Instant Negative Keyword Lists
I’ve written before about how standard negative keyword lists can help to improve your PPC performance. But, what if you need some targeted negative keywords to help your account excel?
Of course you should do your research, but what if there were a shortcut that could help make the whole process a little bit easier? Well, there is.
Earlier this month I was pointed in the direction of this post about Google Sets. Using a Google spreadsheet you can in a matter of seconds generate a ton of similar words to any given keyword. “Cool” I thought and moved on.. Then the genius of this hit me: instant negative keyword lists were go!
All you have to do is head over to Google Drive and create a new spreadsheet. Type your chosen word into the first cell, press Ctrl (Option on a mac), and click on the blue box in the corner of the cell, drag down the spreadsheet and voila! A ready made list of similar terms for you to use as you will.
And now you have a list of negatives that you can add to your account as you see fit. In my example I’ve typed in a big-name car brand for an instant list of competitors to exclude – but it might be a way to generate negatives that you never would have thought to add. Here’s what happened when I ran the test for shoe:
While the list includes some specific types of shoe (sandal, boots), it is more focussed on other types of clothes. If you’re using broad match (particularly if you are using modified broad match), you should add the irrelevant clothes types as negatives.
This list might also give you some inspiration to build on your positive keyword list – if you’re targeting shoes, should you also target footwear?
Using Google Sets shouldn’t replace doing your research, but it may help you to speed up the process. So if you’ve realised that your product type is also a slang term for drugs, you can quickly generate a list of related less-than-savoury terms that you really don’t want to see your ads appearing for.
So has anyone else tried using Google Sets to generate their negatives? Or have you got any other tips for creating negative keyword lists with ease? Let us know in the comments below.