πŸ“ˆ How I increased my Productivity with Data & Coding


Use Data Or Be Used By Data!

​

The June 26 issue of Seotistics is here for you!

It's no secret that we live in a data world and SEO is another industry where this is even more evident.

My journey started around 2019 after I decided to start studying data rather than breathing pure SEO.

This knowledge allowed me (and other people) to be more efficient and productive than the average.

I will show you how to start and why I make such claims.

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πŸ‘‰ Quick Website Check Available !!! [Limited Spots] πŸ‘ˆ

I am launching a new service at a special price.

During the past few months, I've noticed people get their websites audited for pennies...

I still think audits should be deeper but you know... if you want a quick check, you don't need extensive operations.

The price is $150 for a quick breakdown of your website where I give you some quick and actionable tips.

N.B. I don't consider this as an audit. It's some actionable tips to improve your website but not a full-fledged audit by any chance.

Contact me below with your request:

πŸ› The Analytics Foundations

There are many roles in data but the most related to our industry would be the Data Analyst.

Many of you may be familiar with Web Analytics, which isn't really my favorite discipline.

The reason why is that anyone can learn Google Analytics and Tag Manager to define themselves as an "analyst".

When I started, there were no good resources for SEO, only a bunch of books about Google Analytics (with the same usual metrics).

Analytics is full of interesting concepts that are mostly practical. Coding is a tool to achieve an end and you don't even need to be a developer.

The coding level required for Analytics is quite low actually!

You only need some decent knowledge of Python/R and SQL plus the usual spreadsheet tricks.

πŸ’‘ What's the connection to SEO

SEO is an industry or domain of application where you can use Analytics to analyze data.

Some common tasks include:

  • Analyzing traffic drops with GSC and GA data
  • Optimizing the internal linking structure
  • Detect international cannibalization problems between countries
  • Find content opportunities

As you see, some of the most pressing SEO needs can be soothed with some decent data skills.

The SEO industry has been quite stale for several reasons...

Short-term gratification is one reason.

Do you even know how many businesses prefer quick gains rather than a sustainable competitive advantage?

I also talked about 2 media companies that do that...

Analytics is all about speed. SEO usually takes time and Analytics is the perfect partner.

πŸ’‘ The Tools

There are too many tools at your disposal, but the most notable are:

  • Excel/Google Sheets - Spreadsheets
  • Python/R - Coding
  • SQL - Databases
  • Looker Studio/Power BI/Tableau - DataViz

You don't have to learn them all, one of each is fine.

If you are a business owner trying to hire someone, SQL and Excel usually take priority.

In SEO, I'd say Python/R is usually more than enough because:

  • Many businesses don't even use databases for SEO data
  • Most of our data sources are either APIs or CSVs
  • If you know Py/R, you won't have any problems with SQL (connectors exist)

With the advent of AI-assisted coding, the barrier to entry is remarkably lower than ever.

The Right Way To Learn

Projects.

The answer is projects and projects. It takes at least 1 year to become decent.

6 months are enough to learn to code, but I'd say at least 1 year to be sufficiently prepared.

Try solving common problems and frame everything as an opportunity to spot pain points.

No one cares about your cool XML generator or about the basic scripting that every average developer does...

You have to stand out and do something that people want.

But many of you are like me and want some MORE information πŸ˜…

πŸ”Ÿ Steps To Learn Analytics (More Or Less)

This is my quick blueprint:

Step 0: if you already know advanced Excel functions, steps 1 and 2 will be much easier.

  1. Learn one between Python and R. Focus on data wrangling and visualizing data.
    πŸ‘‰ Check the books at the bottom or try Dataquest.
  2. Do one small project applied to SEO (learn to use APIs). This is where you build your first script.
  3. Learn SQL to communicate with databases. Start being familiar with queries and BigQuery.
  4. Build one dataset in BigQuery.
  5. Start learning DataViz and how to communicate your output. Start with Looker Studio first.
  6. Prepare a 5-minute pitch/presentation where you outline the main findings of something you did.
  7. Quick overview of Statistics, so mean, mode, median and probability distributions.
  8. Use those concepts in an SEO Audit (don't force them). Analyze GSC or GA data with your newfound knowledge.
  9. Finalize your old projects, go back and see what you could improve.
  10. Turn them into web apps or cool dashboards.

N.B. Most of them can be skipped with my Analytics ebook, but you can always consult the multiple sources I list at the bottom.

πŸ’‘ Results, Results & People

I want to talk about some people that didn't have a technical background and started from zero.

The best example out there is Lee Foot.

Not only he created the most impressive examples of useful scripts but they are also "new".

Most of those can be even turned into a full SaaS service...

Ah, and he is self-taught, so you have no excuses...

His most recent example is about optimizing titles for category pages (Ecommerce).

Many of you already know that the right titles DO make a big difference so it's worth testing.

The ability to create tools on the fly has tremendous ROI. Imagine saving costs on expensive tools and being able to have your custom solutions!

Another virtuous example is given by Abdulrahman Henedy, who is currently working on a tool and all of this is thanks to his efforts to study coding.

​Simone de Palma also started learning from scratch and developed good data skills that allowed him to improve in Technical SEO.

​His personal website has good articles that cover some interesting tech topics.

But what about me?

I automated a lot of stuff like Lee but for content websites, publishers and sometimes B2B.

Most of my work is spent on processes and analyzing data to make quick decisions.

I recently helped an entrepreneur save $M on aged domains. You know, you have gold but also scams!

Currently, I am trying to build some brands, like this baby below:

⚠️ But Wait... Another Thing

Analytics isn't only coding. If you do scripting, then OK, you can simply learn programming and call it a day.

If you want to analyze data, your level can be much lower if you understand the business and SEO.

Many claim that an Analyst doesn't need Math/Stats, but I strongly disagree.

The best of the best is able to use numbers to their advantage, never settle for less!

You don't actually need that much but a good dose of Statistics is more than enough to be good.

Concepts such as:

  • Mean, Mode, Median
  • Probability Distributions
  • Derivatives
  • Understanding common functions, such as log, exp

Most of these concepts are easy to understand but I admit that some people may need additional effort (like me at the time).

If you ever want to study Machine Learning, then you need to study Calculus to get how things work under the hood.

🧡 My Selection Of Twitter Threads

A quick recap for those who haven't read them all or need a refresher:

πŸ‘₯ Join Our SEO Community

We have launched our Discord community and I will contact every person who hasn't joined yet.

Our goal is to encourage actual SEO testing and building meaningful connections.

πŸ”Ž Analytics For SEO Ebook (v3)

I crafted this resource to help people start their Analytics journey in SEO.

Not only do I update it every month but it's quite practical if you put in the right amount of effort.

It will teach you or your employees to:

πŸ‘‰ Avoid common pitfalls that cost you money πŸ’Έ

πŸ‘‰ Create meaningful analyses that add value πŸ’―

πŸ‘‰ Shorten the learning time of Analytics ⏳

This comes with monthly updates because I want to create the Ultimate Guide out there.

The May update includes the following new information:

βœ… Detecting Keyword Cannibalization (The Actual One) - Use Case 6

βœ… Statistics 101 (Small Update)

βœ… Updates For Use Cases 2 and 5

βœ… Introduction to R

βœ… Brief Introduction to Joins (More in v4)

βœ… N-grams and How You Can Use Them

v4 (End of June) will feature:

  • Data Simulation (How to Generate Synthetic Data for Testing)
  • Updates to Use Cases 2, 5 and possibly creating Use Case 7
  • Going Deeper With Analysis (Google Analytics, Screaming Frog, etc.)

v5 (End of July) and will feature:

  • Financial Analysis (Costs/Benefits)
  • Updates to all the Use Cases
  • Decision Theory and Concepts for Agencies/Portfolio Owners
  • Information Analysis (maybe... to be decided)

πŸ“š Recommended Reads

These Analytics books are among the best out there. If you want to think like a true Analyst, look no further.

It's always the same books because they are so good it would be a sin not to mention them.

❗️ Feedback and Recommendations

If you have ideas/recommendations for the next issues of Seotistics, you can simply reply to this email.

Marco Giordano
​
SEO Specialist & Data Analyst

Follow me on πŸ”½πŸ”½πŸ”½:

Bernerstrasse SΓΌd 169, Zurich, Switzerland
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Seotistics - Analytics & SEO

The Seotistics newsletter is written by Marco Giordano, an SEO Specialist focused on content and Data Analyst. Tired of the usual SEO content? Seotistics teaches you how to use Analytics and data in your workflow while helping you with Content Management & Strategy.

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