One thought I wasn’t able to put in the last post about missing and misleading click data, was about keyword click-through-rates.

Do keywords really have click-through-rates?

Objectively they do because the engines report them. But does that make sense?

If A Keyword Falls In The Forest, And The User Doesn’t See It…

The user doesn’t even know the keyword exists. The user typed a query (which in some small percentage of searches was exactly matched to the keyword, but far more often was only related to the keyword) and was shown (if they even saw it) a text-ad (containing some specific copy) in some position on the page in relation to a number of other text-ads (not to mention the organic search results.)

What portion of the influence in that click, or lack thereof, did the keyword have?

• We know different text-ad copy produces different CTRs.
• We know different positions result in different CTRs.
• We know that the presence or absence of specific competitive adds produce different CTRs.
• We know different queries that may match to the same keyword in broad or phrase match type have different CTRs.
• We can assume that CTRs vary by time and the geography of the user.
• There must be a couple of other factors I’m not thinking of right now… (comments?)

So does the keyword really have a CTR, or do the combinations really have CTRs? Clearly the Keyword CTR is the average of a range of different situations and conditions.

The Average Average is Only So-So

There are a lot of averages presented in search analytics. That’s necessary as we can’t handle all the granules, but close attention must be paid to the composition of these averages, lest they be less than clear or useful.

If the campaign is reasonably constructed in terms of organization and match type application, and are being reasonably run (meaning the text-ads and bids have both logic and dilligence being regularly applied to them), then the average CTR as reported for keywords can be useful. If any of these elements are missing, the utility dwindles rapidly.

As with most averages in PPC reports, if you aren’t sure dive down and look at the components - the more performance diversity you find inside the less weight you should place on the average.

Know Your Metrics

Just another example of the fact that even the simple metrics of paid search have more to or behind them than you might realize, and how some understanding and healthy skepticism can help you get closer to truly understanding what’s happening in your campaigns.

(Credit where it’s due: The idea of questioning KW CTRs, and many other ideas you’ll find in this blog from time to time, was first suggested by Bruce Ernst)

(Upcoming Events: I’ll be at the Semphonic XChange Conference in San Francisco on Aug 17-19, and am Speaking on “Identify, Analyze, Act: SEM by the Numbers” at Search Engine Strategies in San Jose on August 19th)

Another lawsuit aimed and preventing the use of trademarked keywords was dropped this week. This time it was American Airlines who had filed a lawsuit against Google for allowing other to use their name to trigger the display of competitive ads.

According to Bloomberg:

American claimed Google violated its trademark by allowing competing airlines to bid on keyword searches that generate “sponsored link” ads on search-results Web pages. The ads take advantage of the American brand’s popularity, even if the name isn’t used in the ad, the carrier said.

Google settled similar suits by other U.S. companies before the untested area of trademark law could be addressed by a judge or jury. Foreign lawsuits still pose challenges to the advertising practice, part of Google’s AdWords program.

Courts in France have held Google liable for allowing advertisers to select trademarked terms as keywords, according to U.S. regulatory filings. Google, based in Mountain View, California, said it is handling or recently resolved similar cases in Germany, Israel, Italy, Austria and Australia.

Google had argued that its “invisible” use of trademarks isn’t technically “trademark use” under U.S. law. Google compared the program to practices such as placing generic drugs next to name brands in pharmacies and buying billboard ads next to those of competitors.

This last point is the reason I’ve never understood the merits of these suits. Trademark law is designed, in my very simple understanding, to prevent one company from confusing customers with a name that is similar (or identical) to another company.

Does buying a trademarked term as a keyword provide one company benefit from the name and reputation of another? Certainly. But isn’t that why all the car dealers rent space on the same block? Doesn’t it happen when magazines review all the products in one category together?

Every company in the world wants to steal customers and prospects from their competitors. Their efforts to do so yield better features, better pricing, and loads of other consumer benefits.

Using trademark protection to limit confusion benefits consumers. Using it to try and limit consumers knowledge and awareness of competition harms consumers, and should itself be illegal. Great to see a lawsuit go the right way.

The first and second posts of this series introduced and expanded on the concept of the Match Type Keyword Trap. In the first, it said:

Over time, by watching the queries that each keyword attracts we can tune this system quite precisely, not only filtering unwanted queries with new negative keywords, but expanding our total volume through quality score and bidding improvements and tailoring the ROI of different query classes.

And promised to expand and elaborate. So here it is:

Tuning Options

When you buy the same keyword at different match types, or different keywords and phrases at different match types in a coordinated effort to properly target and value queries, your initial settings will be less than perfect.

You don’t know what queries you’ll see, the price you’ll pay for each, or how they’ll perform in terms of conversions.

But you can monitor and measure each of these over time, and make adjustments to create a more effective trap.

There are three controls you’ll primarily use to tune the trap:

• Negative Keywords - Without question your campaigns will see (and you’ll pay for) queries that are either undesirable or prove to be poor performers. You should continually review query reports and add keywords as negatives either to all appropriate ad-groups, or to those which have bids above the keyword value.
• Add or Move Keywords - As you review the queries caught by each keyword and ad-group, and the performance of both queries and keywords, there will be interesting or well performing keywords which should be moved up the match type & bid hierarchy.

  If a query is performing exceptionally well against the Phrase Match option, for example, you might want to create an Exact Match copy of that keyword and give it a higher bid. This should cause that query to be grabbed by your new Exact Match and yet let other matches to that Phrase Match keyword keep matching there.

  Well performing keywords in the Broad Match group (which is usually bid particularly low) are especially good candidates to be ‘promoted’ into the higher-bids & more targeted environments of the Phrase Match or Exact Match ad-groups.

• Raise or Lower Bids - Based on your goals (revenue or CPA or ROI or whatever) and reflecting the measured performance of the purchased keywords, find the right shape of the pyramid by bidding good Exact Match performance up and cutting Broad Match bids as you negative out losers and promote winners.

I should have pointed out somewhere earlier, that by far the best way to configure the MTKT is to separately each keyword group with different Match Types into separate Ad-Groups. This makes reporting and measurement easier, and allows you to control negatives at the right level.

As a naming convention , we end each Ad-Group name with a (E) if it holds Exact Match keyword, (P) if it holds Phrase Match keywords, and (B) for Broad Match. This makes is much easier when visually inspecting reports or making account changes.

Measuring Progress

Success with your MTKT is achieved when you’re attracting only desirable queries and have maximized ROI by setting bids according to conversion profitability.

Reviewing the queries on an ad-group by ad-group basis is the cornerstone of the process.  The Exact Match keywords should be clear and profitable. The Phrase Matches should be on target or quickly either promoted to Exact or made into negatives. And the Broad Match should also winnow down in many cases (but not always) through promotion or negative creation.

In some cases the Broad Match ad-groups are ultimately turned off, or left running with extra low bids just to capture any potentially new and interesting queries.

Results are harder to summarize, although as pointed out in the previous post, what you normally shouldn’t see is great variation between the ROI (or ROAS if you must still use that horrid metric) for the different Match Type divided ad-groups.

There are exceptions, but they should be positive ones where Exact Match, or more rarely Phrase Match groups are extremely profitable while others are just normally so. But very low or negative returns are a sign that either the queries being attracted just don’t have potential, or else something later in the chain is wrong - ad-text, landing page, offer, checkout process etc.

Next Up

In the next post, unless something else comes up we’ll finally cover that Rock Scissors Paper game I promised to disclose.

The previous post introduced the idea of building a Match Type Keyword Trap. This layering of keyword & match type combinations provides control over which, where, and how queries are attracted, and therefore their cost-per-click.

In the simplest case, you’d buy one keyword (say ‘Whaazooh’) three times in one campaign - once on Exact Match, once on Phrase Match, and once on Broad Match.

The goal is to catch all queries which are literally ‘Whaazooh’ with the Exact Match keyword, all queries which are ‘Whaazooh’ plus some word(s) before or after it with the Phrase Match, and all other related queries with the Broad Match.

Why?

Because in almost every case where many different queries exist for a single word or topic, some of those queries are very valuable, some are mildly valuable, and many are not valuable (or at least not valuable enough). We want to segregate these queries by their value to us so we can pay highly for the high value ones and less so for those less valuable.

In the simple cases (I have to keep saying that because not all cases are simple, there are many complex variants of this) we’ll do better by trapping the best ones with the most specific Match Types (Exact if possible or Phrase if not) and using Broad Match to harvest winners and losers which are acted upon accordingly.

Winners are promoted (to Phrase Match or Exact Match). Losers are demoted via lower bids or even made into negative keywords.

We do better not because of the place they’re trapped, but because by segregating them we control the bid (as well as the text-ad, landing page, etc.)

Forcing The Stack

Buying the same keyword three times at different match types does not itself bait the trap. If the same word is purchased at both Exact and Broad, and has the same bid and earns the same quality score, chances are good a related query with be matched sometimes to one and other times to the other.

To force the trap to work you have to stack the bids - higher for the Exact Match versions and sequentially lower for the Phrase and Broad Match versions. This gives the Exact Match keyword multiple reasons to attract and win the Exact Match queries; it is a better match and it is bid higher (which is good in itself and factors into quality score).

When you do this, leave enough room between the various bids. The Average CPC the engines report are averages, so expect a range of bids in each and leave enough room so the ranges don’t overlap.

In this example, we bid higher for several terms that have proven great performers, setting them on Exact Match and bidding $1.25. Several others that are good performers and perhaps come in some variations are set at Phrase Match for $0.65. A larger collection of phrases and concepts are bid Broad Match at $0.15. Over time we shift, add, put in more negatives, and generally take control over how we pay for and catch queries.

Equalizing Return

How do you know if it’s working?

In theory you’ll normalize the ROI (or ROAS if you must) for your Exact, Phrase, and Broad Match keywords. In other words, you’ll raise bids for your Exact Match keywords to maximize profits. You’ll set accordingly lower bids on Phrase and Broad Match keywords until they produce the same return as the Exact Match does - so their lower conversion rates and ROI are compensated for with proportionally lower bids.

They get the bid they deserve.

To Be Continued

Again there are many exceptions and details left out of the above descriptions for the sake of time and length, but I’ll move into examples in future posts which should illuminate the concept. In the meantime, if you have any questions about this leave a comment and I’ll elaborate.

Match Type is the PPC option which has perhaps the highest impact, is the least understood, and is most often under-utilized.

In this and the next few posts, I’ll take a long look at the Match Type option and how and why you should use it to improve your paid search campaigns and results.

Match Game

The Match Type option is the primary connector between your keywords and the search queries users actually enter into the search engines. Each keyword has a Match Type associate with it, which defines how the keyword is connected to queries. On Google we have these options:

• The EXACT Match Type turns the keyword into a rifle. It will only cause your ads to be displayed when the query is identical to the keyword. (At least in theory, we’ll cover some real world exceptions later).
• The PHRASE Match Type turns your keyword into a shotgun. It will hit anything surrounding the keyword as long as the query contains your purchased keyword(s) with anything before or after them.
• The BROAD Match Type turns your keyword into a bomb. It will explode in all directions and send debris and shrapnel farther and wider than you had ever imagined. In other words, the keyword can match pretty much any query the search engine decides is even tangentially related. (There will definitely be more on this later).

In addition to these Google now offers ‘Automatic Matching’ as we’ve written about previously.

The theory of these basic Match Type definitions are easily understandable - but in practice deciding the right Match Type isn’t always easy.

The problem is that each Match Type is a filter of sorts, letting certain queries through and stopping (or reducing the probability of) your ad from showing for other queries.

But these are rather coarse filters, and when considered against the massive diversity of search queries that users type when looking for something, plus the impact of other factors such as bids, quality score, and competitors, any Match Type choice becomes a pretty large compromise.

A Brand New Example

Let’s consider what might appear to be the simplest of all Match Type situations; your company name. Suppose that you’re running the paid search campaign for the well-known excess-capacity auctioneer Whaazooh.com.

What Match Type should you place on the brand name keyword ‘Whaazooh’?

• If you buy ‘Whaazooh’ on Exact Match, your ad is eligible to run only when the search query is ‘Whaazooh’ (or ‘whaazooh’) but miss every other direct variation (’whaazooh.com’, ‘whaazooh inc’, ‘Whaazooh acutioneers’ as well as the mis-spellings ‘waazoo’. Of course, you also don’t get any of the contextual but not literal search queries either - you’ll miss ‘liquidation auctioneer in Palookaville WI’ and thousands of other searches who were intentionally or conceptually asking a question that your ad could have answered.
• If you buy ‘Whaazooh’ on Phrase Match, your ad is eligible to run for ‘Whaazooh’ or ‘whaazooh’ and direct variations that include ‘whaazooh’ such as ‘whaazooh.com’, ‘whaazooh inc’, ‘Whaazooh acutioneers’, ’shop at whaazooh’ or even ‘whaazooh sucks and you should never do business with them’. You’ll still not be running (at least due to this keyword) for any conceptually related searches.
• If you buy ‘Whaazooh’ on Broad Match - the default and most popular match type, everything is potentially covered. You’re ad is eligible to run for ‘whazzooh inc.’ and ‘whaazooh reviews’ and even ‘excess diamond tip drill bit dealers’. You’ve officially cast a wide net.

Each step from Exact to Phrase to Broad opens you up to a larger quantity of (generally) less specific search queries. Some of these incremental queries are relevant and will prove profitable, but many will be  irrelevant, or at least low converting.

Buying ‘Whaazooh’ on Phrase match means you could easily pay for the click of someone who searched ‘Boycott Whaazooh’. And on Broad Match you almost certainly will pay for the clicks of people who searched for things which are 100% unrelated to your company, products, and industry.

So deciding the right Match Type requires balancing the benefits of progressively more diverse query matches against the risks of progressively more diverse query matches.

But for most keywords there is no perfect balance. You’re left to try and find the most acceptable compromise between volume and profitability.

Building Filters With Keywords and Match Types

The problem is actually somewhat easier to solve if we think about it in terms of a group of keywords all working to attract a set of related queries.

This is also more akin to your real world ad-groups, where there are many related words and phrases and each, depending on the Match Type could attract queries related to the same subject or using the same terms. Often even the same keyword will be purchased multiple times within one campaign, setting the Match Type differently in each instance.

In this way you can build a layered keyword trap, using the Match Type option (along with our Bid and several other controls) to specifically capture certain queries at the Exact Match level, others at the Phrase Match Level, and still more at the Broad Match level.

Considering the ‘whaazooh’ brand for example, we can buy the keyword and some related phrases separately at Exact, Phrase and Broad Match Types, and (assuming proper bidding and quality scores) we’ll catch specifically targeted queries at each layer while letting others fall through to be caught (or not) by the levels below.

Over time, by watching the queries that each keyword attracts we can tune this system quite precisely, not only filtering unwanted queries with new negative keywords, but expanding our total volume through quality score and bidding improvements and tailoring the ROI of different query classes.

In a later post we’ll take a detailed look at this tuning process.

Taking Control

The great benefit of this model is that it lets us take pretty significant control over the keyword to query matching process back from the search engines.

Rather than just buying Broad Match keywords and letting the engine decide which queries are important, or buying just Phrase or Exact Match keywords and missing out on a lot of volume, we set the stage to have the best of all worlds.

And with proper Ad-Group and Campaign configurations and good tracking software we’ll have amazing visibility into our progress, so we can understand things clearly and tune rapidly.

To Be Continued

This has been a long post, but covers only a fraction of the issues and side-bars and related topics and option settings necessary for really effect use of the Match Type options. In the next post we’ll look at this Match Type Filter Set more closely, and review the associated bidding strategy that makes it work and drive profitability.

I’ll also discuss in more detail why this works due to a secret game of Rock Scissors Paper going on deep in the data centers of Google.

Questions or Comments about Match Type? Please leave them in the comments!