WIPRO CONSULTING SERVICES The New Airline CEM Strategy: Building Aspirational Journeys for Each Customer www.wipro.com/consulting
The New Airline CEM Strategy: Building Aspirational Journeys for Each Customer By Paul Bennett How is your customer experience management strategy going? Do your customers feel like you really know them? Do they feel you can respond to them appropriately and proactively target their needs? Like most businesses, the airline industry has been striving to provide an individual customer experience. But airlines are behind the curve and customers are losing patience. They want the immediacy and relevance they ve come to expect from other businesses, such as online retailing. When you make a purchase from an online retailer you anticipate the company will suggest a similar item or offer a special deal that matches your interests. But while the specific analytics behind this model work well for retailing, they aren t suitable for airlines. In retailing, each time you shop, your purchase is matched to millions of purchases made by other people within your cohort large groups of consumers with similar demographics and purchasing patterns. That means the recommendations you receive are a good guess rather than truly personalized. But in contrast to buying a book or a set of cookware, travel purchase decisions are more nuanced. In addition to the emotional component of the decision, there s also the timing, the destination options, coach versus business, previous travel experiences, food preferences, travel companions, and even the influence of friends, family members, and world events. Airlines pushing out generic messages based on cohort groups can expect customers to dismiss such outreach as so much noise. Certainly airlines are collecting all the right data, including travel history, frequent flyer redemptions, preferred alliance partners, and ancillary purchases such as car rentals and hotels. So what s needed is a different set of analytics to harness this data to create an individual profile of each customer a profile that addresses and enhances the complex decisions that go into making airline travel plans. Advances in big data computing have made such analytics possible. For more than a year we have been working with Opera Solutions, whose technology identifies patterns and anomalies in big data that can be combined and cross-referenced to predict future customer behavior based on actual behavior. It does this by identifying and classifying data as strong signals and faint 1
signals. For instance, the number of leisure trips taken to a beach resort would result in a strong signal, while destinations where a customer stays over a weekend but never books a hotel or car would be a faint signal, perhaps indicating that the customer is staying with friends or relatives. Such analytics have been in use for 18 months at a major airline, during which time the technology has tracked approximately 15 million customers and billions of customer transactions across most touch points, including real-time website interactions. Thus far, the analytics have helped the airline increase revenue as much as six times the cost of the technology investment, and positive customer perceptions are on the rise. Building Customer DNA As previously noted, most approaches to customer analytics mainly rely on demographics, and sometimes psychographics, for clustering customers into marketing groups. For airlines, the variables are usually age, salary, gender, home base, and frequent flier tier. Some also include previous purchase history to calculate a customer value score. Various offers and Customer s behavioral map reflects their true needs, likes, dislikes, inertia - to enable actions not just insights City Propensity Trailing/ Next 12 Month P & L Ancillary Propensity Pre- Calculations and New s & Signals > Inputs > Data & Events Price Sensitivity Travel Wallet Logitudinal View of Each Customer Offer Participation Health Competitive Prices and Deals Geo Location No-Show/ Cancel Frequency & Seasonality Ratings/ Influencers Revenue Leakage Local Macro Economic Conditions Social/ Familial Affiliations 1000 s of Signals for Each Customer to Power Frontline Applications New technologies collect individual customer data, including geographic location, influencers, and ticket purchases to specific destinations all of which identify their actual interests and needs and convert them into identifiable signals that lead to actionable, targeted marketing strategies you know will appeal to the customer. 2
campaigns are then directed to each target group, and are often ignored. Using a different approach, you can instead follow the actual behavior of each customer as it happens, gradually establishing an individual DNA profile for each customer based on the strong and faint signals identified by the analytics. With this DNA you can create an aspirational journey to predict the types of offers each customer is likely to purchase and, more importantly, when. Plus, for each relevant touch point in your organization you can display the next best offer or action that would directly appeal to that customer. Since all of this is customized to the airline, the signal models are different for each business. This is a radically different approach for airlines, not to mention other industries. Based on the understanding you develop with your customers, you will know the best action to take with them when something goes wrong This model of identifying signals can also be applied to service recovery situations. Based on the understanding you develop with your customers, you will know the best action to take with them when something goes wrong say a delayed flight or lost baggage. In other words, this analytic technology can be used not only to provide insights, as helpful as that is, but also to provide useful, actionable recommendations. So how does this look for an airline? Here are some scenarios: A customer books a flight to Johannesburg and the data tells you she s done this four times previously, staying over weekends. Since the customer didn t book a hotel or rental car the previous times, the algorithm foregoes a car or hotel offer and instead offers additional travel discounts for Johannesburg that the customer or her family and friends can use. A flight is disrupted and all passengers must be reaccommodated to another, smaller aircraft. Who do you help first? If you have a high-value customer who happens to be sitting in economy, the technology can identify that customer with a high lifetime value score who you can help quickly with a first-class or business seat. The technology identifies a customer who will be upgraded from Gold to Platinum level on his next trip. With this information the check-in agent can surprise and delight him on this trip by arranging for him to be escorted to the Platinum lounge. You can identify customers who are likely to defect based on an incident or history of incidents and proactively make an offer to them to incentivize loyalty. You can enhance revenues from existing frequent flier passengers through booking hotel rooms, rental cars, and other amenities; adding one or two trips with the airline per year that might have gone to another airline; and by upgrading bookings from economy to business or first class. At the airline mentioned previously, the initial focus was on optimized cross-sell, up-sell, and new-sell on their known fliers. Since then, individual customer DNA has uncovered opportunities in customer service recovery, disruption management, and even a bottom-up approach to revenue management. Personalized customer content can now be observed across personalized offers to customers while 3
they re on the website, as well as via email and, soon, additional touch points like mobile devices. The airline can also send enriched customer data to a flight s onboard crew via an ipad to assist customers and anticipate needs in flight. Getting Started Clearly, you don t just jump into this. You need to identify a problem requiring fixing, and develop a proof of concept to address it. It could be stalled customer growth or lack of uptake in ancillary revenue offers. Then you decide on the signals and groups of signals that could address the problem and apply the analytics to the available transaction data to generate recommended actions. The actions can then be applied to a customer channel or multiple channels, such as the contact center, social media, your website, your mobile app, or any combination of these. At this point you can build on the types of offers and service recoveries you want to deploy, increasing or finessing them as you learn to use more and more signals in these models. You ll need to get your employees on board, empowering them to make decisions at the front line based on what the data recommends and company policy. This naturally raises a fundamental question about your business in the context of customer experience: What is your brand promise? Once you decide on that, you must create a foundation for how you exhibit this consistently and at every touch point. Travel, whether for business or leisure, is a personal activity, and customers expect to have their loyalty earned. By moving beyond the standard retail model and digging deeper and more individually into your customers actions and preferences based on actual behavior, you can become a true travel concierge. By moving beyond the standard retail model and digging deeper and more individually into your customers actions and preferences based on actual behavior, you can become a true travel concierge A proof of concept project can be achieved in a two-month period. As you go deeper and build a single view of the customer not just from a data or transaction perspective but from a true behavioral understanding you ll take a longerterm approach across the enterprise. Welcome Aboard A more personalized, relevant approach will immediately catch your customers attention. But the technology will be just one piece of your new approach. You ll also need to build in the obvious change management mostly around customer touch points like service desks, reservation offices, contact centers, and on-board crew. You ll anticipate what they want and need, determine how best to fix a problem they ve encountered, and identify when and where to provide them with additional service and offers. At a time of intense competition, all these efforts to surprise and delight lead to increased revenues. As you add more channels to service customers, you will enhance their experience at little additional cost. These are now the table stakes for full-service carriers. Paul Bennett is Consulting Partner, Travel & Transport Industry, at Wipro Consulting Services. He is based in North Sydney, Australia, and may be reached at paul.bennett@wipro.com. 4
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