Back to Skills

standardize-geo-values

TomGranot
Updated 2 days ago
3 views
33
11
33
View on GitHub
Othergeneral

About

This skill standardizes inconsistent country and state/region formats (like "US" vs "USA") to ensure reliable geographic segmentation in contacts and companies. It's used after initial data hygiene to clean records for accurate filtering and reporting. Developers should apply it when preparing data for region-specific campaigns or analytics.

Quick Install

Claude Code

Recommended
Primary
npx skills add TomGranot/hubspot-admin-skills -a claude-code
Plugin CommandAlternative
/plugin add https://github.com/TomGranot/hubspot-admin-skills
Git CloneAlternative
git clone https://github.com/TomGranot/hubspot-admin-skills.git ~/.claude/skills/standardize-geo-values

Copy and paste this command in Claude Code to install this skill

Documentation

Standardize Country and State/Region Values

Convert inconsistent geographic formats (e.g., "US", "USA", "U.S." vs "United States"; "NY" vs "New York") to a single standard format across all contact and company records.

Why This Matters

Inconsistent geo values break geographic segmentation. A list filtering for "United States" will miss contacts labeled "US" or "USA". For B2B companies running region-specific campaigns or reporting by geography, this means inaccurate audience sizes and missed contacts.

Prerequisites

  • Phase 1 hygiene processes completed (invalid/deleted contacts removed first)
  • Access to Contacts and Companies views with bulk edit permissions
  • Key constraint: If your CRM integrates with another system (e.g., Salesforce, marketing automation), agree on the standard format (full names vs. ISO codes) with that system's admin BEFORE standardizing. Mismatched formats between synced systems will cause ongoing data conflicts.
  • Decision on standard format. This skill recommends:
    • Countries: Full names (e.g., "United States", "United Kingdom")
    • States (contact level): Full names (e.g., "New York", "California")
    • This matches HubSpot's default form behavior

Interview: Gather Requirements

Before executing, collect the following information from the user:

Q1: What format do you prefer for country values -- full names (United States) or ISO codes (US)?

  • Examples: Full names ("United States", "United Kingdom"), ISO 2-letter codes ("US", "GB"), ISO 3-letter codes ("USA", "GBR")
  • Default: Full names (e.g., "United States", "United Kingdom") -- this matches HubSpot's default form behavior

Q2: Do you have a Salesforce or other CRM integration that requires a specific format?

  • Examples: "Yes, Salesforce uses ISO 2-letter codes", "Yes, our ERP uses full country names", "No integrations to worry about"
  • Default: No integration constraints -- use HubSpot's default full-name format

Plan

  1. Audit all non-standard country and state values (before state)
  2. Build a mapping table of variants to standard values
  3. Batch update via API script or manual bulk edit in HubSpot UI
  4. Prevent future inconsistencies by configuring property types and forms
  5. Verify all values are standardized (after state)

Before State

API Audit Script

import os
from hubspot import HubSpot
from dotenv import load_dotenv

load_dotenv()
api_client = HubSpot(access_token=os.getenv("HUBSPOT_API_TOKEN"))

# Check for common country variants
variants = ["US", "USA", "U.S.", "U.S.A.", "America"]
for variant in variants:
    result = api_client.crm.contacts.search_api.do_search(
        public_object_search_request={
            "filterGroups": [{
                "filters": [{
                    "propertyName": "country",
                    "operator": "EQ",
                    "value": variant
                }]
            }],
            "limit": 0
        }
    )
    if result.total > 0:
        print(f"Contacts with country = '{variant}': {result.total}")

# Repeat for companies
for variant in variants:
    result = api_client.crm.companies.search_api.do_search(
        public_object_search_request={
            "filterGroups": [{
                "filters": [{
                    "propertyName": "country",
                    "operator": "EQ",
                    "value": variant
                }]
            }],
            "limit": 0
        }
    )
    if result.total > 0:
        print(f"Companies with country = '{variant}': {result.total}")

Manual Audit

  1. Go to Contacts > filter by Country/Region > is any of > "US". Note count.
  2. Repeat for "USA", "U.S.", and any other suspected variants.
  3. Repeat at the company level.
  4. For states: filter by State/Region > is any of > "NY", "CA", "TX" to check for abbreviation variants.

Record all variant counts as your baseline.

Execute

Method 1: API Batch Update (Recommended for Large Volumes)

# Pattern: Build mapping table, search for each variant, batch update

COUNTRY_MAPPING = {
    "US": "United States",
    "USA": "United States",
    "U.S.": "United States",
    "U.S.A.": "United States",
    "America": "United States",
    "UK": "United Kingdom",
    "GB": "United Kingdom",
    "Great Britain": "United Kingdom",
    # Add other mappings as discovered in your audit
}

STATE_MAPPING = {
    "NY": "New York",
    "CA": "California",
    "TX": "Texas",
    "FL": "Florida",
    "IL": "Illinois",
    "PA": "Pennsylvania",
    "OH": "Ohio",
    "GA": "Georgia",
    "NC": "North Carolina",
    "NJ": "New Jersey",
    "VA": "Virginia",
    "WA": "Washington",
    "MA": "Massachusetts",
    "AZ": "Arizona",
    "CO": "Colorado",
    "MD": "Maryland",
    "MN": "Minnesota",
    "MO": "Missouri",
    "WI": "Wisconsin",
    "CT": "Connecticut",
    "OR": "Oregon",
    "SC": "South Carolina",
    "LA": "Louisiana",
    # Add all 50 US states + territories as needed
}

# For each mapping:
# 1. Search for contacts with the variant value
# 2. Collect all matching contact IDs (paginate if > 100)
# 3. Batch update using crm.contacts.batch_api.update
# 4. Repeat for companies using crm.companies

API notes:

  • Search API caps at 10,000 results per query. Unlikely to hit this for geo variants, but segment if needed.
  • Batch update accepts up to 100 records per call.
  • Rate limit: 100 requests per 10 seconds.

Method 2: Manual Bulk Edit in HubSpot UI

For each variant:

  1. Go to Contacts > Lists > Create list (static)
  2. Filter: Country/Region > is any of > [variant value]
  3. Save list
  4. Select all contacts in the list
  5. Click Edit > Country/Region > type the standard value > Update
  6. Repeat for each variant

For companies, do the same from the Companies view using filters and bulk edit.

Prevent Future Inconsistencies

After standardizing existing data:

  1. Go to Settings > Properties > Contact properties
  2. Search for Country/Region
  3. Verify it is a Dropdown select field (not free text). If it is free text, consider converting to dropdown with standard country names.
  4. Repeat for State/Region (though state may need values for multiple countries, making a dropdown less practical)
  5. Check all active Forms (Marketing > Forms):
    • Verify country and state fields are dropdown fields, not free text inputs
    • Verify dropdown values match your standardized format
  6. Check any import templates used by the team to ensure they reference standard values

After State

# Re-run the same variant checks from before state
variants = ["US", "USA", "U.S.", "U.S.A.", "America"]
for variant in variants:
    result = api_client.crm.contacts.search_api.do_search(
        public_object_search_request={
            "filterGroups": [{
                "filters": [{
                    "propertyName": "country",
                    "operator": "EQ",
                    "value": variant
                }]
            }],
            "limit": 0
        }
    )
    assert result.total == 0, f"Still have {result.total} contacts with '{variant}'"
    print(f"Contacts with country = '{variant}': {result.total} (should be 0)")

Verification checklist:

  1. All known variant values return 0 contacts and 0 companies
  2. The standard value count should equal the sum of (previous standard count + all variant counts)
  3. Spot-check 10 contacts that were in cleanup lists to verify values are now standardized
  4. For states: filter by common abbreviations (NY, CA, TX) and confirm 0 results
  5. Forms are configured to prevent future inconsistencies

Key Technical Learnings

  • Do not touch blank/empty values in this process. Filling in missing country data is a separate enrichment task. This process only standardizes existing values that are non-empty but non-standard.
  • Coordinate with integrated systems first. If HubSpot syncs with Salesforce or another CRM, mismatched formats cause sync conflicts. Agree on the standard format before changing anything.
  • Company-level state abbreviations may be acceptable. HubSpot's default behavior for company State/Region often uses abbreviations. Decide whether to standardize company states or leave them as-is.
  • Root cause matters as much as cleanup. The variants were likely created by imports, API integrations, or free-text form fields that bypassed dropdowns. Fixing the root cause (forms, import templates, integration mappings) is as important as fixing existing data.
  • Export before editing (optional safety measure). Before bulk editing, export affected contacts/companies with their current values as a backup CSV.
  • Bulk edit limits vary by plan. HubSpot may limit bulk edits to certain batch sizes (100-250 at a time). For large numbers, you may need to repeat the select-all-and-edit process multiple times, or use the API approach instead.

GitHub Repository

TomGranot/hubspot-admin-skills
Path: skills/standardize-geo-values
0

Related Skills

llamaguard

Other

LlamaGuard is Meta's 7-8B parameter model for moderating LLM inputs and outputs across six safety categories like violence and hate speech. It offers 94-95% accuracy and can be deployed using vLLM, Hugging Face, or Amazon SageMaker. Use this skill to easily integrate content filtering and safety guardrails into your AI applications.

View skill

cost-optimization

Other

This Claude Skill helps developers optimize cloud costs through resource rightsizing, tagging strategies, and spending analysis. It provides a framework for reducing cloud expenses and implementing cost governance across AWS, Azure, and GCP. Use it when you need to analyze infrastructure costs, right-size resources, or meet budget constraints.

View skill

quantizing-models-bitsandbytes

Other

This skill quantizes LLMs to 8-bit or 4-bit precision using bitsandbytes, achieving 50-75% memory reduction with minimal accuracy loss. It's ideal for running larger models on limited GPU memory or accelerating inference, supporting formats like INT8, NF4, and FP4. The skill integrates with HuggingFace Transformers and enables QLoRA training and 8-bit optimizers.

View skill

dispatching-parallel-agents

Other

This Claude Skill dispatches multiple agents to investigate and fix 3+ independent problems concurrently. It is designed for scenarios involving unrelated failures that can be resolved without shared state or dependencies. The core capability is parallel problem-solving, assigning one agent per independent problem domain to maximize efficiency.

View skill