“What is the real value of data?”
The passage of data between a company and its audience is shaping customer relationships and redefining the very nature of business. In this whitepaper, we dive into data landscapes encountered in the European travel industry, and answer the question often asked by our clients: what is the value of our available or attainable data, and how can it attract revenue and sharpen our business strategies?
Answer honestly, now: how much money would you be willing to pay to gain full control of your private data - from your search history, lunch orders, health records, and jogging route, to every single transaction you’ve ever made? Perhaps a better question would be: how much money would you expect to earn by selling this data to the companies that need it? What if you sold it over the dark web? Can you actually measure how much valuable information you create with every move you make online?
As a company working with businesses to realise a vision of their 5 to 10-year future, we’re continually exploring our clients’ questions about data and its infinite uses. Where to get it, how to manage it, what to do with it, with whom to share it... The questions keep evolving, yet one fact remains certain: data is central to the success of any product or service within the markets of today and tomorrow. With continuous advancement of and increased accessibility to mobile technologies across the globe, we’re observing a relentless increase in what customers expect from companies with whom they choose to engage. Data-driven decisions are the key to meeting – and exceeding – these demands.
The good news is that vast amounts of data are already there for the taking, and younger generations in particular are open to sharing their personal information in return for a more efficient and personalised customer experience. A UK study found that 75% of consumers aged 16-24 consented to sharing their data with brands, compared to only 45% of those aged 55 and over. However, a common challenge faced by businesses is a lack of adequate infrastructure, culture and/or analytics required to transform such data into meaningful results. Even more limiting is the lack of a data purpose that’s derived from companies’ mission statements and aligned with their core values. An executive survey by NewVantage in 2021 found that although 99% of companies are investing in big data, only 30% reported having a well-defined data strategy, and even less (24.4%) have fostered a data culture across the firm.
What’s the use of data – regardless of how much of it you may have – if its presence has no purpose? And how can its value and purpose be found?
Data collection often starts with the customer’s first step, or rather their first encounter with a company online. Whether it’s booking a flight or train ticket from a website, reserving a parking space through an app, or tapping through retail offers on social media, new and returning customers provide data to companies using digital tools that in turn enable them to streamline their user experience, ultimately saving effort and time.
In our work with companies in the travel and mobility sector, we’ve noted countless touch points for data collection. Take a traveller passing through an airport, for example:
· Security cameras and Bluetooth sensors track their movement and dwell times
· Transactions from duty free, retailers and food & beverage (F&B) outlets record their shopping and gastronomical preferences
· Parking reservations combined with flight booking details give insight into travelling frequency and behavior
Once customers consent to share their personal data with a company – while joining a Wi-Fi network, downloading an app, or signing into a website via their social media accounts – a profile can be created to which their actions and preferences can be matched. This allows companies to build dynamic customer relationship management (CRM) strategies, paving the way for business decisions to become supported by a realistic, detailed picture of customer behaviour and needs. Exhibit 1 below outlines how this is realised at Heathrow Airport though partnership with database marketing company Acxiom.
We’re all aware that the value of data will keep evolving as newer, more sophisticated tools for collection and analysis are developed. Yet even now, it’s clear that the potential of a company’s data cannot be fully realised through infrastructure and analytics alone; a culture of data sharing must be embedded in a company’s ethos and applied to its collaboration with relevant partners in the field. Cooperation within the multi-faceted structure of mobility service providers such as airports proves essential, as it provides a space for data silos to be stitched together like pieces in a puzzle, creating a holistic picture that holds more value than the sum of its parts. While understanding the need for data security and privacy concerns, we also acknowledge that without effective cooperation between colleagues and teams, as well as clearly defined data sharing processes, knowledge can stagnate, and opportunities are missed.
To sum it up so far: a clear data purpose in line with a company’s mission statement, followed by the setup of solid data infrastructure, robust analytics, and the right company culture, will enable the optimisation of commercial and operational processes... resulting in increased revenue for the company and a happier, smoother experience for its clients.
Across Europe and beyond, we looked into how data-driven decision making is already reaping benefits for businesses and customers alike. Focusing on travel and mobility within the region, we delved into best cases from leaders in the field. So what’s being done so far?
Exhibit 2 provides an overview of where and how we observed data monetisation being implemented by European airports. It comes as no surprise that most initiatives focus on personalisation of the customer experience, with the goal of increasing revenue through already existing channels such as parking, duty free, retail, and F&B. The general strategy seems simple enough: collect data about customers’ behaviour along their travels, combine it with sales data from retailers, F&B outlets and parking services, and use this to inform and develop CRM.
To mention just a few airports leading by example:
· Media spaces are designed for prime locations based on dwell times at Frankfurt, while passenger flow data informs design of duty free spaces at Vienna;
· Zurich provides dynamic, automated pricing for parking reservations, and collects usage data for predictive analytics to maximise parking space capacity;
· Dublin, Barcelona, and Milan foster a personal connection with each passenger by distributing targeted offers and rewards through apps and social media at various points along the customer journey;
and the list of successes goes on…
Quantifying the monetary value of data is by far not a simple endeavour, as it turns out. As summarised in Exhibit 3, a glance at pricings in the US shows that not all data is created equal: the type of data, as well as the population group, has a significant effect on its value. This effect is cumulative, meaning that the more layers of information on the same individual are available, the more valuable the data becomes. This even includes details on major life events, like getting married or buying a house, which usually bring with them a specific set of needs onto which targeted ads can be applied.
While most data used by companies is collected from users through perfectly legitimate means, taking a look at the prices of data obtained under less auspicious conditions provides useful insight on its actual value in today’s world. An assessment in the US reported that the main pricing factor is the type of information being collected, with health records being valued much more than other types of data, since the former often include a more complete collection of a patient’s identity and personal history. When it comes to ethnicity, age and income, the value of user data from a particular demographic group seems inversely proportional to the group’s frequency: the smaller the population, the higher the price.
Interestingly, data from very low earners (less than $10,000 annually), priced at $0.10 per user, proves to be more valuable than data from users earning up to $120,000, priced at just $0.04. Low earners are often students who despite having a limited income tend to be carefree shoppers and frequently discuss products online. Data from users earning over $120,000 annually - who have less financial stress so can shop more freely, and actually have the means to make purchases, is by far the most valuable at $0.33 per user.
This pecking order is based on a system known as value-oriented pricing, where the cost of a dataset is determined by the potential revenue generated from it. Another approach to data valuation would be cost-based pricing, where a dataset is simply sold at a mark-up from the cost required in obtaining it in the first place. So what if users could decide on the price of their own data? The Technology Policy Institute in the US researched this question in 2020[3] by studying the habits of people in several countries and found that:
· German users would want Facebook to fork out around $8 a month for sharing their contact details, while US users only asked for $3.50;
· Users would demand a monthly $8.44 to share bank balance details, $7.56 to share their fingerprint, $6.05 to read their texts, and $5.80 to share cash withdrawal data;
· Location data was deemed to be worth only $1.82 per month to share location data, and users seemed happy to be sent advertisements via text messages for free.
Although there’s no universally accepted formula to valuate our personal data, Google's ad revenue serves as a good indicator. In 2001, each user generated €1.71 worth of advertising revenue for Google. By 2021, this value had risen to €30.74 per user - an increase of almost 1,800%. Where will things will stand by 2031?
We might not need to find that out just yet, but keeping the future of data in mind is crucial for companies to truly understand the untapped potential of the resources currently at hand for optimising customer experience, maximising existing business opportunities and creating new ones.
· Data stored by businesses and generated by their clients holds immense value that can only be realised in the presence of adequate infrastructure and analytics, a culture of cooperation, and a clear data purpose aligned with business goals.
· Combining movement, usage and transaction data with digital user profiles enables companies to improve CRM strategies and processes, creating a virtuous cycle of increased customer engagement that in turn generates more data for company use.
· Data monetisation among European airports is currently focused on personalisation of the customer experience, which includes the use of targeted offers, dynamic pricing, and rewards systems to increase revenue from parking, duty free, retail and F&B.
· The actual price of user data varies greatly and depends on the type of information being collected, the level of detail in each dataset, and the relevant demographic group; for example, health data in the US is the most expensive as it often includes a complete profile and history of each individual.
· Value-oriented pricing determines the cost of a user dataset based on the potential revenue generated from it; the fact that ad revenue for each Google user increased by 1,800% from 2001 to 2021 sheds light on the sheer scale of revenue possibilities for businesses through data monetisation, now and in the near future.
