Data is changing the foundation of hospitality marketing. With personalized content, hoteliers can now engage and nurture their guests like never before. As a result, they have a new way to increase satisfaction and cultivate loyalty to generate profitable revenue growth. In that respect, Marketing departments are realizing that using their own data to compile audiences has become one of their biggest assets. Audience segmentation is the key process that not only makes their data actionable but enables personalization. It allows marketers to change their approach from a pattern of interruption (e.g. TV or radio commercials) to a more efficient engagement strategy that focuses on quality instead of quantity. Below are the steps you need to take to segment your audience and enable true one-to-one marketing.
Hoteliers have a wealth of data in their systems, including Property Management System (PMS), Point of Sale (POS), Central Reservation System (CRS), Call Center, Food & Beverage, Spa, etc.) that they can integrate with online data (Email, Web Analytics, Guest Satisfaction Survey (GSS), and Social Media Platforms) to build the foundation of a robust guest profile. By augmenting their first party data with third party data, they can then access a complete view of their guests that covers an array of useful dimensions:
Implementing Audience Segmentation – Step 1: Know Your Audiences
Now that you've consolidated all of your data into a single view, it's time to cluster guests into relevant marketing segments that you can use to build, automate and personalize your campaigns. There is a wide range of clustering techniques that you can use to segment your audience, most of which are easy to implement. Many people think that clustering techniques require an advance knowledge of statistics or a database, but this is not the case. A simple tool like Cendyn/ONE's Audience Builder, makes guest segmentation relevant and accessible to hoteliers.
We recommend to start your basic segmentation process with the RFM technique, which looks at frequency, recency and monetary value as a way to differentiate your guests. This allows you to organize your profiles in a way that enables you to answer the following important questions:
In addition to the RFM technique, you will want to personalize communications based on specific distribution channels:
We also highly recommend segmenting your guests based on where they stand in the guest cycle:
Once you have the basic segmentations in place, there is no limit to what you can do to further slice and dice your data and create personalized communications. For example, you can always add dimensions to differentiate your audiences based on age, gender, income, the device they use to book their reservation, or interest (golf, spa, food, culture). The idea is to leverage your hotel CRM to move past the basic audience characteristics and discover more specific attributes. Performing exploratory segmentations is easier when you keep in mind what type of organizational needs your marketing needs to support:
The end game is gaining the ability to summarize your major marketing segments into personas that connect lifestyles and life stages to the various guest experiences you offer, both on and around the property. For example:
Step 3: Mine your Big Data, Segment with Clustering Techniques
By and large, we find that a simple, business focused approach to clustering is very effective in serving the specific functional and business needs of hotels or resorts. However, for larger hotels with a complex offering of products, it might be worth exploring more advanced clustering techniques - especially if their guests are demographically diverse and cover a greater range of lifestyles. Those techniques rely on algorithms, and each one of them has its own strengths and weaknesses. They are particularly sensitive to statistical assumptions, for example, some will require your data sample to be normally distributed in order to produce meaningful results.
When segmenting data, it is important to first perform a discriminant analysis to reduce the number of factors involved and determine which variables should be included in your cluster analysis. While there are a variety of clustering techniques available, the most commonly used is K means and decision trees. K means provides interesting insights into the persona behind your marketing segments by looking at the difference in means among groups.
Overall, and before anything else, the most important concern to keep in mind when personalizing content is manageability. The more audience segments you have, the more assets marketing must deliver to launch a new campaign. However, having numerous marketing segments should not hinder the ability to quickly deploy new campaigns.
Furthermore, exploring and mining your data on a frequent basis is a great source of inspiration for personalizing content and finding new opportunities for guest engagement. It is also a good way to stay in touch with how fast guest behavior can change, as we are currently seeing with the rapid adoption of mobile as a booking device.
So at the end of the day, how do you know if your segmentation works? If you are measuring campaign performance, you should be able to see an increase in ROI, email open rates and click-through rates, and 'likes' after implementing a relevant audience segmentation.
Property Technology CRM & Loyalty Email marketing Big Data
Christophe Tayon has over 15 years of experience in the travel & hospitality industry, working for and with OTAs, GDSs, devising data-driven marketing strategies to structure solutions to support and promote retail and channel sales. Christophe is a travel and digital technology advocate. He joined Cendyn as Director of Marketing in 2015.
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