Identifying and Cleaning Bad CRM Data with Clockspring

Dirty Data in your CRM

Dirty data—outdated, incomplete, or incorrect records—is a pervasive issue in CRM systems. It leads to inefficiencies, missed opportunities, and wasted resources. For example, contacts with null names or missing associated companies can skew reporting, hinder segmentation, and cause miscommunication with prospects or customers. Starting an email campaign message with 'Dear null' is off putting to the prospect and harms your brand's reputation. Studies show that 25% of the average B2B database is inaccurate.

We examined our Contact dataset and found significant gaps in the information present. Some records lacked associated company names, while others had missing or incorrect contact details. Without addressing these issues, sales and marketing teams would struggle to engage with customers effectively, leading to lost opportunities and revenue.

Identify and Cleanse Data

Clockspring provides a powerful, flexible toolset for automating data extraction, transformation, and cleaning. Here’s how we used it to identify and address bad data in our CRM

1. Extracting CRM Data – We used Clockspring to pull all Contact data from HubSpot into a structured database. This allowed us to analyze and manipulate the data outside of the CRM’s native interface.
2. Identifying Bad Data – By running queries against the database, we were able to quickly identified key issues:
• Contacts with null or missing names.
• Contacts not associated with any company.
• Duplicates and inconsistencies in formatting.
3. Actioning Data Cleanup – With the bad data identified, we took the following steps:
• Enriching missing company associations using available public data.
• Standardizing name formats for consistency.
• Removing or merging duplicate entries to ensure accuracy.
• Updating records in the CRM with the cleaned data using Clockspring’s data sync capabilities.
4. Automating the process – Clockspring’s automation capabilities ensure that data cleanup becomes a repeatable process. By scheduling regular audits, you can maintain a clean CRM without manual intervention.

By leveraging Clockspring’s automation features, we streamlined the entire process, reducing manual effort and improving data. The best part: Building the integration only took an hour.

Clean Data, Better Results

After implementing the cleanup process, we observed immediate improvements:

• Better Sales and Marketing Alignment – With accurate and complete contact details, teams were able to target prospects more effectively, leading to higher engagement rates.
• More Reliable Reporting – With clean data, sales forecasts and customer insights became more accurate, enabling better strategic decisions.
• Increased Operational Efficiency – Automating the identification and cleanup process reduced manual data entry errors and freed up valuable team resources.

Clean CRM data is critical for business success, and Clockspring provides an efficient, scalable solution for maintaining data integrity. Whether you’re dealing with a small CRM database or a massive dataset, Clockspring can help you ensure that your customer data remains reliable and actionable.