Verifying Emails

Goal

Check addresses resolve before you send to them. Bounces damage domain reputation, and reputation is slow to rebuild.

When to use

Before any first campaign from a new domain, and any time a list is older than about a month.

Two ways

During the scrape (easiest)

If the leads came from Google Maps, verification is a flag on the scrape itself:

python -X utf8 scripts/02_local_businesses/scrape_google_maps.py \
    --search "law firms in Mobile AL" --limit 50 \
    --contacts --leads 2 --verify-emails --out-csv output/verified.csv

Each decision-maker record comes back with an emailVerification object.

On an existing list

python -X utf8 scripts/04_outreach/verify_emails_apify.py \
    --input output/leads.csv --output output/leads_verified.csv

Reading the result

Status	Do this
valid / deliverable	Send.
catch-all / accept-all	The server accepts everything, so this tells you nothing. Send, but keep these in a separate batch so a bad group doesn't poison the main one.
risky	Low volume only, or skip.
invalid / undeliverable	Remove. Do not send.

Rules of thumb

• Keep bounce rate under 2%. Above 5% and providers start filtering you.
• Verify in one batch before the campaign, not per-send.
• Never pattern-guess an address (first@company.com) and send to it unverified — that's how a domain gets burned.
• On a brand-new sending domain, warm up over 2–3 weeks before volume.

Cost

Fractions of a cent per address.