Negative Keyword Research Simplified (Episode #6) – AIMCLEAR‘s Deep in the Sheets

Posted in Analytics & Reporting, Paid Search

Posted on November 19th, 2014

This episode of Deep In The Sheets covers how to simplify extensive negative keyword research with a large query set. Using a scraping tool known as ScrapeBox, we document suggested search query ideas from Google and/or YouTube suggestions. This specialized research allows us to provide targeting fodder for search campaigns or as negative keywords that do not match our targeting criteria.

Check out the video to see the process in action and the video description for the step-by-step detail.

Video Transcript

0:00-0:09
Hey everybody! Manny Rivas here, and on this episode of Deep in the Sheets, we’re going to talk about how to do extensive negative keyword research in a snap.

0:10-19
[Music plays]

0:19-0:27
Okay, so here’s the scenario: You’re launching a new search campaign in a keyword space you haven’t yet explored.

0:27-0:37
So you want to do your due diligence and understand if there are keywords that are completely unrelated to the terms and queries that you’re looking for.

0:37-0:43
So, you could go to Google and look at search suggestions by hand,

0:43-0:49
You could type in particular queries, like for example, we’re gonna do “wizard hats.”

0:49-52
And you can see suggestions that Google gives you.

0:52-56
And you can see some that are relevant, and you may find others that are completely irrelevant.

0:56-1:05
What we’re gonna look at today is a scraping tool called “Scrape Box,” which allows you to do this in mass.

1:05-1:09
So let’s take a look. So this is the tool,

1:09-15
and on the left-hand side I’m going to put in my search term, “wizard hats.”

1:15-1:22
And below you can see “Append A-Z.” We’re gonna do an alpha pattern on our search term, “wizard hats.”

1:23-1:28
Automatically it will append those, and I can go ahead and scrape the suggestions from Google.

1:29-37
So after it gets through doing its search, I then port that over to my Excel file, my working sheet,

1:38-41
and this is what it looks like. I have them all stacked in a column,

1:41-48
And what I do from there is I remove the relevant keyword; the core term, “wizard hats.” And that brings us to this.

1:48-56
And now we have all the other keywords that make up that query. So from here we take our stacked queries,

1:57-2:07
And we simply put them in text to columns; we choose the text to columns function, we break those out, and then we’re going to stack them again.

2:07-13
We’re gonna stack them on one another so we get one column. And what we’re after here is a pivot table,

2:13-22
where in our row labels we have the words, and in our values we have the words. So it’s simply going to give us the count of those words.

2:22-30
So every time it appears in that column, it will count it up. So we can see that “Potter” is at the top of the list.

2:30-38
And we—at a quick glance we can see what keywords are irrelevant to what we’re targeting.

2:38-48
So it’s an easy way—an easy exercise to get at those negative keywords that we want to eliminate out of the gate from our search campaigns.

2:48-55
And that’s how you do extensive, negative keyword research in a snap. [Laughs]

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  • paul

    couldn’t you just use ubbersuggest as this scrapes Google suggest?
    I’m always looking for negatives… more negatives the higher the CTR and hence higher the Quality Score and lower the CPC.

    To find diverse range of negatives I usually just use the KW Planner.

    • Manny Rivas

      Ubbersuggest is totally an option to get negative keyword ideas. What I like about scrapebox is you can run thousands of keywords at once. When doing large batches, the thought is to pivot high appearing terms, to cut through the noise.

      If running smaller batches, ubbersuggest, mozenda, scrapebox, soovle would all be good candidates to get at those suggests.

      Thanks for the comment!

      Cheers