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Big data in the travel industry: How can travel companies do more to collect and use customer data?

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Big data in the travel industry: How can travel companies do more to collect and use customer data?

People leave lengthy trails of data when they travel. Purchases are made online, itineraries are stored in digital calendars, and GPS co-ordinates are shared every step of the way.

Data-based insights can improve every stage of the customer experience, from the first interaction through to loyalty initiatives.

However, collecting and connecting that data remains a challenge; turning it into profitable insights is more challenging still.

Data to insights

Travel businesses are aware of the importance of data analytics [1]. According to The State of Data in Travel Survey 2017, 65% of travel businesses now have a dedicated data analysis team, with 75% of these businesses expecting to increase their data analytics budget this year.

And yet, there is a sense that we are still only scratching the surface of what might be possible for the online travel industry [2].

As it stands, much of the available data is unstructured and requires some wrangling before it can be used to shape decisions. The tasks of capturing, transforming, and interpreting this data requires collaboration between all teams, from CRM through to Analytics and Search. Having a dedicated data team is a significant step in the right direction, but everyone has a role to play in a truly data-informed company culture.

This article will explore some common issues with data capture in the travel industry, before discussing some use cases for this data when it is captured and stored accurately.

Data capture challenges

Incomplete or inaccurate data

One of the most significant obstacles to progress for the travel industry is the unreliable or incomplete nature of some data sets. This is true of many industries, but its ramifications are widespread and severe when applied to an industry that generates as much data as travel does.

This is a fiercely competitive industry where speed is always of the essence, but minimal advantages can reap great rewards. The key to unlocking those rewards in 2017 and beyond will be the use of reliable data to enhance customer experiences.

There are many reasons why a data set can be incomplete or inaccurate, however. Customer data is fragmented across numerous different systems, which can either be proprietary or off the shelf. Bringing this all together into one reliable data warehouse requires a lot of investment, particularly for larger companies which depend on legacy technologies for customer loyalty data, complaint logs, and flight operations.

This can lead to a fragmented ecosystem that looks as follows:

Travel data

Source: Markrs.co

If we factor in the likelihood that a customer will book component parts of their itinerary with different providers, across different devices, at different times, the holy grail of attaining a unified customer view seems rather distant.

The use of a data management platform (DMP) to assimilate first- and third-party data sources can aid with this, but it can only be as effective as the data allows it to be. Marketers need to be capturing data effectively via their different channels to maximize the potential of a DMP. French national railway company SNCF deals with over 90 terabytes of customer data per month, but these are the quantities of data required to understand customers’ behavioral patterns.

If we look at the figure below, we can see that there are severe limitations to the quantity of data each team is gathering and using to shape the customer experience at the typical travel company:

Travel_Industry_Data

This reveals how far the industry has to go, but progress is being made. Real digital transformation takes a long time to bring to fruition, and travel brands would do well to increase their uptake of these different avenues of data collection as a starting point.

The gaps in data capture are very clear, but before tackling the root causes it is also worth considering a development that will only increase the quantities of data at a travel marketer’s disposal.

Internet of Things

In the figure above, 14.8% of senior travel marketers stated that they use Internet of Things [3] devices to gain insight into customers. This area, in particular, is one we can expect to grow substantially over the next 12 months.

Internet-enabled devices, at home, in the car, and on our person, provide a new avenue for travel companies to engage with customers. However, the huge quantities of data that emanate from these devices can be difficult to harness.

IBM_Travel

Source: IBM

Amazon Echo and Google Home are now approaching mass adoption, but marketers do not have full transparency into voice query data.

Google Home, powered by Google Assistant, has partnered with over 70 companies now, while Amazon’s Echo already boasts partnerships with Expedia, Kayak, and United Airlines. As these interfaces open up to more brands and advertisers, more data will become available to aid personalization efforts. This should therefore be viewed as a primary area of focus for innovative travel companies.

Organizational structure

The world has changed significantly over the past decade and businesses need to make fundamental structural changes just to keep up. This is not an easy challenge and digital transformation will be a key challenge for some time to come.

For travel companies, as they seek to maximize the returns on their customer information, it is imperative to build a company culture around data. Accenture estimates [4] that digital transformation will add $305 billion annually to the travel industry, but also that $100 billion will go to new businesses that are established with digital in their DNA.

The traditional airlines and travel agents are taking this as an incentive to overhaul their operations.

As was reported in our recent article on the digitization of airlines [5], Gareth Evans of Qantas highlighted the following areas of focus:

  • Cultural transformation (improving employee skills and engagement)
  • Customer transformation (improving satisfaction and customer experience)
  • Network/fleet transformation (improving operational efficiency and financials)

With regards to cultural transformation, many organizations have established a ‘center of excellence’ within their management structure that focuses purely on data analytics. This ensures that a number of senior figures can effect change throughout the business as digital transformation takes shape.

Travel Structure

This desire to be data-driven comes with pitfalls, nonetheless. Marketers must beware of dangers like confounding variables [6] when conducting data analysis. Travel marketers have reams of data at their disposal and it can be tempting to draw conclusions from correlative evidence.

There is therefore a level of rigor and discipline required if travel companies are to transform their operations and incorporate data at every stage.

What we are ultimately trying to achieve is the location and extraction of meaning where previously we could find none.  That can lead us to put the cart before the horse and arrive at convenient conclusions before we have undertaken a thorough analysis. All marketers are responsible for ensuring that data analysis follows a clear methodology, as there is a significant amount at stake.

Speed

For the travel industry to gain full insight into customer journeys, we would need much better psychological measurement technology than we have today. Myriad factors shape the decision-making process when a customer books a trip, from destination to weather to price.

One thing that we know for sure is that customers want their digital experience to be fast.

Google mobile satisfaction

At the recent Facebook Travel Summit, it was revealed that the ongoing shift from text to image and then on to video content is re-defining how much content users are capable of consuming. Our brains process visual content 60,000 times faster than they process text content; as such, people are scrolling through news feeds faster than ever before.

Facebook estimates that the average Facebook or Instagram user now scrolls through over 300 feet of content on their feed per day. For context, that’s equivalent to the height of the Statue of Liberty and not far off the height of St Paul’s Cathedral.

Of course, that just accounts for social media usage. Factor in all the other data touch points and the complexity of the task for travel marketers is stark.

Marketers can account for this by optimizing social media content assets for this visual era. Best practices include showing the company logo (in a direct or indirect fashion) within the first five seconds of a video and including people, as this tends to engage consumers more.

Travel businesses must ensure that their site experience is as seamless and fast as possible, both for conversion and loyalty.

Success stories

Once more accurate customer data has been procured and converted into meaningful insights, a plethora of opportunities opens up to travel industry marketers.

Above, we have covered some ongoing challenges for the travel industry, but also hinted at the huge opportunity at our disposal. It therefore seems fitting to round off this investigation with a few examples of travel companies that are making sense of big data today and using it to improve business performance.

Internet of Things – KAYAK

KAYAK is at the forefront of big data innovation in the travel industry, using predictive analytics modeling to shape every aspect of the customer purchase journey. As such, it was no surprise to see the launch of KAYAK Explore [7] as an early Alexa Skill.

Users can make a simple voice query like, “Alexa, ask KAYAK where can I go on vacation in October for $1000” and Kayak will assess the options. There is plentiful room for this functionality to improve too, as Kayak learns to personalize recommendations with greater accuracy.

kayak

Customer experience – Schiphol Airport, Amsterdam

Airports typically get a bad rap, but they are an essential part of the travel industry. Amsterdam’s Schiphol Airport tends to fare better than most and always scores well in customer satisfaction studies.

Recent efforts by the airport to improve the experience have seen Schiphol Group (which operates the airport) invest in data science packages and a team of analysts fluent in R and Python to visualize the constant stream of data that is collected.

schiphol-airport-02

Analysts assess heatmaps to see how travelers make their way through the airport, even calculating how far they tend to stray from their departure gate. Noise pollution levels are stored for analysis and all retail sales are fed back into a central system.

The rewards of these efforts are evident: Schiphol has once more been voted the best airport in Europe, citing in particular the efficient, customer-friendly experience.

Personalization: The next big opportunity

Accenture reports that 65% of travel executives feel that they have not yet delivered on the promise of true personalization. It is a significant business priority, of course, but there are barriers to entry that will take some time for all to surmount.

Others are making great headway already, with the likes of Alaska Airlines using analytics to increase their back-end efficiency as well as their customer-facing product.

The applications of personalization for travel companies could really be endless. Some efforts in personalization to date could more appropriately be defined as profiling, however. Users are bucketed into categories based on some similarities and recommendations are provided based on the ‘type of person’ they are seen to be.

Nonetheless, a world where travel companies can serve unique and tailored recommendations to each individual customer, based on the harnessing of big data, is really not so far away.

Related reading

References

  1. ^ data analytics (www.clickz.com)
  2. ^ travel industry (www.clickz.com)
  3. ^ Internet of Things (www.clickz.com)
  4. ^ estimates (www.accenture.com)
  5. ^ the digitization of airlines (www.clickz.com)
  6. ^ confounding variables (explorable.com)
  7. ^ KAYAK Explore (www.kayak.com)
  8. ^ … read more (www.clickz.com)
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