Everybody heard about big data, and its impact in the new economy and many people know what it is, but do you really know how to use it?
It is simply what some big e-commerce platforms have been developing and perfecting form quite some time already. Netflix is the oldest example (probably not the first ever though) that comes to my mind Amazon follows right quickly and honestly I don't know which of them have been doing this longer. If you know, write me, please!
Learn from the Best!
Before Netflix became one most popular streaming service worldwide, it was a DVD Rental (and selling) company. Already then, even before the internet bubble-burst Netflix used the list of your previous rents, your "wish-list" and "hard data" of a movie to recommend you other movies. For example, it recommended you movies done by the same producers, or with the same stars, or the same directors. This is quite easy with a programmer and a database. What fascinated me then was the other way to recommend you movies: It used the lists I mentioned before to position you within certain "affinity groups". In other words it tried to define your movie taste. Then it searched it's database to find people with similar taste and recommended movies to you that were not in your list yet, that a majority of people with similar taste also watched and liked. You can read more detailed how Netflix's algorithm works here.
Mix it all, and create your recipe!
And It's easy to apply this for example to the hospitality business: You have a hotel that is near a concert hall. A band X has given three concerts in the last 5 years in their world tours. If you filter the guests staying at your hotel at these dates, you probably have a first (crude) fan base of band X. Find other artist on the same music genre and repeat the exercise. Repeat this exercise with other genres and you have a (crude) database of your music-fan-guests. Now take a look on the the concert hall's schedule for the next few weeks, sot the concerts by gerne and bingo: you can start offering you music-fan-guests tailor made products!
Even though I used music as an example, you can apply this for anything else such as city-wide (recurring) events such as Octoberfest in Munich or the Brazilian Carnival; yearly conventions such as the CES in Las Vegas or the IAA in Germany.
Start Small and cast your net wide
Start with one of the examples above. Concentrate on one aspect of your guests behaviour, and keep your filters (and mind) open. Start sending out offers for example to all music lovers and you will then see which guests react to which kind of offer, allowing you to further fine tune your database. You will also learn and react faster to mistakes, if you just have one project to concentrate on at the beginning.
Get bolder and use more data
When you got this first part well, then start adding more parameters and see what you can build with it: Some examples are: "Which channel does this group of guests mostly use to reserve a room?", "How much in advance to the check-in date the room is booked?", "which room category is the most used?" and so on. With this information, you can easily then optimise the distribution channels, promote Upsell and early-birds discount to increase your occupancy and drive revenue.
Beware of GDPR
What you are doing here is profiling your guests and with the new Data Protection Law for the EU this can only be commercially used with the consent of the guest. I already covered the basics of GDPR on another post.