For many businesses, leads and data are streaming in from multiple sources all the time into your sales CRM. Business development teams are constantly adding contacts to the database, sales reps add information as they connect with leads, marketing teams add and edit data, and leads themselves are sometimes submitting information through the company website.
But, having a CRM that is bogged down with unnecessary, duplicate, or missing information, errors, or inaccurate formatting can cause huge inefficiencies throughout the entire customer lifecycle. It can mean your sales reps are having to spend way too much time sifting through data than actually being able to make sales. So, you’ll see lower conversion rates, less CRM engagement, and lower deliverability. It can also quickly throw off your territory management strategy if customer records are falling through the cracks due to varying naming conventions or missing information.
Now may be the perfect time to do some spring data cleaning in your sales CRM. But you may be wondering how to clean CRM data. Where should you start? What are the best methods when it comes to sales data cleaning? In this article, we’ll walk you through just that. Through data cleaning, you’ll learn how to leverage CRM data to increase sales.
The Complete Sales CRM Data Cleaning Checklist
If the data compiled in your company’s CRM software is not utilized properly, it can prove to be a costly and inefficient use of time. CRM data management is crucial to a company’s optimal success, both in the short term and for long term growth. That’s why proper practices for CRM data management is so important.
Let’s go through a complete checklist for cleaning up your sales CRM data:
Step 1: Find Duplicate Data
Duplicate records can come in from a variety of ways. Whether multiple team members enter the same information on different days or a customer submits information more than once. According to a study by Forbes Insights, in association with Pitney Bowes, businesses accrue up to 30% duplicate data every year in their CRMs if the data is not properly managed.
So, finding your duplicate data is a huge first step in cleaning up your sales CRM. This can be done manually or some CRMs, like Salesforce, have an app to integrate to help scrub out duplicate entries. There are also ways to automate this, which we’ll get into further into this article.
Step 2: Clean up Duplicate Data
Once you have filtered out duplicate data and customer records you will be able to clean all of that duplicate data up. Essentially what needs to be done is merging any instances of duplicates into one clear, complete customer record. If you are doing this manually, once you have the one record or dataset that you will be using, make sure that the remaining duplicates are deleted.
Step 3: Block Duplicates at the Point of Entry
Once you’ve cleaned up the duplicate data in your CRM, it is extremely advantageous to do what you can now to help keep it that way moving forward. Some sales CRMs have a native feature built-in that can block duplicates at the point of entry. There are also programs available, like RingLead Prevent, that can integrate with your CRM and block duplicates from manual entry, web form, and list uploads. That way, users are alerted when they attempt to enter a duplicate record.
Step 4: Normalize the Remaining Data
Once you have cleaned out duplicate data and you are left with only the data you want to keep, it is important to normalize it through standardizing naming conventions. And keeping those conventions moving forward. This will keep all of your data uniform, improve filtering capabilities, and not risk the chance of skewing sales reports based on varying data inputs.
For example, setting “NY” as the standardized naming convention versus having data records where some say “NY” while others say “N.Y.” or “New York”. This can be done manually, depending on your CRM, or can be automated.
Step 5: Find Missing Data
Another important aspect of cleaning your sales CRM data is determining where data is missing. For your CRM to be most effective, the customer records and data needs to complete. So, pinpoint instances where contact information, firmographic information, and any other necessary data might be missing so you can prepare to start completing and enriching your records.
Step 6: Complete Missing Data
Once you have uncovered the cases where there is missing data in your sales CRM, it is important to try and complete as much of that as possible. Also, take the time during this point to try and enrich the customer record with more beneficial information on the customer’s company or industry. Some instances of missing data may be things that you can take care of on the sales op or sales development side, while some fall on the shoulders of the sales reps.
Either way, the more complete picture you have (and maintain) of your customers and leads in your CRM, the more effective and productive your teams can be. You’ll also see a higher level of customer engagement because of your teams’ ability to customize outreach and marketing.
Step 7: Delete “Old” Data
Another subset of data that might be bogging down your CRM is “old” data. This would be customer or prospect records that are old, aging, or unengaged in your system. If there are records in your CRM that have not been touched within current sales cadences in a long time, have been statused as “do not contact” or have unsubscribed, are not responding to outreach, etc, filter these out and have what can be deleted taken care of. You may have to alert individual sales reps or work them directly to review the customer record and delete what should be deleted. This is also a great opportunity for those sales reps to uncover new sales opportunities within existing prospect or customer records that may have been forgotten.
Getting rid of old data will clear out unnecessary records and help ensure your sales team can and is focusing only on the customers and prospects that matter.
Maintaining Clean CRM Data Moving Forward
It’s a great feeling when you transform a dirty, bogged down sales CRM into a clean, organized system that helps your teams run like well-oiled machines. But, it is important to understand that once you have initially done a thorough job of data cleaning in your CRM, it is not a set it and forget it situation. Without proper data management, as new information and records are added to your CRM, you could quickly find yourself right back where you started with a bogged down CRM.
There are some important things you can implement and keep in place moving forward to help you stay on top of your sales CRM data.
A checklist for how to keep CRM data clean:
Limit the Use of Free-Form Text Fields
Having too many opportunities for free-form text and notes increases the possibility for information to be left out or lost in your sales CRM. Use defined, closed-option dropdowns as much as possible and leave the free-form text fields only for important notes on customer interactions, etc.
Have Required Fields for All Critical Parts of Customer Data
This will ensure that as new customer or prospect records are being added, all of the essential information will be included and reduce instances of missing information.
Standardize Fields and Naming Conventions Upfront
Normalizing your data and implementing standard naming conventions will help keep your data uniform, avoid duplicate records, and avoid skewing reporting and analytics. Once you have established your set naming conventions and data rules, it is equally important to make sure that all teams who use the CRM understand them as well. Document your guidelines so that everyone has access to them to reference as needed.
Block Duplicate Data at the Point of Entry
Utilize resources available to you to eliminate new duplicates coming into the system as you move forward. Whether this is done with a native setting within your CRM or through the use of an additional data management automation tool. This will save a lot of time in data cleaning in the future.
Limit the Number of Users With Full Administrative Rights to Your CRM
Keeping the number of full-access admins to only those who absolutely need it will help maintain your processes. It will also eliminate the chance for an inexperienced user to accidentally turn off an important duplicate checker or other data management feature.
Set up a Maintenance Schedule
Establishing a regular maintenance schedule is key to keeping your data clean moving forward. It is often recommended to do data cleaning once per month. You should also be checking for software updates to your CRM several times per year.
Automating Your Sales Data Cleaning
As you can see, cleaning your sales CRM data is essential to your business. Taking the time to do this regularly can have a huge, positive impact on the efficiency and effectiveness of your teams. Of course, sales data cleaning can be done effectively manually. But it can become daunting and time-consuming if you have a large amount of data in your CRM and/or the data has not been cleaned in a while.
Instead of trying to do all of the data cleaning manually, there are now automation tools available to make the process of cleaning up your sales CRM data much faster and more routine. The processes of uncovering and merging duplicate records, finding missing data, normalizing remaining data, enriching the data, and standardizing naming conventions can all be automated.
Many of these automation tools can also help ensure that your CRM data is accurate. You can be confident in knowing that you have the correct email addresses and contact information, the latest individual company data, etc.
Some of the top data cleaning tools available now include:
RingLead provides solutions to automatically clean your sales CRM data, prevent duplicates at the source, enrich your existing data, and more. Helping you achieve and maintain the highest-quality data. RingLead directly integrates with many of the top CRMs.
Insycle is another powerful data cleaning tool that automates the cleanup, organization, and standardizing of your data. Helping to significantly improve workflows and maintain a clean CRM system. Insycle also integrates with many of the top CRMs.
Clean From Data.com
Data.com Clean is a native, data cleaning and management solution built into Salesforce that can easily be activated. This solution automatically cleans and enriches your customer records and contact/lead data, right within Salesforce.
Data Ladder is a complete data cleaning solution that helps to automate verifying and updating contact data, applying standardization rules, fixing errors and completing missing data, and cleaning up duplicates. This tool also seamlessly integrates with dozens of top CRMs.
Sync from Vainu
Vainu Sync is another robust data cleaning software that saves valuable time by automatically cleaning and enriching your CRM data behind the scenes 24/7. This tool syncs seamlessly with many top sales CRMs.
Take the time to look into and invest in data cleaning automation tools when you first clean up your data. Find the tool that is the best fit for your needs and your company. This will not only help minimize the time it takes to get everything cleaned up properly but also help you keep it that way consistently as you move forward.
Leveraging the Full Power Of Your Sales CRM Data Through Data Cleaning
Your company’s sales reps are only as good as the data and information they have to work with. That’s why it is so important to clean your CRM data now and, even more importantly, implement processes to keep it clean moving forward. Hopefully, after going through this checklist you have a clearer idea of what action items to follow and what to do as you and your company move forward. Whether it is done manually or through the use of automation tools.
Standardized processes, as well as maintaining a regular data cleaning and CRM maintenance schedule, will help your company keep clear, complete, and accurate customer information. These things will also ensure that your sales, marketing, and service teams can efficiently use your company’s customer data and focus on what they need to most. Empowering your teams to operate at the most effective and productive levels.
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