A Series B enterprise AI platform had just raised $20M. The enterprise motion was working, but sales cycles were long and the board wanted faster growth. A well-funded competitor was gaining ground, and leadership decided to go after the mid-market.
Over 20 reps were hired in about three months. SDRs, AEs, the standard playbook. Pulled thousands of contacts from ZoomInfo using basic filters — industry, headcount — loaded them into HubSpot, set up cold email infrastructure, and started dialing.
The Head of GTM was squeezed from both sides. The CEO expected returns on a major headcount investment. Twenty new hires looked to him for direction — who to call, what to say, why these accounts. He didn’t have good answers, because the company had never defined a mid-market motion. The enterprise side had years of accumulated knowledge about its buyers. The mid-market team had a ZoomInfo export and a mandate to move fast.
Underneath the activity was a research and prioritisation workflow that nobody was actually performing. Judging whether an account was worth a rep’s day takes an hour of reading — the tools they use, how support is structured, what their public experience looks like. Nobody had an hour, so nobody did it. Hundreds of dials a day went into a list of thousands with no scoring and no shared understanding of who they were trying to reach.
Meetings were booked. Some with the wrong accounts. Consistency was the problem: a few reps were delivering, but most were working companies that would cost more to service than they were worth. Twenty new hires, hired at a premium to move fast, months of ramp with nothing to show, and a growing pile of misfit deals.
The alternative was to kill outbound, move the SDRs to enterprise, and try marketing-led for mid-market. Survivable operationally, but it would tell the board the mid-market bet had failed.
We started where we always start: with the decisions. Two of them were being made dozens of times a day without context. Which of these accounts is worth my time today? What do I need to know before I pick up the phone?
Both are high-judgment and low-stakes: getting them wrong wastes an afternoon, it does not lose a customer or move money. That combination is exactly where a coworker can run on its own. We ran working sessions with leadership and top reps to write down judgment the best people had built up but never recorded — what makes an account worth pursuing, which signals indicate the problem, what changes the conversation. Not firmographics; things like which support tooling they ran, how the team was structured, what their public support experience looked like. Each data point got a weight and a written rationale. We argued about the weights, then re-ran the scoring by hand on sample accounts to check the output matched what a good SDR would conclude after an hour of reading.
Decision map. Capture the judgment, define data points and weights, agree the autonomy line, validate against real accounts with experienced reps.
Then we built the coworker. It runs the research automatically, including capturing screenshots from a company’s own site, and scores any account against the map we had defined together — a fit score from 1 to 100 with a short written explanation of which signals were present and what they meant. The explanation matters as much as the score: a rep can disagree with it. It scored roughly 12,000 companies from their HubSpot in two days.
The top segment was split across reps using HubSpot lists syncing into the outreach tool they already used. No new software, no changed sequences. The coworker never contacts anyone and never decides who gets called — it prepares. Before picking up the phone a rep reads a brief explaining why this company was on their list, what challenges it likely faced, and what mattered to them — that changed the nature of the conversation entirely.
Build and integrate. Research and scoring in production, 12,000 accounts scored, wired into the HubSpot workflows the team already ran.
4 weeks total from kickoff to live system.
Within the first quarter, pipeline increased 1.5x. Hiring stopped — not a freeze, but because the reps already there began producing at the level leadership had planned to reach by adding headcount. Monthly tool spend dropped from $20K to $10K as half the stack became redundant.
By year-end, the mid-market team generated over $5M in revenue — more than double what the enterprise produced over the same period.
A motion weeks away from being shut down became the company’s primary revenue engine.
Deployment is where the work starts. Scoring drifts as the market moves, sources change shape, and reps disagree with the coworker in ways that are usually informative. We track which data points actually predict fit and adjust the weights, so the second month’s targeting is sharper than the first, and we read cost and performance rather than waiting for someone to complain.
The team also began using the briefs to understand their own ICP more deeply, which meant that expanding into a new vertical started from the existing decision map rather than from nothing. Reps went from quantity to quality: fewer calls, better conversations, higher output.
Bring us the workflow that is costing you the most. A first call is a conversation about one workflow and what could reasonably be delegated.
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