What is booking engine conversion rate? Simply put, booking engine conversion rate is a measure of traffic landing on your booking engine which then converts to a booking. It is a metric that is crucial in maximising your website revenue and the key to increasing your direct bookings.
It is the % of booking engine shoppers that ultimately make a booking.
Bookings / Booking Engine Shoppers
301 hotel bookings / 4,701 shoppers * 100 = 6.4% conversion rate
This also means that 4,400 shoppers that visited the hotel website did not make a booking. So what were those shoppers looking for that they did not find? Was it a different room type? A cheaper daily rate? A more user-friendly path to purchase?
Avvio customers will often ask what their booking engine conversion rate should be. Unfortunately, there is not a one-size-fits-all answer to this question as booking engine conversion rate varies based on a hotel’s your location, grading and type of property. It therefore makes sense to measure your booking engine conversion rate within your comp set or on a year-on-year basis.
There are many reasons for booking abandonment but there are also some great strategies that hotels can implement to deter browser drop-off. To aid these techniques, Avvio’s software team recently launched our first built-in anti-abandonment tool. This new feature is in high-demand and has been designed to deter and reduce abandonment in the guest journey.
The anti-abandonment message is triggered for a new user when we identify abandonment intent – either by tracking guest behaviour which suggests they will leave the website (i.e. hovering over the exit button on their browser) or when they have been idle for a certain period of time. Once triggered, our anti abandonment tool will display a message to encourage the booking engine shopper to stay on the site and convert.
Here are some examples of Hotel’s currently using this tool:
Our anti-abandonment tool also recognises whether the user has already made a booking and will therefore not display the tool if it recognises a pre-stay guest.
If you are interested in learning more about this feature or have any questions about reducing booking abandonment please contact a member of the team.
