4 Steps to Clean Data in Your CRM

There’s an old saying about data and data quality: Garbage in and garbage out. It still holds true, as long as there have been databases. Data quality is essential. Nothing can undermine or torpedo user adoption in a new CRM than having bad data.

Bad data costs you money. It could be upwards of $100 per duplicate record, for example, which is quite serious.

It’s time to clean up your CRM instance and keep it that way. Here’s how.

1. Analyze Your Data

Before you can start cleaning your data, preventing bad data, and enhancing your data, you need to know the overall state of your data. In other words, how dirty is your database? The first step is to analyze and benchmark data quality.

Analyzing the state of your database requires you to ask yourself the following questions:

How bad is our duplicate situation?

Where are the duplicates coming from?

How does your data quality stand up against other salesforce.com customers?

Establishing a data quality dashboard will tell you not only how many duplicate Leads you have, but where they are coming from, when they were created, and other key, actionable information.

2. Clean Your Data

Bad data comes in many shapes and sizes, and therefore, cleaning it does too. Here’s a look at a few of those, including data standardization, duplicate data, and completing missing data.

Data Standardization

A lot of bad data comes down to human error. If an organization doesn’t have any sort of standards or policies to articulate how the data is entered into their CRM, different iterations of your data will exist and be committed to your CRM. The solution is data standardization, also known as normalization, which creates an enforced, organized and consistent environment for entering data into your CRM.

Duplicate Data Cleanse

Duplicate removal is not the only consideration when looking for a fresh start, but is arguably the most critical. The solution is to clean your existing CRM and then stop duplicate data before it enters your system ever again.

Complete Missing Data

CRMs include is a vast number of Data Markers.  These markers are a literal road map to filling in missing data.  For example, if 100% of the emails for a particular company have the email format of [email protected], then you can probably fill in missing emails for other contacts with confidence.  If you have the email domains for contacts, but the account record is lacking a website, that can be filled in too.

Data Validation

Data validation ensures that your CRM operates on clean, correct and useful data. It’s important to routinely check your data validity via set validation rules, constraints and routines identified from the start. This makes sure there is correct and meaningful data in your system.

3. Protect Your Data

Without a protection strategy, your data will continually decay. Not only do phone numbers, emails and titles change, but as your employees are entering data into your CRM, they are creating duplicates and entering data inconsistently.

Protecting your data includes:

•  Ongoing duplicate prevention

•  Ongoing standardization

•  Continuing to Complete Missing Data and Validate Data

4. Enhance Your Data

Without enhancing your existing data, you limit your data potential. Additional information on the record will help to complete the contact’s information, giving you a 360-degree view of the contact. Enhancing your data ensures accuracy by verifying the email addresses and saving your salespeople time from sending bad emails.

When sales teams, customer success teams and other employees do not have access to a complete record, they waste time looking in external systems and on the internet in search of that contact information. According to SiriusDecisions, this results in over 30% of an employee’s time being wasted on contact research.

Follow these steps to achieve total data quality. because data quality is going to put you on the right track to generate revenue.