Mastering Revenue Operations

Mastering Revenue Operations

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Mastering Revenue Operations
Mastering Revenue Operations
Forecasting Revenue with Python
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Forecasting Revenue with Python

Matt McDonagh's avatar
Matt McDonagh
Jun 09, 2024
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Mastering Revenue Operations
Mastering Revenue Operations
Forecasting Revenue with Python
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Python is so powerful it can predict the future.

As this is a trick RevOps is often tasked with performing, Py is my tool of choice for rapidly digesting CRM data and modeling the future of revenue engines… and with it, the business being propelled by those engines.

Let’s assume I want to use the last 36-months of opportunity data to predict the next 12-months.

Predicting the future requires two things at a minimum:

  • data about the past

  • data about that data aka the fabled metadata — when was it captured, what were the conditions when it was captured, etc..

Once you have your data (and an understanding of it) you decide which modeling technique is best suited to deliver the most accurate result.

Broadly speaking you have two choices available:

  1. Time Series Models

  2. Regression Models

Let’s explore each of them to understand them better, and then work with live Py scripts to forecast revenue!

Method 1: Time Series Models

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