How to streamline sales processes with improved CRM data quality

How to improve customer relationship management data quality

To get the benefits of high-quality data, you need to collect and store it in your CRM. To do this, your organisation should adopt a data management strategy that focuses on the quality of the data in your databases.

You can use sales team management tips during the sales management planning process to help your team understand the importance of good data quality:

• Explain how better data quality can make the sales team’s job easier, such as spending less time correcting inaccurate records.
• Communicate the company goals for data quality and how team members can help reach these goals in their everyday tasks.

The best way to implement a data quality management plan is to integrate a data quality system into your CRM. For example, you can implement pre-built CRM data integrations for some of the most popular CRMs available. These full-service data quality management solutions help your business clean up CRM data and maintain good data quality.

With a data quality plan in place, you can explore how to improve sales leads and processes through good quality data.

1. Work more efficiently by cleansing data regularly
   Automation is one of the easiest ways to streamline your sales processes. Any time you can automate a task, you free up more time for your sales team to focus on selling your products and services to paying customers. Cleaning up existing data is an easy task to automate and can save your sales team a lot of time.

   A data cleansing service lets you upload a bulk list of customer contact for validation. Cleansing systems can check, amend, or get rid of inaccurate records in a matter of seconds. You can even schedule regular data cleansing for an automatic CRM data clean-up at periodic intervals.

2. Create reliable reports using accurate data
   The majority of CRMs give your sales team the tools to produce reports on almost any metric—including reports related to leads, prospects, and customer preferences. You’ll get the most out of these reports if the data being used to create them is accurate. When your data is correct, you can trust the reports you create.

   Trustworthy reporting and analysis cut down on the amount of time your sales team spends double-checking the figures in the report. Instead, they can present their findings and use insights from the report to make sales strategies based on customer preferences and trends.

3. Build custom sales processes based on unique customer attributes
   There are no one-size-fits-all approaches to modern sales. Your sales team will be more successful if they create sales processes and strategies customised for different customers. Good quality data makes creating these processes easier.

   If you have high-quality customer data that’s enriched with additional details, your sales team has more information available to tailor sales language and tactics to individuals. Your sales strategies become more effective and the sales team spends less time talking with unqualified leads.

4. Make sure new data is accurate from the start
   How much extra time will your sales team spend checking the accuracy of each new lead that comes into your database? Manually validating the contact data of each new prospect could add several minutes to each record. Over a day or week, your sales team might spend more time checking new data than actually contacting leads.

   Real-time data validation eliminates this manual process. For example, you can use CRM integrations with real-time data validation to verify customer addresses, phone numbers, and email addresses as they enter your system. You can apply real-time validation to the customer-facing side—such as web forms or eCommerce checkout pages—or to forms within your CRM where sales team members enter data. This speeds up checkout and customer service response times for fewer abandoned carts and more satisfied customers.

5. Get rid of database record errors that could lead to lost sales
   Imagine you’re a member of a sales team tasked with calling prospective customers. As you make your way down the list, you make a call to someone named Joe. However, the person who answers the phone explains there’s no one named Joe at that number and hangs up. After cleaning up your CRM data, you realise “Joe” should have been “Joel,” and the prospect was entered incorrectly. This simple typo might have cost you a sale.

   Integrating a CRM data quality solution could save you lost sales from human errors like typos, misheard names, or hard-to-read handwritten sign-ups. Likewise, a data quality solution that validates customer contact data can help prevent typos or incorrect formatting in phone numbers, mailing addresses, and email addresses.

6. Don’t store irrelevant or unnecessary data
   Not having enough data to make accurate insights is a problem, but is it possible to collect too much data? The answer is yes. Too much data can bog down your CRM system and make it difficult to sort through the large amounts of data to find useful information. On top of that, holding on to data that’s not relevant could make you non-compliant with data and security regulations like the General Data Protection Regulation (GDPR).

   Adopting a CRM data quality strategy includes suppressing customer data that’s no longer needed or relevant. You can use tools like suppression data enrichment to easily compare data in your database with the latest available data.

7. Manage CRM data quality with pre-built integrations
   Adding data quality management solutions to your CRM system doesn’t have to be difficult. Pre-built CRM data integrations work seamlessly with your existing system. You won’t have to worry about building custom code to get the benefits of data quality integrations for:
   • Salesforce: Data validation for Salesforce lets you easily capture, standardise, and validate customer data, including phone numbers, email addresses, and postal addresses. The validation process makes sure your customer contact data is up to date and properly formatted so you can focus on making more sales.
   • Microsoft Dynamics 365: This cloud-based system makes it easy for users to work from almost anywhere, but that means you have more users and more points of entry for data. Data validation for Microsoft Dynamics 365 can help check your customer addresses, emails, and phone numbers as they enter your system. Read our blog “7 things you can do to improve your Microsoft Dynamics 365 data” and find out the key considerations as part of your CRM data strategy of Dynamics 365.
   • SAP CRM or ERP System: SAP CRM and ERP systems rely heavily on user-entered data. This means validating it at the point of capture is important for data quality. Data validation for SAP gives you access to real-time data validation as it’s entered by a user. Watch our on-demand webinar “Boosting customer data in your SAP CRM: The Data Quality Do’s and Don’ts” and learn an effective data quality management in SAP CRM system.

How to improve sales pipeline with CRM data analysis and quality management

Ready to learn how to improve your sales processes through CRM data quality best practices? Get in touch with our data quality experts to learn how Experian can help improve your sales team’s efficiency.