Scrap.io collects Google Maps data as you browse.
Scrap.io is a Maps-native Chrome extension. Instead of submitting a batch job and waiting, you browse Google Maps and Scrap.io collects records in real time. For each business with a linked website, the extension visits that site and extracts email addresses from public pages.
The result is a spreadsheet of local business contacts built alongside your normal browsing session. The export includes business name, address, phone, website, email addresses, and social media profile links where available.
Scrap.io is the collection layer. BillionVerify is the quality decision layer. Both steps are required before records enter outreach.
Google Maps Email Scrape and Email Verify
Use the full framework when you need the complete path across data scraping, email verification, routing, and outreach.
What Scrap.io can export.
Scrap.io produces structured Google Maps business records enriched with website contact data. Fields depend on what each business publishes publicly.
| Field group | Common fields | Why it matters |
|---|---|---|
| Business data | Name, category, rating, review count | Helps filter records by vertical or quality signal |
| Location data | Address, city, phone number | Supports geographic or territory targeting |
| Contact data | Email addresses from contact, about, and footer pages | The column that needs verification before use |
| Social data | Facebook, Instagram, LinkedIn, YouTube, X profiles | Supports multi-channel outreach when email is uncertain |
| Maps data | Website URL, Google Maps listing source | Helps trace, deduplicate, and validate records |
Google Maps does not surface email addresses directly. In every Scrap.io workflow, the email comes from the linked business website.
Emails need a quality gate.
Scrap.io finds contact data visible on business websites. It does not evaluate whether those emails are current, reachable, or useful for outreach.
| Problem | What it looks like | Pipeline risk |
|---|---|---|
| Role-based inboxes | info@, contact@, office@, hello@, enquiries@ | Customer-facing inbox, not a decision-maker |
| Catch-all domains | Domain accepts all mail regardless of username | Specific mailbox existence is uncertain |
| Stale emails | Old staff, ownership change, site not updated | Address may still accept mail but no one reads it |
| Invalid addresses | Broken domain, no MX, rejected mailbox | Hard bounce on send |
| Multi-email records | Several addresses per business | Role-based and personal addresses mixed in one export row |
| Contact-form-only sites | No displayed email, form instead | Scrap.io returns no email for these records |
Scrap.io does not run deliverability checks, catch-all detection, or role-based analysis. Those require a dedicated verification step.
Put verification after the export.
The right place to verify is after Scrap.io produces the CSV and before records enter any sending tool or CRM.
- Run a Scrap.io browsing session for the target category and geography.
- Use Scrap.io filters to restrict to businesses with emails and websites.
- Export the list as CSV.
- Normalize — one email per row where the tool returns multiple per record.
- Remove exact duplicates at the email and domain level.
- Verify emails with BillionVerify.
- Join verification results back to the original export rows.
- Route each row by result.
- Sync only approved rows to the CRM, sender, or automation.
Scrap.io stays responsible for collection. BillionVerify stays responsible for the quality decision.
Use CSV for batch cleanup.
CSV is the natural workflow for Scrap.io, which produces per-session exports rather than continuous automated output.
| Step | What to do |
|---|---|
| Export | Download the Scrap.io session export as CSV |
| Normalize | Expand multi-email fields — one address per row |
| Deduplicate | Remove repeated emails, domains, phone numbers |
| Verify | Upload the email column to BillionVerify |
| Join | Add verification result columns back to the original file |
| Import | Move only approved or segmented rows into the next system |
CSV is easy to inspect. It is useful when testing a new target geography or vertical before committing to a larger extraction effort.
Use multi-email data to find better contacts.
Scrap.io captures all email addresses it finds on a business website, not just the first one. A business with a generic contact@ on its homepage may also list a named employee email on its team page.
When Scrap.io returns multiple addresses per record, verify each one individually. Verification will distinguish the role-based addresses from any personal or direct addresses in the same record.
| Address in export | Likely verification result | Action |
|---|---|---|
info@businessname.com | Role-based | Segment for shared-inbox outreach |
contact@businessname.com | Role-based | Segment for shared-inbox outreach |
jdoe@businessname.com | Valid, not role-based | Prioritize for primary outreach |
service@catchalldomain.com | Catch-all | Segment, send with caution |
This separation is only possible after verification. Without it, all addresses in the record look equivalent.
Route each result.
Verification changes what the pipeline does next. Apply a consistent routing decision to every record.
| BillionVerify signal | Scrap.io pipeline action | Why |
|---|---|---|
| Valid business email | Sync or keep | Appears reachable, move forward if business fits the campaign |
| Role-based but valid | Segment | Useful for some local business outreach, not a named contact |
| Catch-all | Segment or review | Domain accepts mail broadly, mailbox is uncertain |
| Invalid | Suppress | Keep out of CRM imports and senders |
| Syntax, domain, or MX issue | Suppress or fix | Technical problem with address or domain |
| Unknown or risky | Review or enrich | Do not send at scale without more context |
Build this routing logic into your import step. It should not depend on someone remembering what to do after each Scrap.io session.
Keep role-based emails separate.
A large share of Google Maps records for local businesses produce shared inboxes. An HVAC company may show service@. A dental practice may use appointments@. A law office may publish intake@ or info@.
Role-based emails are not automatically useless. They are not the same as named contacts.
Handle them separately:
- Verify the address first.
- Store the role-based signal in its own column.
- Keep role-based emails out of named-contact sequences.
- Write different copy when reaching out to a shared inbox.
- For high-value accounts, use the business domain to find direct contacts.
If the Scrap.io export only gives you info@company.com, keep the domain for later enrichment. Social profiles in the same Scrap.io record may also point to a named decision-maker through LinkedIn or Facebook.
Send or enrich next.
After verification, different records should go to different places. Do not route everything to a single destination.
| Record type | Best next step |
|---|---|
| Valid named or business email | Sync to CRM or sender |
| Valid role-based email | Segment for shared-inbox outreach with adapted messaging |
| Catch-all | Keep in a cautious segment or enrich before sending |
| Invalid email | Add to suppression list or exclude from import |
| No email but valid website or social | Keep record for multi-channel enrichment |
| Duplicate address across records | Merge or keep only the freshest record |
Scrap.io social profile data is useful here. When email is catch-all or role-based, a LinkedIn or Facebook presence may offer a better outreach path for high-priority records.
Compare other Google Maps collection paths.
Scrap.io works well when a person is actively browsing and filtering Google Maps. Other collection paths fit different list-building patterns.
Outscraper Verification
Use this path when a platform export and enrichment step create the email column.
GMaps Extractor Verification
Use this path when a lightweight extension exports a smaller local list.
Apify Verification
Use this path when Actors, datasets, APIs, or webhooks move records downstream.
Scrap.io Google Maps FAQ.
1. Does Scrap.io verify the emails it collects?
Scrap.io collects email addresses from public business websites. It does not run deliverability verification, catch-all detection, or role-based pattern analysis. Those are a separate step. Use BillionVerify after the export.
2. Is filtering by "has email" in Scrap.io enough?
Filtering to businesses that have an email removes records with no data at all. It does not evaluate whether the email found is valid, catch-all, role-based, or stale. Scrap.io filters reduce empty records; BillionVerify reduces risky records.
3. Should role-based emails from Scrap.io be removed?
Not automatically. A valid info@ or contact@ at a very small business may reach the owner directly. Segment role-based addresses separately, use adapted messaging, and decide based on the business size and vertical.
4. Should catch-all emails go into cold outreach?
Use caution. Catch-all means the domain accepts mail broadly, but the specific mailbox may not exist or be monitored. Segment catch-all records and send at lower volume than verified clean records.
5. What should I do with Scrap.io records that have no email?
Keep them. Records with social profiles, websites, or phone numbers can still be reached through other channels. Store them in an enrichment segment rather than discarding the record entirely.
6. Can I verify multiple emails per Scrap.io record?
Yes. Expand multi-email fields into separate rows before uploading to BillionVerify. Verify each address individually, then join results back and pick the best address per business record.
7. How does Scrap.io compare to platform-based tools like Outscraper?
Scrap.io runs as a Chrome extension alongside your browsing. Outscraper runs jobs in the background without active browsing. Scrap.io works well for targeted prospecting sessions. Outscraper has more capacity for large-scale or automated extraction. Both produce the same type of output and both require verification before the email column is used for outreach.
8. How often should I re-verify Scrap.io lists?
Local business contact data changes. Re-verify each new session export, and re-verify older lists before reusing them in a new campaign cycle. An address verified as clean a few months ago may have changed status.