Analyzing your Online Booking Engine

Mary C. | 21 May 2005 |

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Analyzing your Online Booking Engine
Q & A: Booking Engine Usability and Abandonment Rates
Christine Burke, Blizzard Internet Marketing, Inc.

Q: I think people are having too much trouble using my online booking engine. I think they check availability a couple of times, then give up. How can I analyze this problem and what should I do about it?
A: There is a lot of variety among the various booking engines, but we can discuss some basic principles here. For the purpose of this article, we will assume that you are using Blizzard Tracker ROI Edition on both your hotel pages and your booking pages. (Many, but not all, booking engines support Blizzard Tracker.)
You can probably get reports from your booking engine that analyze visitor behavior within the booking engine. The benefit of also using Blizzard Tracker is that you can analyze visitor paths that move back and forth between your booking pages and your hotel’s own site. This gives you a more complete picture of what is happening.
You might find, for example, that some visitors begin the booking process, only to decide that they haven’t learned enough about your hotel. They may go back to your hotel site to visit the Rooms pages or Specials pages, and to learn more about the amenities you offer. This is not a bad thing, provided that they eventually re-enter the booking pages and make a reservation.
Other visitors may have a genuine problem if your availability is limited in some way. For example, you may have configured the booking engine for a minimum stay of three nights or more. If the visitor gets the result “Sorry, Room Type Not Available” after repeated attempts to book, you might lose this person as a guest.
If you aren’t filling rooms, it might help to re-examine the parameters that you have set on the booking engine.
Here are some sample reports. Example 1 is from a high-end resort that requires a minimum stay of several nights (it’s an expensive vacation.) As you can see from the illustration, the highest abandonment rate, 91%, was between the second and third step, when 203 visitors chose not to move forward in the process.

Example 1

Drilling down in the tracker to learn where those 203 visitors went, we find that 85 (42%) ended their visit. Perhaps those visitors found the rates too expensive, or maybe they decided to use the phone instead. If the hotel has a dedicated telephone number for website visitors, it can learn how many people decided to call rather than book online.
The rest of the path analysis is too detailed to show here, but suffice it to say that the rest of the visitors went either to the previous booking step, or back to the hotel pages. If this resort wants to improve its online conversion rates, management might work on getting more satisfactory results (such as more variety or more specials) to display on the “Select Room Rate and Type” page. We should keep in mind, however, that an expensive vacation requires a thoughtful decision-making process. It may be natural for a visitor to check availability several times, and ultimately to decide to pick up the phone.
The good news is that there was no abandonment going to the last step, which involved reviewing the reservation and entering a credit card number. If we had seen significant problems there, it could have been due to system errors in the credit card validation process. We wouldn’t want to lose customers over a glitch like that!

Example 2 is from a different kind of lodging company. The web site markets a chain of small-town hotels. As in the previous scenario, the highest abandonment rate, 78%, is between the room selection page and the guest information page—the transition from shopping to buying. However, only 30% of those abandoning at that step ended their visit. The rest went back to previous booking pages and the hotel pages.

Example 2

What does all of this mean? It’s safe to say that all of this information is relative. You can probably learn from your booking engine’s support team what is the average abandonment rate for each step. Compare your results to 1) averages in markets similar to yours, and 2) your own hotel’s trends over time.

Interested in learning more about how Blizzard Tracker can improve your online marketing? Please visit the Blizzard Tracker web site.