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For a Complete Online Booking Experience

Posted on: 16 December '11

Vacations and holiday seasons are just around the corner, and families are clamoring for a dream vacation. Most of us have a busy schedule and don’t have time to find the perfect vacation spot. Unfortunately, most travel decisions are made unconsciously. We simply decide without thinking much about the decision process. It’s like an automated reflex. If we were to sit down and list the pros and cons of each vacation spot, it would take forever.

But, this is exactly what the online booking experience is all about. The average number of searches per user is approximately 25, while the number of sites visited is approximately four. Consumers experiment with various destinations, check the total amount payable, budget for the hotel and car rentals, and then repeat this process. . No wonder the look to book ratio is abysmal for all travel search engines, because none of them address the fundamental need of the consumer – help with the purchasing decision.

Let’s take a look at the purchase behavior:

Purchase Behavior

Purchase Behavior

Steps:

  1. Problem Recognition leads a consumer to outline his or her needs and outcomes
  2. Information Search leads to gathering of data
  3. Alternative Evaluation leads to development of alternatives, and listing of pros and cons of each alternative
  4. Making the decision leads to the Purchase Decision
  5. Post Purchase Behavior leads to Cognitive Dissonance (buyer’s remorse)

First, we have to analyze the problem and then arrive at a decision. The problem analysis is straight forward. It can take the form of:

  • I want to go to the beach
  • I want to go to the mountains
  • I want to go gambling
  • I want to go to an amusement park, and so on.
  • The problem can also be stated as: I have $1000, where can I go?

In the current online booking scenario, the user has to know where and when he or she is going. The booking tools don’t help a consumer with the definition of the vacation need.

Information search takes the form of asking peers, neighbors or relatives for their “expert” opinion. Sites such as TripAdvisor, Yahoo Travel Guide, and others provide a credible user opinion forum. The booking engines don’t help with the problem analysis, and, even less with the decision making process. Problems must be precisely identified and described; objectives must first be established, classified and placed in the order of importance. And then, alternative actions must be developed. Simply put, the online booking experience is antiquated and unsatisfying.

Currently, alternative evaluation takes the form of meta search engines, and comparing a specific origin-destination pair for a specific date. None of them provide alternatives, or provide a venue for “what-if” analysis. None of the online booking engines provide a recommendation based on the consumers search parameters.

The Purchase Decision is a simple choice of credit card or pay-pal payment type. There is no incentive for the consumer to receive a discount if the booking is made right way.

And finally, the Post Purchase Decision is completely ignored by today’s booking engines, and sadly by most suppliers. Buyer’s remorse is an accepted facet of the buying process.

If you have time and access to information, then the decision making process as described above is a viable solution. But, in most cases we are bound by either an optimal decision or something that is good enough. Optimal decisions tend to maximize performance across all variables and make tradeoffs carefully, whereas for many of us “good enough” is just that…good enough.
So, what are the variables in making a vacation decision?

1.Physical Attributes:

  • Budget
  • Location

— Domestic
— International
— Beaches
— Mountains
— Other attributes

2.Social Attributes:

  • Other travelers and Roles
  • Premium traveler

3.Perspective:

  • Time of the year
  • Season
  • Elapsed time (duration)

4.Mood:

  • Relaxing
  • Adventurous
  • Learning

Managing these variables to arrive at a vacation decision is unlikely. Therefore almost all of us go on a vacation that is “good enough.” Imagine that!

Towards a NextGen Booking Tool

Most online booking engines are nothing more than a Graphical User Interface (GUI) placed upon the Global Distribution System (GDS)/ Computer Reservation System (CRS) green screen booking flow. Board-off, departure date, arrival date and number in party are the building blocks of the GDS/CRS availability display. For a game changer that addresses the consumer buying behavior, there are a few items still missing from the online experience.

Firstly, the booking tool needs to be aware of the location. The tool must be able to identify the nearest airport. Most mobiles and tablets are location aware. For other devices, the user could create a profile wherein the nearest airport is hardwired into the search query.

Secondly, allow the user to enter natural language queries. Leading edge booking tools could utilize semantic search algorithms. Building such algorithms is an expensive, tedious, and time consuming endeavor because current databases used by the GDSes that power online booking tools are flat-files. The GDS/CRS APIs need to be modified to accommodate natural language. Thirdly, the booking tool should display the results with the vacation decision making variables as modifiable inputs. Semantic Search engines can’t guess the intention of the user. But the solution is easy, just to give the search results of all possible senses of the word to the user. . Even better, categorize them neatly. This is within the design envelope of semantic search engines. Based on the consumer travel preferences, a recommendation must be provided based on similar preferences. Amazon does this flawlessly when a consumer is buying a book. Adding a social computing functionality to online booking sites is a fundamental nextGen experience. We are after all, social animals.

When it comes to the final step in the online booking scenario, the provision of credit or payment terms may encourage purchase (some online booking tools are already doing this by delaying payment, etc.) A sales promotion such as the opportunity to receive a premium package or enter a competition may provide an incentive to buy now.

On the front end, optimize the performance attributes of the search engine, keep the GUI simple. 80% of the end-user response time is spent on the front-end. Most of this time is tied up in downloading all the components in the page: images, stylesheets, scripts, Flash, etc. Reducing the number of components in turn reduces the number of HTTP requests required to render the page. This is the key to faster pages and faster response time.

On the back end, the nextGen booking engine needs a robust event-based knowledge / rules engine powered by a back-end CRM. Business Intelligence and serving up data based on the consumer profile are winning strategies.

Mindtree Blog Archives

Mindtree blog Archives are a collection of blogs by various authors who have independently contributed as thought leaders in the past. We may or may not be in a position to get the authors to respond to your comments.

  • DR

    The fact is that all booking engines focus on providing lowest cost tickets and they have not gone beyond that value-prop. Its time for the booking engines to change from being a ticket broker to a personal travel consultant.

  • Prashant

    As the founder of a start-up for customized trips we had applied the principles of AI for gaining that customer WOW experience. On a start-up scale it was not completely computerized and was mainly handled by people. Our plan was that on scaling, this function would be taken over by software. On reading your blog post, I was happy to see your in-depth problem analysis and distinctive solution. Having hands-on experience in this field, I cannot help but share my feedback.

    Goal of NextGen Booking Engine: The outcome of problem analysis & decision making process should not be to promote what the seller wants to sell; rather it must be as accurate as possible a solution for what the customer desires – knowingly or unknowingly. Only then can a company gain a reputation for genuinely helping in the purchasing decision. The increase in ‘look to book ratio’ can be enjoyed as a collateral advantage.

    Vacation Decision Variables: The variables in making a vacation decision which you have identified are essential. I feel vacation decision making is a function of a few more important parameters viz. the social value of a destination for an individual, the destination brand ambassador’s influence, and the trust in the trip organizer.

    NextGen Booking Tool Powered by ‘I’: The power of ‘I’ – Intelligence, Intuition and Innovation – should be explored completely through the software. Using semantic search algorithms for the booking tool will partly take care of Artificial Intelligence. The database should be exhaustive and up-to-date. It should be built on a sound Knowledge Management platform with intuitive tagging. Continuous human-centric innovations to fuel this engine will help maintain market leadership.

    Difficult not Impossible: The reason TripAdvisor, Lonely Planet, etc. have gained traction in the travel guide market is because of users’ perception that they are not attached with the generation of sales revenue. In such a scenario building a profitable booking engine with trustworthiness akin to a guide engine is difficult though not impossible. It will need top-notch programmers and best-of-the-breed practices to build a complex program with simple UI. And of equal importance is a willing top management on the Client-side, as the scope is not merely limited to the booking engine, and a capable management consulting firm like MindTreeâ„¢ on the Vendor-side.

    A passionate founder of a start-up (unfortunately an unsuccessful venture), wishes you and your team all the best for creating a ‘Blue-Ocean’ booking engine.