Post by account_disabled on Jan 21, 2024 23:48:55 GMT -6
competitor-based topical keyword research is a brilliant solution. I hope more and more of you will start using it from now on. In addition to these, there are other advanced keyword research techniques. These include theme-based keyword research, content-based keyword reverse engineering, Google Search Console, Latent Semantic Indexing, the set of secondary terms based on TFIDF or even the market of terms collected during On-page search. If the title made you read the article, then I want to confirm again. this is really an advanced SEO post. It also includes data backup, on-page optimization, statistical background, small coding and automation.
But that's what gives it its power. I like this solution because it is smart, useful and Industry Email List elegant at the same time. A few weeks ago, I was riding the 9 bus to work and stumbled upon an article that seemed interesting. Most readers would have probably skipped right over, even most SEO experts. The article was about how to fit a statistical model, a kind of distribution function, to the click rates of our own website in the Google search ranking. I already felt from the title that this could be an interesting direction, because I had thought about it before. Back in 2016, I started the first domestic SEO case study based on CTR click-through rate, but in the end I didn't finish it.
Mainly because I couldn't find a real use case for the end result. However, after reading the article, I had a good idea. The background of the SEO trick This is roughly what I thought. What if I backed up the Google Search Console data? There, would I compare the CTR click-through rate values related to the position with an industry benchmark or even with a unique regression fitted to my own page? After that, I would filter out the outliers and automatically receive an email about them. The question rightly arises. what would all this be good for? Let's look at a simple example. The average click-through rates for the given organic Google position are as follows.
But that's what gives it its power. I like this solution because it is smart, useful and Industry Email List elegant at the same time. A few weeks ago, I was riding the 9 bus to work and stumbled upon an article that seemed interesting. Most readers would have probably skipped right over, even most SEO experts. The article was about how to fit a statistical model, a kind of distribution function, to the click rates of our own website in the Google search ranking. I already felt from the title that this could be an interesting direction, because I had thought about it before. Back in 2016, I started the first domestic SEO case study based on CTR click-through rate, but in the end I didn't finish it.
Mainly because I couldn't find a real use case for the end result. However, after reading the article, I had a good idea. The background of the SEO trick This is roughly what I thought. What if I backed up the Google Search Console data? There, would I compare the CTR click-through rate values related to the position with an industry benchmark or even with a unique regression fitted to my own page? After that, I would filter out the outliers and automatically receive an email about them. The question rightly arises. what would all this be good for? Let's look at a simple example. The average click-through rates for the given organic Google position are as follows.