AI and Machine Learning in Hospitality: Part II

AI and Machine Learning Part 2

As covered in Part I of this series, Artificial Intelligence (AI) and Machine Learning (ML) are becoming more and more prevalent across all industries. In Part II, we’ll dive deeper into hospitality specific use cases for these technologies, helping you as a hotelier understand guest needs and preferences like never before.

 

From smarter marketing to hyper-segmentation

smarter marketing: hyper-segmentation

Sending the same marketing message to an entire database means you’re going to get a small bite from your recipients. Many hoteliers are realizing their guests aren’t all the same, and treating them the same leads to suboptimal outcomes. Instead, slice them into different segments such as VIP vs. non-VIP, families vs. non-families, and local guests vs. non-locals to send personalized email campaigns. The bites individually may be small because the send group is smaller, but when you add them up, you’re generating a higher percentage of bites. Put simply, you’re making more money.

This is where ML can have a big impact. At scale and with proper data, it allows you to slice your database into smaller and smaller segments, increasing your revenue exponentially. There’s no way a human can do this. You can’t segment your database and send emails to three people nor can you set up hundreds of campaigns manually. But ML makes this all possible.

 

Guest data at scale

Guest data is your biggest asset in creating a strategy to maximize guest lifetime value. Take this simple example. A guest Jessica Yu has stayed at your Hotel A. You also have a Jess Yu who has stayed at Hotel B. If that person is the same, you want to know. There is a significant difference between two first-time guests and one more loyal guest.

guest profiles

You will accumulate more data about her throughout the guest journey. When you start layering this data, it becomes even more important. A more robust profile might include:

guest profile

  • Contact info: Useful for marketing initiatives and such
  • Social handles: Useful to understand if she is an influencer and maybe warrants a deal
  • Interests: Useful in deciding which promotions to send
  • Info from past surveys: Useful in learning if she is a promoter but also what services she enjoyed

You have hundreds of guests to remember. Even the best concierge can’t remember every single one, so they have to resort to an impersonal “Welcome back.” But guests want to feel special.

Machines, on the other hand, can remember every stay, every cost, and every on-property activity. They remember every web page the guest viewed and which filters they applied in order to find what they eventually booked. They remember every campaign the guest has seen but hasn’t acted on. All this data and more can be used to recommend the right offer to the right guest, at the right time.

 

If the benefits of AI and ML seem too good to be true, you’re right. As with all good things, there is a side to these technologies we do have to be aware of, which we’ll cover in the final part of our AI and ML series. Stay tuned!

2 responses to “AI and Machine Learning in Hospitality: Part II

  1. This post is very helpful for me. Thank you for sharing information. Wonderful blog & good post.Its really helpful for me, waiting for a more new post. Keep Blogging!!

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