Travel is one of the most fascinating industries due to its complexity, size, and state of development. According to estimates, the travel industry adds up to 12%-14% of global GDP (all value, jobs, and related industries included) and its fragmentation is fabled — from airlines, hotels, short-term accommodation rentals, tours and activities, and even restaurants — there isn’t a single player that has access to them all.

While this fragmentation makes the tech challenge in travel incredibly complex, the product interpretation of the vast array of information still meets the customer at a very basic level.

Usually, it is a display of options. And it is typically in a list or grid format is far from where it needs to be, making travel exploration and purchasing as simple as buying a book.

At a fundamental level, travel is about people, places, and time (thanks G for making me think this way). At a technology level, it is about finding the needle in a haystack in less than a few seconds. At a product level, it is still being defined, but more or less, it centers around two main categories, with a special third case which could easily be the holy grail of travel. Here they are:

1. DISCOVERY

You know your destination, but you are constrained by

• A. Time: you have specific dates when you need to be // can be there
• B. Money: you have a certain budget that constrains your options

2. INSPIRATION

You DON’T know your destination, and again, you are constrained by

• A. Time: you have specific dates when you need to be // can be there
• B. Money: you have a certain budget that constrains your options

3. THE NETFLIX PROBLEM IN TRAVEL

You DON’T know your destination and you DON’T have any constraints.

Let’s take a deeper look at them from a product perspective.

1. Discovery

You know your destination, but you are constraint either by money or time.

A couple of examples will help us set the stage. Let’s say we know the destination (in this case Sofia) and we need to discover travel options that satisfy our contraints. For the ease of argument, I’d use the example of flights, but that could easily be applied to all other travel verticals.

1A. Know Destination // Time Contraint

The consumer use case is pretty straight forward. Origin, destination, and time (main constraint) are known. In this case, the user needs a set of flights that allow them to meet their time limits and most of the drivers will be around money and convenience, where the trade-off will be done within the limits of the time constrain — even if there is a direct flight that is affordable, unless it gets us to the destination on time, it wouldn’t be a preferred choice.

More or less, today’s flight search engines have offered this options as default, where a list of results is displayed, typically arranged by price.

Yet, that’s just one interpretation of how to satisfy Know Destination // Time Contraint. I am sure there are a lot more other ways to do it.

1B. Know Destination // Money Constraint

Another popular search is a decided destination. In our Sofia example, let’s assume that the customer is visiting from Singapore. In this case, the destination is known, but the money constraint places the user in a calendar search mode — when is the cheapest when I can fly? Month/Year search (available at Skyscanner) is one way to solve this problem, heat maps over a calendar is another, even price alerts could be third.

As far as discovery goes, our product thinking should be built around those cases — Know Destinatino // Money or Time Constraint and we as an industry are still far away from satisfying the needs to meet the requirements of the use case.

2. Inspiration

A harder, and I would argue, more challenging use case is the case of inspiration. That’s typically driven by the fact that you don’t know your destinations.

2A. Don’t Know Destination // Money Constraint

You don’t know your destination and you are constraint by money.

Typically exhibited with a map, most players try to plot every possible data point to the extend it becomes almost useless (hint: big search engine). The idea here is that only one problem should be solved, rather than two (all available places with the cheapest price).

Instead of telling me that I need $1,000 for a round-trip to Paris and $2,500 for Dubai, I need a relevant glance at where $400 can get me. This way, the product exhibit will be simplified and it will meet my condition.

I am yet to see a nice way (humble-brag: outside of our white label) to solve this problem with images and videos, and why not even through tinder-like swiping.

2B. Don’t Know Destination // Time Constraint

You don’t know your destination and you are constraint by time.

Another hard problem to solve is when you have a time constraint, such as national holiday, long-weekend, or school vacation. The time is set (in length or month/date). In this case, calendar visualization drives the decision making process — where can I go for 5 days within five hours of a direct flight.

Ordering, usually by price, should ideally give a number of options that satisfy the condition. Its current implementation today is the ‘Anywhere’ feature that we have at Skyscanner, which returns a set of results based on price.

Yet, I am a firm believer that we could improve on this experience by including more calendar-like functionality right from the start.

3. The Netflix Problem in Travel

You don’t know your destination and you don’t have any constraints.

Finally, the hardest problem to solve is potentially the Netflix equivalent in Travel — I have been to XXX number of places and now I’d like to know where to go next. Similar to ‘People who have watched this movie also liked XYZ’, the Netflix problem in travel can only be based on historical extrapolation of personal travel + the wisdom of the crowd.

For example, if I had gone to New York (as in the example above), but I have also been to London, London might not necessarily be a choice that interests me. Hence, it should be removed from the list. At the same time, I might have liked it so much that I’d love to visit again — in which case, it should be part of the list. A really hard one to solve.

I am yet to see a good, even a basic solution in travel that touches upon solving the specific case where the destination is unknown and the constraints do not exist.

Now, that’s just the start. In an ideal world, we as an industry should offer one result for every search and that result should end up being a booking — 100% conversion. In practice, that will be impossible and even better — undesirable — part of the beauty of travel is exploration, where you stumble upon destinations, options, and deals, either in the discovery or inspiration stages.

From a product perspective, we still need to solve these two before we start removing the clutter and refining the engines. And definitely before that, we need add the people part from the people, places, and time matnra, where our travel, an inherently social activity, needs to be synchronized with those we’d like to travel with.

All in all, there are endless product problems that need to be solved in travel and the opportunities are unlimited, especially in a mobile world.

Complex Problems Live in Travel.

Solve them.

For my other musings on the complexity of travel, please use the links below.

Part 1: Complex Problems Live in Travel. Software Engineering Edition.

Part 2: Complex Problems Live in Travel. Product Management Edition.

Part 3: Complex Problems Live in Travel. Business Development Edition. [TBA]

//Expressed views and opinions are my own.