Typically, when we want to gauge the demand for our destination, locality, and even our property, we turn to Google as the primary source of information.
Sure, Google offers a wealth of data through Google Trends, Google Insights, Google Hotel Insights, and Google Travel Insights.
However, in my opinion, this information can be too broad and not entirely functional.
That’s why I pay much more attention to Booking.com.
Indeed, Booking.com provides us with a clear indicator of how strong the demand is, how it’s evolving for our destination, and how we’re performing relative to that demand over time.
Ultimately, the goal is to obtain a line chart or timeline that reveals actionable insights. But let’s start with how to pull out the stats we need from Booking.com.
Within Booking.com’s excellent analytics section, you’ll find a report called the Ranking Dashboard for your hotel’s name.
It features three essential numbers that can give us an idea of how demand has evolved collectively – not necessarily broken down by days, weeks or months – but enough to understand. These are the metrics we want to focus on.
I know Booking.com isn’t the only OTA out there and doesn’t provide a complete picture of total demand for our destination.
However, it does offer a very clear indication. Even if you check your booking engine, it will only represent a small portion of the actual demand you can address in terms of numbers on Booking.com.
So, these are the three KPIs we need to examine:
- Search Result Views (the number of times your property is visible in search results)
- Property Views (how many times users view your property page on Booking)
- Bookings (the number of confirmed bookings).
The Search Result Views refers to people searching for specific days at your particular destination, location, or establishment, and the number of times your property appears in the search results.
In other words, it’s the listing frequency.
Property Views represents the number of times users actually land on your Booking.com’s hotel page.
By default, you can’t expand this data beyond a 90-day timeframe.
However, if you scroll down the page, you’ll find an option to display data over different periods.
While there aren’t many choices besides 90 days or 30 days – which isn’t particularly functional or helpful – selecting the past 365 days will aggregate data by month, which is precisely what we need.
By adjusting these figures, you can monitor search result numbers for each month and observe demand progression.
Now, how can you use this information? This data alone could be enough to understand demand patterns. However, I’d also like to create a final report to glean additional insights.
To delve deeper into these numbers, I manually gather this data since there’s no way to do so automatically. Booking.com doesn’t share this information through any API or tool. So either you collect it manually or not at all – it’s that simple.
For example, let’s examine the timeline table. How is this table populated and where does it come from?
It’s derived from here.
Although it’s a bit more complex than this file or table, it offers valuable insights into demand trends and helps optimize your property’s performance on Booking.com.
There is a lot more data included than necessary because it’s a template I’ve been using for multiple purposes and chats.
For this video, let’s just focus on the following relevant metrics:
- Search Result Views
- Property Views
- Property Views% (in percentage, the number of times the property was viewed relative to the times it was displayed)
- Bookings
- Conversion value (value of the hotel reservation)
- Conversion Rate
Property Views% and Conversion Rate are automatically calculated, so no need to plot in the numbers manually.
Now let’s jump into the analysis.
Let’s take January 2024 as an example, which is the latest complete month.
- Search Result Views = 1,867,821.
- Property views = 46,078.
Once these numbers are plotted, I can feed my trend line or timeline accordingly.
It’s quite simple to see how we use this report and what actionable insights we can gather from it—particularly for upcoming marketing/revenue/distribution strategies.
The blue line represents search result views on Booking.com, which essentially show how demand is evolving over time.
I want to clarify that these data points represent demand that occurred in these months for any future dates.
These search results could be for January but not necessarily for stays in January; this is demand that might be looking for travelling in February, April, March, June, or any other future month.
Having had that clarified, let’s focus on the travel demand, as that’s where the conversions happen.
To give you a little bit of background, this hotel is a typical leisure hotel in the European region.
June and August are very high seasons, with June and September being high seasons as well, but not as high.
Instead November, December, and January are very low seasons.
Also, we know that historically travel demand in January and February is quite good despite being a low season in terms of hotel occupancy.
Let’s analyze July: very high demand with excellent reservation value.
However, property views aren’t proportionally as high.
Indeed it has the lowest Property View rate across the whole year (1.59%).
This means the hotel appeared often but didn’t receive as many clicks as other months.
From a listing perspective, there were probably other properties that were more appealing during that time.
However, if you check the conversion value (2.56%), it is actually the highest among the months.
In summary, from a listing standpoint, the hotel may not have seemed very appealing—there could have been other properties or competitors that were more attractive at that time.
But when it comes to conversions, the hotel performed exceptionally well during this period.
So, what’s the point? What’s the takeaway from this?
I know from other reports that a large portion of these requests, 85, perhaps even close to 90% of the demand this hotel received in July, was for super high-season months, like July and August.
And during the peak season, I want to receive more direct bookings compared to intermediary reservations (OTAs).
This is because, in high season, I can work on margins.
So such high conversion rate in July is quite not a good figure. it means that the hotel has had many conversions through Booking.com and, probably and contrary to that, less conversion through the direct channels like booking engine and CRO.
That is to say, the hotel received numerous bookings, but most likely, the majority of those reservations came from Booking.com or any other OTA and less direct bookings.
If we take January as an example, it’s an entirely different scenario because here, in terms of occupancy, we are in a very low season.
However, this is where the demand for the very high season – July, August, September – typically begins to grow. In fact, over 50% of the requests received in January are for stays in those summer months.
So, to summarise, these figures are saying that, in January, the hotel:
- performed quite well in terms of listing (good number of clicks to the property page on Booking.com from search results);
- performed well in terms of conversion, but that’s not necessarily a good thing, because travel demand is mainly for high season dates, so it would have been better to get those bookings converted directly.
- February and March will see further increases in the number of searches for high season dates.
For these reasons, now it’s time for this hotel to focus on margins, aka direct bookings, rather than increased visibility from the OTAs.
It was different, for instance, in November.
It was undoubtedly a rather poor month concerning conversion rates overall, as demand in November for any future dates was quite low. The minimal demand was for future months during off-peak seasons.
The hotel’s performance in terms of conversion rates was less than stellar, whilst the Property Views% remained average.
Since demand was mainly for stays in off-peak months (November and December), it would have been better having a higher conversion rate, which would have lead to more visibility for dates the hotel was in desperate need of some volumes.
In fact, gaining all possible visibility from the OTAs in off-peak dates is crucial, thus margins (direct bookings) become a secondary goal.
This insight can be applied to next year’s strategy. While each year differs, I can observe trends and focus more on direct bookings during certain months as opposed to others.
Again, this report (and analysis) serves as a starting point and doesn’t provide all the answers that need to be contextualized with other reports based on the data people are searching for, which can only be done through your direct channels and booking engine.
So far be it from being perfect, but this approach provides with numerous insights in terms of where we should be focusing on next: volumes or margins? OTAs or direct bookings?
Give it a try. Let me know if you need this template. It’s not exactly user-friendly and wasn’t initially designed to be shared, but if you find it intriguing and want it for yourself, feel free to reach out to me with a comment or message.
