Keep Dirty Data from Hurting your Data Analytics

Dirty data is data that, over time, becomes outdated, incomplete, or just flat out wrong. Over 600B dollars are spent annually trying to clean up dirty data (TechTarget), and for good reason.  As your big data piles up, it not only gets more difficult to clean, but it also becomes more unreliable, hurting your Salesforce CRM system’s capabilities in numerous ways. Here’s a couple potential issues:

  • Bounce emails. Your sales can no longer reach these people. How can you be certain those emails you are sending are going through to the right email.
  • Messed up reports and Dashboards. Some features you utilize will be limited based on bad data even for your day-to-day operations will be affected.
  • Trusting your variable tags. Which contact to pull from because you might have duplicate contacts, and format of fields are different from one another or even outdated. 
  • Going into the right workflows. How do you know the appropriate prospects are getting put into the right workflows and nurture programs.

Where is Your Dirty Data Hiding?

Dirty data doesn’t only lead to poor analytics but can wreak havoc on different features within your Salesforce (CRM). Let’s see what some of the potential issues that cause dirty data.

Sometimes, the problem is staring right in front of us, user error. Forms are a great way for businesses to increase your database’s accuracy. Forms provide a great way to segment and develop relationships with your customers.

From users to the systems, when we tend to merge data across multiple sets, this can also cause dirty data. Use a unique identifier to prevent duplicate entries or updating the wrong records. This is usually the suspect when you businesses are trying to merge multiple databases at once, or when old technology can’t keep up with the current database demands.

How to Dispose of the Bad and Keep the Good?

Yes, cleaning your data sounds tedious but it is well worth the time. Of course, going one-by-one would take forever, so by using system algorithms will set up a more automated process of cleansing your data. Although it may not catch everything, it will drastically increase the reliability and availability in the type of analytics you can use within your CRM system.

Once your data is clean, the trick is keeping it that way. Here are a couple of helpful tips to maintain that clean database:

  1. Data Scrubbing. This allows you a way to filter out and automate that bad data from ever reaching your CRM system by scrubbing it out.
  2. Building Relationships. Remember you are talking to real people, when you maintain and form a real relationship with your customers, they are less likely to provide false or blank information into your Salesforce.
  3. Data champion. This allows you to not only ensure your data is clean but also to allow your company the ability to know have one point of contact into your Salesforce(CRM) to enable clean and smooth implementations/ health checks.

Identifying and preventing the dirty data from your Salesforce (CRM) can go a long way for your business to see big rewards from big data analytics. Who would have guessed some misfilled forms, a day where you forgot to update a contact, or a simple import of a list could be so costly?