Acme is a made-up company that sells AI sales coaching. Its buyers are sales leaders. This is the page I'd build for a company like that: the market mapped, the buyers named, and a test plan for reaching them.
Acme sells to B2B companies with sales teams of 10 or more reps. Here is that market broken into segments, with the angle we would test first in each.
Sales teams of 10-60 reps, usually with a VP of Sales and a first-line manager per pod. Ramp time is the pain.
Regulated sales calls. Compliance wants every call reviewed, and managers can't listen to them all.
Inside sales reps taking reorders and quotes all day. Coaching happens rarely, if at all.
Recruiters selling to hiring managers. High turnover, so new reps need coaching fast.
This is an example page for a made-up company. Acme is fictional and every count here is a round placeholder. On a real page, counts come from company databases like Overture Maps and Loopster, and every number says where it came from.
Corporate GTM intelligence. Agency speed. AI-powered execution.
Built by someone who's carried a revenue quota, not just managed an inbox.
Most outbound agencies optimize for activity. We apply the same principles used inside corporate revenue organizations: territory planning, buyer segmentation, experimentation, pipeline accountability and revenue forecasting.
None of these disciplines are new on their own. The point is running all of them as one system, every month.
How it works
Five stages, run as a loop. Each month's results feed the next month's targeting and copy. Select a stage to see what happens in it.
Experimentation Lab
Pick a segment and a buyer, choose the angles to test, and run it. The lab splits the contacts across angles, follows each one down to pipeline, and picks a winner the way we would: by qualified pipeline, not reply rate.
Swipe the table sideways to compare angles.
Every number in the lab is simulated from fixed sample rates so the demo is repeatable. The same setup always gives the same result. It shows how tests are run and judged, not how Acme's campaigns will perform.
Buyer intelligence
Select a buyer to see what they care about, what Acme offers them, and the email we would send first.
Each segment gets its own three-email sequence, written differently for executives than for the managers who run the work day to day.
Learning loop
A reply is not the end of the record. Each outcome carries the segment, persona, seniority and angle that produced it, so the next campaign starts from what worked instead of from scratch.
This panel fills from the tests you run in the lab above. Run a few with different buyers and watch the ranking change.
Pipeline forecast
Move the assumptions and the model updates. Each bar shows how much of the step before it carries through. Every number is a scenario estimate built from these inputs, not a promise.
Each inbox sends a small number of plain-text emails a day, from domains set up only for outreach, so your own domain's reputation is never at risk. Every address is verified before anything is sent. To reach more people we add inboxes and domains instead of pushing each one harder.
Implementation
What gets built, in order. The bottom line of each phase shows where this page already demonstrates that step.
Everything above is planned work. The lab, learning loop and forecast on this page run on simulated data until real campaign data replaces it.
D3 Revenue is the go-to-market firm founded by Tam Nguyen. Tam built pipeline inside billion-dollar companies before building it for others.
D3 Revenue runs that same playbook for growing teams: map the whole market, find the right person at every account, and test angles until one earns replies.
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Questions about anything here: reply to the email this link came in.