Ai Editorial: Seamlessness and relevance - what every interaction should reflect

First published on 23rd March, 2017

Ai Editorial: Airlines can attempt to serve passengers in two ways – pre-empt what a passenger might opt for or being ready for the next interaction after analyzing every digital click or interaction via all touchpoints, writes Ai’s Ritesh Gupta.

Making the most of every interaction is what every brand strives to achieve.

An airline may serve the passenger in an apt manner, say at the airport, but if, as an enterprise, there is no consistency in serving the traveller- say a question you have asked via Twitter after collecting your boarding pass and the staff at the gate isn’t aware of it - then it is bound to fall short in terms of seamlessness or relevance.

So connecting the dots between interactions so that it is available in the form of actionable data and blending it the context, location etc. in real-time is something that airlines need to target.

Why?

When the customer has means to ask a question related to their journey, then airlines better be prepared for it. It’s that simple.

In fact, optimization of every interaction is not just about travel. A customer is a part of new experiences that are all about seamlessness and relevance in every sphere of life. So when users are being served by a retail app or a cab hailing app the way they want, then why can’t the airline chosen responds in the same way.

Being prepared

What airlines can do can fall in two categories: proactive and reactive, and in both cases improving upon the functionalities of the touchpoints, including apps, and responding to a request, question etc. in the best possible manner.

- Improving every touchpoint in a proactive manner

Easier said than done, but airlines need to look at the way an app like Uber simplifies the choice of cars, the connection time to the next cab, helping one to visualize where the cab is on the map, the estimated price for the journey, one-click answer to having a conversation with the driver or no clicks at all for payments once you share the details.

The same way airlines can refine their own trip planning, post buying and the day of journey functionalities.

Relevant message/ communication: Digital enterprises are looking at data that tells about “now” or the moment in context. Companies like Amazon are improving upon their offering for mobile app analytics, and supporting real-time analytics. Such insights are helping organizations to target segments from a variety of different data sources, send targeted notifications with personalized messages etc. If an airline can understand the intent, they can send relevant messages. For instance, if a family is looking for a flight to Paris and searches for activity related to Disneyland, Roland Garros tennis etc., then how should airlines gear up for retargeting? Rather than displaying same ads on Facebook or any website, shouldn’t the airline send any useful content or offer around the activity searched for? Yes, if an experience is being “sold”, it would be much better. Since the current shopping cart and the path the customer took to get there can tell you far more about what they do next than any number of prior bookings, do work on new ways to be relevant with notifications, ads and messaging. Airlines can look at crafting a recommendation algorithm, encompassing various stages of travellers’ journey including real-time travel disruption management. Be it for accurately predicting hidden interests, evaluating minute behavioral changes or working out recommendations for various contexts, a proactive approach can assist travellers, and even step up revenue generation.

Analytics: Airlines need to observe the usage of their digital assets, and based on the past and real-time usage, one can come up with predictions about future events.

As SAS points out, predictive analytics and experience “has a lot in common”. In one of its white paper, SAS states, “While experience is important in dealing with uncertainty and should go hand in hand with predictive analytics, the statistical calculations that goes into predictive analytics – has two advantages: the amount of observations (data) that can go into the calculations to validate assumed relations or maybe even reveal hidden relations, and the statistical calculations offer an answer that is more likely to be bias-free – both in terms of the relationship, but also the individual prediction.”

- Keeping track of every interaction

What triggers a search or a question when a user interacts via any touchpoint needs to be captured and the sum of all interactions needs to be analyzed for the future.

There are certain experiences that are intrinsic to airlines as a product – for instance, seating in an aircraft. How would a family of four like to sit in an aircraft, which has either rows of two seats or three seats? Would they prefer to pay for certain seats? Airlines need to find ways to understanding the type of travel, what sort of features or services a traveller is seeking and accordingly, record their preferences. Now if a conversation takes place between passenger at the airport and the airline staff, then how about analyzing the same without any privacy issues? Today, as IBM asserts, technology is in place to “capture the audio of the conversations and run speech-to-text and tone analysis directly on the device, thus completely avoiding sending any sensitive data to the cloud”. Essentially what is being done is “tone analysis” and this can be equated with attributes like happiness, sadness or anger. Such insights can go a long way in coming up with a relevant recommendation when the passenger interacts or attempts a booking next time.

Gain an insight into intriguing issues at Ai’s 11th edition of Ancillary Merchandising Conference in Spain this year. 

Date: 25 Apr 2017 - 27 Apr 2017; Location: Mallorca, Spain 

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