Why Validation Emails Don't Always Work

We stopped playing Whack-a-Mole with bad email data. Here’s what actually worked. A client came to us drowning in dirty email records (invalid domains, typos, embedded newlines, the works) Their sync kept breaking. Their team kept patching. Do we flipped the Allowlist Logic Stop blocking bad. Start allowing only good. No more chasing every .comf, .netcom, .prooo variant, we built an allowlist of legitimate TLDs we actually expect to see. Unknown domain = Flag it. Known typo = Auto-reject. Anything in the gray zone = One human review, then move on Also added a single line before validation: REGEXP_REPLACE(contact_value, '[[:space:]]+', '') (strips embedded newlines before they ever touch the regex. Result = automatic approvals on clean emails, a tiny human-confirmation queue on edge cases, and zero ongoing maintenance on bad-data patterns we haven’t seen yet. Starting with a closed system and allow Legits > Open system and blocking the flops.

Most companies' CRMs are full of dead email addresses, and it's getting worse every day 💀 We have a LOT of hard won lessons from helping sales reps find prospects for the past three years. One unexpected finding: we discovered that we couldn't just verify emails once when they entered our database. 📧 People change jobs every 3 years on average. If your database or CRM is full of work emails, that means roughly 1 in 3 email addresses goes bad every single year. If you're lucky, some portion of those emails will be catch-all, but more often they'll bounce, wrecking your domain reputation. Most companies verify email addresses once (when they enter the CRM) then never again. That's like checking if someone still lives at their address in 2021 and assuming it's still valid in 2025. The fix? Verify on send, not just on entry. 🎯 Real-time email verification catches: → Job changes → Company email policy updates → Typos that slipped through initial validation → Domains that went offline Your email deliverability and sender reputation will thank you.

3 weeks ago, we took 100.000 validated emails to see if they *actually* belong to that person. The result? Only 74% actually did. The takeaway: Even if an email is flagged as valid by a verification tool, 26% of the times it does *not* actually belong to the person you want to reach out to. Let me explain. If a company uses a common email pattern (like first initial + last name): Let's say j.fischer(at)amazon(dot)com And you’re looking for a John Fischer, you could easily end up with a valid email - but it belongs to Jason Fischer, not John Fischer. John Fischer's email, as he joined the company later than Jason, might be: jo.fischer(at)amazon(dot)com And trust me, there are a lot of these cases there. This is how an algorithm email-finder works (most are like that). They try out multiple possible combinations to find the pattern. However, they search until a valid email is found. But not necessarily the one that belongs to the right person. That's why we’ve integrated more and more email database providers. As the databases sourced their data from real-world usage like verified email interactions or opt-ins. Rule of thumb: the bigger the company you want to find an email for, the more likely you’ll face this issue. What are you using to find emails? Algos or databases? 👇 P.S. We conducted the verification in multiple layers - checking the email signature, responses, scraping social profiles etc.