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Hunter returns a result with 62% confidence. Send or skip? This walks through the diagnostic — what the score really means, when low-confidence is workable, and when to find a different path.
Who this is forSDRs and growth teams running cold outreach. If 30%+ of your Hunter results are below 80% confidence, this tutorial saves you from sending to bouncing addresses.
What you'll need
Step 1
Confidence = pattern match + source signals. NOT verified deliverability. Always verify after Email Finder.
Hunter's confidence score combines: (1) match against the company's email pattern, (2) public-web sources confirming this specific email (LinkedIn, GitHub, blog posts), (3) recent verification status.
A 95% score means Hunter is highly confident in the pattern + has multiple sources. Does NOT guarantee the mailbox exists today.
A 65% score means Hunter found a likely pattern but no public-web source confirms this specific email. The mailbox may or may not exist.
Rule: confidence is a probability, not a verification. Always verify before sending.
Step 2
For each <80% confidence result, click Verify. Hunter's SMTP check is independent of the confidence score.
In the Email Finder result, click "Verify" on each low-confidence email.
Three possible outcomes: Valid (safe to send despite low confidence), Invalid (skip), Accept-all/Unknown (treat as risky).
A low-confidence Valid email is workable for warm-leaning outreach. Skip for true cold.
Each verification costs 1 verification credit. Worth it for important contacts.
Step 3
Use the Hunter Chrome extension on the prospect's LinkedIn profile. If LinkedIn surfaces a higher-confidence pattern, trust that.
Open the prospect's LinkedIn profile.
Click the Hunter extension icon.
Compare the extension's suggested email + confidence to the Email Finder result.
If LinkedIn confidence is higher, use that email.
If both are low, this person's email may simply not be in Hunter's index.
Step 4
For high-priority contacts below 80% confidence, run the email through Apollo, Snov.io, or NeverBounce as a second opinion.
For your top 50 priority contacts: cross-verify with a second tool.
Apollo: search the company → find the person → compare returned email.
NeverBounce or ZeroBounce: run the candidate email through their verifier.
If two tools agree on Valid: high confidence. If they disagree: skip or contact via LinkedIn instead.
Step 5
Below 70% confidence + Invalid verification: skip permanently. 70-80% + Valid: warm-leaning sequences only. 80%+ + Valid: full cold sequences.
Decision matrix:
- <70% confidence, any verification: skip permanently. Risk > reward.
- 70-80% confidence, Valid: use only for warm/referral-leaning sequences with personal subject lines.
- 80%+ confidence, Valid: full cold sequences.
- 95%+ confidence, Valid: high-stakes contacts (CEOs, decision-makers worth $$$).
Stick to the matrix. The temptation to send to questionable contacts is universal and always wrong long-term.
Common mistakes
Sending to low-confidence emails to "see what happens"
What goes wrong: 20-40% bounce rate. Sender reputation tanks. Future legitimate sends land in spam. Recovery takes 60-90 days.
How to avoid: Below 70%, skip. The data is not worth the deliverability damage.
Trusting confidence score as verification
What goes wrong: You send to 95% confidence emails without verifying. 5-10% bounce because the score is probability, not certainty.
How to avoid: Always verify before sending, regardless of confidence. Verification is independent and binary.
Not cross-checking with LinkedIn extension
What goes wrong: Email Finder returns 65%. You skip. LinkedIn extension would have surfaced 92% from the same source data. Lost contact for no reason.
How to avoid: For high-priority contacts, always run the LinkedIn extension as a second check.
Verifying only some low-confidence results
What goes wrong: You verify the easy ones. The hard ones (top decision-makers) stay unverified. You send to questionable execs and damage relationships.
How to avoid: Verify ALL results before adding to a sequence. The 1-2 verification credits per contact are the cheapest insurance.
Blaming Hunter for a bad source list
What goes wrong: 30% of your Hunter results are <70% confidence. You blame Hunter. The real issue is your prospecting source (scraped list, old Apollo export) is full of stale data. Switching tools will not fix it.
How to avoid: If 30%+ confidence is low, the input list is the problem. Re-source from a more recent provider.
Recap
Done — what's next
How to use Hunter.io Email Verifier to clean cold email lists
Read the next tutorial
Hand it off
Cleaning low-confidence results is tactical work. Running an entire outreach program with proper hygiene is a job. A vetted specialist will own the hygiene + outreach pipeline. From $14-16/hr.
See specialist rates
Three causes: (1) small company with little public data, (2) recent hire not yet in Hunter's index, (3) the person uses a unique email pattern not shared by colleagues. Each requires a different workaround.
Both matter. Valid = deliverable today. 95% confidence = pattern + sources agree. Together, they are the gold standard. Either alone is incomplete.
70-85% on common patterns (first.last@, first@). Lower on unique patterns (initials, numbers). Always verify pattern-guesses.
For your top 20-50 priority contacts where a bad send damages the relationship. Cross-verify with Apollo, Snov.io, or NeverBounce.
No direct way. Hunter's confidence is based on its index. You can verify externally and trust your verification. Or contact the person via LinkedIn first to confirm the email.
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