3 CRM Data Cleansing Best Practices that Make Your CRM Data More Profitable
Here’s a pair of related facts that make CRM data cleansing look like a great idea:
- Your CRM data is your most valuable data
- About 30% of your CRM data goes bad each year. In fact, 10-25% of CRM databases have errors caused by customer data decay.
CRM data errors cause inefficiency in your business, and eat up more revenue and profit margin than any other data error.
That’s bad. So, what can you do about it?
Well, there’s a very straightforward solution: CRM data cleansing.
Data cleansing is the process of finding and correcting errors and inconsistencies in your databases. The bad data is either corrected or deleted to make the data more accurate and usable. Data cleansing is also called “data cleaning” and “data scrubbing.”
CRM data cleansing is simply a matter of using data cleaning techniques on your CRM data.
CRM database cleansing removes unusable leads and completes partial contact entries. So, your teams waste less time and effort reaching out to people who don’t exist and looking up contact information on their own.
CRM data cleansing also reduces issues that cause bad customer experiences, like shipping errors. That means more customer retention and higher customer lifetime value.
And, data cleansing is super affordable. It might be the most cost-efficient way to increase revenue.
All right, that’s enough chirping about CRM data cleansing. These are the database cleansing best practices that will get the most value from your CRM data.
CRM Data Cleansing Best Practices
There are a handful of steps in the CRM database cleansing process. Implementing these best practices will help you optimize your data cleansing process and keep your CRM database in tip-top shape.
Database Cleansing
Data cleansing is clearly the heart of CRM database cleansing. So, cover these bases when you clean your CRM data.
Data standardization
Without data standards, people will enter data into your CRM system in different formats and organize it differently. Team members may not even ask for certain customer information.
Without data standardization, you end up with disorganized data that’s prone to duplicate and incomplete data. And, your database is harder to search and navigate.
Implementing data standardization policies makes your data easier to use and easier to clean.
Duplicate Data Cleansing
Duplicate data just makes it look like you have a lot more customer contacts than you actually have. This data isn’t a huge time waster. However, it makes it hard to accurately analyze your data and gather useful insights.
Remove duplicate data from your databases so you can use your data to make better decisions.
Data Completion
Incomplete CRM data makes it impossible to use your data effectively.
A first name and an email address isn’t a data error or a completely useless entry. But, it’s much better if you have the last name. The same goes for a phone number without an area code.
You need complete customer data. If you have multiple CRM databases, check them against each other to make sure you have truly incomplete data. Then, use a data append service to complete the partial entries in your CRM database.
This makes your sales and marketing efforts much more effective.
Data Validation
This might seem obvious. But, you need to perform regular CRM data validation. Customer contact information changes all the time. So, you need to validate CRM data before you use it, even if it was correct a month or a week ago.
Establish a regular data validation schedule to keep your CRM data fresh and useful.
Data Protection
Data protection comes in two major brands: data security and data maintenance.
The first is a no-brainer. Never let unauthorized people get access to your customer data. Customer data breaches are really bad for your company’s reputation.
Data maintenance is about protecting the accuracy and integrity of your CRM data. Data decay is one thing. But, you also need to protect your data from errors you cause when you use your data.
This means minimizing manual data entry. Manual data entry is one of the main causes of bad data, because people make mistakes. Design systems, use APIs, and establish data use policies that remove as much manual data entry as possible.
Data Enhancement
If you do multi-channel or omni-channel marketing, you probably have CRM databases with the contact information for one marketing channel, but not for the others.
Maybe you collected a list of names and email addresses with a lead magnet. Or, you have a list of names and phone numbers from a call center. It would be great if you could supplement your email marketing with SMS. Or support your phone outreach with emails.
That’s what data enhancement is for. Data enhancement creates more complete customer profiles that you can use for marketing through any channel. And, it helps simplify your CRM database.
Rather than having separate lists for each marketing channel, you can use data enhancement to create a single CRM database that all your teams can use, regardless of how they’re contacting customers.
Of course, you can create segmented lists, too. But, you’ll have a central database that’s much easier to manage and analyze.
These best practices will protect you from CRM data decay and squeeze more value from your customer data.
Fortunately, you can use a single tool to implement 2 of these best practices right away. We mentioned it earlier.
Data Append
Data append finds missing data and validates the customer data you have. So, you can cleanse and enhance your data in one fell swoop.
And, there are two ways to use data append services: batch processing and data integration.
Batch Append
Batch append is essentially manual data append. You create a list of CRM contacts as a .csv, .txt, or Excel file and upload it yourself. Your data reseller will process the list, add and validate the data, then return your results in a .csv file.
Usually, you’ll get your results in a matter of minutes. But, it can take longer for really large lists. For most lists, the entire process—from upload to download—takes a few minutes.
Batch processing is best if your CRM system has no connectivity for an API. If you can use an API, you should.
Data Integration
If your CRM system is capable of connecting to a customer data source via API, you can use data integration for automated data cleansing and data enhancement.
Typically, a data append API will integrate into your CRM system with a unique URL. The implementation is fast and easy.
Once your data integration is setup, you can configure your CRM system to trigger anytime you receive new CRM data or before you use your data. It reduces manual data entry, and automates your data cleansing and enhancement.
What to Do Now
That’s it. Implement these best practices, use data cleansing tools, and get more revenue from your CRM database.
Try the Searchbug batch append service and our data append API if you need dependable data on demand.
