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2026 年如何用 Apify 從 Google Maps 擷取商家資料並建立潛在客戶名單

How to Scrape Google Maps into a Lead List in 2026 (No Code Required)

AI 導讀

這篇教學示範如何用 Apify 的 Google Maps actor 配合 AI 智能體，擷取商家聯絡資料並整理成潛在客戶名單。該 actor 會瀏覽商家網站提取電郵和社交媒體資料，文章亦示範以 Python 匯出 CSV，並介紹 Agent Skills 套件 g4dr/apify-skills。作者提醒需遵守 GDPR、CAN-SPAM、退訂要求及平台服務條款，不要重新發布個人資料。

正文

You need a list of plumbers in Manchester, dentists in Miami, or roofers in Lyon — with phones, emails, and websites. Doing it by hand takes days. Writing a scraper takes hours... until Google rate-limits you into CAPTCHA hell.

Here's the 2026 way: run a maintained Apify actor that handles proxies, pagination, and anti-blocking — then let your AI agent do the plumbing.

The stack

  • Apify — actor marketplace with ready-made Google Maps scrapers. Free tier includes monthly credits — enough to test this end-to-end.
  • Your AI agent (Claude Code, Cursor, Codex...) — runs the pipeline via a skill that knows the actor inputs.

No proxies to configure. No headless browser tuning.

Step 1 — Get your API token

  1. Create an Apify account (free credits included)
  2. Console → Settings → Integrations → copy your API token
  3. export APIFY_TOKEN=your_token

Step 2 — Run the lead-extraction actor

The lukaskrivka/google-maps-with-contact-details actor doesn't just grab businesses — it visits each website and extracts emails and social profiles automatically:

curl -X POST "https://api.apify.com/v2/acts/lukaskrivka~google-maps-with-contact-details/run-sync-get-dataset-items?token=$APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{
    "searchStringsArray": ["dentist"],
    "locationQuery": "Miami, FL",
    "maxCrawledPlacesPerSearch": 100,
    "language": "en"
  }'

You get back a JSON array with title, phone, website, emails, address, totalScore, reviewsCount, categoryName.

Step 3 — Clean lead CSV with Python 

from apify_client import ApifyClient
import csv

client = ApifyClient("APIFY_TOKEN")
run = client.actor("lukaskrivka/google-maps-with-contact-details").call(run_input={
    "searchStringsArray": ["plumber"],
    "locationQuery": "Austin, TX",
    "maxCrawledPlacesPerSearch": 200,
})

with open("prospects.csv", "w", newline="") as f:
    w = csv.writer(f)
    w.writerow(["business", "phone", "email", "website", "rating", "reviews"])
    for p in client.dataset(run["defaultDatasetId"]).iterate_items():
        if p.get("phone") or p.get("emails"):
            w.writerow([
                p["title"], p.get("phone", ""),
                (p.get("emails") or [""])[0],
                p.get("website", ""), p.get("totalScore", ""),
                p.get("reviewsCount", ""),
            ])

Dedupe by website or phone, filter for totalScore >= 3.5 — and you have a clean outreach list.

Bonus: let your agent run it for you

I packaged this (plus 7 other scraping patterns — jobs, Amazon, social, SERP) as Agent Skills:

npx skills add g4dr/apify-skills

After installing, tell Claude Code "get me all roofers in Birmingham" — it picks the right actor, builds the run input, and hands you the data. Full repo: g4dr/apify-skills.

For the bigger picture (proxies, headless browsers, niche actors), I maintain an awesome-web-scraping list.

Compliance note

Google Maps data is public business info — but respect GDPR and outreach laws (CAN-SPAM, opt-outs). Scrape public data, don't republish personal info, and honor platform ToS.

Questions? Drop them in the comments — happy to share run inputs for specific niches.

來源：DEV Community · dev.to

#教學/實踐#Agent