First Published on 1st January, 2018
Ai Editorial: The prowess of data in uplifting the performance of loyalty programs is increasingly coming to the fore, be it for fostering a positive emotional connection with members or working out a viable financial model, writes Ai’s Ritesh Gupta
For airlines, any opportunity that can improve the performance of their FFPs needs to be grabbed since the lure of flying for free, an upgrade or making the most of loyalty currency means travellers tend to have high expectations from their FFPs. In order to meet these expectations, airlines need to count on data. We look at some of the critical areas, especially considering the fact travel marketers acknowledge the challenges associated with personalizing offers, content, and experiences based on data:
1. Preparing for digital API economy: Airlines aren’t agile enough to embrace change. But sticking to this approach isn’t going to help, as digital API economy will not make an exception for airlines. Imagine, a loyal traveller interacting via a chabot on Facebook or WeChat, and the preferences of the same traveller along with all sorts of data – loyalty, merchandising, fare, schedule, availability etc. being combined to work out the best possible set of recommendations. The more data you will have and the more systems you will have in your digital ecosystem, the better proposition you will have for your customers. Also, other than 3rd party ecosystems, airlines also need to dig deeper into their own platform strategy, because such economy works through a platform economy model. In a recent interview with Ai, Evert de Boer, Partner at FFP Investment and Advisory, pointed out that akin to the characteristics of digital disruptors, such as Uber and Airbnb, FFPs, too, don’t own the physical assets and are in a position to capitalize on data analytics and predictive modelling based on rich datasets that such programs have worked out. “Typically operating in a digital environment, (FFPs) it is a very agile business (and in comparison far more agile than a typical airlines business),” he said.
All of this is extreme importance as there will be no single customer journey. So in order to build affiliation, the loyalty programs need to be a part of the connected world.
Specialists also point out that organizational structure needs to be in place for various stages of the digital strategy – right from defining digital transformation mission to finalizing priorities to implementing them, and then also assessing the role of a digital business unit that eventually pave way for innovative offerings. So airlines need to evaluate areas such as structure, leadership, talent, operating model etc. to succeed as digital enterprises and in turn foster loyalty.
2. Reimagining loyalty with data: Data strategy is of no use if airlines can’t act on it to offer value to members or for competitive advantage. “We take specific learnings and then we act on it, and then observe (what happens). The problem is everyone sees data and don’t really take action. We try to experiment from what we are seeing, try to stimulate activity or some type of behavior,” says Hong Kong Express Airways’ reward-U program CEO Steven Greenway.
Here are few use cases:
· Offering value: Hong Kong Express Airways is working on the concept of “Tribes”, 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. This is scheduled for Q1, 2018. Tribes is about recognizing your everyday spending and everyday activity patterns. So if a user prefers to go out, they could be a part of wining and dining tribe. When combined with some of the existing activities such as relevant and personalized loyalty communications, this can result in strong engagement.
· Customer acquisition: Loyalty data can help in overcoming generalized assumptions. Blending data from CRM programs and other sources and integrating it with a loyalty solution can help in understanding customers. According to Merkle, organizations can dig deep to assess the profiles of their “best customers”, and then build on it further via data-driven look-alike modeling. So by partnering with 3rd party ecosystems or other companies, airlines can sharpen their customer acquisition based on real customer attributes.
3. Capitalizing on prowess of mobile devices: Travel companies need to capitalize on contextual signals that a device like a smartphone offers, and blend it with attributes or data available about a loyalty program member for them to avail an offer or even enable them to plan or book a trip. For example, a traveller tends to book in specific months and going by previous trip details (social context, price, destination etc.), how about an offer or a reward with all loyalty status details or possibilities of using the currency? In fact, the option to be rewarded from everyday purchases has opened up the realms of the FFP even to the average or infrequent traveller, how about incorporating traits of one's lifestyle and even coming up with a relevant content and deal? So, for instance, a co-brand card is used for a specific event, such as tickets for a ballet concert. How about considering the same and offering a similar ticket in a new destination? Interacting with a known traveller and better even if one can predict their needs, it would be incredibly powerful when it comes to building loyalty. It is imperative to assess how and where travellers expect to be engaged on their own terms; as they are hardly disconnect from their personal device such as mobile. So airlines need to shift loyalty rewards and experiences to smartphones, digital channels and social platforms.
4. Data and financial model: Behavorial and demographic segmentation, spend-level analysis etc. all have a role to play in working out the financial model of the program. And with better data, this can only sharpen the viability and profitability analysis. The model design depends upon various factors, and the sort of data available is one of them. As Merkle points out, airlines or loyalty team can feature passenger segmentation from custom data to study the impact that various customer segments have on four main summary metrics – enrollment, revenue, cost and profitability. Overall, a deeper study of member behavior can one to precisely assess how members’ accrual, redemption and engagement would change as the terms of the loyalty program get amended.
5. Data and redemption: Retailers are relying on data analytics techniques to evaluate rewards. Similarly, airlines can also study the efficacy of redemption options via a statistical experimentation technique (data scientists alert that a wrong group of travellers can also result in sampling bias). Plus, analyze the effectiveness of each reward and figure out the incremental revenue as well. Then also further study behavior before and after the redemption activity.
Other than working on simple earn and burn policies, paving way for fast and frictionless redemption experience and offer instant, relevant, contextual options for redemption, airlines need to gear up for latest developments in the arena of data, analytics, cloud, APIs etc. and how cognitive technologies can lend new dimensions to an organization’s ability to make sense of voluminous data to reimagine loyalty going forward.
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