Finding duplicates
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      Best practices for using Dedupely’s search pads using Dedupely’s search pads

      This guide shares best practices for using Dedupely's Search Pads, with tips on match types, filters, phone logic, and avoiding common merge mistakes.

      Here are some of our best practices when using Dedupely’s Search Pads to get the most accurate duplicates for efficient data management. Here are some tips and strategies to optimize your deduplication process, particularly focusing on match options and filters.

      1. Use Similar Word Match for companies and addresses

      When dealing with company names or addresses that may have abbreviations or variations, use Similar Word Match (Any Order) and focus on the first two words to catch potential duplicates.
      • Why it works: Company names and addresses often include variations in word order or abbreviations. Matching the first two words helps identify duplicates even when the full names differ slightly.
      • Examples:
        • "Tech Solutions LLC" matches with "Tech Sol LLC."
        • "123 Main St." matches with "123 Main Street."
      • Best practice: Apply this strategy with Filters to narrow the search to specific record types, like Companies or Addresses.

      2. Leverage Fuzzy Match for contact names

      Use Fuzzy Match when dealing with contact names to account for typos, misspellings, or phonetic variations.
      • Why it works: Fuzzy Match uses a phonetic algorithm to detect names that sound alike but are spelled differently.
      • Examples:
        • "Johnathan" matches with "Jonathan."
        • "Catherine" matches with "Kathryn."

      3. Use Domain Root Match for companies

      When deduplicating company records, use the Domain Root Match option to identify duplicates based on email domains or URLs.
      • Why it works: Companies may have multiple contacts with different email addresses but the same domain. This option helps consolidate company records.
      • Examples:
        • "support@example.com" matches with "sales@example.com" because both share the root domain "example.com."

      5. Focus on the last 7 digits for phone numbers

      When deduplicating phone numbers, use the Similar match option to focus on the last 7 digits, ignoring formatting symbols.
      • Why it works: Phone numbers can be formatted differently (e.g., with hyphens, parentheses, or country codes). Focusing on the digits ensures consistency.
      • Examples:
        • "(123) 456-7890" matches with "123-456-7890" and "+1 123 456 7890."
      • Best practice: Apply this strategy when phone number can help you match duplicates.

      6. Combine Filters and Match Options for Precision

      For large datasets, combining multiple Filters and Match Options can help achieve more precise results.
      • Why it works: Combining criteria helps you refine searches and avoid overmatching or missing duplicates.
      • Example Workflow:
        • Filter: Contacts that belong to a specific owner or salesperson
        • Match option: Fuzzy Match on First Name and similar Match on Email.
      • Best practice: Use different fields to get different results.

      7. Regularly review and update Search Pads

      Deduplication needs can evolve over time, so regularly reviewing and updating your Search Pads ensures they remain effective.
      • Why it works: Keeping your match criteria and filters up-to-date ensures you catch new types of duplicates as your database grows.
      • Best practice: Clone existing Search Pads when making adjustments to avoid losing previous configurations.

      8. Backup data before Bulk Merging

      Before performing a bulk merge, always create a backup of your CRM data to prevent accidental data loss.
      • Why it works: A backup ensures you can restore data if unexpected issues occur during the merge process.
      • Best practice:
        • Export data using Dedupely’s Export feature.
        • Confirm the backup before proceeding with bulk merges.

      9. Use Auto Merge for ongoing maintenance

      Set up Auto Merge to keep your data clean so you do not have to bulk all the time manually.
      • Why it works: Auto Merge runs in the background based on your predefined criteria, saving time and maintaining data integrity.
      • Best practice: Configure Auto Merge for straightforward duplicate types (e.g., Exact Matches on Email and first + last name) and review the results regularly.

      10. Note on blank fields and duplicate matching

      When configuring your Match Criteria in Dedupely, it's important to know that blank fields will not count as duplicates. If a field selected for matching contains many blanks, records with a blank in that field will be excluded from the scan results.
      • Why this happens: Dedupely requires data in the selected fields to compare records. If a field is blank, there’s no value to match against, so those records are skipped.
      • Example:
        • If you choose to match based on the Email field and some records have no email address, those records with blank emails will not appear in the duplicate results.

      Conclusion

      These are suggestions to optimize your deduplication progress. We recommend you begin by merging using multiple fields to match in the beginning to avoid fewer mistakes if you run into them.