
If you aren’t already familiar with the term, “dirty data” refers to information that is erroneous, invalid, duplicate or untimely. It’s also information that can include typographical or numerical errors, inaccurate contact information, misspellings or other factors.
The cost of dirty data to today’s enterprises is astonishing. According to recent research, approximately 12 percent of a company’s yearly income is wasted due to bad data. And a Data Warehousing Institute report recently revealed that data quality problems cost U.S. businesses over $600 billion each year.
In addition to lost revenue, there are numerous consequences companies can experience as a result of bad data, such as:
- Decreased productivity resulting from time wasted following up on the wrong leads
- Diminished trustworthiness which can damage company reputation
- Costly fines related to issues surrounding compliance
- Difficulty in reaching prospects due to incorrect contact information
Also, dirty data, like duplicates, can result in inaccurate lead scores. Score sharing between duplicate leads means neither record gets a high enough score to move further down the sales pipeline.
Identify and Clean Up Your Dirty Data
Today’s businesses must understand what causes dirty data, and be able to take proactive steps to fix and update the causes. Below, we highlight five tips that can help your data shine like new:
1. Take Time to Conduct an In-Depth Analysis
Regardless of your company size or type, you can’t begin cleaning up your dirty data until you thoroughly analyze the quality of your data. Take time to determine how bad the data is, where the bad data is coming from, and its quality.
Once you determine the answers, create a dashboard that illustrates how many leads you have, where they come from, when they were added to the system, as well as any other pertinent information. You can use this dashboard as a benchmark for future leads.
2. Roll Up Your Sleeves
When you clean up your CRM data, aim to focus on several tasks, including completing missing data, removing duplicates and running data validation, a routine check of your data against set validation rules that ensures your CRM has correct and useful data.
While eliminating duplicate data is pretty self-explanatory, completing missing data requires a little extra elbow grease. Some companies opt to utilize client websites, LinkedIn or other online directories to help fill in any blanks.
Finally, regarding data validation: if an email address is bad, get rid of it. Having an incorrect contact in your CRM prevents your team members from sending bad emails or wasting time making calls to the wrong leads.
3. Do a Data Double-Check
There’s a reason automation was created, so use it when you can. Today, many third-party sources can serve as referential data points for spotting variances in your data and locating invalid records. Automation technology can also update the erroneous records, helping to improve your company’s lead conversion strategy.
4. A stitch in time …
The most straightforward approach to preventing bad data is to make sure it never initially enters your CRM.
For example, by creating better CRM templates, you can ensure all the data you want to gather from prospective customers is required. You should also segment and categorize the information in the CRM based on the contact’s stage in the sales cycle.
5. Enforce a Set of Guidelines
While you should enforce regular data cleaning throughout the calendar year, it’s crucial to require – at the very minimum – a quarterly cleanse into your company’s routine to make sure you have the most current data.
Develop and enforce a set of clear guidelines that institutes a consistent process for entering data into your company’s CRM. Document these processes in a format conducive to repetition like a project management tool with workflows (click here for recommendations). With this strategy, you minimize the chances of having to do a significant clean-up of data as the information already meets your organization’s standards.
Last But Not Least
Finally, never keep the contact information of old prospects that have unsubscribed. You should remove them from your CRM immediately – and entirely – right after they unsubscribe.
There’s no denying that dirty data can be a headache; however, it can also be an eye-opening experience to start becoming more proactive.
Putting clean, valuable data into action at your company is worth the time it takes to achieve it and can help launch your organization to the next level, generating quality leads, and helping you to get targeted messaging to the right people.
Lisa C. Dunn is a writer for TechnologyAdvice.com and a freelance writer, copywriter and ghostwriter who develops high-quality content for businesses and non-profit organizations. For over 20 years, she has worked with numerous PR and digital marketing agencies, and her work has been featured in well-known publications including Forbes, VentureBeat, Mashable, Huffington Post, Wired, B2C, USA Today, among others.