The Seotistics newsletter is written by Marco Giordano, a Data/Web Analyst with the goal of combining business and web data. Tired of the usual boring Analytics content without any business impact? Seotistics teaches you how to use Analytics, web data and even content in your workflow while helping you with Strategy.
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Real Life Web Analytics (With Numbers)
Published 3 days agoΒ β’Β 7 min read
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Use Data Or Be Used By Data!
The May 18 issue of Seotistics is here for you!
In the last issue we saw which actions are more important and which aren't, based on web data.
Today I wanna show you some actual examples to motivate you.
For sure, I can't make explicit names now or spill the actual tea π
Please move this email to your Primary inbox or reply to it. This is to prevent Seotistics goes into spam by accident. Gmail users can read this tutorial to do it.
This will be for Analysts or everyone wanting to explore Web Data in general, not only SEO.
The course is split in 4 amazing modules: β β GA4, GSC and other data sources: how to use them β LLM Workflows, BigQuery, SQL & Python β Dataform & Pipelines β Real Use Cases at work
I will speak at Web Analytics Wednesday (June 2) and MeasureCamp Copenhagen (June 6).
I will talk about Data Modeling at WAW and for Measureamp... let's see!
If you wanna meet up, just reply to this email and we can arrange something.
Boring (Yet Effective) Analytics
Most of the good Analytics work is boring. Sorry to disappoint you but most of the stuff you see online is fictional.
Companies barely have the basics in place,
By boring I don't just mean GA4 and GTM and go home...
I simply intend simple and repeated action.
Storing Data Drove $100K Decisions
This is what I tell you every issue because it's foundational!
Especially for Ecommerce, you must be sure to have it for seasonality analysis!
Recently I've been trying to compare the results for an Ecommerce but...
we only had month-over-month data so the results were unreliable.
But in one of my other projects, we have data from 2024 until today which is GOOD.
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We were able to make YoY analyses and evaluate products properly.
This was not only related to sales but also about the convenience of a given technical implementation.
You know, some features you pay for and you need to assess their econimical convenience.
Even though I am still on it, you could:
calculate product margins and/or prices per product
assess cost of implementation
calculate conversion rate
Yes this is another thing altogether but it's based on the concept that you stored your data before because we are comparing 2 whole years and beyond!
And this is also true for a redesign I am working on... how can you even combine different data sources with the clunky Google UIs?
I tell you, it's not possible!
To give you some approx. numbers, we are in the order of $10Ks to $100Ks. β For bigger websites, we can also talk about MILLIONS of $.
Saving Thousands With Dashboards
Dashboards and DIY apps are extremely powerful, despite all the hate they get.
That's because people don't structure research properly and don't ask the right questions early on.
Mind you, I am not saying that every single dashboard I build is to be used every day. But my failure rate is lower than the usual haha
Anyway, companies already have a dashboard in most cases and it may not get used for its performance.
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So many examples, like:
1 quadrillion blends
crazy expensive queries
If your dashboard is slow, people ragequit. If it's expensive, it gets discontinued.
This happened to me with a PowerBI use cases, where we had to change a LOT of things.
From a loading time of 2 minutes to around 5-8 seconds... quite good!
And for the expenses, I made an example at MeasureSummit actually, which is real:
And this is by using GA4Dataform. Now imagine doing proper optimization on every single query and detail :3
I don't need to explain you that these things alone:
saved dead data products -> tons of money saved
made operations cheaper
Dashboards should be super cheap. β So if I let you save $1K/month for one dashboard, it's a BIG win. β Now scale it and the amount of money involved quickly scales to the order of $10Ks.
Anomalies Anyone? A Case With China
One of the easiest ways to leverage web data on large websites is to spot anomalies.
You know, those pages with crazy values or that get NO traffic or too much traffic.
I can even tell you crucial mistakes I've found recently with basic wrangling skills:
a super wrong redirect coming after a migration
pages that were deleted by accident (traffic loss in GA4 & GSC)
Bot traffic coming from countries like China and Singapore
broken tagging (sudden drop in events)
It doesn't have to be a complex algorithm, I swear it's that simple and people don't do it!
You can walk your way in and do this in almost any company.
Recently, I had to "fix" some data because Chinese fake traffic was inflating direct traffic.
Needless to say, the data was inusable before and didn't make any sense lol
Once again, basic data skills.
How Answering The Right Questions Improved Results
How often does it happen that you do analysis and then the outcome is peanuts?
Most likely you've answered the wrong questions or put the focus on misleading paths.
Once I remember doing an analysis on some pages to just realize that it didn't even matter.
Or as said in the past, understand which metrics matter before you do anything.
Most of those were barely relevant to the website and had to be pruned (regardless).
So how do you prevent this type of issues?
Well, with common sense and by asking what matters right away:
which decisions will it affect?
will it make any sense from a company perspective?
who will execute the actions?
And if they can't answer any of these, it's your goal to redirect the questions.
Do you know how often I moved the discussion from traffic and vanity to money? β Especially in B2B, traffic matters up to some point!
n8n & Scaling Data
I will cover this nice tool in more detail, I was too harsh in the past with it.
Actually no, it's still used incorrectly by most people and often engagement bait for LinkedIn.
Recently, I'm working on a simple yet effective use case:
scrape SERPs
analyze competitors
label intent
provide recommendations
Not only this works for EVERY company but it's extremely impactful for my content.
You can even go beyond and scrape Reddit, forums and you name it. There is no limit!
I was experimenting with n8n for another project too, so nice :3
My only complaint is the same as before, marketers with no clue about this will sell their clunky automation.
There is much more behind a data product, it's not like you plug some data and call it a day!
As of now I pay for a Hetzner VPS where I can play with n8n and do all the weird stuff in an isolated environment.
I recommend doing the same if you wanna get more technical quickly.
Will show numbers and results once I am done!
From Tools To Autonomy
That brings us to the next way to add value with Web Data, replacing those crazy expensive tools.
OK maybe for a small business you don't see a difference BUT you do see it for medium-large businesses.
Imagine having to pay a wrapper to play with your Google data.
Familiar, right?
This is OK for smaller players who have no time for data and suchlike.
Now you can build whatever with LLMs, don't sleep on them.
But for a serious business, this isn't an option. At all.
My advice is not to force businesses to ditch tools but to let them realize themselves.
Once they see that most are overpaid wrappers, they will follow through.
This isn't even a problem for any medium/big website out there, it's so easy.
Once I saved $100K annually with a very simple solution lol β Just saying that enterprise tooling is often robbery.
OK, So... Also Efficiency?
Yes, Analytics without action is useless.
The good news is that most problems have easy and simple solutions and you don't need any strange algorithm.
What you need to learn as a professional are the basics and common sense.
As a company, you need to have the right conditions to be successful.
Analytics feels intangible at first but once you figure it out... it will make SO MUCH sense.
With LLMs and technology, it makes absolute sense to talk about efficiency.
The holy measures of effectiveness vs efficiency.
Being effective aka achieving your goal is another issue.
Back to Analytics, I recommend you always estimate your savings in terms of time and costs.
If a process took months and not it takes hours, your efficiency drastically improved. β This is how companies (and industrial society) evolve.
All of this is related to the next Seotistics issue too π Until next week!
π₯ Join Our Community
Our Discord community offers a small place where we can talk business and web data.
If you hate all the noise of social media, then this place is for you.
I will start posting more there as we have a forum channel now.
This is the best way to stay updated in real time on Seotistics:
The Seotistics newsletter is written by Marco Giordano, a Data/Web Analyst with the goal of combining business and web data. Tired of the usual boring Analytics content without any business impact? Seotistics teaches you how to use Analytics, web data and even content in your workflow while helping you with Strategy.
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