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Google Analytics for Hotels Tip Digital-Marketing Data to Serve Your Revenue Strategy

Google Analytics for Hotels | Tip #4: Digital-Marketing Data to Serve Your Revenue Strategy.

How many Revenue Managers make use of Google Analytics as a tool to support their strategy and tactics?

Point being, often times Google Analytics gets automatically associated to everything that comes to marketing– and/or eCommerce-related stuff.

However, as said before and with few extra steps, GA can also serve our Revenue Management decisions.


Think of Digital-Marketing and Revenue Management as the 2 sides of the same coin.

And Google Analytics serving both sides.

So, today, I’m going to talk about 2 new revenue-related metrics that you can easily setup, literally, in a matter of seconds.

Average Daily Rate (ADR)

If you are familiar with the E-Commerce set of reports that Google shows in its console, you might have seen a metric called Avg. Order Value.

Avg. Order Value

You have to understand that Google Analytics has mainly been conceived for general E-Commerce platforms.

In other words, sites that sell goods, mainly tangible goods (physical products), like Amazon, for example.

For those, a metric like the Avg. Order Value makes totally sense, whilst it doesn’t say much to us, hoteliers.

In fact, we rather value the Average Daily Rate, however Google doesn’t tell us by default.

The good thing is that we can easily create it, in less than 30 seconds, directly in Google Analytics.

ADR is the result of Revenue, divided by the number of nights, usually tracked under Quantity.

This is exactly what the GA feature called Calculated Metrics is for.

Calculated Metrics

Admin > Calculated Metrics (under column View).

Create a new Calculated Metric, the setup should be as simple as this:

ADR Formula

If you are lazy and don’t want to manually type in the formula, here it is for you to copy/paste ?:

{{Revenue}} / {{Quantity}}

Same old story now. As said in the previous articles, just create your own Custom Report the way you want it to be, under Customizations > Custom Reports.

ADR Custom Reports

And how the report ultimately looks like:

ADR Custom Reports Frontend

Booking Window

Easy to do, difficult to explain.

This is how I would describe what comes next.

If you remember, before in this document I showed you how to track, for example, the Booking Window.

In there, I specifically referred to it as a Dimension, as it’s called in Google Analytics.

Now, we are going to track the same value as a Metric.

Why? What for?

Let me quickly explain what the difference between Dimension and Metrics is.

Dimensions and Metrics

In very few words:

  • Dimensions are attributes of your data;
  • Metrics are quantitative measurements.

Let me give you an example.

This is how a report would look like, being Booking Window a dimension:

Booking Window Dimension

Booking Window, first column, is an attribute, meaning a Dimension.

All other columns are the quantitative measurements (Metrics) that relate to each Booking Window value.

Now, why would we need to compute the Booking Window as a metric?

Because of its Average.

I have probably lost you, have I? ?

Keep following 30 more secs.

Booking Window Metric

Searches conducted with Length of Stay = 1, for example, are made 10 days prior the selected arrival date on average.

You get it?

Both your Marketing and Revenue Management departments can now benefit from this information.


For instance, today is the 12th of September. Let’s say that you are evaluating whether applying a Minimum Length of Stay of 2 nights on the 20th of September, meaning 8 days ahead (booking window).

Based on the figures above, probably this is not a good move, as people tend to search your rooms and rates for 2 nights way in advance, so the odds are not much in your favor.

There may be other factors that could affect your ultimate decision.

However, this also makes you see the overall approach from a different angle.


Apparently, last-minute visitors of your website are likely not interested in searching rooms and rates for more than 1 night.

If you are running paid campaigns on Google or Facebook, promoting a “Stay 2 Nights, Get X% Off” special offer to boost bookings on a low-demand period which is happening in 30 days from today, your performance will probably skyrocket.

Average Booking Window

Back to the ‘how-to’.

If you get 2 sessions, …

  • search with Booking Window = 3
  • search with Booking Window = 5

… and you simply track the Booking Window for each as a metric, then Google Analytics will report:

  • Sessions = 2
  • Booking Window = 8 (3+5)

Instead we want to have:

  • Average Booking Window = 4

That’s why we need to take 2 steps. First, let’s track the Booking Window for each session. To do so, let’s create our Custom Metric under Admin > Custom Definitions > Custom Metrics.

The settings should look like this:

Custom Metric GA

Same as what we went through in the previous article, now we just need our booking engine to send the respective Booking Window value for each session, so just ask your IBE provider to provide you with the right variable.

If you track IBE data through Google Tag Manager, like I do, and you have all variables listed in there, just set up your new BW Custom Metric in your general Google Analytics Tag. In the example below, I want to send the value of Booking Window, both as a Dimension and as a Metric:

Google Tag Manager

Now, let’s compute the average BW by heading to Admin > Calculated Metrics.

Simple math again, the final value is the result of Booking Window divided by the number of Sessions.


Average Booking Window - Calculated Metrics

Now you can create Custom Reports with your newly created Calculated Metric:

Final Custom Report



I know I lost most of you way on the way while reading this quite long post. But if you are reading these final lines, first, thanks much for paying attention 🙂

Secondly, I hope you will be implementing these and other great features you can turn on with, again, just a little extra step.

I promise, doing what it’s been said in this article will take way less than the time you spent reading this article 😀

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