Digital & Data Strategies for Travel 2017 Round-up

Amsterdam: November 29-30, 2017

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© EyeforTravel Ltd ® 2018

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The information and opinions in this report were prepared by EyeforTravel Ltd and its

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Authors

Pamela Whitby, Editor, EyeforTravel

Senay Boztas, Yekko Creations

Digital & Data Strategies for Travel 2017 Round-up

Amsterdam: November 29-30, 2017

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We bring together everyone in the travel industry, from small tech start-ups to international hotel brands, to form a community working towards a smarter and more connected travel industry.

Our mission is to be the place our industry goes to share knowledge and data so that travel and tech brands can work collaboratively to create the perfect experience for the modern traveler.

We do this through our network of global events, our digital content, and our knowledge hub - EyeforTravel On Demand.

Our Values

We believe the industry must focus on a business and distribution model that always puts the customer at the center and produces great products. However, to deliver an outstanding travel experience, the strength, skills, and resources of all partners in the value chain must be respected and understood. 

At EyeforTravel we believe the industry can achieve this goal by focusing on a business model that combines customer insight with great product and, most impor-tantly, places the traveler experience at its core.

At our core we aim to enable the above by valuing impartiality, independent thought, openness and cooperation. We hope that these qualities allow us to foster dialogue, guide business decisions, build partnerships and conduct thorough research directly with the industry. 

These principles have guided us since 1997 and will continue to keep us at the forefront of the industry as a vibrant travel community for many more years to come.  

Our Services

Our events are at the heart of EyeforTravel. These draw in experts from every part of the travel industry to give thought-provoking presentations and engage in discussions. It is our aim that every attendee takes back something new that can help their business to improve. This might be in the fields of consumer research, data insights, technological trends, or marketing and revenue management techniques.

Alongside this we provide our community with commentary, reports, white papers, webinars and other valuable expert-driven content. All of this can be accessed through one place - the On Demand subscrip-tion service. 

We are always expanding the content we create, so please get in touch if you want to write an article for us, create a white paper or webinar, or feature in our podcast. 

EyeforTravel in Numbers

■ 80,000+ database contacts

■ 2,500+ annual event attendees

■ 100,000+ monthly online reach

■ 1,000+ online conference presentations 

About EyeforTravel

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Contents

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

1. Digital Vision, Data Driven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.1 Travel Suppliers and Their Digital Journey . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

1.2 Lessons from the Travel Tech Elite . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

1.3 Startup Success . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

What You Should Be Doing According to the Data Experts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2 Into the Future: What Next for Travel? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.1 Rethinking Organizational Networks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2 Blockchain – Beyond the Buzz . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.3 Why Humans Still Count . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

Case study 1: Kiwi.com – the Customer Is Human! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Case study 2: Trainline’s Busybot – Powered by Human Selflessness . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3 The Rise of Data Science . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.1 Everybody Is Doing It . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

The Three Skills of Data Scientists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

3.2 All Data Isn’t Equal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

New Data Regulation: A Big Issue . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

The Top Three Questions from the Conference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.3 In Search of Truth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Top Data Tips . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Technological innovation just keeps on accelerating and keeping up is a tough act in itself. Data science is now a recognized discipline. Google positions itself as an Artificial Intelligence- (AI) first company. Lufthansa and Air New Zealand are jumping into blockchain in the hope of leveling the playing field. As people speak to their phones, Sofia, a human-imitating robot, has made it onto the December 2017 cover of the woman’s magazine Elle.

This is our digital world, and in technology terms it is fair to say we have come a long way. However, even though travel brands are becoming more data-driven, just 0.5% of data out there today is being harnessed, as EyeforTravel Conference Director Leo Langford pointed out in his opening address in Amsterdam.

So, to address this mismatch, attendees from around the globe came to Amsterdam, Europe’s 2016 Capital of Innovation, for EyeforTravel’s co-located data and digital

shows. They drew a wide-cross section of high-flying speakers and sponsors, as well as engaged and curious delegates from all corners of the industry.

As attendees gathered over two days to hear about trends shaping an increasingly data-driven industry, as well as practical tips and advice about how to move forward, there were questions in air.

What exactly will the travel organization of the future look like? Does my business even have a future? Will I have a job?

Admittedly, the travel industry may still be slightly behind the cutting edge when it comes to imple-menting data-driven digital strategies, but that is changing. The pace of that change, and the impact of it, varies widely and on a number of factors, not least where companies stand in the vast travel ecosystem.

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Introduction

What Were the Attendees Talking About?

Digital Vision, Data Driven

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underpinned by data. 2017 was “its best year in five years,” according to Dan Christian, the company’s chief digital officer. Principally, this had been also been driven by data centralization and sharing.

Echoing what proved to be a common theme over the two-day event, Christian said a big shift had been to get data into one place, and then derive insight from it: “It’s one thing having a business intelligence tool, but a whole other thing getting more business, and more bookings from it,” he said. However, by looking at and sharing data across all its brands, which TTC wasn’t doing just 18 months ago, Christian said they had seen a “huge uplift in business”. Extending the sharing theme, TTC found that API partnerships too had been a huge and important focus.

While TTC had transitioned from being a silo-based organization to one that is leveraging data from all channels to drive traffic and boost conversions, he was clear that at all times “the focus has to be on being an amazing travel company, not a digital company,” and he is “not confused about that”.

Christian was also quick to stress, however, that improving a brand’s digital presence didn’t have to be complicated. For example, you could make a difference by simply taking steps “as basic as having no more than four form fields, in order to optimize the onsite experience”.

Similarly, on a panel considering the ‘appetite for apps’, Stephen Glenfield, head of digital, Heathrow Airport, recommended that brands bring in the expertise of

1.1 Travel Suppliers and Their Digital Journey

Three years ago, Accor Hotels embarked on the digital transformation of what was an operator-led business model into one focused on delivering services to two customers – guests and hotels. Although this remains work in progress, today Fabrice Otano, Accor’s chief data officer, seems quietly proud of developing a huge data-driven hub-and-spoke organization.

“We have tried to create competitive advantage by making digital the broad vision,” he said, “but it’s one that is more and more driven by the data.”

Otano admitted to sometimes going too fast with its data strategy, when the business wasn’t sufficiently mature. An important lesson, he said, was to empower people to use the data, and “to train them not to be shy or afraid of it.” This was as much a human and cultural transformation, as it was technological.

Other hotel insights came from NH Hotels Group, and an early realization for Fernando Vives, the company’s chief commercial operator, that teams should not be working from different data sources. NH has, therefore, moved all hotel systems – from property management to customer relationship and central reservations – into a centralized database.

In another goodbye silo move, it has implemented regional powerhouses, in places like Frankfurt, Berlin and Amsterdam, so that operations marketing, sales and revenue management now share the same office. This means they are able to use the same data to influence each other, and are driving higher revenues as a result.

The Travel Tech Corporation (TTC), a USD2 billion travel agency with 30 brands under its umbrella, has also seen revenues rise as a result of sustained digital efforts

“The focus has to be on being an amazing travel company, not a digital company”

Dan Christian, Chief Digital Officer, The Travel Tech Corporation

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Also speaking on a data keynote was Mark Shilton, Skyscanner’s principal data scientist, who admitted that there had been a few failures on a journey, which began in 2012, to ensure data science contributed the highest value to the business.

Shilton warned against being seduced by flashy new technologies and the promise of new techniques, a view also held by other speakers including Eurostar Head of Digital Neil Roberts.

In outlining its move to AI-driven data science Shilton said: “None of it is worth anything unless you have a solid base to work from. And funnily enough, that base looks very much like the lower tiers of business intelligence and analytics”.

Skyscanner’s efforts to build a data platform have not been superficial. “From real-time metrics to reporting the raw data, we needed to build machine learning models and the tools to train, test and put them into production,” he said.

One of positive results of its efforts has been the ability to offer customers the ‘best value’ flight based on their search history and preferences.

partners and keep away from the complexity of creating an app: “If you’re starting out today, don’t bother with an app – instead have an omnistrategy, use Facebook, bots, do deals and share information. The ‘app-y-sphere’ is overcrowded.”

In summing up, Vives said that instead of thinking about the ‘what do we do’ and ‘how do we do this’, firms should ask more qualitative questions such as ‘why do we want to do this?’

1.2 Lessons from the Travel Tech Elite

Onno Zoeter, named one of Fortune’s 20 Big Data All Stars in 2013, joined Booking.com as its principal data scientist two and a half years ago.

What he quickly discovered was that putting hotels in the right order for customers is anything but easy.

“You might have a beautiful hypothesis backed by sophis-ticated technology, but more often not than you like to think, the customer won’t like what you’ve done,” he said.

In the digital environment A/B testing is, therefore, very important. “It allows you to invert the traditional organization, putting autonomous teams on top. What this means is that teams can go fast, they don’t need to ask permission, and can really experiment with what might work for the customer,” he said.

Zoeter also stressed the need for a certain rate of failure. “If nothing fails you aren’t learning,” he said.

Credit: Dumitru Brinzan (brinzan.com)

“Booking.com is positioning itself as a customer-first AI company.”

Onno Zoeter, Principal Data Scientist, Booking.Com

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outlined, still in the early days of personalization and overly reliant on mass marketing, AI techniques are revolutionising this. With a lot of venture capital funding today going towards building business networks that more systematically harness technologies like AI and drive trust, start-ups are benefiting.

Nishank Gopalkrishnan, the chief business officer of Musement, provided an example of how it was using personalization built on data. The company has built a machine learning-based approach that combines intelligence about destinations and activities with user profiles and historical purchasing behavior. By parsing more than 15 terabytes of information from more than 10 million customers, they were able to build a recom-mendation system that is used by a variety of partners. The primary “pillars” of the recommendation system is detailed tags for the more than 50,000 destinations in their database and the understanding of users through personas built using a wide variety of context such as social data, interests, and purchase history and intent.

Meanwhile, WeSwap, a peer-to-peer currency exchange, which now has 300,000 users and has swapped currencies to the tune of GBP100 million said lots of little things can make a difference. CMO Rob Stross stressed, in particular, the importance to ask qualitative how and why questions. The most important of these was to find and identify the core Key Performance Indicators for the business. “By making incremental changes to just a few key KPIs for us has really transformed our business,” he said.

For Skyscanner, something seems to be working. As of November, it is owned by Ctrip, China’s largest travel company, and is used annually by 60 million people speaking 30 languages.

1.3 Startup Success

Innovative data-driven business models from the start-up community were also well represented. Although the travel industry is still, as Christian Hylander, advisor and vice president of Mastercard,

What You Should Be Doing According to the Data Experts

■ A/B test, test and test some more. The first hypothesis is rarely correct - replacing a system without sufficient testing is unlikely to lead to improvement.

■ As you grow and build out, you need more skills than just machine learning to have an impact.

■ Vertical-specific solutions still outperform everything else because, according to Booking.com “a ‘view’ in our domain is never a political view, but a view from a hotel room”.

■ Putting the customer experience first and letting technology follow delivers the best result, which is why Booking.com is positioning itself as a “customer-first AI” company.

Musement pulls together more than 15TB of data to make its recommendation engine. Credit: Musement

Into the Future: What Next for Travel?

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“they will have to fundamentally ask themselves what their networked strategy is”.

Organizations will have to “find deliberate and specific strategies on where to position themselves, and then carefully design how they play in that corner”.

Clearly companies will evolve in different stages with the extreme version being blockchain-enabled automatically governed platforms, driven by smart contracts and steered by an AI wherever needed.

2.2 blockchain – beyond the buzz

If you are talking about dismantling hierarchical businesses, then you can’t ignore the potential for ‘public permissionless blockchains’.

Interestingly though, as Tim Gunstone, MD, EyeforTravel, said: “Having talked to dozens of data and tech heads at this Amsterdam show, it’s clear that the industry does not know what the implications are for blockchain or where it might lead.”

Amsterdam’s Day 1 closing panel discussion on blockchain, certainly caused a buzz and attempted to cut through some of what Esser described as the ‘blur’ surrounding what could be 2018’s big disruptor.

Asked to summarize the technology in sentence or two, he said that blockchain is a decentralized database, with inherent governance capabilities that allows trust to develop at scale. The panel also highlighted the important distinction between public and private blockchains.

Most companies backing the technology today – TUI, WebJet-Microsoft, S7 Airlines, Amadeus and IBM – are

2.1 Rethinking Organizational Networks

If the Day 1 key note presentations were about the lessons travel brands had learned over the past few years, Day 2 looked squarely at the future. As Jonathan Moore, Trainline’s chief marketing officer, put it, “that we overestimate the impact of innovation over the short term but fail to grasp the long-term impact”.

What we can say today, however, according to Joerg Esser, a theoretical physicist, former group director at Thomas Cook, and now partner at consultancy firm Roland Berger, is that “thriving companies are way more concerned with organizational structures and how innovation flows than others are”.

In a high-level take on the future of travel organizations, Esser looked to ‘network science’ for answers. The field draws on an academic field, which studies complex networks, including everything from telecommunica-tions to biological, computer and social networks. He said that like all forms of life, companies today are hiera-chical structures. They start slowly, increase in speed, level out and eventually die – in other words, they are either gobbled up by M&A activity or go insolvent.

“In networks that are hierachical … there is always a bandwidth issue. This is why there is always a level beyond which they cannot grow,” he said.

Cities, on the other hand, the second type of network structure, grow exponentially and as as they grow, so too do the number of patents, which are viewed as a useful marker of innovation, as do socio-economic issues like crime.

In the future, Esser argued that the art of cooperation and network design will take center stage. It won’t be enough to be, as businesses are today, focused on what they intend to do and what they are capable of doing,

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This said Esser is where “all the war stories emerge from,” and is what had delegates on the edge of their seats, and wondering whether this may give them an alternative to costly intermediary relationships. While the business models are not yet clear, Esser, who has been working to help Lufthansa’s sales’ teams better understand the implications, outlined three possible use cases:

doing private blockchains, which could be likened to an intranet. This might be useful but not ground-breaking.

On the other hand, Winding Tree, which has signed partnership agreements with Lufthansa and Air New Zealand (and post conference it announced a hotel partnership with Nordic Hotels), claims to be the building the only ‘public permissionless’ blockchain for the travel industry, with its own Lif token, that supports a decentralized travel industry.

Joerg Esser, a theoretical physicist, former group director at Thomas Cook, and now partner at consultancy firm Roland Berger, believes companies need to pay more attention to how they are organized and apply scientific standards to their structure. Credit: Manu Corbet

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2.3 Why Humans Still Count

Nobody in Amsterdam was disputing the disruptive power of machines and how they are capable of replacing human jobs. Filippo Onorato, CIO Lastminute.com group, for one, argued that AI certainly has the ability to add scale to human-like reasoning.

One example of this, came from Michael Mrini, director of information technology at Edwardian hotels who provided an update on Edward, a much-loved staff member at the UK hotel chain. Now eighteen months old, the artificially intelligent valet has just started a new adventure, responding to voice commands and speaking to guests. “We went from SMS to a chat app, and now Edward can talk as well – a lot of people think he’s a butler!” said Mrini.

Nevertheless, there were plenty of examples of why humans are still important in travel, and two case studies stood out:

■ Revolutionary disruption: Here we’re talking Winding Tree and its public permissionless blockchain. How this plays out is anyone’s guess, and there were many questions in Amsterdam, both from the panel audience and in networking sessions afterwards. Particularly curious were the hotel chains, and just for the record, shortly after the Amsterdam event, Winding Tree announced a deal with the Nordic Choice hotel chain.

■ Private blockchains: a new-age ‘intranet’: Essentially these are to be used for supply chain management such as airline maintenance initiatives. The Webjet-Microsoft deal was an early example of this and while it may not be wildly disruptive, it does, according to Esser, hold great value by easing efficiency in the supply chain.

■ Travel meets financial services: The complexity of financial transactions in the airline space is huge. Esser cited the example of a business traveller located in Russia booking a flight from London to Bali on a Dubai-based airline and paying with it from a US bank account. That transaction could take at best up to 15 days and at worst as many as 40 days, with fees skyrocketing in the process. Blockchain technology, with its smart contracts, would solve that problem and could disrupt the global distri-bution systems, which are currently backed by the so-called Billing and Settlement Plan.

Credit: Dumitru Brinzan (brinzan.com)

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“We are working with a shit load of data.”

Martin Ratoliska, Chief Data and Automation Officer, Kiwi.com

Case study 1: Kiwi.com – the Customer Is Human!

At Kiwi.com, data is processed from 400+ sources, 10.5 terabytes of flights, 50 million searches, 65 billion potential combinations, and with an average API response time of 0.3 seconds. Clearly technology is central to Kiwi.com’s business, which does everything from machine learning to dynamic yielding and analysis of sales in real time, and with a 95% success rate of most automation services. According to Martin Ratoliska, Kiwi.com Chief Data and Automation Officer, the OTA that launched in 2012 and has grown to a business employing 1,500 people in 10 countries, processes “a shit load of data”.

So, why not automate one of the costliest services that travel businesses operating in multiple countries and languages must provide? “In working out ways to decrease the cost of internal customer support, we said: OK, let’s create a chatbot, it will be easy,” Ratoliska said.

The reality, however, was quite different. Why? Because travelling is a physical activity and queries can be complicated, especially when travel plans blow up! When there is a problem with check-in, when a flight is cancelled or delayed, or when bags are lost, people, said Ratoliska, are “desperately looking for help, comfort and hope and they want it ASAP!”

Today, a chatbot without human support simply cannot deliver – the technology is not there yet. So, Kiwi.com decided to approach things slightly differ-ently, and has developed an AI-driven chatbot that is integrated into the interface used by human agents, tasked with calming down disgruntled customers.

The agent is able to choose from best AI-driven answers or can continue chatting as normal. Ratoliska explained: “Every time an agent chooses something from the AI, it gets adjusted and the chat bot learns from it”.

So while automation remains crucial to Kiwi.com’s business, it is a strong believer in the human touch.

Case study 2: Trainline’s Busybot – Powered by Human Selflessness

Trainline chief product officer, Jonathan Moore, told the EyeforTravel Amsterdam 2017 conference: “BusyBot was to answer a simple question: are there any free seats on your carriage? A train operating company was talking about spending hundreds of thousands on pressure gauges – and we had to tell them we had solved it for free with software.” 

BusyBot, which is found with the journey tracker part of Trainline’s app, asks customers to report how busy trains are and uses the hundreds of thousands of reports to make predictions for any service on any route. 

What Trainline discovered, was that customers were happy to do the work for the firm in building a dataset if they saw clear benefit. “We see 150,000 unique inputs every week into this feature,” he said. “There’s a real selflessness in this number – there’s no reason to interact with this feature unless you make someone else’s life a bit better on another day.” 

On whether machines could beat humanity Moore had this to say: “Without humans there wouldn’t be machines. And at Trainline, we innovate with people at the heart.” 

The Rise of Data Science

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3.2 All Data Isn’t Equal

Steve Pinchuk, IBM’s worldwide lead for customer intel-ligence and revenue management, said that customers often talked about ‘big data’ as if all data was the same. However, there was a distinction to be made between structured data (e.g. from sales, purchasing points, customer behavior and so on) and unstructured data, which could include anything from weather forecasts to customer insights from social media, reviews, predic-tions about events and shifts in labor legislation.

Soft data gathered from reviews can directly impact the bottom line. As NH Hotels pointed out, monitoring competitors and benchmarking against customer reviews can increase a hotel’s pricing power.

They aren’t the only ones benefitting from the soft and social data. At Holiday Pirates, where only 7% of the traffic it drives is paid for, not a single penny has been spent in Google Ads – all of it is in social media marketing. Said Holiday Pirates, CEO, David Armstrong: “It’s easy to spend money in Google. You just have to top up an account and press a button – but that is not sustainable.”

Eurail a purely digital company that markets, sells and distributes European rail passes does not have big databases holding unstructured data. Eurail doesn’t yet do predictive analysis based on unstructured data, instead taking a more focused approach. “Data is big, its

3.1 Everybody Is Doing It

Whether the interest is in artificial intelligence, machine learning, chatbots, voice search or natural language processing, today everybody is doing ‘data’ in some form or other. However, the nature of the beast has changed or it has, at least, been given a new all-encompassing name – data science, a term that until three years ago did not exist.

To put this in perspective, when Mark Shilton joined Skyscanner six years ago he was one of two ‘business intelligence’ analysts delivering data reports. Today he heads a team of 23 data scientists. Meanwhile, at Booking.com there are 50 data scientists. It’s not stopping there, as both companies, and many others represented in Amsterdam, are actively hiring for the field.

The Three Skills of Data Scientists

In an ideal world companies are looking for mathematics and statistics, computer science and domain expertise (knowledge of the business). However, this is rare, said Shilton, who warned that people without mathematics and statistics should raise a red alert. At Booking.com, on the other hand, Zoeter looks for people who are “technically autonomous and commercially aware”.

The Top Three Questions from the Conference

How is everyone going to approach using legacy data once GDPR comes into effect? 13

How do you plan to train people in the field to use the data? Or do you plan to move to a more tool-driven decision process? 10

Does anyone know who has the most advanced chatbot in travel? 10

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New Data Regulation: A Big Issue

The General Data Protection Regulation (GDPR) is a law that strengthens and unifies data protection across all 28 EU countries. Among other things, it means that EU residents have control of their personal data and it increases the definition of ‘personal’ to include things like an IP address. People can ask for personal information relating to them to be deleted, and have to give explicit consent for data to be collected and used. The fines for non-compliance are up to EUR20 million or 4% of global turnover.

Implications on the new legislation were a hot topic in Amsterdam. But Ignacio Longarte, a strategic advisor on the digital value chain for multinational companies stressed that data legislation doesn’t just have to be cumbersome. In fact, patents and copyrights can add value to your company, and actually complying with GDPR should be part of wising up to a responsible approach to data management.

Top Data Tips

■ Communicate and build data into the company culture

When data is missing from an overall industry set, it’s important to communicate what the gaps are and what they might mean. According to Grintchenko, everybody should be 100% clear and on the same page as to what the gaps are and why they are there. Do this and the data can still be used.

Skyscanner’s Shilton agreed that if you can have a conversation about the limits and ranges of accuracy, then you can agree a model and get an idea of what risk is involved in running with it. “If we are looking at spending millions of euros on something then we will want to talk about having tighter ranges,” he said.

■ be transparent

Moderator Steven Pinchuk said that in his work in customer intelligence and revenue management at IBM, he’d found that a marketing person’s truth may be different to the RM professional because they are looking for different outcomes.

“I’ve been in meetings where we can have the same data source but different inferences. In these situations you have to be able to explain what you did with the data and defend why you did it,” Pinchuk said. “In an analytically driven company, you need to be able to explain your version of the truth or it could lead to chaos.”

■ Speak the same language

For Gopili, it’s crucial that data is embedded in every single department, and every vertical so that everybody is aligned. “We have to design common concepts, and have everyone speaking the same language. For example, what is a client, what is a session, a visitor, a sale,” Raoul said.

■ Question everything, including the maths, and think beyond the price

On a Day 2 RM session, Henrik Imhof, managing director of yield management and pricing at Sixt warned that brands should be careful when

3.3 In Search of Truth

Getting data into an organized, clean, coherent and usable state is no small feat, but it is something that data professionals are constantly striving for. Speaking on a data keynote at EyeforTravel’s recent Amsterdam event, Andrei Grintchenko, head of business intelligence at IATA, an association that supports global aviation standards said: “Having fragmented data from multiple sources, or the same data from multiple sources, is your worst nightmare.”

Some of the data-driven tips that emerged in Amsterdam included:

everywhere, but you need it small to make decisions,” she said.

In one of many occasions where the use case for third-party technology was highlighted. TTC, for one, uses Feefo to check authenticity of reviews, because of the impact on conversion rates. Said Christian: “Trips that have reviews are twice as likely to be booked. And if a positive review is near the book button, 30% more people book.”

Echoing this point on another panel, Raj Dhawan, chief technology officer at Contiki, said: “In-house you may not have all capabilities but you may be able to leverage third parties”.

THE RISE O

F DATA

SCIENCE

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interpreting data and the maths behind it. Response rates to campaigns, he said, did not always directly translate to conversion rates, and nor did conversions directly translate to price elasticity. The good news, however, is that both could be analyzed and predicted with machine learning techniques and data mining that allow teams to look beyond the surface. On the issue of pricing, Gian Caprini, the head of digital marketing at Expedia Affiliate Network, said the way to succeed in the coming year is by “offering a clear value proposition beyond the price”.

■ Create one overarching data analytics organization

Creating one unit for analytics people from all over the business silos can lead to “huge cross-pollina-tion”. Analytics becomes more believable, according to Pinchuk, “because it didn’t just somehow come out of marketing”. It also helps to consolidate costs, gives these “tortured data serfs” a career path, and crystalizes data within an organization to serve internal customers.

■ Learn from other industries

IATA recommended that travel look to other industries, in particular healthcare, as it collects masses of sensitive data, but somehow manages to share it for the greater good. Neil Roberts, head of digital, Eurostar, pointed out that if brands could share data they could make “an end-to-end itinerary piece,” which there is a real need for amongst travellers “but it doesn’t exist yet - every-one’s trying to own the customer and not sharing data.” While many view API partnerships as hugely important to more collaboration and sharing, Andrei Grintchenko, head of business intelligence at IATA, wanted to make this point: “You are still looking at data quality, reliability and a willingness of organizations to release it. To my mind, APIs are secondary to the data subjects that have to be resolved first.”

■ Find your own version of truth

Every organization is different, and needs to assess its own degree of maturity before deciding whether to democratize access to data or stick with static reporting.