Google Ads: Hotel Case Study. Right Data, Wrong Decisions?

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An object may look different depending on where you observe it from.

Data, instead, doesn’t change its meaning, which is always absolute. What changes though is our judgement: depending on how we make use of it, the outcome (thus our decisions) may be totally different.

That’s the case of this hotel case study, in the context of Google Ads: thinking that the performances are good (high level), whilst the truth (granular level) says something different.

Let’s dig in.

This a Google Ad account of hotel. It’s a very simple structure.


As you can see we only have three campaigns. I’ve selected a very short period of time (12-14 November) so that we can laser focus on a specific case without getting distracted by too big numbers.

I’m not going to question the naming convention of this structure, but you can easily guess what each campaign is for: we have a brand protection campaign (Branded), a campaign that targets people searching for the hotel name to protect potential website traffic from being diverted to, for example, the OTAs.

And then we have a Location campaign which of course targets people searching for specific areas, locations or points of interest that are relevant to the hotel.

Then we have a remarketing campaign which is of course a campaign that targets users who have already interacted with the hotel, like visiting the website or interacted with the social media pages, and so on and so forth.

Very, very simple.

The one campaign we are going to be focusing on today is the Location campaign because it’s the one that targets new traffic, so it’s the most interesting from a hotel marketing perspective.

By looking at Conversion column we can see this campaign has got one conversion, meaning one hotel direct booking, worth $1800.


So, we spent $248 for getting a booking that was worth $1800. Pretty good, right? The ROAS (return on advertising spend) is of course positive: we spend that little money for getting that much, even if it was just one booking.

At this point you might think: “Good, we got a booking coming from new traffic”.

Next you might want to know how exactly that user came to the hotel and how exactly was the booking funnel, more specifically what was the first touch point on Google that led the lead first, who then turned into a booker.

In other words, what exactly did this use search on Google in the first place?

We can do so, of course, by looking into first the ad groups.

Now, bear with me, but I have to hide the name of the ad groups for obvious privacy reasons.


Even though you can read the names, these 3 three ad groups represent 3 different areas (or points of interest) of the city the hotel is located in.

As you can see we got a booking from the first ad group.

Now let’s see what is the keyword that triggered that booking, going deeper on a Search Keyword level.

The first listed keyword is the one that brought the conversion.


Even though I can’t show you the list of KWs, just know this one being the most generic location-based keyword with format hotel + [city], like hotel london, or hotel paris, hotel new york.

If you just stop here with your analysis, you may think: “Ok, we got a new booking coming from new traffic, and that user had started his or her search on Google with the term “New York City hotel” or “London hotel” or “Paris hotel“, or “Las Vegas hotel“.

Besides, the point here is that, as you can see in the second column, all these keywords are in broad-match type, which the broadest and most inclusive match type we can work on in Google Ads.


Put another way, broad-match type keywords trigger broad search terms.

As a matter of fact, if we narrow down to the Search Terms level, we can see the exact terms triggering this keyword and, more specifically, the exact term that later on resulted in a hotel booking.


You can’t see it, so I’m going to tell you: the first term of the list, which is the one that converted the booking, is… the hotel brand name.

Hotel brand name should have triggered the brand-protection campaign, not a location campaign.

The problem lies in the broad-match type selected for those location-based keywords, because it is like telling Google to trigger our ad whenever people search any hotel-related term. And the name of the hotel is, indeed, a hotel-related term.

This is particularly a problem with the hotel industry, first because Google as a high preference for broad-match keywords, to the point that, generally speaking, it will increase your Optimization Score within Google Ads.

The reason behind this is simple: Google wants more data to feed its machine learning. Google essentially tells you “Give me broader terms and then I will optimise for you”.

The point that Google doesn’t take into account is that the hotel industry is much more complicated and different from any other.

Let’s take another industry, for example, “Concrete Coatings”.

So “hotels” on one side and “concrete coatings” on the other side.

If you were in the concrete-coatings industry, how many other concrete-coating player would you have to deal with in your city or town?

Even if you don’t know, you can make a quick search on Google: you might be leaving in a very big city, but I bet you won’t find more than a handful players.

The hotel industry? Even if you live in a small city, you’re dealing with hundreds other hotels.

The numbers are totally different.

So what does that mean?

For broad-match keywords that include, for example, the term “hotel”, like hotel + [city], Google will trigger every single hotel brand name.

Even though you can’t see the list of terms from the last picture above, I can guarantee you that 80-90% of these terms are hotel competitor names.

A brand term triggered the location campaign, as opposed to the brand-protection campaign, so we got a booking from a campaign that was not supposed to be bringing traffic from this target.

An option would be to negative out all hotel brand terms from this location campaign, but… good luck listing thousands of hotels. Definitely not a good option.

Furthermore, since all these terms are not relevant to this location campaign, people may not convert. Not converting, performance of the campaign will likely get worse, as a result of a lower quality score, which lowers the ad rank, which increases CPCs (cost per clicks), which make profits slimmer and slimmer.

I’m not saying broad-match keywords don’t work, but it’s extremely complicated and it’s extremely difficult to go on profit, especially in the hotel industry.

The more specific, the better. Profits always rule the game.

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Digital Strategy & E-commerce Expert for Independent Hotels.


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