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@secretagentdad made a great tool with DomainSheeter! I have a feature request and I don't think he'll implement this feature unless more people ask for it. So, here is how to use such a feature I'm asking for and what it can do for you 
If you like this, please let @secretagentdad know that you want a column in DomainSheeter for "Featured_Snippet_Appears_On_SERP_But_Some_Other_Site_Is_Featured".
Ok, on to the actual content. The idea came from https://blogs.bing.com/webmaster/ju...tent-for-Search-Questions-using-Deep-Learning , which was Hamlet Batista's post on the Bing blog, where he discusses BERT, a new Natural Language Processing Algorithm. In the article, Batista suggests that webmasters can: install BERT on their computer; run it for their URL, for a particular query, that has a featured snippet; and then run it for the site, that is featured on the featured snippet, for that query. Then, the webmaster should edit their URL so that the confidence score from BERT for their URL is higher than the confidence score from BERT for the URL that's on the featured snippet. This should lead to Google's featured snippet algorithm to feature the webmaster's URL, as Google's NLP algorithm is similar to BERT. This would also work for Bing's featured snippets as well.
So, what am I talking about, in a step-by-step process? Let me give you an example.
Let's say your site is penguins.com and you found out that penguins.com/weight.html rank top 10 for "penguin weight." On the SERP for "penguin weight" is wikipedia.org and the featured snippet says "How much does a penguin weigh? A penguin weighs 10 pounds."
Let's say Wikipedia is #2 in this SERP and it's also featured in the featured snippet. Your site is, let's say, #5. If you can get the featured snippet, you'll get a lot more traffic.
Since the featured snippet algorithm is a Natural Language Processing Algorithm, it's a different algorithm than Google's Organic rankings. This gives you 2 shots to rank on the top for this keyword. That's why this process is so valuable. You can get 2 listings on the SERP or get a top ranking listing, without as much work as the organic results, if your webpage is optimized for the featured snippet.
Ok, now that you've understand that, how do you optimize an article for a featured snippet? Easy. If you read that article on the Bing blog, the NLP algorithm works by reading all texts in an index, figuring which ones are relevant to the query, and then figuring which article has the highest confidence score for the query. Then the article with the highest confidence score is displayed as the featured snippet. For Google, the index would be Google's index. For Bing, the index would be Bing's index. If you run BERT on your PC, the index will be whatever documents or text strings you feed BERT.
So, let's go back to penguins.com/weight. If that article does not state clearly and plainly the weight of a penguin, it's not optimized for the featured snippet. An edit can be "<h2>Penguin Weight</h2><p>A penguin weights 10 pounds</p>". By having such a clear and concrete piece of text in the article, the NLP algorithm can easily tell that it's an answer to that query. It'll then give you a shot at ranking in the featured snippet, when you had no chance before.
Do this for all keywords that your site ranks for, where there's a featured snippet and, Cha-Ching, more traffic It's only about 1 or 2 sentences per keyword to make these edits.
Now... if there was only an easy to use tool where it'll show you the keywords your site is ranking for and if that keyword has a featured snippet box, where your site's not featured.... Hmm....
If you like this, please let @secretagentdad know that you want a column in DomainSheeter for "Featured_Snippet_Appears_On_SERP_But_Some_Other_Site_Is_Featured".Ok, on to the actual content. The idea came from https://blogs.bing.com/webmaster/ju...tent-for-Search-Questions-using-Deep-Learning , which was Hamlet Batista's post on the Bing blog, where he discusses BERT, a new Natural Language Processing Algorithm. In the article, Batista suggests that webmasters can: install BERT on their computer; run it for their URL, for a particular query, that has a featured snippet; and then run it for the site, that is featured on the featured snippet, for that query. Then, the webmaster should edit their URL so that the confidence score from BERT for their URL is higher than the confidence score from BERT for the URL that's on the featured snippet. This should lead to Google's featured snippet algorithm to feature the webmaster's URL, as Google's NLP algorithm is similar to BERT. This would also work for Bing's featured snippets as well.
So, what am I talking about, in a step-by-step process? Let me give you an example.
Let's say your site is penguins.com and you found out that penguins.com/weight.html rank top 10 for "penguin weight." On the SERP for "penguin weight" is wikipedia.org and the featured snippet says "How much does a penguin weigh? A penguin weighs 10 pounds."
Let's say Wikipedia is #2 in this SERP and it's also featured in the featured snippet. Your site is, let's say, #5. If you can get the featured snippet, you'll get a lot more traffic.
Since the featured snippet algorithm is a Natural Language Processing Algorithm, it's a different algorithm than Google's Organic rankings. This gives you 2 shots to rank on the top for this keyword. That's why this process is so valuable. You can get 2 listings on the SERP or get a top ranking listing, without as much work as the organic results, if your webpage is optimized for the featured snippet.
Ok, now that you've understand that, how do you optimize an article for a featured snippet? Easy. If you read that article on the Bing blog, the NLP algorithm works by reading all texts in an index, figuring which ones are relevant to the query, and then figuring which article has the highest confidence score for the query. Then the article with the highest confidence score is displayed as the featured snippet. For Google, the index would be Google's index. For Bing, the index would be Bing's index. If you run BERT on your PC, the index will be whatever documents or text strings you feed BERT.
So, let's go back to penguins.com/weight. If that article does not state clearly and plainly the weight of a penguin, it's not optimized for the featured snippet. An edit can be "<h2>Penguin Weight</h2><p>A penguin weights 10 pounds</p>". By having such a clear and concrete piece of text in the article, the NLP algorithm can easily tell that it's an answer to that query. It'll then give you a shot at ranking in the featured snippet, when you had no chance before.
Do this for all keywords that your site ranks for, where there's a featured snippet and, Cha-Ching, more traffic
It's only about 1 or 2 sentences per keyword to make these edits.Now... if there was only an easy to use tool where it'll show you the keywords your site is ranking for and if that keyword has a featured snippet box, where your site's not featured.... Hmm....
