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backfill-geo-data回填地理数据

Agent Skill

用于辅助数据整理、表格处理、CSV/Excel 分析、指标计算和图表准备。它适合让 Agent 清洗字段、汇总数据、发现异常、生成统计口径或把分析结果转成可读说明。使用时需要确认数据来源、字段含义和时间范围,避免把样本数据当全量事实;涉及敏感数据、导出文件或批量写回时,应先确认权限和脱敏边界。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:backfill-geo-data(回填地理数据)
来源仓库:https://github.com/tomgranot/hubspot-admin-skills
仓库路径:skills/backfill-geo-data
安装命令:
npx skills add https://github.com/tomgranot/hubspot-admin-skills --skill backfill-geo-data
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/tomgranot/hubspot-admin-skills --skill backfill-geo-data

简介

backfill-geo-data 用于回填 HubSpot 联系人与公司缺失的地理数据,支持区域分配和合规需求。

  • 适合批量补全国家、州和城市字段,需先运行标准化流程确保数据一致性。
  • 通过 npx skills add 安装,需配置 HubSpot API token 并安装 Python 客户端库。
  • 涉及 GDPR 合规时应验证数据脱敏和地域法律要求。
  • 建议在非高峰时段执行批量操作并监控 API 配额使用情况。

SKILL.md

Backfill Geographic Data

Fill in missing country, state, and city values on contacts and companies. Geographic data enables territory assignment, regional reporting, and compliance (GDPR, state privacy laws).

Prerequisites

  • HubSpot API token in .env
  • Python with hubspot-api-client installed via uv
  • Standardized geo values already in place (run /standardize-geo-values first)

Enrichment Methods

Method 1: HubSpot Workflow Enrichment (Simplest)

Use HubSpot's built-in Operations Hub data quality tools or Breeze Intelligence (if available on your plan) to auto-fill geographic fields.

  1. Create a workflow triggered by: country is unknown AND email is known
  2. Use the "Enrich contact" action (Operations Hub Professional+) or Breeze Intelligence enrichment
  3. If enrichment fills country/state, the workflow completes
  4. If enrichment fails, branch to flag for manual review

Method 2: Company Domain Lookup (API-based)

For contacts with a company domain but no geo data, look up the company's geographic information:

from hubspot import HubSpot
from hubspot.crm.contacts import PublicObjectSearchRequest

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

# Find contacts missing country but with company association
search = PublicObjectSearchRequest(
    filter_groups=[{
        "filters": [
            {"propertyName": "country", "operator": "NOT_HAS_PROPERTY"},
            {"propertyName": "associatedcompanyid", "operator": "HAS_PROPERTY"}
        ]
    }],
    properties=["email", "associatedcompanyid"]
)

Copy country/state/city from the associated company to the contact (same pattern as /enrich-company-name).

Method 3: External Data Provider

Integrate with a third-party enrichment service (Clearbit, ZoomInfo, Apollo, etc.):

  1. Export contacts missing geo data
  2. Run through enrichment provider
  3. Import enriched data back via CSV or API

Step-by-Step Instructions

Stage 1: Before — Assess the Gap

  1. Count contacts missing country, state, and city.
  2. Segment by source — which lead sources tend to have missing geo data?
  3. Choose the enrichment method based on volume and budget.

Stage 2: Execute — Run Enrichment

  1. Apply the chosen method (or combine methods for maximum coverage).
  2. Process in batches of 100 to respect rate limits.
  3. Validate enriched values against the standardized geo format from /standardize-geo-values.

Stage 3: After — Verify

  1. Re-count contacts missing geographic fields. Calculate improvement percentage.
  2. Spot-check 20-30 enriched contacts for accuracy.
  3. Set up the new-contact hygiene workflow to prevent future gaps.

Stage 4: Rollback

  • If enrichment data is inaccurate, filter contacts updated by the enrichment process (use hs_lastmodifieddate range) and clear the geo fields.
  • Keep a backup export of the original data before running enrichment.

Tips

  • IP-based geolocation (from form submissions) is already captured by HubSpot in ip_city, ip_state, ip_country. Copy these to the standard fields if the standard fields are empty.
  • Do not overwrite manually-entered geo data with enrichment data — always check "if empty" before writing.

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