Google Suggest isn’t exactly a tool, but I’ve found that it can be useful for identifying potential keywords. As you type a query on Google.com, Google Suggest recommends search queries based on other users’ search activities. These searches are algorithmically determined based on a number of purely objective factors (including popularity of search terms) without human intervention. The Suggest dataset is updated frequently to offer search queries that seem to be trending upwards. This feature is largely one of the reasons that you may see repeat traffic of seemingly long tail keywords. By identifying these long tail keywords and optimizing for them, marketers can capitalize on seemingly obscure keywords with little competition.
This isn’t the only tool that mines Google Autocomplete. There’s also KeywordTool.io, but this tool restricts results to ~700 keywords (more are available for “pro” members). Infinite Suggest is another alternative, but despite the name, I’ve found that it still doesn’t find anywhere near the number of keywords that Keyword Shitter finds. And there are tons of other Google Autocomplete miners too. Just Google “google auto suggest tool” for more. There’s also this tool from SEOChat which mines autocomplete suggestions from Google, Bing, Amazon, and YouTube.
Basically, Google shows the autocomplete suggestions whenever you start typing anything into Google search box. It is in Google's best interest to show the most relevant keywords in the autocomplete suggestions. Keywords that would help Google to retrieve the most relevant websites and help users find the most relevant content for their search query.
I love Moz’s interface and how they give you data on the keywords. It’s easy-to-read, making it an ideal solution for both experts and newbies alike. They’ll show you both numeric and visual representations of a keyword’s monthly search volume, its opportunity for ranking, priority, and difficulty. They’ll also show you keyword suggestions and SERP analysis, which is fantastic and detailed.
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What I really like about them is extensive detail including the keyword difficulty. Ahrefs uses clickstream data to also show how many clicks you will get from the search engine. This is very useful after knowledge graph integration, as many keywords may have huge traffic but they hardly get any clicks from the search engine. Reason being, they get answers directly from the Google search result. Example of one such query is: “birthdate of any celebrity”
If you’re serious about making a success of blogging, you need a keyword research tool like this. Such tools can also prove useful before you even begin. If you have several ideas, you can do your research up-front, and see which niche gives you the most chance of success, and which is already highly competitive. Working this out can save you an awful lot of time and money in the long run.
Understanding the balance of terms that might be a little more difficult due to competition, versus those terms that are a little more realistic, will help you maintain a similar balance that the mix of long-tail and head terms allows. Remember, the goal is to end up with a list of keywords that provide some quick wins but also helps you make progress toward bigger, more challenging SEO goals.
Wordtracker is another service that requires an annual subscription to utilize all of its features. Their database is made up of 330 million search terms, collected from the major metacrawlers, Dogpile and Metacrawler, and is updated weekly. The search data they show is a record of the number of times the exact keyword or phrase has been searched in the United States over the last 365 days. As in the case of Keyword Discovery, this difference in default keyword matching type causes Wordtracker to display search volumes significantly lower than what Google’s tools show.
For the first few months, there was certainly a transition period. However, the new team was able to take over the reigns fairly quickly. A big reason for the quick transition is because I had automated most of the business already. So, the fact that I was stepping away didn't make a huge difference since all the sales, marketing emails, and many other details were already happening on an automated basis.