Why the problem matters
Most TAM/SAM/SOM calculations rely on lagging indicators: LinkedIn profiles that haven't been updated in months, enrichment databases built on stale or inferred data, and tools that prioritize coverage over accuracy.
The result is a distorted view of your market. You think you're targeting 10,000 potential buyers — but in reality, only a fraction of those roles actually exist or are reachable.
This creates a cascade of downstream problems. Outbound effort goes to non-existent roles. ABM campaigns are built on false assumptions. Forecasts get inflated by contacts who will never respond because they're no longer there.
In other words: you're optimizing strategy on top of bad data. And bad data doesn't just reduce efficiency — it kills precision.
The core distinction: probabilistic vs. deterministic market sizing
Traditional market sizing is probabilistic. You estimate based on what you can observe: headcount data, job postings, industry reports.
SMTP probing makes parts of that model deterministic. Instead of asking "How many engineers does this company probably have?", you ask "How many engineers can I verify actually exist — right now?"
That's a meaningful shift for ABM and competitive intelligence. A role that existed in Q1 may not exist today. A department that appeared in a LinkedIn search may have been restructured. SMTP verification reflects the current state of the inbox, not a snapshot from six months ago.
Step-by-step: refining TAM, SAM, and SOM with real-time probing
Step 1: Identify your target roles
Start with the job functions relevant to your ICP: engineering leads, sustainability officers, finance decision-makers — whatever roles you're targeting at a given account tier.
Step 2: Generate email permutations
Most companies use predictable email formats. Generate permutations for each target role at each account:
firstname@company.comf.lastname@company.comfirstname.lastname@company.comfirstnamelastname@company.com
For functional departments rather than named individuals, test role-based aliases:
engineering@company.comsustainability@company.comesg@company.comhr@company.com,hr1@company.com,hr2@company.com
Abstract's Bulk Email Verification lets you run these permutations at scale — thousands of addresses across entire account lists in a single batch request.
Step 3: Run verification and interpret results
The API contacts the target mail server directly via SMTP and returns a response for each address. The fields that matter most for market intelligence:
FieldWhat it tells youis_smtp_valid: trueThe inbox exists and is activedeliverability: DELIVERABLESafe to send; high confidence the address is realdeliverability: RISKYAddress exists but has risk signals (catch-all domain, recently created)is_disposable_email: trueTemporary address; likely not a real employee
If you generate 100 email permutations for engineering roles at a target account and 40 return is_smtp_valid: true with DELIVERABLE status, you now have a verified floor: at minimum, 40 engineers in that function with active, reachable inboxes. That's more actionable than a LinkedIn headcount estimate, which may include contractors, alumni, and roles that were never backfilled.
Step 4: Run a catch-all control test first
Before interpreting your results, you need to know whether the target domain is a catch-all server — one that returns "valid" for every address, regardless of whether the inbox actually exists.
The test is simple: ping a nonsensical address at the target domain before running your real permutations.
asdfghjkl123@targetcompany.com
If that address comes back as DELIVERABLE, the server is a catch-all. Your verification results for that domain aren't conclusive — the server confirms everything. Flag those accounts separately and don't count them as verified floors in your TAM model.
If the nonsensical address comes back as UNDELIVERABLE, the server rejects unknown addresses. That means your positive results are real.
This one step separates useful intelligence from noise.
Step 5: Analyze and refine your market model
Once you have verified results across your account list, you can build a more precise SAM:
- Replace estimated headcounts with verified inbox floors
- Identify which accounts have active presence in the departments you're targeting
- Deprioritize accounts where most permutations return invalid (the function may not exist, or the company may use a different email format)
- Flag catch-all domains for manual follow-up rather than bulk outreach
The output isn't a clean list — it's a tiered account map based on verified organizational reality.
Mapping departments that don't appear in org charts
Some functions don't show up in LinkedIn or enrichment databases: sustainability teams, internal ventures, special projects, newly formed units. You can probe for their existence before investing in full outreach sequences.
Test functional aliases:
sustainability@company.com
esg@company.com
innovation@company.com
ventures@company.com
A valid SMTP response on sustainability@ tells you the function exists and is monitored. That's useful signal before you build a campaign around it. A bounce tells you not to waste the sequence.
You can also estimate department density by testing indexed formats (hr1@, hr2@, hr3@). The point at which the server starts returning invalid responses gives you a rough floor on team size within that function.
Scaling this with Abstract's Bulk Email Verification
Manual verification doesn't scale, and more importantly, it doesn't generate usable intelligence fast enough to act on.
Abstract's Bulk Email Verification processes thousands of permutations across entire account lists or industry segments in minutes. Because it hits mail servers directly via SMTP rather than querying a cached database, results reflect current organizational reality — not a snapshot from the last time the database was refreshed.
For RevOps teams using this for TAM/SAM/SOM refinement, that distinction matters: you're not cleaning a list, you're auditing a market.
How it fits into your existing stack:
- Export your target account list from your CRM or ABM tool
- Generate email permutations in a spreadsheet or via script
- Run the batch through Abstract's Bulk Email Verification endpoint
- Import verified results back into your CRM, segmented by deliverability status
- Use verified floors as inputs to your market sizing model
Practical use cases
Conclusion: from estimation to verification
Most market sizing models are probabilistic by necessity — you estimate based on what you can observe. SMTP-level verification makes parts of that model deterministic. You stop guessing how many engineers a competitor has and start knowing which ones have active inboxes.
The catch-all control test takes 30 seconds. The permutation logic is straightforward. And the output — a tiered account map based on verified organizational reality — is more useful than any enrichment database snapshot, because it reflects what's true today.
That's the edge: not better data sources, but a different kind of verification that runs in real time.
Get started
Run your first existence test with Abstract's Bulk Email Verification. Free plan includes 100 requests per month — no credit card required.
For implementation details, see the Email Validation API documentation.
