Forecasting for teams without a data science team

Know what next quarter looks like before it happens.

I build revenue and demand forecasting models for small and mid-sized businesses — validated with real backtesting, not just a trend line dragged across a spreadsheet.

Try the free demo See how it works →
REVENUE — ACTUAL VS. FORECAST ±4.2% MAPE
TODAY
Actual
Forecast
90% confidence interval
The offer

One model. Built for your business, tested before you trust it.

No dashboards you'll never open, no black-box outputs. A forecasting model built on your actual data, validated against your actual history, and handed off in a form your team can run without me.

INCLUDES

Custom forecasting model

Built on your historical data — revenue, demand, or a metric specific to your business.

INCLUDES

Backtested accuracy report

MAPE and RMSE validation against real past periods, so you know the error margin before you rely on it.

INCLUDES

Plain-language handoff

A walkthrough your team can actually use — not a notebook that only makes sense to me.

OPTIONAL

Monthly retainer

I re-run and re-validate the model as new data comes in, so accuracy doesn't decay over time.

The process

Three steps, start to delivery.

01

Scope the model

A short call to understand what you're forecasting, what data you have, and what "accurate enough" means for your decisions.

WEEK 1
02

Build and backtest

The model is built, then tested against periods it hasn't seen — so the accuracy number you get is real, not theoretical.

WEEK 2–3
03

Deliver and walk through

You get the model, the accuracy report, and a session to make sure your team can run and trust it without me in the room.

WEEK 4
Why trust the numbers

Rigor comes from research, not just industry experience.

2,148
posts analyzed in a peer-reviewed compliance study
χ²=22.60
statistically significant findings, p<.001
MAPE/RMSE
every forecast validated the same rigorous way
Background: Doctorate from Syracuse University's iSchool, with prior experience across FP&A and consulting. Forecasting models are validated through backtesting before delivery — the same statistical rigor applied in academic research, applied to business decisions.
Get started

Let's find out what your numbers are trying to tell you.

A 20-minute call to see if this is a fit — no pitch deck, no pressure.

hello@greymatteranalytics.io