Ai Editorial: Learning from "data stories" of HK Express Airways, Finnair and JetBlue

First Published on 26th March, 2018

Ai Editorial: It is not easy for an organization like airline to collect data, unify it to work on a profile and "operationalize" into actionable data. But airlines are moving in the right direction, writes Ai's Ritesh Gupta

"If you are just looking at data, then you aren’t really doing anything. The problem is everyone sees data and don’t really take action," this statement from a senior executive from Hong Kong Express Airways is an apt answer to why airlines tend to lag behind in the race of data-driven decision-making.

One of the biggest gains that has emerged from what the likes of JetBlue, Hong Kong Express Airways, Finnair etc. have done over the last 18-24 months is their decision to start, be it for loyalty or customer service. Here are few examples:

Hong Kong Express Airways’ reward-U program: This lifestyle and loyalty program, launched in April 2016, had over 1 million members in 16 months. Serving a growing segment of Millennials, the program has been working on a plan to club members according to their preferences, behavior etc. and forming different tribes. The concept of “tribes” is based on overall activity, for instance, travel, retail, food etc. and a member can be in multiple tribes at any time base on a minimal level of activity. The team has been analyzing data and this new initiative is a direct result of spending pattern that the team has been observing in terms of consumption and activity. The team also asserts that they have been getting a picture of what people are doing, and the association with a low-cost airline doesn’t mean that the members are "low spenders". They are high spenders. They might save money on airfares, but they can spend (relatively lot more) money on accommodation and so forth. Their retailing activities are not low-cost either, can be termed as high-spend. They are bargain hungry but not averse to spending, too.  

The airline decided to take specific learnings from data, chose to act on it, and then observed what happened.  "We try to experiment from what we are seeing, try to stimulate activity or some type of behavior. Rather than accumulating data in huge amounts, we are taking snapshots and acting on it," shared a senior executive from the airline.

JetBlue's focus on customer service: JetBlue today is able to aggregate a single view of the customer (on service channels). So all interactions (say featuring a JetBlue account on Whatsapp, Facebook Messenger, Instagram etc. or an interaction at the airport or with a call centre executive) are captured and aggregated into a single conversational view of a customer. The airline is looking at adding information to the “profile” of a traveller. Their platform sits on the top of a CRM and augments customer service. It can aggregate data on its own too – relating a profile’s social media handle, email id, phone number etc. By capturing data and maintaining profiles, any organization can move from mass personalisation to macro personalisation to micro personalisation, and eventually to analytics-driven personalisation. 

Finnair's journey of personalisation: Finnair also has been on the path of moving from rules-driven personalisation to an analytics-driven phase. The team is clear that every time passengers interact with the airline, the team ends up learning more about them. The focus is on behavioural profiling, demographics and personal data, as well as historical and preference data. The airline has been displaying targeted content based on segmentation analysis, dynamic content for the upcoming flight (ancillary up-sell) etc.

Key learnings:

• Do remember personalisation is a never ending story, there is a need to start somewhere, and don’t try to include all the touchpoints from the beginning.

• Be ready for the grind, prepare in an earnest manner: The way airlines are handling data today it is not easy to take information out of that, process it, store it in a way for serving a future purpose/ running analytics on that. That’s an important aspect, plus can be a costly affair too. So that’s where data cleansing, deduplication, integration, pool management etc. comes into play. Overall, airlines should be able to integrate, cleanse, standardize and dedupe data to create a single view of the traveller by merging all of the available online and offline data. Curation is equally important. It could be about blending – demographic information, online behavior (website visit, purchase etc.), in-app behavior (sessions, last opened etc.), email interactions, social media activity and offline interactions.“For any airline to achieve personalisation at scale – the success lies in being able to unite all of their data,” shared an executive. “At some point, the issue of increased complexity would arise, but that’s where involving data science and decision making algorithms would assist.” As highlighted by Boxever, data-driven organisations ensure their customer data collection fits in with constantly evolving behavior based on their context. So if an airline doesn’t end up connecting the dots and act on the context of a situation, then it would end up missing out on optimizing the experience.

• Also, move towards “operationalising” actionable data. “It is imperative to interact with passengers across channels from one core hub and having an ability to answer swiftly and aptly in context,” shared a source. Airlines also need to plan for how to set up rules and decisions for all channels, so even if starting with one channel – so say offer or deal for one channel, how the same can be established for all digital plus say offline channel e. g. boarding gate at the airport.

• Delivery of content: How would an airline deliver dynamic content, what sort of architecture is needed for the same? Also, what would it take to adopt omni-channel approach to content management? The content ideally needs to be crafted once and the organization should be able to reuse it on multiple digital properties without the need for duplication. Explore the pros and cons of coupled versus decoupled web content management architecture (for instance, in case of coupled architecture while the initial setting up is simple, scaling up is one issue. As for headless CMS can result in freedom while finalizing on a front-end user interface technology say for an app, on the flip side the CX or customer experience ends up being decoupled as well.  This would limit the ability to personalize the overall experience).  

• Don’t rush to eradicate the problem of silos. Be careful about pushing for a sudden change. People aren’t going to be responsive to “new jobs, new skills, and new people to work with” resulting from drastic steps. Don’t risk the continuity of teams.

Hear from experts at the upcoming Ancillary Merchandising Conference, to be held in Edinburgh, Scotland this year (9-11 April, 2018).

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