Who’s responsible for an organization’s Salesforce data cleansing best practices? The answer isn’t as simple as you think.
Luckily, with the right strategy and data cleansing tools, Salesforce data cleanup and maintenance are just a few steps away.
Poor data quality destroys business value. In fact, Gartner research shows organizations believe “dirty data” is responsible for an average of $15 million per year in losses.
In today’s business environment, dirty data is created by a variety of sources. It has the potential to cause any number of undesirable outcomes, from inconvenient disruptions in the normal flow of business activities to more disastrous impacts on a company’s revenue or reputation.
Dirty data in Salesforce typically falls into one of these categories:
Data cleansing involves identifying and correcting (or removing) the above inaccuracies and inconsistencies to ensure your organization is working with accurate and reliable information. Regular upkeep of your database results in:
There are a lot of stakeholders who rely on clean data in Salesforce. So, who should be responsible for achieving it?
The sales rep who manually enters customer data?
The marketing manager who periodically imports leads en masse?
The senior managers responsible for setting company policy?
Or the Salesforce administrator who manages the database?
The correct answer is “all of the above”.
While it’s easy to assume the responsibility for an organization’s Salesforce data cleaning strategy lies solely with the Customer Relationship Management (CRM) admin, that isn’t really the case.
Sure, a CRM admin may have primary responsibility for data cleansing in Salesforce, but anyone involved with data should work to ensure its quality is top-notch. For example:
Data auditing is a systematic review and evaluation of your data to ensure it is accurate, complete, and compliant. This process typically involves identifying and documenting data sources, reviewing data for accuracy and completeness, and running reports to compare data to established standards and regulations.
Data auditing may also include testing of data systems and processes to ensure they are functioning properly, as well as to identify and address any issues or discrepancies. The goal here should be to identify what data you collect, where it comes from, and how it is (or should be!) formatted.
At the end of your data audit, you should have identified any invalid data, duplicate records, or anything that is otherwise “unclean”. This will help you plan your Salesforce data cleanup.
Standardization ensures data is consistent and conforms to a set of established standards and conventions. After the audit is complete, you can begin to standardize data by transforming it based on established rules.
This involves defining the format, naming conventions, data types, and any other rules the data must adhere to, then converting and integrating your data into the desired format and systems (i.e., any other databases outside of Salesforce or another CRM).
The last step is to verify that the above steps have resulted in data that makes sense. Run reports and check that all the data returned is standardized, deduped, and accurate.
This is your chance to check your work and make any necessary adjustments. You should also take this opportunity to document the process from beginning to end: What were the results of your audit? What established standards have you set moving forward? What was your data cleaning process?
This will all come in handy the next time around (and there should be a next time––data cleaning should never be just “one-and-done”).
Of course, as any experienced CRM user knows, mistakes are inevitable. Even with the best company policies in place, the rules won’t always be followed.
So, what are you to do? There are a few key strategies to help you maintain the integrity of your data.
As mentioned above, regular data cleansing should be part of your process. To simplify this task, you need to select the proper data cleansing tools for your organization. Take the following into account when selecting a tool:
A high-quality data cleansing tool (or mix of tools) should ultimately help you audit, dedupe, standardize, and verify your data on a regular basis.
Maintaining clean data is an ongoing practice. In a perfect world, all inputs would be perfectly standardized and the data would never change. But we all know that will never be the case!
Even if you never enter bad data, things change. Your data needs and your customers’ data will always be evolving. This means setting up a regularly occurring data cleansing cycle that ensures your data is never able to get too far out of whack.
Regular data cleaning in Salesforce is good practice, but maintaining high-quality data will benefit your organization even more. Once you have standardized your data, you need to identify the causes of bad inputs that contaminate your data and slow your teams down.
Look across your teams to assess all data input to your CRM. How is the data entered and how is it checked (if at all)? Custom-built forms should be created to support your data structures and maintain them.
Fields should be bound properly to only accept the correct data types and/or patterns (such as only numbers in a phone number field). Users should also be properly trained on the data structures so they know what they should be entering where (and why!).
This is one area where Salesforce admins can really shine by championing high-quality data in their organization.
As ambassadors, they’re the ones who develop and enforce data governance policies, train team members in the CRM application, maintain open lines of communication between departments, and otherwise encourage other Salesforce users to do their part.
Consider establishing a cross-functional data governance team to ensure data is secure, high quality and relevant to your business’s goals.
Trustworthy CRM data is vital to the success of any business and can play a big role in increasing revenue. However, without a defined approach, your data management process is likely to be ineffective in helping your sales teams hit revenue goals.
By following best practices like regularly reviewing and updating data, using data validation rules, removing duplicates, using tools for data cleansing in Salesforce, and keeping track of data quality, you can rest assured that your data is clean and reliable.
For more insights into the entire data management process and recommendations for tools and technology to support your data quality efforts, download our free guide, The Dirt on Data Quality.