Numbers that predict, not just report.
An engagement to define the metrics that matter, build the dashboards your team will actually use, and ship a forecast you'd defend in the boardroom.
Dashboards everywhere. Decisions nowhere.
Most marketing teams report a lot and predict almost nothing. The numbers describe the past, then disappear into a Google Doc nobody opens.
of bespoke marketing dashboards stop getting checked within four weeks of launch. Built once, abandoned.
MarTech Alliance survey
average miss on annual marketing forecasts at mid-market companies. Most are wrong by enough to break the budget.
CMO Council benchmark
per week the average marketing leader spends pulling numbers manually. None of it is the work that grows the company.
Internal client benchmark
A forecast, not a folder of charts.
A working forecasting system, plumbed into your stack, with the cadence and ownership to keep it honest.
Forecast model
A pipeline and revenue forecast that learns from your real data. Confidence intervals, drivers, sensitivity. Backtested against the last 24 months.
- $3.2M central estimate. ±$240k at P80
- Top driver. SQL volume from PSEO. 42% of variance
Custom dashboards
Two views, built for the rooms that need them. Exec view, and the operating view.
Metric architecture
A map of leading indicators that move first, the lagging KPIs that pay rent, and the calculations between them.
Anomaly alerts
Slack pings when a metric drifts beyond its expected band. Caught early, fixed early.
Forecast cadence
A review rhythm that fits how you actually run. Recorded, indexed, owned by someone on your side.
Five steps. Modeled, then trusted.
A condensed engagement that gets the model in front of real numbers fast. Most of the work happens against your data, not in slides.
Inventory
Audit the data sources, the dashboards in use, the forecasts that exist. What's accurate, what's stale, what's fiction.
Architect
Map the leading-to-lagging indicators. Define which numbers earn a place on the dashboard and which don't.
Model
Build the forecast against your real data. Backtest against the last 24 months. Surface the assumptions, not just the answers.
Wire
Plumb dashboards into the tools your team already opens. Set up anomaly alerts where the metrics live.
Cadence
Run the first review with your team. Train the owner. Hand over a system that keeps itself honest.
What credibility reads like.
A redacted forecast briefing from a recent engagement. The page exec teams cite when allocating the next quarter's budget.
Q3 forecast
The pipeline projection for the next 90 days, with the drivers, the assumptions and the things we don't know yet.
Three things this forecast names:
A driver, not a vibe. SQL volume from Programmatic SEO explains 42% of variance. The rest is downstream.
A confidence band, not a single number. P80 says we'll land between $2.96M and $3.44M. What we'd defend in front of a CFO.
A list of unknowns. What changes the model, what we're watching, what we'd need to revisit if it shifts.
Questions we hear most.
If yours isn't here, ask. We'll answer plainly.
Do we need a clean data warehouse to start?
No. We work with what is real. If your data lives in Salesforce, HubSpot, GA4 and a Google Sheet, that is what we plug into. If you do have a warehouse we sit on top of it. We will tell you if the data is too thin to forecast off honestly.
Will you use AI in the model?
For pattern detection, anomaly thresholds, and scenario drafting. Yes. For the headline forecast number we use traditional statistical methods (Bayesian or regression) because they are auditable. A CFO can defend an interval; nobody can defend a black box.
What tools do you build on?
Whatever you already pay for. Most engagements end up in Looker, Metabase, or a custom dashboard plumbed into your warehouse. We will not lock you into a tool you do not want to renew.
How accurate are your forecasts?
MAPE (mean absolute percentage error) in the 4 to 8% range for the central estimate, with P80 intervals that hold in backtests. We share the backtest results, you decide if the accuracy is worth the engagement.
Can you also run paid channels?
Not in this engagement. BI & Forecasting is the analytics half. If you also need media buying we have Channel services that share the same metric architecture, so the dashboards and forecasts stay coherent.
See the next quarter. Earlier.
A short call to see if a forecast engine is the right next move. If it isn't, we'll tell you what is.