Hoteliers today face a number of problems - coming from within their own sector and from on the peripherary.
As well as the perennial issue of competing with rival hotels, the growth of private accommodation bookings through platforms such as Airbnb is also concerning.
Now more than ever, hotels need a healthier distribution of selling their rooms, initiatives that boost their sales and increase the chances of repeat business.
NB: This is an analysis by Kristian Valk, co-founder of Hotelchamp.
This article explains why personalisation is the key solution for hotels. If hotels can offer guests an experience that feels tailor-made for them, there are numerous benefits to be had.
A greater number of positive reviews on TripAdvisor and the like, a higher likelihood that the guest will return, and better upsell opportunities can all result from providing customised services.
The challenge with personalisation, though, is that there are so many different types of hotel guests.
It’s more complicated than simply thinking in terms of business or leisure - there are so many other factors that dictate the parameters of a guest’s stay and how much margin can be made by the hotel.
At the very least, hotels need to be thinking about identifying segments and sub-segments of guests, and then using different approaches to each in order to maximise the potential for profit.
So the question is - how can a hotel best identify and target the high value customers?
The answer lies in big data.
Beyond the hype
While this is a buzzword that has been heard across many business sectors in recent years, the hotel industry seems to be behind other industries in terms of actually harnessing and using this data to its full potential.
Think of all of the data generated from the process of booking, for example.
With most bookings made online, there is a lot of data that can be digitally captured - whether the booking is made directly through the hotel’s website or through an OTA.
- Where in the world does the guest come from?
- Are the dates of the stay significant - such as Christmas or the beginning of the school holidays, for example?
- How big is the party and what is their relationship to one another?
Once the guest arrives at the hotel then there are a number of other data points that can be extracted.
- How did the guest arrive?
- What facilities are they interested in using?
- Are they using the in-house dining facilities, or going elsewhere?
Ensuring that they have a system in place that is capable of capturing this data is one thing, but hotels also need to be able to look for the patterns and react accordingly.
For instance, guests booking for a family stay during school holidays should be offered discounts on local entertainment providers and attractions, childcare and the like as a matter of course.
If the Presidential Suite is booked, then human intervention is required - a customer service rep should immediately be looking to directly contact the guest and build a bespoke experience for them.
The best way of making the entire process - from the booking to post-stay follow-up - as personal as possible is through direct engagement with the guest.
While the high proportion of stays booked through OTAs makes this difficult, there are ways around this.
Often guests check the actual website of the hotel - usually to verify that it exists or to look at pictures - before returning to the OTA to make the booking.
If hotels can take this opportunity to draw the guest in and convince them to book directly, then this personal relationship begins - and the quality of the data improves.
At the coalface
By using the data points gathered when a guest is on their own website - which pages they look at for example - hotels can establish an even more personal bond with the customer.
Offers of discounts on the kinds of components they might want as part of their stay, rather than generic one-size-fits-all discounts, show that the hotel really values the guest.
By stressing the urgency of making the booking quickly - borrowing a tactic from the OTAs - the hotel can also boost its chance of bagging the customer.
But while some insights can be drawn out from data immediately, others might not be so obvious.
When it comes to pricing strategies, it’s often the best idea to try a variety of discount levels - say 5%, 10% and 15% - to see which best increase the chances of a booking and boost potential upsells.
For example, a generous enough discount might mean that a customer decides they would like to switch from a room-only deal to half-board.
This kind of A/B testing is easy to carry out if hotels have the right system in place to gather and analyse the data.
Hotels also need to consider how they deal with historical data that they have stored but never mined, where they will find insights about past guests that will help them to develop their customer segments and sub-segments.
Careful consideration needs to be given to the technology solutions they put in place to help them deal with data past and present.
With competition in the industry only set to increase, it will be the hotels that do the best job of harnessing and interpreting their big data that win out.
With much of the industry still only part of the way through this journey, there is a big opportunity for forward-thinking hotels to get ahead in the race.
NB: This is an analysis by Kristian Valk, co-founder of Hotelchamp.