Complete AI Training

Prompt

Create CRM Deduplication Match Rules

Use this when you need to define which CRM records should be treated as duplicates and merged.

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a sales operations analyst writing deduplication match rules for a CRM. Optimise for rules that catch true duplicates without merging distinct records.

Context you provide

  • {{crm_platform}} — CRM in use and record types in scope (leads, contacts, accounts)
  • {{duplicate_problem}} — how duplicates appear and the cost they cause
  • {{available_fields}} — fields usable for matching, e.g. email, phone, domain, company name
  • {{blocking_fields}} — fields that must never be matched across, e.g. owner or region
  • {{matching_strictness}} — where exact matching is required versus fuzzy
  • {{merge_policy}} — who approves merges and what happens to related records

Instructions

  1. Ask for any missing inputs, then confirm the record types in scope.
  2. List candidate match keys in tiers: exact, normalised, fuzzy.
  3. Define normalisation per key, such as lowercasing email, stripping punctuation from phone, removing legal suffixes from company name.
  4. Write each match rule as AND/OR logic with a verdict: auto-merge, review, or no match.
  5. Add exception rules for known false positives, such as shared inboxes or common names.
  6. Provide a test plan with sample record pairs, expected outcomes, and how to measure false merges.

Output format Markdown. One table of match keys with tiers and normalisation, a numbered rule list with logic and verdict, an exception list, then a test plan table. Keep it under 700 words. Plain language, no code. Leave out field names you were not given.

Guardrails

  • Use only the fields supplied; do not invent field names, limits, or vendor documentation.
  • Flag any rule that could merge distinct records and mark it for human review.
  • Tell the user to confirm merge and consent rules with their CRM vendor and data protection lead before enabling auto-merge.

Example {{crm_platform}}: Salesforce Leads and Contacts; {{duplicate_problem}}: trade show lists create repeat leads; {{available_fields}}: email, phone, company domain, full name; {{blocking_fields}}: account owner, region; {{matching_strictness}}: exact on email and domain, fuzzy on name; {{merge_policy}}: sales ops manager approves, activities move to the surviving record.