Your market is bigger than your database.
A GTM engineering and RevOps team that finds the accounts your database misses and wires them into your CRM.
Illustration: vendor databases cover venture-backed software and mid-market tech well, but trades, franchise networks, licensed professionals, and regional operators are mostly missing until they are sourced directly from license registries, permit filings, franchise and dealer locators, licensing boards, directories, and marketplaces.
Where are you stuck?
Pick the one that sounds like your team.
What's actually going on
If your model says 40,000 accounts but your database surfaces 4,000, the gap is the index's blind spot, not your market. Mainstream tools plateau near 78–84% coverage on well-documented segments and fall away sharply elsewhere, so any sizing built on one of them undercounts. Datum maps and captures your entire real TAM from primary sources (registries, directories, marketplaces, filings), dedupes it into a defensible account universe, and scores it. You get a market you can plan territories against and show a board, not a number that quietly excludes most of your buyers.
You'll recognize it when
- TAM vs. reality gapThe market is obviously bigger than what your tools return, and nobody can explain the difference.
- Territory planning stallsReps run out of named accounts that clearly exist in the wild. They've driven past them.
- The number won't defendYour addressable market can't be justified past the database it came from, which makes board conversations uncomfortable.
- Segments look emptyA vertical you know is real returns a handful of rows, and the handful are the largest players only.
What's actually going on
A data-poor market is one the major databases barely index: trades, regional operators, niche verticals, net-new categories. There, single-source coverage that already plateaus near 78–84% on mainstream B2B collapses further, and reps burn weeks on lists that mostly don't exist. Datum sources the market at its real origin (directories, registries, marketplaces), then enriches, verifies, scores, and wires it into your CRM. Your reps work scored accounts no competitor can even find, instead of fighting over the same picked-over exports everyone else in your category bought.
You'll recognize it when
- Exports come back thinYour ICP filter returns a few hundred rows when the real market is tens of thousands.
- Reps research by handThe team copies data off websites manually because no tool has it, and quietly builds private spreadsheets.
- Generic tools underperformOff-the-shelf data simply doesn't cover the accounts you sell to, at any price tier.
- Everyone has the same listYou and your competitors are working identical exports, so the contest is who calls first rather than who targets better.
What's actually going on
Lean teams feel the data problem first and have the least capacity to fix it. Mapping a TAM, building scoring, wiring enrichment into the CRM, and standing up automations spans data engineering, analytics, and CRM administration: three skill sets one junior hire rarely has, against data that decays about 30% a year whether or not anyone is maintaining it. Instead of juniors who take months to ramp, you embed senior operators with 20+ years of combined GTM experience. We build and run the systems, so a small team operates like one with a full bench.
You'll recognize it when
- Founder-led GTMThe founder is still running prospecting between everything else, and it's the first thing dropped in a busy week.
- Tool sprawl, no systemYou're paying for three data tools and still copy-pasting between them.
- Hiring is the bottleneckYou can't justify a senior RevOps hire yet, and juniors would need managing by someone who's also busy.
- Nobody owns the CRMEveryone edits it, no one maintains it, and reporting is already something people argue with.
What's actually going on
Large teams already own a licensed database, a CRM, and a warehouse, and still have coverage holes, decaying records, and manual work nobody has time for. Because B2B data decays about 30% a year, even a well-funded stack degrades between refreshes. Datum augments what you have rather than replacing it: we capture the segments your licensed data misses, chain providers to lift match rates past the 78–84% single-source ceiling, score on your own outcomes, and build agents that fit your governance. Output lands in your systems, with documented provenance on every record.
You'll recognize it when
- Coverage gaps persistWhole segments are thin even with enterprise data contracts at $12k–$80k a year.
- Decay outpaces refreshRecords go stale faster than anyone can maintain them, and nobody can say how stale.
- Engineering is the bottleneckData and RevOps work waits behind product priorities, quarter after quarter.
- Provenance is unknownNobody can say where a given field came from or when it was last verified.
- Shadow spreadsheetsTeams maintain private lists because they don't trust the system of record.
What's actually going on
Agencies live or die on the data behind their campaigns. When a client sells into a market your tools don't cover, results stall and churn follows. Rebuilding data ops per account destroys the margin that made the account worth taking. Datum is the sourcing and systems layer behind your delivery: we handle the hard ICPs, the provider chaining, the scoring, and the CRM and reporting wiring, so your team keeps strategy and the client relationship. Off-the-shelf data plateaus near 78–84% on the easy markets and far lower on the hard ones: exactly where accounts are won or lost.
You'll recognize it when
- ICP varies per clientEach account needs different data you don't have on hand, and nothing carries over.
- Results stall on coverageCampaigns underperform because the underlying data is thin, but the post-mortem blames the creative.
- Delivery doesn't scaleAdding clients means re-solving data ops every time, at full cost.
- You're declining good accountsHard ICPs get turned away because you can't confidently deliver on them.
Four services that run as one system
Each works alone. In order, they turn a market you can't buy into pipeline.
Stage 1
Map
Define the ICP from who actually closes, then capture the whole market as data.
TAM mapping & prospecting dataStage 2
Build
Enrich, score, and automate: the agents and software around the data.
AI agents & custom softwareStage 3
Report
Wire HubSpot or Salesforce into reporting you can forecast against.
RevOps integrations & reportingStage 4
Execute
Embed with your reps and iterate until the accounts close.
Embedded pipeline management
Three ways to get this built
Buy more tools, hire someone, or embed a senior team (20+ years of combined experience).
| Buy more toolsZoomInfo, Clay, Outreach | Hire in-houseA RevOps / GTM engineer | Embed DatumGTM engineering, executed | |
|---|---|---|---|
| Your real TAM | Only what's already in the index | As far as one person can map it | We map and capture all of it |
| Time to first pipeline | However long you take to build it | 3–6 months to hire and ramp | We execute from week one |
| Who runs it day to day | Your reps, off the side of their desk | One seat, one point of failure | Embedded with your reps, in your Slack |
| Reporting | Dashboards you wire up yourself | If they get to it | RevOps reporting, actually analyzed |
| When it breaks | Your problem | Their problem, then yours | We own it and iterate |
What we build against
Industry benchmarks, not Datum results.
One database tops out at 78–84% accuracy. Chaining providers clears 90%+.
How waterfall enrichment worksAbout 3 in 10 contact records go wrong within a year, mostly because people change jobs.
Why B2B data decaysTeams that use AI to help reps see 2.8× the pipeline of teams using it to replace them.
What GTM engineering is
- When is scraping the right solution?4 min
- What is GTM engineering?6 min
- Does lead scoring actually work?7 min
- What is waterfall enrichment?6 min
- Why your B2B data decays about 30% a year7 min
- How much does B2B data enrichment cost?7 min
- How to choose a B2B data sourcing partner7 min
- What does done-for-you data enrichment actually mean?6 min
Common questions
A GTM engineering agency builds the data, software, and automation systems behind a go-to-market motion instead of adding headcount. Datum maps your real TAM, sources and enriches the accounts databases miss, scores them on your closed-won history, builds AI agents and automations for the busywork, and wires it all into HubSpot or Salesforce with reporting on top.
Those are tools and databases: they cover what is already in an index and leave the configuration to you. Datum is the team that builds and runs the system. We buy data where it is well covered, source the gaps at the origin, and chain providers so a single-source ceiling near 78–84% accuracy becomes 90%+ match.
No. Everything Datum builds is pre-outreach: the market map, the data, the scoring, the CRM and reporting. Your reps own the conversations. We embed alongside them and tune the system on what they learn.
Teams selling into markets databases cover poorly (trades, franchise and dealer networks, licensed professionals, regional operators) and lean teams that need GTM engineering without hiring a full data team. If you sell to mainstream software companies and trust your list, you probably don't need us yet.
Everything is built inside your stack: your CRM, your warehouse, your accounts. How each build is owned and handed off is scoped per engagement rather than promised as a blanket policy, and every record carries its provenance.
A 30-minute working session, not a pitch. We look at who actually closes for you, estimate how much of your market is sourceable, and tell you straight if you don't need us. We reply within one business day.
Something else? Email us. We reply within one business day.
Book a discovery call
Thirty minutes, no deck. We'll tell you how much of your market is sourceable.
We reply within one business day. Or email david@datumpipelines.com