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Reporting and forecasting turns CRM records into numbers people act on: pipeline and stage reports, weighted and committed forecasts, win-rate and activity analysis, dashboards and scheduled exports. In Treepie Flow reports read the live records every product writes, every figure opens to the rows behind it, and submitted forecasts are stored so they can be compared with what actually closed.
Pipeline reports showing movement, ageing and conversion by stage; immutable forecast submissions compared with what actually happened; activity reports that measure effort against outcome; cohort analysis by when deals started; per-role dashboards built from saved queries; scheduled exports; and goals measured against the live number.
Every figure opens to the rows underneath it, including the ones that make it look bad.
Because a report that cannot be opened is a claim. The review spends its time deciding whether the number is right rather than what to do about it, and everybody leaves with the view they arrived with.
Forecast accuracy makes it worse. The forecast is a number said in a meeting, so when a quarter misses the conversation is about the quarter — never about the fact that the same person has been 20% optimistic for six of them.
A dashboard can show pipeline coverage, delivery health from Loop, overdue cash from Books and escalations from Desk on one page, because the records are on one platform rather than in seven. The weekly leadership meeting stops beginning with four people exporting four systems.
And forecast accuracy becomes a measurable property of a person. Knowing one manager runs 18% high across five quarters is more useful to a forecast than their current number is.
It reports the pipeline you recorded. Deals that sat in the wrong stage for three weeks are measured as having sat in the wrong stage for three weeks, and no report will correct for stage discipline that is not there.
Cohorts show differences between groups without explaining them. A slower cohort might be the market, the pricing or a new rep ramping, and the report cannot tell you which of the three it was.
Decide what a submission means before asking for one — a number, a date and the deals behind it. A submission that is only a number cannot be compared with anything useful when the period closes.
Build dashboards per role rather than one for everybody. A dashboard that serves four audiences is read carefully by none of them, and it is the fastest route back to screenshots in a deck.
Books reconciles closed revenue against what was committed and reads rate cards when comparing periods. Nest supplies team structure for rollups and working time so activity denominators account for leave. Growth supplies the acquisition source that cohort analysis groups by. Scheduled exports send the same figures to whoever still wants them in a spreadsheet, from the same saved query, so the spreadsheet cannot quietly diverge.
| Exported spreadsheets | Separate BI tool | Treepie Flow | |
|---|---|---|---|
| Freshness | As of the last export | As of the last sync | Live |
| Checking a number | Rebuild the formula | Ask the analyst | Open it to the records |
| Other teams’ data | Separate exports | Joined by an analyst | Delivery, support and cash on the same record |
| Forecast accuracy | Not tracked | Custom build | Submissions stored and compared with actuals |
| Who can build reports | Whoever owns the sheet | Analysts | Anyone with access, scoped by role |
A dashboard can show pipeline coverage, delivery health from Loop, overdue cash from Books and escalations from Desk on one page, because the records are on one platform rather than in seven. The weekly leadership meeting stops beginning with four people exporting four systems.
It reports the pipeline you recorded. Deals that sat in the wrong stage for three weeks are measured as having sat in the wrong stage for three weeks, and no report will correct for stage discipline that is not there.
Decide what a submission means before asking for one — a number, a date and the deals behind it. A submission that is only a number cannot be compared with anything useful when the period closes.
Pipeline, stage movement and ageing, conversion, win rate, activity, cohort analysis, forecast versus actual and goal tracking.
Yes. Save any live query as a dashboard tile, scope it to a role and share it.
Yes. Delivery health from Loop, open tickets from Desk and overdue invoices from Books can sit beside pipeline data.
Each person’s committed number for a period is stored as submitted, then compared with the actual outcome.
Yes. Saved queries can be delivered as CSV on a schedule, or served through the API.
Yes. Readers see only the records they already have access to.
Yes, through scheduled exports or the API.
Live. Reports read the same records the interface shows, with no overnight sync.
Fourteen days, every module, no card. Or half an hour with someone who will run it on your own records and tell you where it does not help.