agency-intelligence-forecasting-demo-transcript

Demo Script: Revenue Forecasting

Purpose: Use this transcript to record a demo of the 12-month revenue forecasting and daily pacing dashboard.
Platform: Agency Intelligence Platform
Last Updated: 2026-02-20

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Demo Script Structure

WHAT: Introduction

Hi, my name is [YOUR NAME] and today we’re demoing Revenue Forecasting on the Agency Intelligence Platform.

WHY: Value Proposition

This feature is important because it solves the problem of paying $300–600 per brand per month for forecasting tools like Orca Analytics, plus hours of analyst time to build and maintain 12-month forecasts across your portfolio.

Agencies managing dozens of DTC brands need revenue visibility and pacing—without per-brand SaaS costs and manual spreadsheet maintenance. With this feature, you get cohort-based returning customer predictions, editable daily forecasts, and a pacing dashboard that shows you exactly where each brand stands—all in one place.

HOW: Feature Walkthrough

Here’s how it works:

1. Select the brand — Choose the brand you’re forecasting. The system pulls historical data from Shopify (and connected ad platforms) to power the model.
2. Understand the overview cards — At the top, you see key metrics: Revenue, Ad Spend, New Customer Revenue, and MER (Marketing Efficiency Ratio). Each shows actuals vs. forecast and variance.
3. Review the daily grid — Scroll to the daily breakdown. Past days show actuals from your data. Future days (marked with “F” for forecast) are editable—you can override any day with a specific revenue number (e.g., for a President’s Day sale or product launch).
4. Edit and recalculate — Change a future day’s value and watch the totals update instantly. The system recalculates monthly and annual forecasts, plus pacing metrics.
5. Track pacing — The “Versus Pace” (or “Pacing”) metric answers: “If we extrapolate from actuals so far this month, where are we on track to land?” It combines actuals to date plus your forecasted values for the remaining days—so a planned sale doesn’t make you look “behind” when you’re actually on plan.
6. Set goals — Adjust revenue targets and new-customer goals. The forecast model uses cohort-based returning customer predictions so you see the split between new and returning revenue—critical for subscription and repeat-purchase brands.
7. Save forecast versions — Save different forecast scenarios (e.g., conservative vs. stretch) so you can compare and share with clients or leadership.

The system eliminates per-brand tool subscriptions and reduces analyst time by 80%+—you get a single platform for forecasting across all your brands.

REVIEW: Recap

Thanks for watching me demo how you can run 12-month revenue forecasting and daily pacing on the Agency Intelligence Platform.

This feature replaces expensive per-brand tools with one unified forecasting engine—cohort-based, editable, and tied to your live data.

BRAND: Call to Action

At Brainforge we specialize in implementing agency intelligence platforms and revenue forecasting engines. If you’re interested in learning how we can help you eliminate per-brand forecasting costs and scale visibility across your portfolio, please get in touch.