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Data science is our thing here at Vertical Leap. We’re able to automate a lot of SEO tasks and data handling using our AI tool, Apollo
Insights, including forecasting. But what I’m going to show you today is how to set up a simple forecast that takes minutes in excel that
can add REAL value to your work that doesn’t require python scripts and AI.
SEO is very ambiguous. What you thought will work, sometimes doesn’t. Even though it’s worked before. A lot of SEO is guesswork -
educated guesswork! But guesswork nonetheless.
When I started in SEO after working in advertising and selling media for 5 years, this part of SEO really unsettled me. How could I tell what
I was doing was worthwhile and making a difference? Because in advertising, I could promise a client exactly how many people would
hear or see their ad or content. I could tell when if their ad reaches their target audience. And they would be happy because I had given
them what they’d asked for - sometimes even more!
With SEO, it can often feel like stabbing in the dark, or trying to see into the future using magic.
How do you know when the on page updates you made have worked?
- Could it have been a small algo update that has changed the characteristics of your niche?
- Was there a sudden unseasonal demand?
- Was there subtle fluctuations in the market which has caused a competitor of yours to underperform?
SEO is dealing with people. Not Algos. And this is important to remember that to get to the bottom of the ambiguity issue is just that.
We’re no longer second-guessing what a team at Google will do next. We’re all - search engines included - trying to understand people
and why they want the things that they do and when. And most importantly, what.
This is why we need to take a scientific approach to search. By asking questions, creating a hypothesis, and testing that hypothesis over and
over will we ever be able to make SEO less ambiguous, and more helpful. We need to able to tell what is unusual, and what is just natural
fluctuations in traffic. Imagine being able to tell your client that your work has made an impact, and how much impact.
This is where I’m going to introduce you to something called “Standard Deviation”. You may have heard of this before if you studied
maths at any point in your life.
This is standard deviation. There are two types of equation, n and n-1.
N is population. Use this formula if you have all your data you want to measure present.
N-1 is a sample, and the -1 corrects the discrepancy. Say you want to measure your data over a year but you don’t have a complete year’s
worth, use sample
If you’re sitting here thinking, oh no maths...
… don’t worry. This is SIMPLE basic stuff. How do I know?
I have dyscalculia. I am dyslexic with maths. I have struggled with maths all my life. I still find it hard to read out a long line of
numbers or a serial code. But Like many other dyscaclulics, (sup einstein) I need CONTEXT. And this is going to give you context.
Never ever think data science isn’t for you! It is!
Complete data =
Incomplete data = Sample
All you need to remember is that:
Download your data. You can use any time-series data for this. For this we’re using sessions from GA.
Take 2 year’s worth of your data for a specific subfolder, URL, etc that you want to measure. Download it as a csv/excel.
Put your time-series into two columns. Then split them by the 2 year s like this.
Then average out each day using =AVERAGE. And remove the year in the date column. You can do this by formatting the cells as dates,
then removing YYYY. We want the dates lined up here. If there’s leap year, remove the extra day. Outliers gone.
This is probably the most maths you need to do. And this will spit out a single number. That single number is how much your data deviates
on average over time.
And there you have it. You now have a basic forecast. Clever you!! You can now tell what is usual traffic fluctations and which aren’t.
Interestingly, the drops in this graph abive correlate exactly with the March 2019 core updates.
Now make the changes you need to on the site. Test your hypotheses. Go wild. Simply add in your data at the end of the graph and you can
see if you’ve made a difference to your traffic. Or if there’s no change. Or if you’ve made it worse unusually!
You made it! Hooray!
What can you now do with your forecast?