Microsoft Dynamics is an invaluable sales tool, but it all comes down to the underlying sales data. Learn how prioritizing data quality in CRM can significantly boost adoption rates and drive organizational success.

Don’t worry, though, because I’ve got you covered with some effortless techniques to enhance data quality across the board.

The importance of data quality

Let’s dive right in and talk about the significance of data quality. Your Microsoft Dynamics system relies on complete and accurate data to power your sales cycle.

When your customer data is top-notch, it becomes an invaluable resource for engaging potential customers and smoothly guiding them through the sales funnel.

However, if your data isn’t up to par, you risk missing out on connecting with individuals who have a genuine interest in what you have to offer. A single letter or number can make or break a promising lead.

The statistics around CRM data quality

Now, brace yourself for an eye-opening statistic: approximately 70% of all CRM data becomes incomplete, inaccurate, or irrelevant on an annual basis, according to Salesforce. That’s a substantial problem with far-reaching consequences. Bad data has been known to waste 550 labour hours and result in a loss of $32,000 for each sales rep. Even seemingly minor errors can have a substantial cumulative effect.

Operating with anything less than perfect data is simply not sustainable. Manual data error detection and correction are unrealistic, considering the scale of the problem. Thankfully, automation can come to your rescue, replacing the need for an army of analysts and delivering spotless data in less time.

3 steps to automated data quality

Let’s explore the 3 steps to automated data quality for Dynamics CRM:

Step 1: Data Capture

Users enter the info for a new contact, account, or lead. Whether it’s through manual entry or data import, this step is prone to human errors and can corrupt crucial details like addresses, phone numbers, email contacts, or even names.

Step 2: Automated verification

A plug-in directly integrated within Microsoft Dynamics works its magic. It checks the entered data against existing records, automatically correcting inaccuracies (like misspelled names) and adding missing information (like postcodes) to the CRM record.

Step 3: Automated matching

Once the data is clean, the same plug-in searches for duplicate records, even if they only share partial information. Users can effortlessly view and merge these records into a single comprehensive entry. The most complete and current information takes precedence, while the rest becomes inactive.

From start to finish, this process takes just a few minutes and leads to the most comprehensive customer profiles possible. Imagine the time and stress saved by automatic data cleansing. Instead of managing data, your sales staff can focus on connecting more effectively.

To maximize your Dynamics platform and ensure top-notch data quality, check out Precisely Trillium.

Trillium includes certified connectors to cleanse and match records directly within Dynamic CRM, ensuring rapid and sustainable delivery of quality data. For more information, view the Precisely webcast titled “Boost Your Customer Outreach with Strong CRM Data.“

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