Andrew Charlton – Forecasting For SEO (2021)


Andrew Charlton – Forecasting For SEO (2021)

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Course Download Size :

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SEO Forecasting is an expectation.

Before businesses invest in SEO, they want to know what they’re getting for their money.

The pressure for businesses to be data-driven means it’s more important than ever to be accountable for your SEO performance.

And it’s rewarding.

Being able to reliably forecast SEO performance can:

Win you more clients.

Increase investment into SEO.

Challenge unrealistic business targets.

But with so many unknowns – algorithm updates, implementation issues and economic challenges – how can you possibly predict the future?

It’s possible. I’ll show you how to embrace this uncertainty.

Introducing Forecasting For SEO.

Who am I?

I’m Andrew Charlton and I’ve been working in SEO for over 10 years.

I’ve successful led agency teams, and consulted on some of the largest brands in the UK.

Some of that time I spent as a forecasting sceptic. I always thought it was impossible to project SEO performance.

But like SEO, the same mysterious complexity drew me to forecasting. And the more I learned about it, the more I understood and valued it.

So much so, I now build forecasts for many SEO agencies and businesses across the world with FutureThought.

I want to share everything I’ve learned and the principles I’ve tried and tested in this course.

What’s inside?

Here’s an outline of what you can expect:

The thing about forecasting

Why forecasting is challenging

The two views of forecasting

Using the outside view

Why you should forecast

The forecasting cycle

Setting the right expectations

How to forecast organic traffic

Forecasting for SEO process

Data collection

Data analysis

Forecast modeling

Forecast evaluation

Linear regression + seasonality

Holt Winters

Facebook Prophet

Forecasting with no data

Why forecasting isn’t enough

Forecast interventions

Using keyword scenarios to show opportunity

How to forecast organic revenue

Breaking revenue down

Building plausible revenue scenarios

When you should forecast

Know when not to forecast

Managing communication and risk


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