Temberton Insights

Every business could be better served by having increased visibility of their customers, and customer relationship management (CRM) systems are built to help companies do just that. A CRM system is a crucial tool for managing customer data at scale for sales, marketing, and customer service needs.

It’s important to remember, however, that a CRM is only as good as the data it contains.

Without quality data, your marketing and sales teams will inevitably fall short in deriving the insights you might have hoped to get from the CRM.

In fact, 47% of organizations say they can’t trust their CRM data, according to a 2021 Forrester report. Bad CRM data quality means wasted time and resources, increased bounce rates, and lost revenue (among other things).

With this in mind, here are some steps to take to ensure reliable, high-quality CRM data throughout your organization when implementing a CRM platform.

1. Standardize data management process across all teams within your organization

Your organization will invest valuable time and money implementing a CRM system with the expectation of gaining the benefits a CRM promises.

But it’s important to remember that a CRM is only as valuable as the data it contains. As such, you will need streamlined processes for capturing, cleaning, and standardizing customer data or the CRM will inevitably be filled with incorrect, missing, outdated, and duplicate records.

Defining the CRM data management process and standardizing it across all teams that touch the CRM is critical in ensuring your CRM consistently contains clean, correct, and current data. Having clearly defined use workflows and data management processes will help to standardize the capture and storage of information in the CRM throughout your business. And each team manager should be on board in training and supporting their teams regarding standardized CRM data management.

To standardize the CRM processes, you should:

• Establish required fields on all important business data when new contacts are added
• Use standardized CRM naming conventions
• Create data entry and deduplication rules

2. Ensure all existing data is correct, complete and up-to-date before adding to your CRM

Companies lose 3.1 trillion USD a year to bad data, according to a recent study by IBM.

Before pulling legacy data into your new CRM system en masse, save your organization the inevitable headaches by cleaning and correcting the data first. This is the most efficient way to start implementing proper CRM data management and ensuring it stays that way moving forward.

Bad data can be data that is simply filled with errors, but it can also be irrelevant data that’s inapplicable to your specific needs.

Remember that customer data is not static: customers can change their phone number, email address, location, job and more at any time.

Here are a few processes you can use to ensure existing customer data is correct and complete:

• Filter the data: to hone in on records that are missing critical data, first filter the data by each critical category. For example, filter by records whose contact numbers or email addresses are empty. Then, filter by record owner to assign data cleaning tasks to the appropriate team member.
• Run exception reports: An exception report is a document that states those instances in which actual performance deviated from expectations. Running exception reports monthly once data is initially cleaned will help uncover any records with incomplete data.
• Merge or delete duplicate records: Sort records to find duplicates and assign them to the correct record owner so they can review each contact record to merge or delete duplicate information. In many instances merging two records will create a complete record that does not need cleaning.

3. Ensure all data sources and new lead data are validated

Just as you should ensure all existing customer data are correct and up-to-date, so too should you validate any new data.

All new data used to feed your CRM should come from vetted, reliable data sources. By maintaining clean data in your CRM moving forward, you will ultimately save time, money, and eliminate future frustrations.

Keep in mind that information submitted by leads through your company website or other channels may not always be clean or complete. Implement a process to maintain clean data as it is pulled in.

This can be done manually or with one of the many automated data cleansing tools that integrate with your CRM.  Validate and enrich lead data as it comes in by removing any fake or false data and adding data that might be missing.

4. Harness the power of automation in your CRM data when possible

Save time and improve the accuracy and completeness of your CRM data by utilizing tools to automate CRM data entry.

Automation tools can help reduce inaccurate, missing, or duplicate data and can ensure your data is up-to-date.

Many CRM platforms have built-in automation capabilities. This will help your team spend more time focusing on building customer relationships and less time focusing on CRM “data janitor” work.

Following these simple rules before you implement your CRM will help to ensure that the data you capture and store on your prospects, leads, and customers are accurate, complete, and current. With this accomplished, you and your teams will reap the full benefits of your firm’s investment in customer relationship management software.

Need help prepping your data for business intelligence? Contact our Data Specialists at Temberton Analytics for a free consultation.