Think of the last time you planned a trip. If you're like most travelers, you went through a lengthy and labor-intensive process to determine the travel timeframe, decide on where to go, figure out how much you can spend and book the reservations. In an informal survey of our employees last fall, we found that it took one or two weeks for them just to plan a simple three-day trip.1
The fact is, travel planning is still time-consuming, despite radical changes in the last decade due to the Web and social media. Although technology has made it easier to access information, share opinions and make comparisons, today's travelers must navigate a range of channels at every turn. They might view photos of a friend's trip on Facebook or Instagram, check TripAdvisor for reviews, do further research on destination Web sites and compare hotel and airline prices on Orbitz and Expedia. Additionally, they might check their bank account or credit card balances to determine their budget realities, as well as the calendars and schedules of their travel companions to determine a travel timeframe.
But by 2020 — if the current pace of consumer digital activity and technology advancements continues — travelers can expect a much more automated and personalized approach to how they plan trips. By then, a single entity — an intelligent planning engine — will aggregate and analyze the far-flung pieces of data that are either provided outright or generated implicitly through the digital behaviors of travelers, devices, organizations and other entities within the travel and hospitality ecosystem. The result: intuitive development of a customized trip plan that is personalized to individual preferences, availability, spending habits and scheduling needs.
By offering this type of predictive and personalized capability, the travel industry follows other industries that have been disrupted by future- thinking competitors (i.e., Amazon, Google, Pandora) that are making meaning from the digital trails of people, organizations and devices. We call these digital pools of data a Code Halo™ and they not only form around travelers — many of whom lead vibrant online lives, sharing their digital information with travel agencies, social media Web sites, search engines, banks and more — but also companies (where travelers work), hotels (where travelers stay) and travel intermediaries (where they often book trips). By analyzing these Code Halos and distilling meaning at key intersections, airlines, hotels and travel intermediaries can better understand current behaviors and even anticipate future needs and desires in ways they never could before.2
For instance, the brand and type of a hotel or resort can connect to form a destination Code Halo that reveals the place and type of travelers it attracts. Or the browsing or social networking data of a group can form a traveler Code Halo, which can reveal the destinations they prefer by examining which ads they clicked on (providing insight into their preferences) or social posts they "liked."
Getting from 'Here' to 'There'
To understand what needs to happen to enable this transformation, let's consider the three types of information that would populate the Code Halos used by the personalized planning capability, as well as the meaning that could be derived (see Figure 1).
Primary data: Basic, readily available information, including:
Places and locations: When information about numerous destinations is categorized in a standard way, with an adequate volume of guest rankings, travel providers could systematically determine the best places and locations for individual travelers.
Suppliers and availability: By analyzing offers and packages in real-time, providers could offer dynamic packaging based on supply data and the estimated number of guests who would be interested.
Schedules: An intelligent planning engine could synch the schedules of the travel group and plug in the information related to holidays, vacations and time off. Once these timing constraints are shared, the system could determine the optimal time for vacation.
Budget and financials: Spending boundaries would be established, based on funds data and credit availability.
Explicit data: Factual information pertaining to an individual or group that is explicitly expressed. Examples include:
Preferences: Most groups and individuals have a fair idea of what they don't want; if they supply information on these preferences, an intelligent engine can use these inputs to eliminate the obvious.
Past expenses: Expenditures from previous vacation expenses, such as hotel, travel, food, amenities, etc. can offer valuable input for the planning engine to determine the budget for various activities.
Implicit data: Preferences and interests derived from implied information. Examples include:
Social activity: Social platforms generate a plethora of data expressed as likes, tweets, posts, etc. that can be analyzed to gauge an individual's inclinations and preferences. In trip planning, the biggest influencers are recent trips by friends, colleagues and relatives. The planning engine can analyze this social activity to optimize recommendations.
Digital footprints: Browsing history, links clicked, ads viewed and articles read or shared form another set of data that can be leveraged by the planning engine to gain meaningful insight into a traveler's preferences and interests.
When all three types of information are made available and compiled, providers can use an intelligent planning capability to make a trip recommendation, with a personalized schedule and budget that fits the traveler's needs. Using what it knows about the traveler, based on her Code Halo, the provider can predict the optimal destination and all the traveler needs to do is click on the "booking" button to make the travel and hotel reservations. It's easy to imagine this capability being offered for free, but providers could also offer upgrades to premium subscriptions for travelers who want advanced features, like the ability to alter recommendations or make travel plans for larger groups.
Travel providers need to understand two Code Halo principles to develop a successful intelligent planning capability:
Process melt: In addition to delivering highly personalized experiences, travel and hospitality companies can apply Code Halo thinking to more accurately estimate future demand and provide better and more targeted promotions. Consider an offering that we call the "reverse Groupon" approach. When group-sharing Web sites offer deals, it is difficult for them to predict how many customers might be interested and, thus, how many offers the promotion will yield. But if we think through the prism of Code Halo thinking, a dynamic package can be formed by reversing the model. In the Code Halo world, we call this a business process "melt."
For example, suppliers and travel intermediaries could collate implicit and explicit preferences of travelers to analyze how many people in the New York area are interested in a trip to Hawaii. They could then negotiate airline and hotel prices with suppliers for this group to develop a New-York-to-Hawaii trip package for these selected travelers. By synchronizing the demand and availability equation, the planning engine could match the group with interested suppliers and build a dynamic package, customized to their needs. The underlying assumption here is that the dynamic trip package is unique and not available anywhere else.
The give-to-get principle: Consumers are increasingly savvy about the worth of their personal information and are unwilling to give it away if they don't trust how the data will be used and protected and without the promise of something in return. In our informal employee survey, 82% of respondents said they provided online feedback for just three out of 10 trips they took. However, if a reward was associated with providing feedback, then 91% of respondents said they would provide online feedback for eight out of 10 trips.
In many cases, the prospect of time or cost savings, targeted deals and customized experiences is enough of a lure to encourage the sharing of personal information. The bottom line is that giving information needs to be worth the perceived reward value.
Jump-starting the Transformation
Travel and hospitality providers can begin to transform their business models and develop an intelligent planning capability by taking the following steps:
Build A Strong "Product/Places Halo."
Form alliances to develop and maintain a standardized catalog of various places and locations in different regions and geographies. An intelligent planning engine will heavily rely on such a database of places, with authentic listings of "things to do" along with genuine traveler ratings.
Build a "traveler halo."
Develop innovative ways to assimilate the traveler information from social media networks, digital trails and different travel entities to build a complete traveler halo. Such profiling will help the planning engine sort implicit traveler preferences.
Build capabilities for Code Halo interfaces.
Different entities across industries should build new interfaces through which they can collaborate. For instance, tourism board information on local festivals could be used for effective promotion to travelers who have interest in local cultures and cuisines. The exchange of such digital data will enrich traveler Code Halos, offering important insights that can be distilled by the planning engine to determine next trip budgets.
Build an ecosystem of sharing Code Halos.
Seemingly unrelated organizations should develop digital channels to expose information upon authorized request. For example, travel agencies cannot currently see travelers' available vacation days. The sharing of individual calendars and schedules can help the planning engine optimize the best time for a group to travel.
Fast Forward: Travel 2020
The transformation of the travel industry will at first be marked by sporadic change, but gradually, as the digital ecosystem matures, the environment will be ripe for the development and widespread use of intelligent trip planning. Already, many of our hospitality clients are mining the social media data they collect to track travelers' implicit preferences, which is helping them build new systems to generate offers to individuals based on their explicit historical data. A few players, such as Flextrip, Gogobot, Tripit and Stay.com, have already begun the transition by focusing on the social aspects of trip planning and incorporating these insights into their offerings.
While there are undoubtedly challenges and obstacles that stand between "here" and "there," including data privacy and regulatory changes, companies cannot ignore the vital signs exhibited by the early adopters of Code Halo thinking, such as the ability to predict customer preferences and expectations. As new business models elicit increased customer acceptance, the industry will gradually be defined by seamlessly integrated travel planning engines. The time is now for the travel industry to identify the sparks of change and begin planning to compete on code and distill meaning from Code Halos.
1Our Travel and Hospitality Practice conducted a focus group survey of 90 employees in October 2013.