Project revenue, demand, or signups with the model that backtests best on your history. Compare scenarios, see 65% and 95% intervals, and choose the plan that hits your target without ignoring risk.
No code and no model wrangling. The platform fits, backtests, selects, and stores the assumptions behind every forecast.
Backtested model choice
Compete candidate models on held-out history and use the best performer.
65% and 95% intervals
Plan with a likely range and a conservative range, not just one line.
Scenario optimization
Compare plans and choose the one that hits the target within acceptable risk.
Assumptions stored
Version forecasts, model choices, and planning assumptions for future review.
Revenue forecast: 65% and 95% intervals
Every forecast comes with 65% and 95% confidence intervals — so you see the likely range and exactly how sure the model is.
The best model for your data, honest uncertainty on every number, and scenario optimization to turn a forecast into a plan.
We fit a competition of time-series models, backtest them on your own history, and automatically pick the one that forecasts your business most accurately.
Every forecast ships with both a 65% and a 95% confidence interval, so you see the most-likely range and exactly how sure the model is.
Forecast under different plans for spend, pricing, or headcount and find the scenario that best hits your target, not just one fixed projection.
See how each model performed on held-out history before you trust it, and track forecast error over time as real actuals come in.
Layer in incrementality tests and MMM outputs so forecasts reflect causal evidence, not just last year's trend repeated forward.
Every forecast, model choice, and assumption is stored and versioned, ready to compare against what actually happened.
Four steps, no spreadsheets, no model-wrangling. You stay in control of the assumptions and the call.
Add historical outcomes such as revenue, demand, or signups at daily or weekly grain. Connect a file or a source, no code required.
We fit a competition of time-series models, backtest each on your data, and select the most accurate one for your business.
Get a forward forecast with both a 65% and a 95% confidence interval, with the likely range clearly shown instead of a single guess.
Compare scenarios, see the forecasted outcome of each, and choose the plan that best hits your target.
Don't forecast a single future. Compare scenarios side by side, each with its own confidence range, and choose the plan that best hits your target.
Projected outcome by plan
Each plan is forecast with its own 65% and 95% interval, so you optimize for the target without ignoring the risk.
So we don't force one. We fit several, backtest them on your own history, and let the most accurate model win, then show you why.
You don't need to be a statistician. The hard math runs under the hood; you point, click, and make the call with the full picture in front of you.
Business forecasting sits on top of the measurement triangle: incrementality testing and your MMM tell the forecast what marketing really drives, so the plan you project forward is grounded in causal evidence, not just last year's curve.
Inform. Attribution gives the MMM a fast, directional read on what's working between tests.
Calibrate. Incrementality tests anchor the MMM to causal ground truth, not just correlation.
Validate. Holdout tests check that attribution and the model agree with what really happened.
The models and tests matter, but the workflow around them matters too. Shako Stats is designed to become the operating system around experiment planning, metadata, documentation, and cross-test learning.
Centralize datasets, mappings, and historical records so experiments and models always start from the same source of truth.
Organize tests by audience, creative strategy, bidding logic, or business objective so learnings remain searchable and reusable.
See what tests are planned, in-flight, or completed so overlapping interventions and measurement conflicts are easier to manage.
Turn methodology, definitions, and experiment design guidance into an internal operating system instead of leaving them scattered across decks.
Connect any AI agent through MCP/API to read-only forecasting context: scenarios, assumptions, selected models, intervals, backtests, and actuals. Shako Stats runs the statistical forecast and stores the assumptions; the AI helps your team understand which plan is most defensible.
Meet your AI Marketing ScientistOne-click OAuth for Claude & ChatGPT, read-only, anyone on the team can ask
Design tests, understand results, and connect your team to one statistics-backed measurement workspace.
Paid B2B plans built for brands & agencies.