Data Cleaning & Normalization: Elevating Data Quality with Clay's Cleaning Tools

Now that you’ve gathered a wealth of company and contact data, it’s time to clean it all up.

Getting data is just the first part of the journey. But if you’ve worked with data in the past, you know that “garbage in” is “garbage out.” Good news: Instead of relying on AI formulas or spending credits on enrichment, Clay provides native data cleaning functions that handle common data normalization tasks efficiently at no additional cost.

In this lesson, we’ll explore how these tools can transform your workflow.‍

Why Data Cleaning Matters

Raw data often comes with inconsistencies, making it difficult to use effectively. Common challenges include:

• Variations in company names (e.g., “Clay Labs Inc.” vs. “Clay”)
• Unnecessary legal suffixes (LLC, Inc., Agency, etc.)
• Mismatched formatting across different records

Rather than manually fixing these or creating complex AI formulas, Clay’s native cleaning tools automate the process, helping you save time while keeping your CRM clean and standardized.

How It Works: Normalizing Company Names

How often have you encountered company names cluttered with legal suffixes or unnecessary prefixes? Our normalize company names function tackles this issue head-on.

For example, "Panamax Inc." becomes simply "Panamax," and "Cora, a company of blank" becomes just "Cora." This clean-up not only makes your data more uniform, but it also prepares it for seamless use in email copy or other communications.

How does it work? Simple: 

1. Navigate to the “Add enrichment” panel 
2. Select the "Normalize" option in the sub navigation to the left
3. Select "Normalize Company Names’ from the pre-built options
4. Choose the appropriate input column (in this case, the company name from your company table)
5. Run the action across your rows

The result? Clean, consistent company names ready for your next campaign or analysis.

💡Tip: Clay’s native normalization will cover most standardization needs, but for complex cases, experiment with AI formulas. Just always start with built-in functions for efficiency and to save credits. 

Beyond Company Names: Versatile Normalization

Our normalization tools extend far beyond company names:

1. Text Whitespace: Ensure consistent spacing across all your text data
2. Phone Numbers: Standardize formats, removing or adding parentheses as needed
3. Locations: Create uniformity in how addresses and locations are represented

These are just a few examples. But we encourage you to explore the full range of normalization options available in Clay.

One of the best parts about our data cleaning tools? They're completely credit-free. Since these functions operate by parsing existing data and executing code, rather than reaching out to external data providers, we can offer them to you without any additional charge.

Unlocking the Potential of Clean Data

Congrats! That’s a wrap on data cleaning and normalization in Clay. 

Clean data leads to more accurate analyses, more effective outreach, and, ultimately, better business outcomes.

In the next lesson, we’ll show you how to generate AI snippets for personalized outbound. 

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