Data is changing the foundations 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 audiences compiled from data have 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 few steps you need to take to segment your audience and enable true one-to-one marketing.
Centralize your Data to Build a Robust Guest Profile
Hoteliers have a wealth of data in their systems 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:
- Guest history
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 them are simple and easy to implement. Most people think that clustering techniques require an advance knowledge of statistics or database but this not case. A tool like Cendyn’s Audience Builder, make 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:
- Who stays with you the most often?
- When do they stay?
- Have they visited lately?
- How much do they spend?
- How much have they spent over time?
- Who are your high-yield guests?
- Who are your lapsed guests
In addition to the RFM technique, you will want to personalize communications based on distribution channel:
- Direct bookers:
- Call Center
- OTA bookers
- Travel agency reservations
We also highly recommend segmenting your guests based on where they stand in the guest cycle:
- Pre-Stay Guests with a Reservation
- On Property Guests
Step 2: Keep Exploring Your Audience Segments
Once you have the basic segmentations in place, there is really no limit to what you can do to further slice and dice your data and create personalized communication. 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 audience attributes. Performing exploratory segmentations is easier when you keep in mind what type of organizational needs your marketing needs to support:
- need period campaigns,
- room upgrades,
- remarketing to third-party distribution channel guests,
- prospecting for new guests.
- personalized check-ins,
- reservation confirmation and cancellations,
- guest service issues.
- rate categories with different terms and conditions,
- a change in hotel occupancy or REVPAR.
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:
- romantic getaway,
- family vacation,
- active lifestyle/sports/adventurous excursions
Step 3: Mine your Big Data, Segment with Clustering Techniques
By and large, we find that a simple and a 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 very demographically diverse and covering a greater range of lifestyles. Those techniques rely on algorithms, and each one of them has its own strength and weakness. They are particularly sensitive to statistical assumptions, for example, some of them will require for your data sample to be normally distributed to be meaningful.
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. 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.