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There is a common Pay Per Click (PPC) misconception floating around out there for Google Adwords. Many search marketing specialists believe, because “broad” match is the default and arguably the most common match type, it is the match type that has the highest cost per click (CPC) for good ad positions. So these specialists focus on the “phrase” and “exact” match types in the hopes of stretching their marketing dollars by paying a lower CPC.

Now I must admit, I was in the category of believers of this misconception when I first started doing PPC. *Hangs head in shame* But, as I gained experience, I noticed something. For certain local niches, “exact” match had a way higher CPC than the “broad” match type. But why?

Think about it. If you were a personal injury lawyer in Houston, someone searching for “houston motorcycle accident lawyer” and using the exact same phrasing in the search, are more likely to turn into an actual client; which is worth more than the visitor that came from a “broad” match type. The “broad” match type visitor saw the ad and clicked it even though they used the phrase “houston motorcycle accident lawyer stories” in the search box. Someone looking for stories is obviously less likely to turn into a client and more likely to be doing a research paper for class. Now there is a way to avoid this using negative keywords, but that is another topic.

Now, I did mention that I noticed this for certain local niches, but that doesn’t mean this only applies to local niches. Every industry is different. The competition is different, the search volume is different, the demographic is different, etc. etc. The golden rule in proper PPC management is, analyze the data, make adjustments, test, analyze the data, make adjustments, test, analyze…well you get the point.

So the trade off is often, pay more for highly relevant and qualified leads, but eat through your budget faster; or pay less for less relevant leads, but stretch out your budget further to get more traffic. How do you decide? Well, as stated before…….test, analyze the data, make adjustments, test analyze the data, make adj……