Personalization is becoming a well-recognized and well-discussed term in the hospitality industry, and for good reason. As competition for the consumer’s attention in the noisy digital environment increases, hotels are looking for any edge that can set them apart and keep the consumer coming back.
InterContinental Hotels Group recently conducted a comprehensive study of its global consumer base and came to this conclusion attributed to Richard Solomons, CEO, IHG: “Hotel brands have traditionally concentrated on being 2-D – how to be both global and local. But our research shows that the rise of personalization means brands must be 3-D [personalized, local, global] in order to build both trust and lasting relationships with guests and to win in a highly competitive global market."
Arne Sorenson, CEO of Marriott International, has widely publicized his vision for the NextGen traveler, most recently in his LinkedIn influencer profile, and in an interview with HOTELS magazine, Chris Nassetta, CEO of Hilton Worldwide, acknowledged that Hilton’s customers are looking for more choice and control over their hotel experiences. Hotels need to provide value to the consumer, not just by offering a deal on their products and services, but by providing a compelling and engaging personalized experience during every interaction across the entire guest lifecycle.
Consumers are leaving digital trails all over the Internet – across social media platforms, review sites, travel sites and your own Web and mobile sites. The challenge for hospitality companies will be to use all of this rich data about their customers, augmented by offline guest profile data, in concert with operational insights and delivered through relevant marketing messages to execute this vision of a highly personalized guest experience. It’s also clear that simply applying business rules derived from aggregated Web analytics data will not be enough to capture the attention (and share of the wallet) of today’s consumer. The company that is able to leverage advanced predictive analytics in a digital environment, combine that data with offline guest data, and deliver intelligent, personalized recommendations (in real time), will win the battle for the consumer.
This article defines what personalization means and how it can work in a hospitality environment. It will discuss why traditional Web analytics cannot effectively support the execution of true analytically derived personalization. In the follow up blog post on hospitalityupgrade.com, we’ll describe the technology and data management requirements available today that can support detailed data collection, integration and analysis for personalization programs. The article series will conclude by providing the steps a hotel can take toward the path to personalization.
Personalization, a Vision
In a technology context we’ll use this definition by James Dorman on Quora: Personalization technology enables the dynamic insertion, customization or suggestion of content in any format that is relevant to the individual user, based on the user’s implicit behavior and preference, and explicitly given details.
Hotels have two opportunities within the umbrella of personalization. First, hotels can provide content, recommendations or experiences that match the guest’s expressed or inferred needs and preferences throughout the guest lifecycle. This isn’t a new idea – frankly, it’s just good service – but with technology enablers, personalization can be infused into every interaction, and delivery can be standardized across touch points, whether digital or in person. For example, when a guest is researching a vacation on the hotel’s website, the content he or she sees can be customized to his or her search patterns (pictures of Caribbean properties in the Web frames if they are searching for resorts). Further, follow-on offers can be developed based on previous searches that did not result in a booking. For example, if this same guest did not book during the session, marketing can follow up with an email offer or awareness communication about resorts in general or for the specific resort the guest viewed.
Another opportunity within personalization is giving the guest control over certain key aspects of his or her stay – flexible packages, attributes of the room, amenities, on-property activities or local experiences – effectively allowing them to customize their own experience. Offers and choices should be captured so that profiles can be updated, recommendations improved and the program can continuously evolve.
These two opportunities are linked by the common goals of making it easy to do business with the hotel, increasing engagement and loyalty, and providing value above and beyond the room rate.
Consider the diagram which depicts the stages of the guest experience in broad strokes. At the center, we have Ann Roberts, our loyalty program member who is planning a weekend getaway. Roberts generally stays for business, but her digital interactions quickly demonstrate that her search patterns are different than normal, so she’s shown leisure-oriented properties, packages and room types. As she narrows the search and selects parameters, analytics including pricing and availability controls from the revenue management system, can predict the three packages she’d be most likely to book, and display only those with appropriate pricing and restrictions. When she arrives at the hotel, the front desk offers her a discounted upgrade to a room type that she looked at but did not select on booking – again based on the pricing and availability controls from the revenue management system.
During her stay, the hotel staff delivers personalized recommendations, such as an invitation to the hotel’s Friday night wine tasting. She attends a concert on Saturday night and tweets about what a great event it was. The hotel’s social media monitoring picks up the tweet and real-time decisioning determines that she qualifies to be invited to a special performers’ reception at the hotel. She’s messaged back with the invitation. As she checks out, her profile is updated with her stay activity, and subsequent offers reflect her stay pattern and preferences.
Other opportunities to leverage online and offline behavioral data include flagging profiles of guests that have had service problems in the past, so that staff can be aware of any existing sensitivities. Also, if you have social media identification information from the guests, you can mine their social media activity for preferences or monitor communications for opportunities to improve their experiences. Even for limited-service properties, guest data about room-type preferences, amenities or local attractions can still add value to the guest’s stay experience when designed and offered appropriately.
Why Traditional Web Analytics Just Aren’t Enough
The biggest challenge hospitality marketers face is stitching together fragmented sources of data to deliver on this vision of integrated, personalized marketing. Traditionally, online, offline and third-party data are stored in silos, and therefore are very difficult to pull together in a logical, efficient and easy-to-use format. While data-driven marketers have used powerful, advanced analytics to perform sophisticated analyses – such as regression, decision trees or clustering – they have been limited to using offline data, primarily due to restrictions on access rights to online data from third-party technology vendors. On the flip side, Web and digital analytics tools primarily aggregate and report on historical information and do not enable predictive analysis. Obtaining an omni-channel, integrated view across the fragmented digital ecosphere has been extremely difficult. As a result, it has been practically impossible to get a data-centric, comprehensive view of the guest that could feed integrated marketing analytics, or more specifically, provide prescriptive recommendations for marketers. Enter digital intelligence.
Digital intelligence is defined as: “The capture, management and analysis of customer data to deliver a holistic view of the digital customer experience that drives the measurement, optimization and execution of digital customer interactions.”
Traditional Web analytics data are siloed by channel and frequently aggregated up to a level that is only suitable for business intelligence, as opposed to advanced analytic applications which require detailed one-to-one data. The vision of digital intelligence dictates that marketers focus on understanding who, what, where, when and why of digital experiences. It requires considering larger downstream business applications and use cases when determining what digital data to collect. For example:
- Predictive analysis to identify what unique behaviors or attributes in a visitor’s digital journey are deemed most important in correlating with revenue-generating events
- Analytically forecasting website visitation by traffic source and identifying which ad-centric channels have the largest effect in increasing overall traffic
- Predicting online and offline behavioral drivers of digital conversions using analytically driven segmentation techniques and improving outbound and inbound targeting rules for future marketing communication and personalization efforts
To support the opportunities outlined above, Web and mobile data, if collected and prepared appropriately, can be merged with a company’s first-party (or company-owned) customer data, and then streamed into its analytics, visualization and interaction automation systems.
In the coming weeks the second article in this series will be posted on the Hospitalityupgrade.com TechTalk blog and will discuss how the new opportunities in data management for digital intelligence will work for hospitality organizations and provide a path to get started on the journey toward personalization.
Kelly McGuire, PhD, leads the Hospitality and Travel Global Practice for SAS. In this role, she is responsible for driving the offering set and setting strategic direction for the practice. Suneel Grover, MBA, MS, is a senior solutions architect at SAS, specializing in the areas of predictive analytics, digital analytics, visualization and data-driven integrated marketing.
