We live in the age of the customer, an era in which we expect to get what we want, when we want it and in a manner of our choosing. Never before have consumers been so empowered. For this, we have much to thank global behemoths such as Amazon and Netflix – they not only appear to know what we need but are particularly good at telling us before we even know we want it.
In contrast, the rail industry has historically been relatively unsophisticated in its digital interactions with its customers. Communication of operational data such as delays, cancellations and other disruption is seen as an obligation rather than an opportunity.
It is unbelievable that in today’s digital age, train and station operators still put up information posters to inform passengers of upcoming travel disruption. Passengers now demand sophisticated, accurate, up-to-date information on-the-go through any channel. Train operators need to live up to the high communications expectations fostered in other industries, or face ever increasing dissatisfaction.
Customer frustration with poor communication often comes to the fore when trying to find information about delays and diversions to services. Twitter has become the place for train operators to broadcast disruption information: all 23 British train operating companies run Twitter accounts, and collectively they have more than 3 million followers who use the platform to find out information about their services.
Yet neither the transport operators nor Twitter make any effort to sort or prioritise information so that it’s relevant to the individual. Owners and operators have historically relied on mass broadcast techniques to communicate with the people who use their networks but as the irrelevant information overload continues to grow, so does customer disengagement.
The core issue with the poor passenger communication in the rail industry is relatively simple: thanks to the syndication of open transport data to third party developers and Mobility-as-a-Service (MaaS) providers, the basic train operator-passenger relationship, that is so essential for communication, has been usurped. Put simply, more often than not, train operators have no idea who is travelling on their trains and certainly no ability to communicate directly with them. A mass broadcast over Twitter or Facebook is considered satisfactory. But this scattergun ‘hit-or-miss’ approach misses more often than it hits.
A quick Google search for “passenger communication” pulls up a series of web pages looking predominantly at how to improve Wi-Fi on trains, including a now-closed Department for Transport consultation. There is very little relating to direct operator to passenger communication, when in reality operators simply need to be asking the straightforward question: “How do we get the right information to the right people at the right time?”
The answer is personalised real-time information for the individual traveller, delivered proactively through a “push” rather than “pull” application. It is, for example, an operator talking directly to everyone on a specific service or even just to the passengers travelling between two stations. By providing relevant information direct to individual passengers before they feel the need to search for it themselves, operators would be able to reduce the effects of disruption before they even take hold. Passengers on delayed or cancelled trains could be re-routed mid-journey. It is the highly-targeted personal approach which not only vastly improves the customer experience, but also puts operators on the front foot when it comes to improving network efficiency.
An increasing number of technology platforms is being developed to solve this challenge of personalised customer communications, but the required technology already exists in other sectors and needs to be embraced by the rail industry. Looking back at Amazon and Netflix, in order to deliver their unparalleled level of customer service, they do one thing extremely well: they understand the value of human behavioural data. The data generated through how customers interact with information, when they interact, and even how long they take to make a decision based on the information presented to them, is incredibly valuable.
This sort of data has been used in online advertising technology for many years and underpins the ability to both understand and engage more meaningfully with the customer. At an individual level in the rail sector, this data can help to build a unique profile for every passenger, and ultimately deliver an enhanced personalised customer experience. Using this profile, operators can embark on highly targeted behavioural change programmes aligned to overall strategic aims and operational reality.
Zipabout is the only data platform available globally which can facilitate personalised two-way communication. It was initially developed to manage passenger demand for Transport for London during the London 2012 Olympic Games. Based on technology developed in the online advertising sector, it combines the increasing proliferation in available big data with advanced algorithms, unprecedented real-time processing capability, serverless computing through a partnership with Amazon Web Services and NoSQL/Graph databases.
In practice, the platform consumes live streams of operational, environmental and passenger-level behavioural data across an entire transport network. This data is processed, normalised and made available to operators both in real-time and historically. It uses advanced machine learning and artificial intelligence (AI) techniques to identify data patterns, generating unique passenger and service level insight as well as making predictions around future performance of the network and its effect on customer experience.
Unlike other platforms, which simply repackage available open data, the Zipabout platform provides a dynamic communications channel which allows operators to engage with passengers at a one-on-one level. Using a complex system of behavioural triggers based on the aggregated data, communications can be automatically initiated taking into account a range of factors such as travel patterns, disruption, behaviour or service performance.
We have just started to work with ScotRail on a 12-month project to personalise disruption information for their passengers via Twitter, based on live condition-based mapping and sophisticated communication. Covering most of Scotland and delivered by ScotRail using the Zipabout platform integrated into its existing system, the project will identify upcoming disruption thanks to AI analysis of real-time operational data, and tweet or directly message individual travellers who may be affected, eradicating the need for mass broadcast messages.
As the Zipabout platform consumes data from sources beyond solely the rail network, this ScotRail project is truly multi-modal. ScotRail will be able to identify live problems anywhere during a passenger journey, including for example disruption on the roads getting to and from a station, and can send a direct message warning of disruption and providing an alternative journey plan.
Zipabout is also collaborating with Britain’s passenger watchdog Transport Focus on a customer experience application programming interface (API) which will enable transport operators and other stakeholders to collect highly-targeted passenger feedback in real-time. The Zipabout platform, which is being integrated with a number of customer-facing apps and websites as part of a pilot programme starting in late 2017, will enable the delivery of precisely-targeted micro-surveys to passengers who have been affected by specific types of disruption. For example, the API will allow customised surveys to be delivered only to passengers affected by delays or cancellations, or travelling on a specific train or bus service. This two-way communications channel will generate a unique insight into passenger experience across the transport network. Clearly the ability to target information to individual or groups of passengers will have significant benefits to both operators and their passengers, and will help to make rail a more user-friendly mode of transport.