If you've been using the Parity Monitoring product for some time, you probably have a good grasp on what your undercut rate tends to look like and how it has improved over time. But what does the score actually represent, and how should you interpret it?

When a user makes a search on the booking engine, this triggers some price comparisons with OTAs. We consider the results of each comparison together - if we find that any of the OTAs are cheaper than direct, we'll count this as an undercut. So if 1 OTA is undercutting direct, and 3 OTAs are more expensive, this would counts simply as 1x 'undercut'.

Similarly, if we find that direct is cheaper than 3 OTAs, but in parity with 1 OTA, we'll count this search being as 'in parity'. We only consider the hotel to be 'cheaper direct' in our metrics if we find that all OTAs have a higher price than direct.

As our undercut rate is directly tied to the number of guests searching on your website, this undercut rate represents the proportion of your guests who could have found a better price for your hotel elsewhere on the internet. Another way of thinking about this is that your undercut rate represents the proportion of your guests' booking decisions that were influenced by availability of lower prices on OTA sites.

This way of calculating undercut rate closely resembles the 'winner-takes-all' ethos of metasearch.

On meta, where all OTA prices are listed next to direct for easy comparison, it's very easy for guests to identify who has the best price. Any OTA undercut will therefore influence guests' booking behavior.

On meta, having a better price than 9/10 OTAs is no longer good enough, as that 1 OTA that is undercutting direct will draw guests' attention and will siphon away bookings from the direct channel. Our method for calculating the undercut rate reflects the harsh reality of parity, not just on meta, but across the whole internet as guests become savvier and more able to find the cheapest possible rate for your hotel.

Of course there's still room to break down your score and analyse further. Because we count any undercut as a loss, you might find that your undercut rate is heavily influenced by a single OTA. Using the OTA parity breakdown, you can easily identify which OTAs are causing your score to increase, which you can use to focus your efforts when it comes to improving your parity.

In the above example, you can see that the overwhelming majority of undercuts for this hotel are seen on Agoda. Therefore if your OTA undercut rates look like this, our recommendation would be for you to focus your efforts on bringing Agoda's pricing more in line with direct as that will have the biggest impact on your overall undercut rate.