Social media managers and content marketers can use Google and third-party tools to pinpoint specific topics, not just broad keywords, that people are actually searching for.
Marketers need more than broad keywords
Social media marketers now know the importance of researching and using keywords to attract organic search traffic; however, they may struggle with finding out exactly what audiences want to know about the targeted keywords.
For instance, if part of your job is to manage the blog of a company that develops and markets data visualization tools, you need to develop contents related to “data visualization” – but indeed, how do you keep coming up with relevant topics, and feel certain that these are the contents people want or need?
To answer that question, we can examine actual searches related to the “seed keywords,” and actual search volume for the related searches. To that end, I recommend using three tools: Google autocomplete, Keyword Researcher and Google Keyword Planner.
Find out actual searches related to “seed keywords”
When you type in the search box at Google.com, Google automatically suggests actual searches related to what you are typing in. This feature is called autocomplete; and those suggestions are based on actual search records that Google tracks and keeps.
So, if you type in the search box “data visualization,” Google will suggest a few actual searches, as seen in this screenshot:
Now you have some content ideas. However, what if the few suggestions are not what you need, or if you just want more ideas? One trick is to add alphabet letters, one at a time, at the beginning and/or end of the “data visualization,” and Google will fill in with actual searches that contain “data visualization” as well as that one letter.
As a demonstration, I added the letter “a” after and before “data visualization,” and this is what Google suggested:
If you repeat the demonstration above and continue to add, one at a time, the remaining 25 letters of the alphabet, you will have a whole bunch of actual searches, some of which will provide for good content ideas and some others, such as “a brief history of data visualization,” can be a ready-made topic for blog posts or for content curation.
Sounds great. But there are two issues with this method:
- It’s tedious, if not impossible, to run through the alphabet and write down all the Google suggestions.
- With the many relevant phrases, how do we know which ones to use in content creation? You don’t want to work on the ones that only a few people are searching.
The solution is to use two other tools: Keyword Researcher and Google Keyword Planner. Keyword Researcher can automate the tedious autocomplete search, and Google Keyword Planner can tell us actual search volumes of each of the autocomplete suggestions.
How to automate autocomplete searches
Keyword Researcher is a paid program that you can download and install on your computer. Once activated, it emulates a human user, repeatedly types in the search box and repeats the autocomplete searches as we discussed above. The user will end up having hundreds or thousands of actual search phrases related to the seed keywords.
Disclaimer: I am not associated with the developer of Keyword Researcher and am not promoting the purchase of this tool; actually, I’ve been using the free version of the program which runs the alphabet from A to H.
As an example, following the tool instructions, I looked up actual searches related to “data visualization,” and received a list of 161 related searches (the free version stops at H); below is the partial list:
How to find search volume for relevant keyword phrases
With this list of keyword phrases, I used another free tool, Google Keyword Planner, to find out actual search volumes for each of the 161 phrases, and rank-ordered the results based on average monthly searches; the results are shown in the screenshot (partial table):
Looking at the search data, it seems “a brief history of data visualization” is not a worthwhile topic to invest our time, because the two history-related keyword phrases on the list both have low search volumes: history of data visualization, 50; data visualization history, 30.
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