Let me share with you how one PPC advertiser achieved…
- An ROI increase from 77% to 323%
- A conversion rate increase from 6.15% to 8.39%
- A CTR increase from 6% to 8%
…solely through match type testing and refinement.
But first some background… Match types have come under more and more scrutiny in the past 2 years, given the coming of Google’s Expanded Broad Match and Automatic Match types. In fact, the unmonitored reckless use of Broad Match was the subject of a presentation I made this year at SMX West’s Avoiding PPC Pitfalls search session.
The fact that I presented Broad Match as a ‘pitfall’ actually does not mean that I am adamantly against the use of Broad Match. It can be a powerful tool for exploiting the long-tail and increasing sales and leads. But Broad Match (and Yahoo’s Advanced Match for that matter) can all-too-easily become a major pitfall, if left unchecked.
Like any other PPC lever at our disposal, match types do not lend themselves to any sweeping generalizations – ‘always broad match’, ‘never broad match’, ‘only use exact match’, etc. Instead, like any other element of PPC you should continually test, monitor and adjust with the end goal of improving ROI and in turn increasing the lead or sales volume for your company.
Even though my SMX presentation was over 6 months ago, this issue of match types has resurfaced and spurred me on to write this blog post for 2 closely related reasons. First, we’ve followed our own test-monitor-adjust advice and discovered some more interesting match type learnings since SMX West that I’d like to share with our readers. I’ll get to that in a bit…
The second reason I revisit this topic now is that PPC Hero (one of my favorite PPC blogs which I HIGHLY recommend subscribing to, by the way) posted 2 match type related articles in the past month. The first, A Poor PPC Account Structure Will Make Your Campaign Suffer, described some oddities that Hanapin Marketing discovered upon inheriting a PPC account. One of these oddities (which turns out not to be an oddity after all) was that the campaigns were broken into ad groups according to Broad, Phrase and Exact match types.
The second major offense, and this strategy puzzles us, is that they had match types separated into different ad groups. For example, one keyword would appear in three different ad groups; one for broad, one for exact and one for phrase. Using match types can help determine user intent and you can use this data to focus on the match type that works best for your audience. But separating the match types doesn’t make much sense.
This account structure is actually the same highly effective manner in which Closed Loop Marketing has conducted some of its match type testing! In fact, apparently other PPC Hero readers have tested similar tactics and alerted the author that separating different match-typed keywords into unique ad groups was in fact a viable match type strategy.
Admirably, Joe posted a 2nd article less that a week later: Two Match Type Strategies That Can Enhance Your PPC Performance:
Last week I wrote an article about an account that we inherited that had been constructed and managed poorly. One of the strategies I called into question was separating keyword match types into unique ad groups within Google AdWords. However, we had quite a few comments from our readers stating that this is a strategy that they employ frequently with great results.This is one of the best things about our blog: I’m always learning how different people manage their PPC campaigns! After conversing with our commentators I thought I would give everyone a summary of what has been discussed.
So, in light of all of this — our match type testing results and the recent PPC Hero’s articles that directly tied in — I would like to share with you how one of Closed Loop Marketing’s clients has increased its ROI more than 4X by refining its match types (finally, you’re thinking).
One of our clients that we provide PPC auditing services for had historically been broad matched across-the-board for nearly all of their search terms. Upon auditing their campaigns in search for areas of improvement, we discovered literally hundreds of thousands of dollars of wasted spend that had resulted from irrelevant broad matched iterations. It was the worst case of broad-match-gone-bad that we had ever seen.
In the midst of all of this poor broad matching that had occurred within their account, their coverage levels for their most strategic keywords averaged only 30-50%! So essentially, this client’s ads were dark over half of the day for the keywords that were their largest revenue drivers, because their budget was being eaten up by keywords that had nothing to do with their offerings!
Needless to say, one of our many recommendations was to test other match types, tracking each for revenue and ultimately ROI. Couple this with building out a robust negative keyword list and we’d be on our way to seeing some major improvement.
Curiously, this was met with a lot of resistance by those actually managing the campaigns in question. They felt quite adamantly that everything should remain Broad Matched. So being responsible advertisers, we all agreed to put it to the test.
Much like what is described above by PPC Hero, a subset of keywords were chosen, all 3 match types were applied to each keyword and then those keywords were split into Broad, Phrase and Exact match ad groups. Aside from the match types, all else was equal – same ad copy, same landing pages, same bid strategies.
During the first half of the test, with all bids set to target #1 positioning, the results were as follows:
As you can clearly see, the ROI, conversion rates and CTR for the Exact and Phrase matched keywords are significantly higher than their Broad Matched counterparts. The first thought is to toss out Broad Match all together. But…
During the 2nd half of the test, in order to see if Broad Matched keywords could be salvaged and still prove some value (i.e. be made to be profitable), the Broad Matched keywords were bid down to position 3. Exact and Phrase Matched keywords remained in position 1.
The Broad Matched keywords increased from a measly 14% in the #1 position, to 261% in the #3 position! In essence, even though the Broad matched iterations of the keywords weren’t as valuable as the Phrase and Exact matched terms, by placing lesser value on them (i.e. placing lower bids) they were capable of producing revenue at a profitable level.
Now don’t get me wrong, this is not the end of the story. The next task is to apply this to a larger set of keywords and continue to refine. In fact, the client is now on Round 3 of this match type testing and has since found that Phrase Matched terms needed to be bid down to position 2 in order to maintain profitable ROI. For the time being, the strategy stands as Exact Match ad groups being bid to position 1, Phrase Match position 2, Broad Match position 3.
This particular position-based, match type strategy is just one match type lesson learned for one of our clients. Many of our other clients aren’t using Broad Match whatsoever because it just simply hasn’t proven to be advantageous for them at their current budget levels.
And this is why we need to avoid making any sweeping generalizations. All campaigns are individual – test, monitor and adjust. I highly encourage all PPC advertisers to conduct similar tests on their keywords, as match typing is an often overlooked strategy that if refined can be a dramatic source of increased revenue and ROI.