Best Way to Build a B2B Prospect List from Google Maps (Step-by-Step)

Why Google Maps is a Goldmine for B2B Prospecting

Google Maps lists millions of local businesses, and many listings include phone numbers, websites, business descriptions and sometimes links to social profiles. For B2B teams looking to generate targeted leads, Maps is a reliable source of up-to-date contact information — if you know how to pull it efficiently.

Manual copy-paste doesn’t scale. The best approach combines smart targeting, automated extraction, data cleaning, and thoughtful outreach. Below is a full step-by-step workflow you can follow today.

Common Problems with Manual Prospecting

• Slow & Error-prone: Manually opening pages and copying data introduces typos and misses fields like emails found only on business websites.
• Incomplete Coverage: A single search (e.g., “plumbers in CA”) rarely returns everything — you often need multiple queries by city or ZIP code.
• Hard to Scale: Building a list of thousands of prospects with consistent formatting is unmanageable without automation.

Step-by-Step: Build a High-Quality B2B Prospect List from Google Maps

Step 1 — Define Your Ideal Customer Profile (ICP)

Before you scrape anything, be extremely clear about who you want to reach. Define:

• Industry / vertical (e.g., dental clinics, HVAC contractors, independent coffee shops)
• Location scope (city, metro area, state, country)
• Business size proxies (e.g., number of reviews, rating, multi-location vs independent)
• Key decision roles (owner, manager, bookings contact — not every listing exposes this)

Example ICP: “Independent dental clinics in Lahore with 10+ reviews and a visible website.”

Step 2 — Create Smart Search Queries

On Google Maps, keywords + location work best. Use multiple query patterns to improve coverage:

• plumber in Chicago
• plumber Chicago IL 60601 (search by ZIP to get deeper coverage)
• IT services near Canary Wharf London

Tip: For large regions, break the area into city or ZIP-level searches. This avoids missing businesses hidden deeper in the map results.

Step 3 — Pick an Extraction Tool

Use a Google Maps scraping tool to automate collection. Manual scraping will cost hours; tools give you consistent output and exports. Recommended features to look for:

• Extracts 20+ fields (name, address components, phone, website, coordinates, rating)
• Bulk/multi-search support (upload list of search terms)
• Exports to CSV/Excel with clean column headers
• Ability to extract emails from linked business websites
• Human-like browsing to reduce the chance of being blocked

Bot tip: Botsol Google Maps Crawler provides these features — multi-search automation, 25+ fields, Excel/CSV export, and a free version to validate results.

Step 4 — Run a Small Test (Sanity Check)

Always start with a pilot: pick 3–5 searches, run the scraper, and inspect the exported CSV. Confirm:

• Columns match what you expect (phone, website, email, lat/long)
• No duplicate rows from the same listing
• Emails (if captured) are valid or point to company domains

Fix your extraction settings if fields are missing or misaligned.

Step 5 — Run Bulk Extraction Using Multi-Search Files

Prepare a plain text file with one search term per line (e.g., “restaurants in Chicago 60601”). Use your tool’s multi-search option to queue thousands of queries and let it run. If your tool supports scheduling or overnight runs, use them to minimize human oversight.

Step 6 — Clean & Enrich the Data

Raw scraped data needs cleaning:

• Normalize phone numbers: convert to international format if needed (E.164).
• Deduplicate: compare by business name + address or by coordinates.
• Email validation: run email verification to remove invalid addresses and reduce bounce rates.
• Enrich: add fields like company size, LinkedIn company page, or technology stack using third-party enrichment APIs if relevant.

Step 7 — Segment & Prioritize

Segment your list for outreach efficiency:

• High priority: businesses with websites + email + phone
• Medium: businesses with website but no visible email
• Low: listings missing contact info (use for local SEO research)

Prioritization helps tailor outreach messages and increases response rates.

Step 8 — Import Into CRM / Outreach Tools

Export final lists to CSV/Excel and import into your CRM (HubSpot, Pipedrive, Salesforce). Map columns carefully (Company, Phone, Email, City, Source) so automations and sequences work. Use tags or custom fields to record the search query and date scraped for future segmentation.

Step 9 — Outreach Best Practices

• Personalize: reference a local detail (city, recent review) in the first sentence.
• Keep it short: 2–3 sentences, clear value proposition.
• Stagger sends: avoid blasting thousands of emails at once — throttle by small batches.
• Test sequences: A/B subject lines and CTA types (call, demo, download)

Tools & Resources

Here are tools that support this workflow:

Practical Tips to Avoid Blocks & Improve Data Quality

Respectful scraping

Don’t scrape aggressively. Configure delays, randomized pauses, and keep batch runs reasonable. Tools that mimic human browser behaviour and paginate like a user will face fewer restrictions.

Split large regions

Large geographic areas (e.g., entire states) should be split into cities or ZIP codes. This produces more complete results and reduces missed listings.

Use sample files

Always download a sample CSV before a large run to confirm fields and format. That small check saves hours of rework later.

Why Automate with a Dedicated Tool (and Why Botsol)

Generic automation platforms or manual scraping lack dedicated support for Google Maps quirks (pagination, dynamic loading, email extraction from linked sites). Dedicated tools like Botsol focus on depth (25+ fields), reliable exports, and multi-search automation — which translates into faster workflows and higher-quality prospect lists.