Discover and read the best of Twitter Threads about #advertools
Most recents (6)
Link Velocity... the good, bad, and ugly (+ 🐍code!!)
(A 🧵 of threads )
(A 🧵 of threads )
First a quality scale for content sites:
⭐️⭐️⭐️ Quality + maintained + high velocity
⚪️⭐️⭐️ Quality content + maintained
⚪️⚪️⭐️ Quality content
⚪️⚪️⚪️ Quality content + not maintained
💩💩💩 Poor quality + high velocity
⭐️⭐️⭐️ Quality + maintained + high velocity
⚪️⭐️⭐️ Quality content + maintained
⚪️⚪️⭐️ Quality content
⚪️⚪️⚪️ Quality content + not maintained
💩💩💩 Poor quality + high velocity
How do you measure content velocity?
1⃣ scrape the sitemap for content
2⃣ determine content date (published, updated)
3⃣ plot the trend & volume
Examples and more info below: 👏👏
1⃣ scrape the sitemap for content
2⃣ determine content date (published, updated)
3⃣ plot the trend & volume
Examples and more info below: 👏👏
1/
@Target's XML sitemap
Has 2.6M URLs with ~1M duplicates (39%)
Consistent URL structure mostly 4 dirs
5 types of pages
product
category
search
brand
store-location
Data
bit.ly/3WKbw3H
Code
bit.ly/3XB0sGH
#DataScience #advertools #SEO #Python #DataAnalytics
@Target's XML sitemap
Has 2.6M URLs with ~1M duplicates (39%)
Consistent URL structure mostly 4 dirs
5 types of pages
product
category
search
brand
store-location
Data
bit.ly/3WKbw3H
Code
bit.ly/3XB0sGH
#DataScience #advertools #SEO #Python #DataAnalytics
2/
Checking top category pages, we see the top 10 are mostly toys.
A more accurate approach is to count the words in those URLs, which shows that clothing and home are bigger.
We can also check the percentage of category URLs that contain those words for a different/better view
Checking top category pages, we see the top 10 are mostly toys.
A more accurate approach is to count the words in those URLs, which shows that clothing and home are bigger.
We can also check the percentage of category URLs that contain those words for a different/better view
3/
We can easily go deeper by filtering URLs that contain "clothing", and checking what the top words are for those URLs.
We can go to sub-sub-categories by filtering for URLs containing "clothing" & "kids" for example.
You can interactively explore any combination you want.
We can easily go deeper by filtering URLs that contain "clothing", and checking what the top words are for those URLs.
We can go to sub-sub-categories by filtering for URLs containing "clothing" & "kids" for example.
You can interactively explore any combination you want.
XML sitemap of @Apple with a quick audit/analysis
105,244 (26.2%) duplicated URLs with 45% with a mysterious parameter "fh" which mainly provides an empty page.
Data: bit.ly/3WKbw3H
Code: bit.ly/3J86xWw
#DataScience #SEO #advertools #Python
1/
105,244 (26.2%) duplicated URLs with 45% with a mysterious parameter "fh" which mainly provides an empty page.
Data: bit.ly/3WKbw3H
Code: bit.ly/3J86xWw
#DataScience #SEO #advertools #Python
1/
Unsurprisingly /shop/ is the biggest directory (number of URLs), and we can also see what are the biggest product categories under that with a simple filter.
But what is /today/ ??
It seems they run live online events for product demonstrations and explanations
2/
But what is /today/ ??
It seems they run live online events for product demonstrations and explanations
2/
Most of these ~13k pages are empty (event expired), and it's not clear why they even have them in the sitemap.
This definitely needs fixing. But we can still use the data to understand what topics they focus on in their events (iPhone, photo, art)
3/
This definitely needs fixing. But we can still use the data to understand what topics they focus on in their events (iPhone, photo, art)
3/
A new SEO workflow for e-commerce sites. In this tutorial, we will create internal links on PLP
1⃣ Extract text using #advertools 🕷️
2⃣ Get queries from GSC
3⃣ Compute Similarity
4⃣ Add semantic markup
- wordlift.io/blog/en/intern… [blog post✍️]
- bit.ly/3aRvN4o [code🐍]
1⃣ Extract text using #advertools 🕷️
2⃣ Get queries from GSC
3⃣ Compute Similarity
4⃣ Add semantic markup
- wordlift.io/blog/en/intern… [blog post✍️]
- bit.ly/3aRvN4o [code🐍]
I worked on the @FILAUSA website (not a client of ours) that currently doesn't have a related search widget.
To build one, we will index 'title', 'meta description', 'intro text' and 'breadcrumbs' and use the title of any other PLP as 'query'.
To build one, we will index 'title', 'meta description', 'intro text' and 'breadcrumbs' and use the title of any other PLP as 'query'.
We will generate a JSON that recommends 3 or 4 relevant links for every page.
For those who are new, here are the best online resources to learn #Python3 for #SEO Specialists.
This thread will show you what you should read and how to hone your skills 🧵
This thread will show you what you should read and how to hone your skills 🧵
holisticseo.digital/python-seo/
You have to know this. Semantic SEO, clear case studies, topical authority, and lots of Python.
Everything you need for 2022.
You have to know this. Semantic SEO, clear case studies, topical authority, and lots of Python.
Everything you need for 2022.
seopythonistas.com
It's not a simple list of projects, it's the legacy of a great man. Check it out, it's full of awesome works.
It's not a simple list of projects, it's the legacy of a great man. Check it out, it's full of awesome works.
I mentioned projects or books for #Python3 in my other threads but let's talk about the very best resources for #SEO: blogs!
This a thread 🧵
This a thread 🧵
1. holisticseo.digital/python-seo/
You have to know this. Semantic #SEO, clear case studies, topical authority and lots of #Python3. Everything you can ask for in 2022
You have to know this. Semantic #SEO, clear case studies, topical authority and lots of #Python3. Everything you can ask for in 2022
2. seopythonistas.com
It's not a simple list of projects, it's the legacy of a great man. Check it out, it's full of awesome works.
#pythonlearning #DataScience #SEO #Python3
It's not a simple list of projects, it's the legacy of a great man. Check it out, it's full of awesome works.
#pythonlearning #DataScience #SEO #Python3
