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Applying The Theory of Sets In Match Types
When I was a math teacher, I spent a lot of time doing what I thought was, well, ‘teaching.’ In my first few months on the job, I focused on the logic behind the mathematics, not the formulas or other shortcuts. Students constantly complained about this, and they were failing tests, so, after higher-level discussions, I started going over the easy way to do things: the formulas.
I was rather surprised when students started doing really well on tests – but when I verbally assessed their understanding of the logic, I was still greatly disappointed.
Furthermore, they completely fell flat on more complicated problems that require more than just plug and chug. Students were just cramming and memorizing and didn’t truly learn that much.
In paid search, there are a lot of parallels. I run across many account managers who believe in exact match and don’t believe in broad match. It’s a rule to them, in fact – an axiom in their minds. When prodding further by simply asking ‘why,’ I feel like a math teacher all over again. Ask ‘why’ and you get shallow half-answers that remind me of the plug-and-chug crew,
I’m not much of a paid search historian, but imagine it’s about 1997, and you’re part of the team developing the first pay-per-click platform. There’s no such thing as match type, so how do you create the concept? What question was “match types” trying to answer?
Well, to me (and assuming “keyword” was already a concept), it’s “how do we determine which sets of queries keywords are matched to?”
If you’re focusing on match types in paid search, you’re focusing on the ‘formulas’ – which means that a lot of the logic is being lost. To understand how to best use the ‘formulas’ of match types, you must understand the theory of sets.
First, we’ll define the match types based on sets. Then we’ll explore query-to-keyword mappings by match type – what works, what doesn’t, what we should strive to achieve.
Then, we’ll show how layers of complexity like negative keywords can create chaos within match types.
By the time we hit the conclusion, my hope is that you’ll have decided for yourself that simply managing accounts by match type leaves a lot to be desired – and a lot of ROI on the table.
Defining Match Types Based On Sets
Depending on the platform, the sets of queries matched to a particular keyword match type varies. Here’s the current AdWords definition of each match type. (Note that I’ve replaced the word ‘searches’ with the phrase ‘set of queries.’):
- Broad match allows your ad to show for the set of queries on similar phrases and relevant variations.
- Broad match modifier allows your ad to show for the set of queries that include your broad match keyword or close variations of your broad match keyword.
- Phrase match allows your ad to show only for the set of queries that include the exact phrase, or close variations of that exact phrase, and possibly other words as well.
- Exact match allows your ad to show only for the set of queries that use that exact phrase, or close variations of that exact phrase, and no other words.
By now we should have consensus that match types are not required to exist. They vary in quantity and definition across platforms and capture slightly different sets depending on current match type definitions. They are simply answers (they could be correct or incorrect answers, by the way) to the question of how to capture queries.
In PPC, we’re required to use match types; we don’t have any other choice. However, now that we understand that our actual question is ‘how do we deal with sets,’ our perspective on what makes a good SEM may change.
When dealing with sets, you must also deal with mappings – in our case, query-to-keyword mappings. When studying mappings, you will find Google employs one-to-many mappings and many-to-one mappings, but it almost never uses one-to-one mappings.
The first image is a ‘one-to-one’ mapping, the second ‘many-to-one,’ and the last ‘one-to-many.’ The input (X), in this case, is the query, which is matched to the keyword, the output (Y).
Looking at these images, which do you think would be the most optimal way to run a PPC account?
Hopefully we all agree it’s better to be in control of mappings, and the one-to-one mapping is best in instances where there is enough actionable data to make use of it. Despite this, I don’t think I’ve ever seen a true one-to-one mapping, unless we force the one-to-one mapping with crafty account structure.
The other mappings are essentially the advertiser giving the platform liberty to control the mappings, and, when given the chance, the platform will do mass experimentation to maximize the SERPs eCPM.
To really nail PPC, optimization efforts must be made on consistent, hopefully non-overlapping sets. If the sets are constantly changing, then you are optimizing against a moving target.
Some may think that exact match creates one-to-one mappings, which is why so many people “believe in exact match, but not broad match.” However, at best, exact match creates a one-to-many relationship. This means that, yes, the exact match keyword can only be matched to one query, but the query can be matched to many other different keywords. It could, for example, be matched to the broad-match version of your exact match keyword if it exists.
Going back to our match type definitions, the query ‘wedding invitations’ could be matched to not only the exact match [wedding invitations] but also the phrase match, broad match, or modified broad match version. By viewing the search query report, you should see one query being matched to multiple different keywords at different times.
Essentially, the factor that determines where the query is matched is ad rank (QS x bid). And, you’ll find that most of the time for similar keywords the QS is similar, so the match usually finds its way to the highest-bidded term.
With ‘near match,’ exact match can also become a many-to-one mapping, where multiple queries are matched to one keyword. This means that advertisers are not in control of much of anything, particularly if they follow the common best practice of ‘using all match types.’
I don’t want to simply make a blanket statement and say that one-to-one mappings are what all advertisers should strive for with every query. That’s impossible, and it’s also not optimal! I do, however, think it’s important to understand the mappings within an account and, based on what the advertiser has determine is optimal, create the desired mappings.
In general, however, one-to-one mappings are best (one query goes to one keyword every time), and many-to-one (many queries go to one keyword every time) are second-best. Worst is one-to-many mappings (one query goes to many different keywords) from an advertiser’s perspective because there is very little control, and data is very fluidly going one from keyword to the next.
From Google’s perspective, the opposite ordering is true, and they prefer one-to-many mappings. That is why Google sends so much traffic to your broad-match keywords! For Google, more chaos equals more money. Most of the time, advertisers have nothing but one-to-many mappings across their account.
Sets Influence Other Sets
Think of a negative keyword as a knife. It must be used with care, otherwise you’ll cut out some good stuff. But be too conservative with your knife, and you’ll be left with a lot of wasted spend.
What a negative is doing is removing queries from your reach. So, it’s taking one set, whether it is the set of queries matched to your campaign or the set matched to your ad group, and eliminating a sub-set.
This isn’t the most complex logic until you start thinking of how, in actuality, the removed sub-set actually impacts many sets at once. In the case of campaign negatives, it impacts the entire set of queries sent to any one of your keywords at any time.
Where this can get really scary is when people start to create account structure based off of match type considerations, and not sets. For example, it’s common to set up one campaign in exact match (no negatives), one in phrase (only exact negatives), and another in broad (phrase and exact negatives). Each campaign would have the same positive keywords.
Consider the set of queries an advertiser who sells iPads and iPad 2s would find relevant. The advertiser may conclude he/she only needs two keywords: iPad and iPad 2. Let’s agree with this assumption for the purpose of simplicity.
So, you’d have the following:
Campaign A – the set of queries ‘ipad’ and ‘ipad 2’:
Campaign B – the set of queries containing, but not equal to ‘ipad’ and ‘ipad 2’
Campaign C – the set of queries to whatever Google deems relevant but not containing or equal to ‘ipad’ or ‘ipad 2’
If a user then queries ‘buy ipad 2,’ where does the query get sent to? The answer is….somewhere in campaign B but I don’t know where. I think ‘ipad 2’ is more likely than ‘ipad’, but it depends on the ad rank!
This is starting to sound like quantum physics, and I don’t think it’s good to run accounts like quantum physics (set theory is hard enough).
Instead, consider the following:
Campaign A – The set of queries that contains ‘ipad’(or minor variation) but not ‘2’ AND (in a different ad group) the set of queries that contains the token ‘ipad’ (or minor variation) but in only conjunction with ‘2’.
Ad Group 1
Ad group 2
Campaign B – The set of queries Google deems relevant but not those containing the phrase ‘ipad’.
Ad Group 1
Ad Group 2
-“ipad” (feel free to add in -“ipad 2” if you’re a neat freak!)
In this structure, which is quite a bit simpler in my opinion, I’d know that any query containing ‘2’ and ‘ipad’ goes to the ad group for the ipad 2 in Campaign A.
That’s important because I have different ad copy for that ad group, and probably a different bid. Not to mention I have different margins for each product, and a different quantity in stock. So, I know when someone queries ‘buy ipad 2’ it goes to my ‘+ipad +2’ ad group.
I don’t think this is the type of an article that needs a conclusion. My hope is that you’ll say ‘hmmm,’ and ‘I’m not quite sure about that’ a whole bunch! The idea is simply for everyone to get their thinking caps on and start thinking about queries and query sets, and not keywords.
Making great accounts is about more than great copy, great landing pages, and great products; it’s also about great query mappings and valid data based on consistent sets. Many paid search accounts are like whack-a-mole, where fixing a problem one place just results in it popping up elsewhere. If you can create a solution to the whack-a-mole problem, then you’ve got a great PPC account.
All right, “class,” this week’s homework assignment is to tell me what is wrong with my proposed campaign structure!
Some opinions expressed in this article may be those of a guest author and not necessarily Search Engine Land. Staff authors are listed here.