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AI agent for crm managers

Address Standardization Agent

A clean address file where each address is verified or flagged, with duplicates found

Data cleanupIT and development
See how it worksGet access
Address Standardization Agent: what goes in, what the agent does and what you get

What it does

Inconsistent addresses cause returned mail and failed matches between systems. This agent standardizes addresses against a reference source. It flags ones it cannot verify and tries common variants, such as abbreviations and unit numbers. After changes, it rechecks the file for new duplicates, since two different spellings often turn out to be the same place. It keeps the original value next to the standardized one so nothing is lost. A person approves the update of source records. Edge case: two records for the same house, one with Apt 2 and one with Unit 2, so the agent flags them as a possible duplicate.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Address file is ready for cleaning 2 USES A TOOL Match each address to the reference source 3 DOES Standardize format, case and abbreviations 4 CHECKS THE RESULT Did each address match a reference record? If not: try variants such as unit forms and spelling,then flag what still fails. Back to step 2. 5 DOES Keep the original and the standardized valuetogether 6 DOES Search for duplicates created by the changes 7 CHECKS THE RESULT Are possible duplicates reviewed and none leftunexplained? If not: list them for a person to review. Back to step6. 8 YOU APPROVE A person approves the update of source records 9 USES A TOOL Write the approved values to the source records 10 RESULT Cleaned file and a list of unverified addresses
Read the steps as a list
  1. Address file is ready for cleaning
  2. Match each address to the reference source
  3. Standardize format, case and abbreviations
  4. Did each address match a reference record?If not: try variants such as unit forms and spelling, then flag what still fails. Back to step 2.
  5. Keep the original and the standardized value together
  6. Search for duplicates created by the changes
  7. Are possible duplicates reviewed and none left unexplained?If not: list them for a person to review. Back to step 6.
  8. A person approves the update of source recordsThe agent waits here for your OK.
  9. Write the approved values to the source records
  10. Cleaned file and a list of unverified addresses

How it decides

An address is standardized when it matches a reference record. Unmatched addresses are tried with variants and then flagged.

  • Match first, standardize second
  • Flag addresses with no reference match
  • Treat records at the same address and name as a possible duplicate
  • Keep the original value

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Reference source
  • Abbreviation rules
  • Duplicate match rules
  • Country settings

What keeps you in control

It always asks you first

  • A person approves the update of source records

Hard limits

  • Never overwrites source records without approval
  • Never deletes the original address

It stops when

  • Done: all addresses are verified or flagged and the update is approved
  • Stop: the reference source is not available

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA file of 8,400 customers had 7,900 matches. The agent tried variants on 500 failures and fixed 310. After standardizing, 42 pairs looked like duplicates, such as '12 Oak St Apt 2' and '12 Oak Street Unit 2'. The agent listed them for review. The reviewer merged 35, and the update was approved.

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