The fundamental principle behind PPC is the keyword match type. It’s literally how we determine when we show our ads on the search engine results page, so understanding this concept is an important step in comprehending PPC as a whole. When I first learned PPC, it was explained to me like so:
Exact match must contain the search query exactly.
Phrase match requires that the keyword be in the query in that order, but can include anything else around it.
Broad match allows queries to match with your keyword… broadly.
There’s a lot of room for interpretation there with broad match, right? Google defines their broad match rules as…
“Broad match lets a keyword trigger your ad to show whenever someone searches for that phrase, similar phrases, singular or plural forms, misspellings, synonyms, stemmings (such as floor and flooring), related searches, and other relevant variations.”
Bing uses the exact same nomenclature for their match types. Exact, phrase, and broad can be found on Microsoft’s network as well, and they define theirbroad match rules like so…
“Any word in your keyword, in any order, including words closely related to your keyword, must be in the search query or other input. Example: if your keyword is red flower, searches for red flower, flower is red, and buy crimson flower will trigger your ad.”
That all sounds well and good, but keep in mind that these broad match algorithms are proprietary. It’s not like Google and Bing are going to be sharing their work between one another for the good of all. They behave differently, and understanding that difference is key to saving your business money.
There are two common complaints levied against Bing broad match:
It wastes money
It drives irrelevant traffic
But is that true? And if it is, what are some strategies you can employ to keep it under control? To find out, we’re putting Bing broad match on trial to examine just how different they are.
For that first question, I’ve compiled some data from two different accounts over the last 30 days to examine the difference in both brand and non-brand keywords. These accounts are the same structurally across both Google and Bing, with the only differences coming down to routine management needs- basically, negative keyword additions and bid adjustments.
Here’s how they stack up on the non-branded term:
This is actually a pretty favorable comparison for Bing: this broad match term has a lower average CPC, yet a better average position and a higher conversion rate. It’s driving more traffic and providing more customers. While we have 3,827 unique search terms in Bing compared to Google’s 119, this analysis is confounded by one variable:
Google’s “Other Search Terms” data.
Simply put, any analysis of how broad Google’s broad match actually is will be stymied by the sheer number of queries hidden behind that “Other Search Terms” barrier. The actual Google statistics for that generic term are:
So there are 11,382 impressions that we can’t account for in the Search term data- about 87% of the total impression volume for this keyword. Based on some rough napkin math, the actual number of unique queries for Google is likely over 5,500- but we’ll never know. Click volume favors Bing here because we can bid higher due to less competition- so there’s a logical explanation for why we’re seeing these metrics as they are.
If anything, Bing may be guilty of too much transparency here, at least when compared to Google.
But what about the actual query content? If we’ve got 3,827 unique searches, how many of them are truly relevant to our original keyword?
To analyze that, let’s break down the percent of queries containing no relevant stems of our original keyword. So, for instance, if I’m looking at a keyword like “automated calling”, I’ll be looking for queries that don’t contain the term “auto” and/or “call”. Here’s how the generic term stacked up:
In this case, 88% of the queries contained *some* basic idea of the keyword. So of those queries, about 500 contained no relevant stem terms- a 13% rate. These findings are better than I’d expect from a broad match keyword in general, in either Google or Bing.
Here’s what we’ve established for this generic keyword:
It drives more traffic than Google due to the lower average CPC, lower bid, and higher CTR
87% of the search queries contain relevant stem terms of the original keyword
All in all, the traffic is relevant, and the money isn’t wasted. But what happens when we perform the same analysis on a branded keyword? Well… everything kind of falls apart:
For the sake of an honest argument, here’s the Google data including “Other Search Terms”.
So our branded broad match keyword in Bing gets six times the impression volume, seven times the click volume, at double the average CPC at a worseaverage position than Google… all while accruing 4,987 unique queries.
What happened here? The answer lies in the query stem analysis:
Ninety-two percent of our queries on the brand broad match term in Bing contain no relevant stems- meaning that vast majority of traffic from this “brand” term come from people who didn’t search for your brand. While the traffic is, in general, related to the product and industry, it’s not as targeted as a brand query.
This keyword was a victim of its own success. A brand term will have a higher bid due to successful performance and a higher quality score due to relevance. The problem is that Bing broad match will then allow that high bid and quality score to supersede your other keywords- meaning that your brand term will start drawing in a ton of non-branded traffic, even if you already have those keywords in the account elsewhere- which we definitely do in the above example.
According to Google, and outlined in this post by Amanda West-Bookwalter, their broad match follows some pretty defined matching rules. Rules like “if you have the actual keyword in your account, we’ll prefer to match with that”. Based off of these results, I’m not 100% convinced that Bing has the same restriction in place.
My assumption is that we’d see the same issue pop up with our generic keyword if the Max. CPC was high enough; it’s just less likely. A generic keyword won’t normally have the kind of performance to justify that high a bid.
Here’s what we’ve established for this brand keyword:
It drives more traffic than Google due to the overly broad queries
92% of the search queries contain no relevant stem terms of the original keyword
In this particular case, it is guilty of wasted spend and irrelevant traffic.
So what can you do to guard against this problem?
Use more negative keywords, especially in your brand campaigns. In fact, you may want to consider adding all your other keywords in as campaign-level negatives to keep that brand traffic pure.
Use modified broad match. This eliminates the issue entirely, and is probably a bit easier than the alternative.
Of the two, the second option is your best bet. A question that was recently posed to me was “why even use Broad match for your brand campaigns at all?” It’s a valid point- and one best answered by saying “well, you can usually get away with it in Google.” Bing broad match is a different animal, and it may be worth your while to treat it as such.
You don’t necessarily need to follow the above rules for every campaign- the generic keyword with a reasonable bid seemed to behave itself. However, you absolutely need to watch your brand broad match keywords. At some point, your bid and quality score will be high enough that they start to poach your non-branded traffic, and that can lead to all kinds of performance problems in your brand (and top-performing) campaigns.
What about you, PPC Heroes and Heroines? Have you noticed similar discrepancies in your own search term reports? What’s the weirdest query your Bing broad match terms have matched with? Let us know in the comments and, as always, thanks for reading!