PPC Strategy: Match Type vs. Negative Keywords

When making a pay-per-click campaign, the goal is for your ads to show up only for the people that they are most relevant for. Hence, match type and negative keywords as a way of doing just that. But what’s the right combination of match types and negative keywords? Here’s my theory:

If you sell ballerina shoes, for example, bidding on the broad term ballerina shoes will result in your ad showing for the most random search querys such as:¬† “name of ballerina wearing red shoes in that one movie.”

So you may decide to you phrase match, as in, “ballerina shoes.” Impressions will go down, cost-per-click will go down, but your click throughs should go up as you’re reaching a more targeted audience. Run another Search Query Report in AdWords and you will see traffic coming from querys like: ballerian shoes pictures.

Obviously you don’t want your ad appearing for people looking for pictures. So you can choose Exact Type, as in, [ballerina shoes]. This way you’re only getting people searching for those two words in that order. Impressions and CPC will go further down but click thoughs should still go up (relatively) and conversions should also go up since you’re getting an even more targeted audience.

Now take a look at this (PDF):


Searches with 5+ words have increased an average of 10% year over year. People are using more words in their querys which  means your exact match bid on [ballerina shoes] will be missing a lot of potential customers since using only two words in a search query is down 5% year over year.

New strategy: Keep your exact match bid going on [balleria shoes] since the your average cpc on those keywords will be lower. Then keep the broad match keywords but load up on the negative keywords. Run Search Query Reports and look for all the words that don’t have to do with your product and add them to your campaign as negative words: -images, -free, -download, etc.

This way you can keep out the unrelated random searchers but keep attracting the people getting very specific with their search querys.

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