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Industry Normalization

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Step Overview

Industry Normalization automatically standardizes messy industry data from your leads into consistent, predefined categories. Instead of having dozens of variations like “Tech,” “Technology,” “Software Development,” and “IT Services,” this step maps all industry inputs to your standardized list, giving you clean, actionable data for segmentation and reporting.

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Business Value

  • Consistent Reporting: Transform chaotic industry data into standardized categories for reliable analytics and campaign performance tracking
  • Better Segmentation: Create targeted campaigns based on clean industry classifications rather than guessing what “Tech Co.” actually means
  • Intelligent Mapping: Uses AI to interpret context from company names and job titles when industry fields are blank or unclear
  • Flexible Standards: Customize your industry list to match your business needs and target market focus

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Setup Instructions

Prerequisites: Your leads should include industry data, company names, or job titles for best results Configuration Steps:
  1. Add “Industry Normalization” to the appropriate spot in your workflow
  2. Go to Lab > Skills > “Industry Alignment Normalization” to customize your industry categories
  3. Click “Industries” under Tweaks to edit your industry list - you can add, remove, or modify categories to match your business focus
  4. Test your configuration with Lab > Skills > Test using sample data from your typical lead sources
  5. Once satisfied with results, click Lab > Skills > Publish

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How It Works in Practice

Input Requirements: At minimum, one of these fields should contain data:
  • Industry field (primary source)
  • Company name
  • Job title
  • Enriched company/job title data
Processing Logic: The step follows this intelligent hierarchy:
  1. If industry field has data, maps it to your closest standard category
  2. If industry is blank, analyzes company name and job title to infer the most likely industry
  3. Uses contextual understanding to handle variations (e.g., “SaaS startup” → “Software”)
  4. Returns empty string only when no meaningful data is available
Output: Clean industry classification that matches your predefined categories exactly

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Best Practices

  • Test with Real Data: Use actual messy data from your CRM to validate the mapping logic works for your specific lead sources
  • Customize Categories: Modify the default industry list to reflect your target market - remove irrelevant categories and add industry-specific ones
  • Review Edge Cases: Test with international companies or unusual business models to ensure proper classification
  • Monitor Results: Periodically review what’s being classified as “Other” or “Unknown” to identify new categories you might need
For advanced configuration options or custom industry setup, contact your allGood success manager.

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Frequently Asked Questions

The step will return an empty string rather than making a poor guess, allowing you to handle these cases separately in your workflow.
Yes! Edit the Industries tweak to include any categories relevant to your business. The system will map inputs to whatever categories you define.
The AI can interpret many international business contexts, but test with your specific data. You may need to add common foreign terms to your category examples.
Place it after enrichment steps so it can leverage enriched company and job title data for better classification when the original industry field is empty.