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Google's Product Review Update, April 2021
This is a great overview of Google's product review update from Jonathan Jones π π
Content
Perfecting On-Page SEO for Ecommerce Product Pages - A Cheatsheet
Paddy Moogan with an awesome, visual guide, to perfecting on-page SEO for ecommerce product pages. π‘
Tech
Keyword Planner from Google Ads API with Python
Want a script to use the keyword planner tool from Google Ads API with Python to do your keyword research? Daniel Heredia Mejias shows you how!
Automatically Find SEO Interlinking Opportunities with Python
This is cool from Greg Bernhardt π How to use Python to speed up the process of discovering internal link opportunities.
5 Top Crawl Stats Insights in Google Search Console
The Crawl Stats report in Search Console is pretty powerful. Tomek Rudzki provides some use cases to help diagnose indexing issues and optimise your crawl budget.
Processes & Frameworks
How to Solve Nine Common Sales and Marketing Problems
This isn't anything to do with SEO, but we're all marketers, right? You've probably faced some challenges with sales in your time, this is a brilliant article by Alex Kracov on how to solve some of them.
Critical & Common E-commerce SEO Issues that Need to Stop Happening (& How to Fix Them)
I absolutely love this article from Aleyda π₯. She explores some of the most common ecommerce SEO issues and how to fix or minimise them.
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Curated SEO Tweets Wrapped Up, Every Week
Want a way of keeping up to date with SEO Twitter? Check this out from Adam Durrant!
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Hi there π
I stumbled upon a great article last week (which is my Post of the Week) from the team at SISTRIX. Competitive analysis in SEO can be challenging and most audits I see take a very simplistic view of competition. Either from who the business thinks is their competition or a quick export from third party SEO tools.
This is fine but it assumes they all compete in the same single area of the market. They don't. There are various submarkets, and you should know your relative visibility in each submarket to better understand opportunity.
Researchers from Goethe University Frankfurt & the University of North Carolina at Chapel Hill (USA) are designing market maps to do just that.
In SISTRIX's latest article, they show how researchers used SISTRIX data to create a 2d map of the 'Retail Banking' market.
They used NLP and unsupervised machine learning to identify submarkets based on search result data.
The map, which represents websites as dots, shows strongly competing providers appearing close together, while poorly competing providers are further apart. You can see the interactive 2d map here.
This is absolutely fascinating. The concept of visualising search markets and their respective submarkets can not only be used to identify opportunities but to tell a clearer story with data. A must read π₯
Until next week!
Andrew Charlton