• Cognizant 20-20 InsightsLeveraging Advanced Analyticsto Drive Customer Behavior in theAirline Industry   Executive Summa...
Advanced analytics can enable airlines to gain an         center data. Many have attempted in several ways          increa...
Assembling CCV Vectors                                                                       Peer                         ...
CCV Attributes                                                                number of trips, perhaps due to flying with ...
strength of other vectors, such as the value of an    campaign. For example, say an airline wants to              extra ba...
that have natural and statistical affinity among      different active loyalty programs. For instance,themselves. Vector d...
because of the airports they fly from; more than           knows the specific customer’s behavior, prefer-            two ...
CCV in Action                                                      CCV Effectiveness Evaluation                           ...
According to one industry survey,8 more than one      partnership with retail and hospitality stores in               in t...
opportunity at airports is the opportunity of the       facturers and automobile companies are alreadyin-flight time spent...
targeted and personalized offers pertaining to         Analytics can help identify the right customer               servic...
tomer, including the cost of incentives and assess-   The third component required to implementing probability of acceptan...
Footnotes1     “Global Media Day, Geneva,” IATA Web site, Dec. 14, 2010,     http://www.iata.org/pressroom/speeches/pages/...
About the AuthorSiddhartha Tomar is a Director in Cognizant’s Enterprise Analytics Practice and is the global leaderof ana...
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Leveraging Advanced Analytics to Drive Customer Behavior in the Airline Industry


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Airlines can use advanced analytics as a competitive lever by increasing their understanding of customer behavior patterns, identifying cost-optimized ways of serving customers and enhancing opportunities for revenue generation and loyalty among existing and potential customers.

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Leveraging Advanced Analytics to Drive Customer Behavior in the Airline Industry

  1. 1. • Cognizant 20-20 InsightsLeveraging Advanced Analyticsto Drive Customer Behavior in theAirline Industry Executive Summary Last, but not least, looking at the customer through the lens of CCV will allow airlines to The past decade has been tough for airlines, treat customers differently by leveraging their due to a wide array of macro-economic factors, heterogeneity and allowing for connections at socio-political uncertainties, increased cost of an individual level. This, we believe, will increase operations, a stagnating and in some cases even customer loyalty and overall brand equity over declining market and tremendous increase in time. We also offer a vision of the technology infra- competition. In light of these challenges, airlines structure required to make CCV a reality, including need to continuously reinvent themselves and custom in-house deployments or delivered as stay connected with customers, increase returns hosted, managed application services. on every dollar spent and build a loyal customer base. Advanced Analytics: This paper provides insights into ways advanced A Competitive Lever analytics can be leveraged by airlines to address With overall airline industry margins at less than these challenges by improving their customer 3% in 2010,1 the industry continues to lag in share- centricity. It looks at customer behavior in the holder value creation by not matching traditional airlines industry from three aspects. We start cost of capital measures. While conventional with the hypothesis that any numeric customer levers such as increasing operational efficiency index that captures the value of the customer to and monitoring KPIs and metrics are still impor- the airline needs to reflect the heterogeneity of tant, they are not sufficient for creating a com- customer behavior. This can be best achieved by petitive edge. Studies show that while fuel cost using a multi-dimensional customer index, or what instability and revenue management are among we call the Customer Composite Vector (CCV). the top challenges for airlines, it is customer loyalty and retention that are viewed by almost all Secondly, a numeric customer index (single airlines as the lever with the most potential posi- aggregated score or multi-dimensional vector) tive impact on their business.2 is not only a way of understanding customer behavior, but it also has the potential to be used That’s where advanced analytics can play a by airlines as a lever to shape and drive customer crucial role. Analytics can help uncover elusive behavior in a manner that increases customer trends and patterns and unearth uncommon yield and profitability. insights across all areas of the airlines business. cognizant 20-20 insights | september 2011
  2. 2. Advanced analytics can enable airlines to gain an center data. Many have attempted in several ways increased understanding of customer behavior to understand the profitability (i.e., cost-to-serve) patterns, identify a cost-optimized way to serve or to link non-travel revenue with other customer them, enhance opportunities data; however, they have not found any directSatisfying customer for revenue generation and mechanism to compute it. demand is not build strong brand perception/ In an attempt to use disparate customer infor- loyalty among existing and sufficient; airlines potential customers. mation, they end up creating multiple versions need to shape of customer databases, each specific for each This and more can be accom- requirement. In some cases, airlines have and drive existing plished by leveraging proven hundreds of different customer databases, each customer behavior statistical and scientific built for analyzing customer data in a different in a manner that methods. These methods way. While many airlines have consolidated can significantly improve the customer data from disparate sources under a maximizes returns quality of decisions by reduc- common customer database or data warehouse,and keeps them one ing “gut-feel” decision-mak- they have not yet been very successful in utilizing step ahead of both ing and increasing scenario- the insights this data reveals in a cohesive based decision-making that manner. the customer and is fortified with data-derived the competition. foresight. In today’s hyper- Most airlines currently have one view of the competitive marketplace, customer through their customer loyalty advanced analytics can be the crucial element database, and they use frequent flyer data to in identifying ways for airlines to differentiate differentiate customer profiles — which may not themselves with customers and ensure continu- be an accurate reflection of their lifetime value ous business improvement on an ongoing basis. or profit contribution. Some have even gone a step further and used customer data to assign a Airlines are obsessed with new customer acqui- score to customers, indicating the relative value sition. However, they also realize the importance or importance of individual customers. Creating of retaining and generating more revenue from a single customer score is valuable; however, it existing customers while also has its limitations, as the heterogeneity of Creating a single enriching their experience customer behavior is lost when it is aggregated customer score is and thereby increasing cus- tomer loyalty and stickiness. under a single score. valuable; however, They have worked hard to Sometimes, customer scores are used to quantify it also has its understand customer behav- the value of the customer from a lifetime per- limitations, as the ior, with The key question of success. varying degrees is spective. Such a value does not provide insight into the customer’s behavior at any particular heterogeneity of how airlines can move beyond time, and it does not provide any insight on how customer behavior merely understanding custom- to change the customer’s current behavior to the is lost when it is er behavior. is that satisfying hypothesis Our fundamental airline’s advantage. A single customer score or lifetime value does not provide any indication ofaggregated under a customer demand is not suf- how airlines can connect better with the customer, single score. ficient; rather, airlines need ultimately resulting in increased yield and spend. to shape and drive existing More specifically, it does not help airlines to customer behavior in a manner that maximizes assess how different offers may have a different returns and keeps them one step ahead of both impact on different customers. the customer and the competition. Customer Composite Vector: Limits of Traditional Customer Scoring A Multi-Dimensional Customer View At most airlines, customer data is generated by An alternative to an aggregated customer score is different sources and is manifested in different a Customer Composite Vector, or CCV, which can shapes and sizes. Some examples include ticketing form the foundation for generating customer- data (e.g., owned and online travel agency Web specific actionable insights. By definition, CCV is sites, intermediaries, agents, etc.), frequent a multi-dimensional customer value along a set of flyer data (e.g., owned, alliance or third-party), behavioral dimensions or vectors. The definition marketing data (e.g., partner information) and call of vectors will differ from industry to industry cognizant 20-20 insights 2
  3. 3. Assembling CCV Vectors Peer influence Travel spend per trip In-flight Trip modifications Trip profitability behavior Airport behavior Airline performance/ Travel frequency experience Ancillary spend Demographic/ (airline services) socioeconomic Cost-to-serve background Passenger type Online/digitally savvy behavior Ancillary spend (partner services) Competitive consideration set Figure 1 and even within the airlines industry from airline a vector is appropriately captured. For instance, to airline. For example, airlines could define the while three trips per month is more valuable than CCV along the vectors of travel frequency, travel one trip per month, five trips per month is signifi- spend per trip, non-travel spend, trip profitability, cantly more valuable than three trips per month. cost-to-serve, passenger type, peer influence and/ The second objective of the conversion is to ensure or competitive consideration set (see Figure 1). a vector can be defined as a combination of two or more parameters. For example, if an airline While the definition of vectors can be customized, wants to define a single vector comprising both the concept of the heterogeneity of CCV, which the “frequency of travel” as well as “spend per is its biggest asset, remains trip,” then appropriate conversion rules will allow constant. CCV is a set of CCV is a set of numerical values defined numeric computation of one vector value from two different parameters. Lastly, if at any time an numerical values along different vectors. For airline wants to combine two or more vectors todefined along different each customer, each vector arrive at a single value, again, in that case, these is represented by a single vectors. For each numerical value, which is conversion rules can aid in the numeric computa- tion of one value across vectors. customer, each vector arrived at using pre-defined is represented by vector rules. For example, Apart from a numeric value, vectors may also the value for a vector such have non-numeric or qualitative attributes, which a single numerical as “frequency of travel” provide descriptive details of the vector value. Forvalue, which is arrived can be arrived at by using instance the “passenger type” vector, which will at using pre-defined the appropriate vector have a calculated numeric value, may also have conversion rule, which a qualitative attribute describing whether the vector rules. converts the number of person is primarily a business or a casual traveler, trips a customer takes per mostly travels alone or prefers to travel with month on average into a numeric vector value family, is a long-haul traveler or typically goes on according to the vector rules (e.g., one trip per short trips, etc (see Figure 2, next page). month = 2, three trips per month = 7, five trips per month = 15). Similarly, a “competition consideration set” vector may provide the list of the top two or three The idea behind such a conversion is three-fold: competition airlines with which the passenger The first is to ensure that the “non-linearity” of typically flies or is an active member of their cognizant 20-20 insights 3
  4. 4. CCV Attributes number of trips, perhaps due to flying with another airline, and should be provided with offers and communication, incentivizing him to return to his previous level of travel with the Aging Assigns more airline. The second customer is increasing her weight to data travel, suggesting that offers related to increas- pertaining to recent Descriptive behavior Timeliness ing spend per trip may be more impactful. Gathers qualitative Recalculates vector (non-numeric) insights, Data timeliness: CCV also signifying consumer values at every customer event ensures the “timeliness” of CCV allows airlines choice CCV the customer data. The CCV to target customers Attributes value for each customer with the vector that Conversion Progression Rule gets recalculated at every Incorporates Exposes historical values for each vector customer event. This is most important “non-linearity” of vectors and enables Strength as well as potential ensures that the airline is and relevant for vector comparison future values Indicates relative always looking at the most them, as well as importance of each current, or recent, value of vector for the customer the CCV when using it for the one where they analysis. For example, when may have a higher the marketing department propensity to act.Figure 2 wants to run a campaign, it can use the most relevant CCV vectors for segmentation and be sure that these CCV vector values reflect the most recentfrequent flyer programs. Such non-numeric and customer behavior.qualitative vector attributes may be extremelyinsightful and can be used in the interpretation of Perceived value to the customer: Variousthe numeric values and to gain a holistic under- customers ascribe different values to products andstanding of the customer. services. CCV allows airlines to target customers with the vector that is most important andCCV Considerations relevant for them, as well as the one where they may have a higher propensity to act. For instance,CCV takes into account several important aspects studies show that frequent flyers perceive someof customer data. These include the following: attributes of a loyalty program as more importantData aging: CCV considers the “aging” of than others.3 However, in most cases, there is acustomer data while calculating vector values. substantial gap between what customers wantCustomer behavior patterns change over time, and what they get. According to the research,and it is important to assign more weight to bridging this “want-get” divide can lead to up tothe most recent actions compared with older a four-fold increase in the percent of customersbehavior. The rules for aging customer data are who will be willing to fly the airline more. Not onlydefined for each vector and are uniform across all this, but if airlines offer products and servicescustomers. This process ensures that more recent that customers value more highly, then the costbehavior is given more weight, while at the same of these promotions will be also be less.time allowing older data to remain relevant. The basic hypothesis here is that the higher theFor example, if two customers both have an perceived value of a particular product, serviceaverage frequency of three trips per month for or experience by a particular customer, the lowerthe past three months, but their histories vary the incentive required to drive the behavior.beyond three months, they will have different CCV This perceived benefit by the customer can bevector values. The first of the two customers used captured as a CCV “strength,” which indicatesto average five trips per month, while the second the relative importance of that vector for thatcustomer used to average one trip a month. As a particular customer. For example, a customerresult, the vector value for the first customer will may travel three to five times per month, butbe different from the second. that may be the highest level the customer has the potential to achieve; therefore, the strengthThis is an important insight, because now the of the trip frequency vector will be ranked lowerairline knows the first customer is reducing the than other vectors. On the other hand, the cognizant 20-20 insights 4
  5. 5. strength of other vectors, such as the value of an campaign. For example, say an airline wants to extra baggage allowance or services such as free drive traffic in a particular sector, so it decides wireless access at the airport, may have more to offer bonus frequent flyer miles to customers. of a bearing on the customer’s future behavior, Using the combination of vector values and vector and hence, it will be ranked higher than the trip strength for each customer likely to fly on that frequency vector. sector, the airline can identify the initial customer set. Then, using the progression pattern of vector The strength of a vector can be calculated in a values, the airline can then perform an economet- couple of ways. The easiest is at the customer ric modeling of what kind of bonus mile incentive segment level, where customer segmentation can is required to increase the probability of each provide an indication of what types of services are customer flying that particular route. It can use valued by which segments, which can provide a this information to create a personalized offer for segment-level strength value for each vector. This each customer, with specific bonus miles that are segment-level strength value can be assigned to most likely to drive the customer’s behavior. all the customers in that segment. Moreover, for customers who are likely to fly on The more accurate way is to that route anyway, offering bonus miles may not Over time, the calculate the vector strength result in additional traffic, and hence, airlines evolution of at an individual customer can significantly improve the campaign ROI by level. This can be achieved customer behavior by examining the specific making the offer only to those who are not likely to fly without this incentive. Such a CCV-based across different set of services and offers approach is likely to be more effective, as it can vectors can be used and accepted by the transform mass generic campaigns into highly customer from the variety analyzed to provide of offers provided as part of personalized ones, with higher campaign success rates and significantly higher campaign ROI. an even deeper recent promotions. In someunderstanding of the cases, a direct customer Over time, the evolution of customer behavior survey can also provide across different vectors can be analyzed to airline’s relationship additional insights into which provide an even deeper understanding of the with its customers. vectors are valued more by airline’s relationship with its customers. Analysis the customer. The combina- can also be conducted to identify which vector tion of the vector value and progression paths lead to greater customer strength is the best way for airlines to target loyalty and improved customer yield over time. their customers and ensure the best return on This insight can provide inputs to the types of investment (ROI). offers, promotions and campaigns that need to be designed to drive customer behavior in the desired Vector progression: Another big advantage of direction. Analysis of how the different vectors of the CCV is vector “progression.” Vector progres- CCV progress over time can provide much more sion exposes the historical and future path for meaningful insights about how to reduce attrition each vector. This concept allows the airline to and address low-yield customers. Additionally, not only know the current value for each CCV potential red flags can be raised much sooner, as vector but also how the customer has progressed the propensity to lose a customer will be high- along each vector over time — and the potential lighted much sooner. for his progression in the future. This capability is crucial when building scenarios and performing The definition, conversion rates, aging process, econometric modeling for campaigns directed at strength and natural progression path for each moving the customer up the value chain. The net of the CCV vectors vary from airline to airline, advantage of this capability is that it allows the depending upon their specific needs. Defining airline to predict whether or not the customer the vectors and identifying the optimal number will move up the value chain (i.e., increase the of vectors is a crucial foundational step. Creating vector value), what the cost will be and with what too many vectors can make analysis difficult probability. and decision-making, hazy. On the other hand, creating too few vectors will compromise the Benefits of CCV Analytics heterogeneity of customer behavior. While Using such CCV-based analytics, airlines can defining vectors, it is important to combine improve the effectiveness of a marketing only those parameters under a single vector cognizant 20-20 insights 5
  6. 6. that have natural and statistical affinity among different active loyalty programs. For instance,themselves. Vector definitions and associated even the most cost-conscious budget traveler willrules should be defined only after thorough due be willing to pay a slight premium to travel on andiligence and impact analysis. airline in which she is a member of the frequent flyer program in order toApplication of CCV: Driving Behavior accrue additional miles and Creating too manyAirline operators spend millions of dollars on rewards. And so, the campaignspromotions and campaigns to attract customers. and promotions that will drive vectors can makeThey acquire new customers who often enroll in the customer’s behavior need analysis difficult andtheir frequent flyer loyalty programs, allowing to differ depending upon the decision-making,them to collect more data and provide better competition consideration set,offers and communication. While engaging which, again, the CCV can help hazy. On the othercustomers in loyalty programs is important, the decide. hand, creating toogreater benefit comes from tracking customer Learning from Retailers few vectors willbehavior on an ongoing basis. Airlines can also learn from compromise theSetting the initial value of the customer’s CCV retailer loyalty programs, heterogeneity ofvector values is the essential first step in thisprocess. The new customer may be slotted into an especially when it comes to customer behavior. creating customized promo-existing customer segment, and his CCV vector tions at an individual level.value counter would be set by extrapolating While most airlines only conduct mass marketbehavior from other customer behavior patterns. campaigns that are not based on individual cus-The initial assignment of the CCV dimensional tomer behavior, leading retailers have carried outvalues becomes the starting point of the air- targeted and highly individualized promotions forline-customer relationship and should then be years based on their customer data and loyaltysubsequently used over the customer’s lifetime programs. Airlines should consider emulating theto continuously change the CCV vector values, way retailers analyze in-store and online spenddepending upon different customer journey and behavior and attempt to increase the customer’slifecycle events. total spend. Retailers do this by performing a market basket Every customerThroughout the customer lifecycle, a variety analysis and delivering target-of events occur, which feed into the CCV and trip, nature/class of ed promotions, increasingly in real time and in context (i.e., travel, non-travelenrich the understanding of the customer. Thisthen improves the ability of airlines to use that where they are searching for related purchase,information and respond meaningfully. Every or comparing products).customer trip, nature/class of travel, non-travel cancellation/related purchase, cancellation/postponement, For instance, a leading UK postponement, callcall center interaction of an individual customer,customer preference and so on enriches the retailer uses individual cus- center interaction of tomer market baskets to clas-CCV. Even non-events like not flying enough sify the customer into one of an individual customer,can provide inputs to the CCV. Also, informa- over 20 lifestyle segments. customer preferencetion such as rival airline frequent flyer programsof which the customer is a member can help in It then uses that segmenta- and so on enriches the tion to not only understandunderstanding the airline consideration set for the customer but also influ- CCV. Even non-eventsthat customer. Studies show that while 9 in 10 of ence her behavior based on like not flying enoughbusiness travelers belong to at least one frequentflyer program, more than three in five belong to customized offers and promo- can provide inputs to tions.5 Similarly, customers’three or more such frequent flyer programs.4 flying patterns can be ana- the CCV. lyzed to determine when theyThus, in theory, all else being equal, the optimal are likely to fly, how often they fly, which sectorspricing strategy is not to be the cheapest they fly, etc. All this information can potentiallyamong all airlines but to be the most attractive be used by airlines in tailoring their relationshipin the customer’s consideration set. Similarly, a with customers.customer with two active frequent flyer programswill have significantly different response behavior For instance, three in four of all U.S. air pas-compared with the customer with five or six sengers choose the airline they fly most often cognizant 20-20 insights 6
  7. 7. because of the airports they fly from; more than knows the specific customer’s behavior, prefer- two in three cite convenient schedules.6 This ences, propensity and reasons to defect, etc. For means that based on the most frequent sectors, example, a small incentive like a simple upgrade airports or flight times preferred by the customer, voucher for the customer’s next flight may not airlines can offer promotions specific to those only help retain the customer but also prove to particular sectors, airports or flight times. Offer- be the crucial event that can potentially cement ing sector, airport- or even the airline/customer relationship for a very long schedule-specific incentives time. Knowing when to offer and whom to offer Offering sector-, and promotions will be more what kind of incentive and promotion is where airport- or even effective compared with a CCV-based analytics can help airlines improve the schedule-specific generic mass-market offer. effectiveness of their retention efforts. Such promotions may also be incentives and used to level out occupancy Learning from Financial Services Providers promotions will and utilization across differ- Some leading financial product providers in the be more effective ent sectors and across differ- e-commerce space conduct “test and learn” ent times of day. experiments, where they try to identify the compared with nature and timing of promotions that can have a generic mass- Airlines also have an advan- the most influence on customer behavior across tage over retailers in that various customer segments. By identifying whom market offer. they know in advance (i.e., as to give what kind of incentive and when, they are soon as the customer books able to drive customer payment behavior toward his/her ticket) where customers are going and financial products that are more suitable and when. Retailers would turn that knowledge into arrest possible attrition, as well as those that are a pot of gold by targeting the customer with a more profitable for the company. Airline operators variety of up-sell/cross-sell offers. can adopt a similar model, whereby they create micro-promotions based on experiments at an The ability to predict cus- individual customer level and use the results to tomer reason and probability If a dip in travel guide customer behavior. of defection is crucial for air- frequency points lines in trying to retain their The ability to understand the impact of loyalty toward a change in a existing pool of loyal and status promotions, campaigns and offers on the profitable customers. CCV-customer’s preference decisions made by customers when selecting based analytics can provide the preferred airline is crucial to ensuring the for a different airline red flags at appropriate right amount of money to spend on the kindsas the primary airline, stages (event-based or pat- of promotions that elicit the required customer tern-based). For example, an CCV-based vectors behavior. For some customers, on-time arrival unusual dip in travel frequen- may be more important than price. And if the can provide insight cy can be flagged as a poten- airline is able to identify those customers andinto what is important tial case of customer defec- design a promotion exclusively on timely arrival tion and marked for further to the customer and rather than focusing on low prices, then this offer investigation. From there, will not only attract more such customers and create an incentive proactive measures can be improve the customer yield, but it will also prove that will increase the taken to retain and recapture to be a clutter-breaker in the competitive market- the customer. probability of gaining place. the customer back. For instance, if a dip in travel For example, airlines can guarantee an on-time frequency points toward arrival (by promoting actual arrival time within a change in a customer’s plus or minus 30 minutes of the scheduled arrival preference for a different airline as the primary time) or promise to reimburse the customer in airline, CCV-based vectors can provide insight some form (i.e., an in-kind cash-back offer). This into what is important to the customer and create will be similar to the 30-minute guarantee or an incentive that will increase the probability of money-back promotion used by pizza chains. gaining the customer back. This approach could be hugely popular among a particular segment of customers, say business Conventional wisdom suggests it is less costly travelers or late-evening flyers, where flights have to retain a customer than to acquire a new a higher propensity for delay. one. However, this is possible only if the airline cognizant 20-20 insights 7
  8. 8. CCV in Action CCV Effectiveness Evaluation CCV Econometric Modeling Σ Bonus air $ miles for more than certain Discount on extra trips on baggage, in-flight meals, that sector online check-in Vouchers for specific Airline restaurants, car rentals Travelers with decreasing travel services Partner $ Σ frequency services Be price-competitive Travelers only with regards to with low ancillary competition specific revenue to traveler Travelers with Improved competitive sector ΣΠ consideration set profitability Dynamic pricing Offer/Promotion Offer/Promotion econometric effectiveness Decreasing Identify travelers CCV Engine: modeling evaluation profitability of active in sector for Identify vectors specific sectors past 12 months relevant to Perform cost-benefit Track and monitor Customer with analysis of each offer the success of all offers individual travelers high itinerary and promotion and promotions modifications Online Flexible flight plan Offer free change Campaign execution and digitally Airline savvy travelers in flight or $ cancellation performance & Additional bonus air experience miles, online check-in or Σ discounts for buying Compensate services online for past delays Drive online behavior Offer complimentary $ services for past delays or cancellations Σ CCV Econometric Modeling CCV Effectiveness EvaluationFigure 3Again, CCV-based analytics can help identify the security screening7 to reduce waiting time at theright audience for this offer, calculate the cost of airport. The vector of time or convenience is moresuch a promise and compute the returns on such important to a certain set of passengers, and theypromotions. The econometric modeling of such are willing to pay extra for it. This indicates anpromotions is crucial to ensure that the incremen- opportunity for the airlines to charge extra fortal revenue/profit over a period of time more than such services from such business passengers.offsets the cost of risks undertaken and, hence,the overall cost of such promotions. Similarly, there might be dif- ferences in other categories of A one-size-fits-Personalization Counts passengers, such as the long- all approach does haul traveler vs. a short-hop traveler. A long-haul/multi-leg not work in mostA one-size-fits-all approach does not work in mostindustries, and the airline business is no exception.It is important to treat different customers dif- traveler may value access to industries, and theferently and understand the differences among special lounges more than airline business is no anything else, which will ease transit significantly. Providing exception.categories such as business traveler vs. casualtraveler, frequent flyer vs. occasional traveler,single traveler vs. travelers with family, long-haul that additional feature at thetraveler vs. short-hop travelers, etc. Each of these time of booking, even at an extra cost, may notcustomer segments has its own characteristics, only increase the yield but also do wonders forwith significant implications for airlines. the long-term loyalty of the customer. Similarly, for a traveler with family, providing discountedFor instance, a study shows that more than one vouchers for a restaurant at the airport might bein two business passengers may be willing to pay the most valued promotion.$10 more for services such as priority airport cognizant 20-20 insights 8
  9. 9. According to one industry survey,8 more than one partnership with retail and hospitality stores in in two customers prefer the aisle, while more than airports. While some operators are already doing two in five favor the window. For either customer this, it is mostly conducted at a mass-market level type, the booking system can use previous flight rather than at an individual customer level. history to offer a guaranteed aisle/window seat for a small fee. For instance, a mass-market promotion in which all frequent flyers get, say, 5% off at a particular The crucial aspect in creating these customer- store or restaurant will be far less effective than centric services and offers is the use of CCV-based a targeted promotion in which a customer gets advanced analytics to identify the right set of 10% off on a store or restaurant that she is more customers for the right set of promotions and likely to visit. The key difference is that an indi- incentives. Airlines can predict the impact by vidualized promotion means the preferred store using ROI analysis and econometric modeling to will differ from customer to customer, and hence, optimally decide the level of incentive and, then, the promotion response rate and the ancillary can apply actual response data to improve their revenue will be significantly higher for the same analytical accuracy and effectiveness over time. amount of campaign spend. Ancillary Revenue Opportunities Optional travel products/services: CCV-based Industry estimates suggests that ancillary rev- advanced analytics can provide insights into enues currently account for approximately 7% of likely customer behavior, product preference and global airlines’ top line, a figure that is expected preference of retail and hospitality stores, both to almost double by 2015.9 Co- inside and outside of the airport. This, in turn, can be leveraged for a more targeted promotion with Many customers branded credit cards are the a much higher conversion rate. spend as much quickest airlinesmostadd ancil- way for and to popular time at the airport lary revenue. Many frequent Micro-campaigns can be analyzed along different CCV vectors, and their progression over time as they spend in flyer loyalty programs are also can be mined for ROI. The results can be used to flight. The boom in combined car rentals or hotel grams of with the loyalty pro- continuously refine and optimize campaigns to the airport-based chains. However, this oppor- achieve ancillary revenue targets. According to research,10 almost one in two U.S. online airlineretail and hospitality tunity for ancillary revenue passengers have paid a travel fee in the past 12 industry is a big generation ifcan be increased many-fold airlines are able months for at least one optional travel product or opportunity for to understand individual cus- service. According to another study, more than two in three travelers booked at least one additional airline operators to tomer preferences and behav- service at the time of booking their last trip, with better connect with ior and provide personalized promotions. Here are some services ranging from insurance, to meeting customers. examples: facilities, to restaurant reservations, to other travel services.11 This shows that a tremendous Airport-based revenues: Going beyond the opportunity exists to increase ancillary revenue, revenue generated through the loyalty card part- provided that airlines can understand who needs nerships with car rental agencies, hotels and what at the individual customer level. credit card companies, tremendous opportunity Airline/airport partnerships: With the evolving exists to engage with customers while they are concept of smart airports,12 and with a growing at the airport or by charging for services that are number of users opting for a mobile Web valued most by them. Customers at the airport experience, airlines can enhance the customer are increasingly viewed as a captive audience. experience by partnering with airports to provide Many customers spend as much time at the enhanced services throughout the journey. With airport as they spend in flight. The boom in the the flight data, services such as discounted stays airport-based retail and hospitality industry is at an airport hotel in case of flight delay or valet a big opportunity for airline operators to better services for travelers in case of a late-night flight connect with customers. will help provide a better customer experience. CCV-based analytics can help airlines decipher In-flight opportunities: Similar to the enhanced customer behavior and preferences, and that customer experience and ancillary revenue can help them design co-branded promotions in cognizant 20-20 insights 9
  10. 10. opportunity at airports is the opportunity of the facturers and automobile companies are alreadyin-flight time spent by the customer. While this is doing this very effectively, and airlines would bestill an evolving space, a greater understanding wise to apply lessons learned from their digitalof customer behavior can be leveraged to enrich marketing strategies. CCV can help analyze thethe customer’s in-flight experience, which can impact of social media interactions and drivenot only augment ancillary revenue and increase airlines’ digital marketing and social mediaprofits per trip but also be a way for the airline to strategies. Airlines need to analyze the impactdifferentiate itself. of such social media behavior and try and understand the drivers for customers choosing aFor example, in 2010, Virgin America launched the particular airline over others.first ever digital shopping platform on seat-backvideo screens. Korean Air will roll out the world’s Malaysian Airlines, for example, An airline’s digitalfirst flying duty-free store onboard its first A380 has launched an applicationby the end of 2011.13 With technology making such (MHbuddy) on Facebook that marketing strategyservices possible, the key is to identify whom to allows users to book and check should primarilyoffer what kind of service at what price point. in for a flight while sharing serve digitally-savvy their trip details with theirThus, providing Internet access to business social network. While the digital customers, and CCVpassengers through an in-flight wireless facility world is in hyperactive mode, it vectors can enablemay be a very simple and effective way of not onlyincreasing revenue potential but also increasing is also important for airlines it to make this to differentiate and segmentcustomer loyalty in a hyper-competitive market. digitally-savvy customers from distinction.For instance, Delta offers a 24-hour pass for digitally-challenged ones. Anunlimited Internet access.14 CCV-driven analytical airline’s digital marketing strategy should pri-insights can help airline operators design and run marily serve digitally-savvy customers, and CCVsuch additional products and services and make vectors can enable it to make this distinction.offers to customers who value them most and Knowing which customer is impacted how muchhave a higher propensity to accept them. by digital media and the most effective way to reach him can help airlines make optimal use ofOnline/social media opportunities: Studies their marketing dollars, especially digital market-show that almost two in three bookings today are ing spend.conducted online through airline Web sites15 andthat customers are increasingly using comparison/ Peer influence: CCV-based CCV vectors canaggregation Web sites for comparing fares and analytics can also enable air-making bookings. Online and peer review sites are be used to design lines’ assessment of the impactalso becoming an increasingly important vector in of peer influence on a customer referral campaigns tothe customer’s decision-making process. Holiday and the ability of customers to help airlines reach theand casual travelers increasingly rely on Web influence others who span theirbuzz, including the formal and informal feedback customers they want direct or indirect influence.from third-party and social media sites, as well as Network analysis of customers to attract through theindependent blogs. and their connections can help network of customers analyze their impact on peersSocial media sentiment is becoming an important they already have. (family members/friends/officeaspect, and hence it is crucial for airline operators colleagues, etc.) and see whichto be proactive in the online space through vectors have a higher correlation and identify aeffective use of advanced analytics. While the greater influence. CCV vectors can help connectability to listen and analyze the sentiment of this very important linkage among the peeronline chatter is crucial, it is becoming increas- group, which can be used effectively in designingingly important to ensure social media attitude is referral campaigns to help airlines reach the cus-managed like any other brand attribute. Thus, the tomers they want to attract through the networkability to shape key opinion leaders’ views in the of customers they already have.social media space is crucial. While ancillary revenue opportunities areAdvanced digital and social media analytics can immense, it is important for airlines to ensurego a long way in augmenting airlines’ overall that customers are not inundated with numerousmarketing strategy to manage brand perception. frivolous offers and are instead offered only a fewIn fact many retailers, consumer goods manu- cognizant 20-20 insights 10
  11. 11. targeted and personalized offers pertaining to Analytics can help identify the right customer services that are valuable to them. segments with a higher propensity to change and also illuminate the appropriate level of incentive, High-end analytics such as a CCV model can such as bonus frequent flyer miles for driving dramatically help airlines understand individual specific customer behavior that supports cost customer behavior and create personalized rationalization initiatives. offers and promotions. In a recent survey,16 93% of respondents felt that loyalty programs were Airlines can apply analytics to such data to not serving loyal customers but were primarily generate the optimal balance of fare and frequent a marketing tool. CCV-based analytics can flyer miles. Analytics can also help in changing enable airlines to leverage data embedded in the incentive lever, such as which rewards should these loyalty cards to do exactly what they were be offered, how rich they should be or when they originally intended for example, to get closer to should be offered. For example, it might make customers and increase their loyalty. more sense to target very busy airports when providing a bigger incentive like more bonus miles Analytics as a Key Lever for for lower-cost online or kiosk check-in during Cost Rationalization peak hours/seasons than providing it at all times The global economic downturn was particularly or uniformly at all airports. hard on airlines because of their higher fixed cost Another focal point could be around services such structure. Per International Air Transport Asso- as in-flight meals and cost of extra baggage. For ciation (IATA) estimates,17 the airline industry is example, buying in-flight meals or extra baggage set for a 40% decline in combined profits in 2011, in advance, through online services, or at the time falling from $15.1 billion in 2010 to $9.1 billion in of booking at a cost significantly lower than the 2011. Though revenue is set rack rate, could not only improve the yield per CCV can allow to growmargins $598fall by profit 5.8% to will billion, customer, but also reduce operational costs. rationalization of almost half to 1.5%. Thus, Again, CCV-based analytics can enable airlines to cost as a continuum a lean and mean operation identify when to offer what promotion to whom to across multiple is thehence industry mantra, and new it is important drive the maximum change and have the biggest cost impact. This will also allow airlines to identifyvectors rather than a for airlines to rationalize all the economics (quantitative), as well as the toggle decision. costs, including the expense perceived benefit (qualitative) of such services, of serving customers. thus reducing cost of operations by converting no-fee services perceived as less important into However, a cookie-cutter approach of slashing paid services. costs, especially on customer-facing services, can have disastrous long-term impacts on customer Bring CCV Alive: Implementation Ideas loyalty, revenue and brand equity. That makes To implement CCV-based analytics, airlines need it important to be prudent in understanding three essential components. First is the “CCV the impact of cost rationalizing measures on Engine,” which is at the heart of the solution and customer behavior. calculates the CCV value for each customer on an ongoing basis, based on different customer CCV-based analytics can help airlines identify journey events. The number and definition of the right ways to rationalize costs in a proactive different customer vectors is a crucial consider- manner with minimal customer impact. CCV ation and needs to be decided after careful delib- can allow rationalization of cost as a continuum eration. across multiple vectors rather than a toggle decision. For example, the first move for airlines The CCV Engine identifies customer preferences is to examine ways of driving customer behavior and the products and services most valued based in a manner where cost of service can be reduced on different vector values. The engine analyzes without compromising customer service, such customer behavior patterns and identifies prob- as moving customers toward using self-service able customer preferences, along different CCV kiosks, online and mobile check-in facilities. While vectors. This analysis is then used to identify those most airlines have these capabilities, much more dimensions that can be leveraged by airlines in can be done to drive customers toward desired driving customer behavior by optimizing incre- actions, especially on a case-by-case basis. mental revenue and the cost of serving the cus- cognizant 20-20 insights 11
  12. 12. tomer, including the cost of incentives and assess- The third component required to implementing probability of acceptance. CCV vector values CCV-based solutions is “CCV Analytical Services.”are calculated in an offline manner on a periodic Initially, this is required for building the CCV(weekly or monthly) basis and on-demand for all Engine and different CCV Business Applications.customers. Subsequently, these services are required to ensure that customer data and related inputsCCV is an independent engine that can provide computed by the CCV Engine and CCV Businesscustomer vector values for any given customer Applications are optimallyto any system or program within the airline’s applied to different business From a technicalIT landscape. From a technical perspective, the scenarios and ongoingCCV Engine is developed using a set of advanced decision-making exercises. perspective, the CCVstatistical and mathematical techniques and CCV analytics can also be Engine is developedalgorithms. The engine is specific to each airline delivered as a business or using a set ofand must be built based on specific customer data knowledge process outsourc-and core intellectual property. Once developed ing (BPO/KPO) service, in advanced statisticaland matured, the CCV Engine can be operated like which clients entrust a third- and mathematicala black box, with minimal maintenance overhead. party specialist to identify techniques andHowever, persistent change in the business envi- and make customer-specificronment may necessitate continuous fine-tuning recommendations offers. algorithms.of the algorithms and logic inside the CCV Enginefrom time to time. CCV: Approaching Take-off It is a continuous quest for airlines operators toThe second component required to implement increase customer yield in these economicallya CCV-based solution is a set of “CCV Business challenging, highly competitive times. AdvancedApplications” that can be leveraged by different analytics is the most under-utilized lever todaybusiness groups and functions within each and has significant potential to aid and optimizeairline’s business group to optimize their decision-making at all levels. Analyzing customersday-to-day decisions using CCV-based analytics. along different CCV vectorsThese could be across the business value chain, can improve airlines’ under- CCV Businesssuch as marketing, promotions and campaigns, standing of customer behaviorpricing and revenue management, ancillary Applications can be patterns and enable them to offer services, promotions developed specific torevenue opportunities, partnerships with otherloyalty programs, etc. and campaigns that are an airline or could be customized for individualCCV Business Applications could range from a set delivered as hosted,of simple business rules, to complex algorithms customers. This, in turn, willspecific to a business function. And since these have a higher probability of managed services.are pure business applications, they should be driving customer behaviorfairly flexible to changing market dynamics. CCV in the desired direction that will increase theBusiness Applications can be developed specific customer trip yield and profitability and ultimatelyto an airline or could be delivered as hosted, increase customer stickiness and loyalty, which ismanaged services. These business applications the industry’s Holy Grail.can even be consumed in the evolving software-as-a-service (SaaS) model, which reduces the costof investment required to deploy and leveragetheir benefits. cognizant 20-20 insights 12
  13. 13. Footnotes1 “Global Media Day, Geneva,” IATA Web site, Dec. 14, 2010, http://www.iata.org/pressroom/speeches/pages/2010-12-14-01.aspx2 “Airlines: Customer Loyalty and Retention has Most Positive Impact,” 4Hoteliers.com, Oct. 19, 2009, http://www.4hoteliers.com/4hots_nshw.php?mwi=64663 “Better Business Results from Elite Frequent Flyers,” Carlson Marketing and Peppers & Rogers Group, 2009, http://www.icisconference.com/uploads/assets/Carlson%20Marketing%20Better%20Business%20 Results%20from%20Elite%20Frequent%20Flyers%20FINAL(1).pdf4 Philip Charlton, “Targeting: The Achilles’ Heel of Frequent Flyer Programmes,” The Wise Marketer, February 2004, http://www.thewisemarketer.com/features/read.asp?id=425 Edward Yurcisin, “Advanced Analytics,” presentation, MicroStrategy World, Monte Carlo, July 13, 2011, http://www.microstrategy.com/microstrategyworld/europe/download/world2011/MCW11_T4_S7_ Advanced-Analytics.pdf6 Henry H. Harteveldt and Elizabeth Stark, “What Airline Passengers Value — And What Airline eBusiness Professionals Need To Do About It,” Forrester Research, Inc., April 13, 2009, http://www. forrester.nl/rb/Research/what_airline_passengers_value_%26%238212%3B_and_what/q/id/53217/t/27 Henry H. Harteveldt, “The Ancillary Products U.S. Airline Passengers Want — And The eBusiness Challenges Airlines Face,” Forrester Research, Inc., May 22, 2009, http://www.forrester.com/rb/Research/ancillary_ products_us_airline_passengers_want_%26%238212%3B/q/id/54060/t/28 “Survey: What Passengers Want from Airlines,” eTurboNews, March 15, 2010, http://www.eturbonews.com/14902/survey-what-passengers-want-airlines9 “Cross-Sell Your Way to Profit,” Forrester Research, Inc., January 2011, http://www.amadeus.com/AU/ documents/corporate/Cross-Sell%20Your%20Way%20To%20Profit%20_%20ENG_Final.pdf10 Henry Harteveldt and Elizabeth Stark, “Airlines Need To Convince Passengers To Use Digital Channels To Buy Ancillary Products,” Forrester Research, Inc., Jan. 7, 2010, http://www.forrester.com/rb/Research/ airlines_need_to_convince_passengers_to_use/q/id/53237/t/211 “The Well Connected Traveller: A Survey of Consumer Travel Trends,” Travelport, 2010, http://www.travelport.com/~/media/Global/Documents/Customer%20Community/Travelport%20 The%20Well%20Connected%20Traveller102010.ashx12 Amir Fattah, Howard Lock, William Buller and Shaun Kirby, “Smart Airports: Transforming Passenger Experience To Thrive in the New Economy,” Cisco Systems, Inc., July 2009, http://www.cisco.com/web/about/ac79/docs/pov/Passenger_Exp_POV_0720aFINAL.pdf13 “Korean Air to Introduce World’s First In-Flight Duty-Free Shop on A380,” Terminal U, April 6, 2011, http://www.terminalu.com/travel-news/korean-air-to-introduce-worlds-first-in-flight-duty-free-shop- on-a380/8166/14 “In-Flight Wi-Fi Access,” Delta Web site, http://www.delta.com/traveling_checkin/inflight_services/ products/wi-fi.jsp15 “Ninety Major World Airlines Surveyed,” eTurboNews, Nov. 29, 2010, http://www.eturbonews.com/19795/ninety-major-world-airlines-surveyed16 Andrew Watterson, Scot Hornick and Raj Lalsare, “The New Economics of Loyalty Programs,” Mercer Management Journal, No. 22, http://www.oliverwyman.com/pdf_files/MMJ22_New_Econom- ics_Loyalty.pdf17 “Global Media Day, Geneva,” IATA Web site, Dec. 14, 2010, http://www.iata.org/pressroom/speeches/pages/2010-12-14-01.aspx cognizant 20-20 insights 13
  14. 14. About the AuthorSiddhartha Tomar is a Director in Cognizant’s Enterprise Analytics Practice and is the global leaderof analytics for multiple industries, including travel, hospitality, manufacturing, logistics, energy andutilities. Siddhartha can be reached at Siddhartha.Tomar@cognizant.com.About the Cognizant Enterprise Analytics Practice (EAP)With over 900 consultants, Cognizant’s Enterprise Analytics Practice (EAP) is partnering with clientsacross the globe by providing business-specific and enterprise-wide analytical services. EAP usesadvanced statistical, mathematical and econometric models, combined with deep domain knowledge toprovide predictive and descriptive analytic solutions to drive fact-based enterprise decisions. CognizantEAP’s philosophy is to extend the classical hindsight analysis by providing uncommon business insightsand predictive foresights in a manner that brings analytics to the masses in a highly accessible manner.For more information on how EAP can help your organization in gaining analytical insights and foresights,contact analytics@cognizant.com.About CognizantCognizant (NASDAQ: CTSH) is a leading provider of information technology, consulting, and business process out-sourcing services, dedicated to helping the world’s leading companies build stronger businesses. Headquartered inTeaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industryand business process expertise, and a global, collaborative workforce that embodies the future of work. With over 50delivery centers worldwide and approximately 118,000 employees as of June 30, 2011, Cognizant is a member of theNASDAQ-100, the S&P 500, the Forbes Global 2000, and the Fortune 500 and is ranked among the top performing andfastest growing companies in the world. Visit us online at www.cognizant.com or follow us on Twitter: Cognizant. World Headquarters European Headquarters India Operations Headquarters 500 Frank W. Burr Blvd. 1 Kingdom Street #5/535, Old Mahabalipuram Road Teaneck, NJ 07666 USA Paddington Central Okkiyam Pettai, Thoraipakkam Phone: +1 201 801 0233 London W2 6BD Chennai, 600 096 India Fax: +1 201 801 0243 Phone: +44 (0) 20 7297 7600 Phone: +91 (0) 44 4209 6000 Toll Free: +1 888 937 3277 Fax: +44 (0) 20 7121 0102 Fax: +91 (0) 44 4209 6060 Email: inquiry@cognizant.com Email: infouk@cognizant.com Email: inquiryindia@cognizant.com© Copyright 2011, Cognizant. All rights reserved. No part of this document may be reproduced, stored in a retrieval system, transmitted in any form or by anymeans, electronic, mechanical, photocopying, recording, or otherwise, without the express written permission from Cognizant. The information contained herein issubject to change without notice. All other trademarks mentioned herein are the property of their respective owners.