How we analyze why deals are won and lost
The win-loss agent we run on Kortix — a weekly cron reads every HubSpot deal closed-won or closed-lost since the last run and posts the patterns by segment, competitor, price, and stage of death to Slack.
Every closed deal is a data point about why customers choose us or choose someone else, but the reason usually lives in one line of a HubSpot field, written by a rep in a hurry between calls. Read one at a time, those lines say nothing. Read across a hundred deals a quarter, they say exactly where we're strong, where a competitor is beating us, and where our own pipeline quietly falls apart.
We run a win-loss analysis agent on Kortix that reads closed deals from HubSpot every week and posts the patterns to our sales Slack channel. It only reads deal data; the single output is the Slack post. This is how we watch our own win rate.
The problem
Close reasons and competitor mentions get logged in HubSpot because the CRM asks for them, not because anyone reads them back. A closed-lost deal gets a one-line reason and maybe a competitor field, then disappears into the pipeline history. Nobody aggregates it, so the same loss pattern — a competitor consistently winning on price in one segment, a deal category that reliably dies at the same stage — can repeat for two quarters before a sales leader notices it by gut feel in a QBR.
The common approaches don't fix this. A win-rate number on a dashboard tells you the score changed, not why. A quarterly deal-review deck is thorough but looks back three months too late to change this week's playbook. And nobody wants to be the person who reads two hundred close-reason fields by hand every Monday.
What we built
On Kortix, a weekly cron triggers an agent. It spawns a fresh session (a cloud sandbox) with read-only access to HubSpot, pulls every deal closed-won or closed-lost since the last run, and breaks the outcomes down by segment, competitor, price band, and the stage where lost deals actually die. It synthesizes the patterns into themes and concrete recommendations, and posts the summary to Slack. It writes nothing back to HubSpot.
How it works
Run on a weekly cron
A cron trigger fires the agent once a week. Each firing spawns a fresh session in its own sandbox. One week maps to one run on one disposable machine, so the analysis is recomputed from HubSpot's current state every time and nothing carries over between runs.
Give the agent the analysis rules
How we break down a win or a loss lives as a skill that travels with the agent: which fields hold the close reason and the competitor, how to band deal sizes, how to bucket segments, and what turns a pile of one-line reasons into a small number of real themes rather than a hundred unique snippets.
Connect HubSpot read-only
Through a scoped connector, brokered server-side so no raw token reaches the model, the agent reads:
- Closed-won and closed-lost deals — every deal that closed since the last run, with amount, segment, and the stage it moved through.
- Close reasons and competitor fields — the specific HubSpot properties a rep fills in at close, read verbatim.
- Stage history — where a lost deal was sitting before it died, not just that it died.
- Posts to Slack — the one weekly summary of themes and recommendations.
Set the guardrails
The agent is read-only on HubSpot. It has no write access to any deal, contact, or company record, so it cannot change a stage, a close reason, or an amount. Its only output is the Slack post. Credentials are encrypted in the Secrets Manager and injected at runtime, never shown to the model or written to logs.
Post the themes and recommendations
With that in place, each week brings one Slack post: win rate and loss count for the period, the breakdown by segment, competitor, and price, the stage where deals most often die, and a short list of themes with a recommendation attached to each. The sales team reads it and decides what to change. Nothing is written back to HubSpot automatically.
The pattern
A weekly cron spawns a fresh session with a read-only connector into HubSpot. The breakdown rules live as a skill. The agent reads every closed deal and writes nothing but the Slack post.
Guardrails
The agent reads every closed deal in HubSpot, so its access is scoped and one-directional:
- Isolation. Every run happens in its own microVM sandbox. The session can reach only HubSpot, and only the Slack post leaves the sandbox.
- Scoped secrets. The HubSpot credential is encrypted in the Secrets Manager and injected into the sandbox at runtime, never exposed to the model or the logs.
- Read-only. The connector into HubSpot is read-only. The agent cannot change a deal's stage, close reason, competitor field, or amount; it can only report on what's already there.
- Report only. The agent never contacts a rep, a prospect, or a lost deal. It surfaces the pattern; a human decides what to do about it.
- Everything is code. The agent's breakdown rules, skill, and HubSpot permissions are files in the repo, versioned and changed through a reviewed change request rather than a dashboard setting.
The outcome
Win-loss reasons that used to sit unread in a HubSpot field now arrive as one weekly summary in the channel where the sales team already works, with the themes named and a recommendation attached to each. The agent only reads; the people decide what to change in the playbook.
Read more
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