Pipeline automation
Stage logic, forecasting inputs and hygiene rules enforced by the system itself.
- Engagement
- Short fixed-scope build with your sales leadership
- Typical timeline
- 3 weeks
- Starts with
- An export of every deal won and lost in the last twelve months, with dates.
The forecast says four hundred thousand closes this month. Two of those deals have not been touched in six weeks, and one contact left their company in March.
A forecast you would be comfortable taking to the board.
What we build
Concrete artefacts, handed over and documented.
Stage definitions with exit criteria, a deal cannot reach negotiation without a named decision maker and a date
Staleness detection that flags or slips deals with no real activity, instead of letting them decorate the forecast
Signal-driven movement: proposal opened, contract viewed, buyer replies, procurement invited, each nudging the stage or the owner
A weighted forecast built from your own historical stage conversion, shown next to what the reps are claiming
What changes
Forecast and result stop diverging by the same embarrassing margin every quarter
Dead deals leave the pipeline within days rather than at quarter end
Pipeline reviews spend their time on deals that can still move
How it runs
01Define the stages
Two hours with sales leadership to write exit criteria a machine can check, rather than criteria a meeting has to judge.
02Signals and hygiene
Activity, document and email signals wired in, with staleness thresholds set from your own closed-deal history.
03Forecast model
Stage conversion calculated across the last twelve months, published alongside the rep-entered view.
Chosen per project. Named here so you can see the shape of it.
- HubSpot
- Postgres
- Metabase
Questions we get asked
Tell us the outcome, not the tooling.
Send us the situation you are in. We will tell you which discipline it belongs to, what we would do first and what it costs, including when the answer is to wait.