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Data quality is a serious hurdle for revenue operations teams. Approximately 47% of new data collected by businesses has one or more critical errors. And that doesn’t even account for the percentage of bad data you may have from old contacts that have expired.  

The truth is, if you’re facing data quality issues, you’re not alone. Only 16% of companies characterize their data quality as “very good.” But what this also means is that by maintaining data integrity, your organization can have a major competitive advantage.

With that being said, here are the most common types of data quality issues and how to avoid them in the future.

What Data Quality Is and Why It’s Important

Data quality is a measurement of how dependable your organizational data is in terms of accuracy, validity, completeness and consistency. With your Salesforce org being the cornerstone tool connecting your GTM teams, maintaining data integrity is critical for allowing your revenue operations team to confidently:

  • Build accurate GTM reporting 
  • Build personalized customer and prospective workflows 
  • Add/remove fields and make changes within your org 

When data quality is poorly managed, admins can’t successfully execute on these business critical-tasks. As a RevOps leader, it’s your responsibility to ensure your data quality is measured by six characteristics:

  1. Competition: The data isn’t missing values 
  2. Uniqueness: There aren’t duplicate records of the data
  3. Timeliness: The data is up to date  
  4. Consistency: When reported upon, there isn’t discrepancies across departmental data 
  5. Validity:  All data is formatted in the same type and ranges
  6. Accuracy: The data values are accurate

Common Data Quality Issues & How to Avoid Them

Even teams who follow the best practices in analyzing and maintaining data integrity are likely to face data quality issues on a regular basis– making regular Salesforce data cleanup a critical routine. But before you can run an effective cleanup project, it’s important to know how to identify poor data quality within our org.

Here are some of the most common data quality issues your admins are likely to experience and pro tips on how to avoid them: 

1. Duplicate data

Duplicate data is a problem for a variety of reasons. First of all– it takes up storage space, which costs the business money. Secondly, it prevents your GTM team from having a holistic view of your customer when their data is spread across multiple contact records within your CRM. This leads to lack of personalization, miscommunication, poor customer service and inaccurate reporting. 

A few examples of duplicate data might include:

  • Contacts who fill out a form on multiple occasions using different personal emails
  • A sales rep adding a contact to the CRM without checking to see if a record already exists 

Pro tips to avoid duplicate data: Luckily, there are a variety of ways to help decline the number of duplicate data that enters your Salesforce org, including:

  • Activating duplicate rules within your instance that notify sales teams that records already exist and prevent them from adding a new contact  
  • Use the duplicate record set object to report on how well your duplicate rules are actually catching duplicate records
  • Implement third-party tools that automatically identify duplicate records and either delete them or merge them together.   

2. Manual data entry errors

When GTM personnel are in a hurry, it’s easy for mistakes to get made. And regardless of the countless hours of training you provide them, there’s no cure for human error. A few examples of manual data errors might include:

  • Misspelled contact names
  • Missing characters in email addresses
  • Creating duplicate records
  • Using the wrong format for objects like birthdays and projected revenue 

Pro tips to avoid manual data entry errors: While you will never be able to eliminate human error all together, there are ways your admins can prevent the amount of manual data entered into your CRM to help mitigate errors. Some tips include:

  • Adding picklist values for required fields 
  • Set predefined data set types to ensure validity is maintained 

3. Lack of complete information 

Another common data quality issue is lack of complete contact information. Removing the barrier to entry is critical for companies today trying to capture lead data– and in most cases, that means reducing the number of fields on your forms. While this may increase a prospects’ aptitude to fill out the form, it also hinders your ability to gather beneficial first-party data like first and last names, company names, and phone numbers. 

Additionally, your sales teams may be rushing when creating contacts within your Salesforce. So while they may add the basic info like the prospect’s email address

Without this information, your GTM teams are left to hunt it down in order to build meaningful and personalized campaigns. The more time they are manually hunting down data, the less time they are spending on revenue impacting projects for your organization. 

Pro tips to avoid lack of complete information: You don’t want to elongate your forms– we know that won’t increase conversion rates. So the best way to automate the collection of incomplete contact data is to use a data enrichment tool that integrates with your Salesforce org. Enrichment tools merge their contact data with your CRM data to provide you a deeper insight of contacts.

For example, if you only gather email addresses, an enrichment tool can fill in the gaps, providing you with the contacts:

  • First name
  • Last name
  • Job title
  • Company name
  • Social media handles
  • Intent insights 

And more! 

Lastly, you can set up required fields within your Salesforce so your GTM teams know what to fill out each time they add a new contact. 

4. Expired data 

Data is never static. People change jobs, switch phone numbers, move, get promoted… and having all those changes accurately reflected within your CRM is an inevitable challenge. The truth is, you’re never going to prevent data from expiring. The question then becomes, how do we know when data expires so we can cleanse it?

Pro tips to manage expired data: 

  • Build lists that folder out contacts with unknown emails, who have unsubscribed or bounced from your list, or haven’t engaged with you within the past 10 touch-points. Then remove those contacts from your database or mark them inactive. 
  • Run all your contacts through an email verification tool and remove any contacts with invalid emails from your database. 
  • Set up alerts and notifications to notify admins of Salesforce changes
  • Set up audit trails and commit messages
  • Assign project owners to ensure data changes are managed properly 
  • Ensure your team is using sandbox to avoid poorly managed data changes in Salesforce

5. Invalid Data

The final most common data quality issue is invalid data. On average, 65% of contact data generated from online web forms is invalid. As a result, employees spend 50% of their time dealing with mundane data quality tasks. Unfortunately when a lead fills out a form, there’s no way to know for certain whether the data provided is valid or not. Some examples of invalid data might include:

  • Prospects using an initial as their first name or last name rather than spelling it out. (i.e. Someone named Bob simply putting “B” as their first name. 
  • Leads using a fake email or an account that is no longer used/exists  
  • New contacts filling out the form in all caps or all lowercase letters
  • SPAM bots auto-filling out forms on your website 

Pro tips to avoid invalid data: A few ways you can help streamline the collection of inaccurate or messy data include:

  • Use third-party form tools that block fake emails or non business email addresses
  • Using reCAPTCHA on your forms to ensure it isn’t a bot filling it out 
  • Use third-party CRM tools that will automatically clean and update your data upon submission

Solving Data Quality Issues with Sonar

Every organization deals with data integrity issues within their Salesforce instance. So while it isn’t completely avoidable, with the tips above, your admins can implement tools and processes that reduce manual work for your teams and the amount of data qualification issues your instance has. 

Want to take data quality to the next level? Tools like Sonar help give your admins a blueprint for managing data changes. Help them understand the dependencies between your data so they can easily fill gaps without breaking things across your Salesforce Org. Try Sonar for free today