mack grenfell

A Better Way to Forecast Marketing

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This article focuses on my generic marketing forecaster, for forecasting on any marketing channel. I've recently launched channel-specific forecasters too, for Facebook Ads, Google Ads, and Snapchat Ads.

When you're launching a new marketing campaign there's always one question on your mind: what sort of results am I likely to see from this campaign?

If you've found yourself in this situation before, you've likely used one of the many online forecasting tools out there, or perhaps attempted to build your own in a spreadsheet.

These approaches are great for getting some quick estimates, but they all suffer from the same problem; they're rigid and inflexible. No marketer knows exactly what their CPC is going to be before they launch, or what sort of conversion rate they're likely to see.

To accommodate for these issues, I created the marketing forecaster below using Causal.

This forecaster allows you to enter ranges instead of exact figures. This means you don't have to know that your conversion rate will be 2.5%, you can simply say that it'll be somewhere between 2% and 3%.

The model then runs 100,000 different simulations with conversion rates between 2% and 3%, and shows you how your other metrics look in each of these simulations.

How do I use the forecaster?

The forecaster has been set up with some dummy figures below, under the Inputs section. To use the forecaster, change these numbers to some that look reasonable for your campaign.

Note that you don't have to enter precise figures, but that you can use ranges. If you think your cost per click would be between $0.20 and $0.30 for example, you can write this as 0.2 to 0.3.

Once you've changed all the inputs, the numbers in the Outputs section will show you a range of what you can expect to achieve with your marketing campaign.

The graphs will also give you a more detailed look at the number of conversions, and profit, you can expect to generate.

Found this forecaster useful? Have thoughts on how it can be improved? Reach out to me on Twitter @mackgrenfell

To create your own forecasts and models, sign up at causal.app