Hotels, Looking Forward: Big Data in Hospitality

The New Otani Kaimana Beach Hotel

What if hotels could predict future business levels, customer behavior and demand? With technology, they can.

Last month, we addressed technologies that are improving the actual guest stay. This month, we take a step back and discuss how analytics technologies allow hotels to deliver content to prospective guests that provides the information travelers need to know in advance of choosing a hotel.

Big data is a term that dominates technology news, but its real-world applications often seem ambiguous. However, it is changing the game of hotel marketing in a meaningful way, for both the hotel and the guest.

Marketing teams now serve as specialists in content generation, data segmentation, digital advertising platforms and brand advocacy, integrating a wealth of information to create trackable campaigns that contribute to the top line. But how do hotels make sure prospective guests see the information most relevant to their needs?

Hospitality marketers use predictive analytics to examine customer behavior viewing patterns, and browse search paths, content interests, shopping habits and social activity. Analytics also identify how a guest interacts with web content, what type of device or browser is used, engagement with social content, clickthroughs in email marketing and more. This knowledge drives marketing strategy and helps identify measurement goals, leading to integrated campaigns that drive consistent guest experiences with relevant and valuable content.

This deep insight allows hotels to now reach the guest through multiple touchpoints, customizing the delivery channel based on customer preference. Broad-based marketing programs are being replaced, as consumers opt in for information specific to their needs.

Predictive analytics condenses this data into manageable specifics, giving marketers an accurate roadmap on how to deliver a holistic customer journey that is relevant and targeted to guest preferences. Showcasing to guests that the hotel is aware of their wants and needs and delivering on those – all before the reservation is booked – builds trust and brand advocacy, which increases the likelihood of booking.

Using metrics to understand the success of campaigns in real-time drives revenue. The ability to see how the guest interacts with content gives marketers the chance to deploy different content if they’re finding minimal interest.

There are several ways hotels are using big data to attract guests and secure bookings:

  • Creating content that encompasses a broad list of information, distilled into three buckets – owned, earned and paid media. Owned media is brand-created content such as photos and images, social content, blog posts, websites, newsletters and anything else the brand controls entirely. Earned media is generally considered media coverage because of media relations by the PR team. Wikipedia calls it publicity gained through promotional efforts other than paid media advertising, like articles written for media websites or sites other than the hotel’s, media interviews, social media content by a third party, and general word of mouth. Paid media, or advertising, includes PPC advertising, branded content and display ads.
  • Tracking the buying path of loyal customers to successfully reach “guest-like” consumers, meaning those who behave similarly to loyal guests but haven’t booked. Comparing the data allows hoteliers to market at different stages of the funnel. For instance, a marketer can gather information about their target audience using analytics such as how often the customer is looking at owned media, how long they’re spending on the site, which social posts they’ve engaged with, and other relevant sites they’ve visited. Using this information, marketers can then use programmatic marketing (media buying, marketing and advertising), defined as the algorithmic purchase and sale of advertising space in real-time. During this process, software automates the buying, placement and optimization of media inventory via a bidding system. The software uses information about the consumer and the property to predict an appropriate room rates and determine the length of promotions.
  • Testing and revising offers in real-time is crucial to campaign success. Prior to big data and predictive analytics, hotels would cast a wide net to reach potential customers. This approach didn’t consider personal preferences of guests, nor did it tailor offers based on those choices. Using data, hotels can increase bookings and target upsell opportunities, raising revenue in bookings and incrementally. The approach is a win-win because hotels can anticipate the needs of guests which builds brand loyalty by delivering personalized service, and results in an optimal customer experience.

The goal of predictive analytics is to look forward. Traditionally, hotels have looked backward at bookings, room rates and revenues to predict the future. New data sources provide a fuller picture and more accurate forecast conversion and price optimization. The aim is to manage future demand, target specific markets at specific times of the booking cycle, and target the right customer at the right time using the right tactics. In the past, hotels set their own benchmarks, defining a competitive set most favorable to the specific hotel; this “gamed the system,” as general managers benchmarked against hotels that gave them the best advantage in the share game. The reality today is that customers decide who is considered the competition. The right data set will give hoteliers the insight to know what the customer is thinking as well, and serve them information to make an informed decision. This is not the future, it’s now.

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