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.

1. • Cognizant 20-20 Insights
Leveraging Advanced Analytics
to Drive Customer Behavior in the
Airline 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. 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 direct
Satisfying 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 of
aggregated 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. 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 to
defined 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. For
value, 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. 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 recent
frequent flyer programs. Such non-numeric and customer behavior.
qualitative vector attributes may be extremely
insightful and can be used in the interpretation of Perceived value to the customer: Various
the numeric values and to gain a holistic under- customers ascribe different values to products and
standing of the customer. services. CCV allows airlines to target customers
with the vector that is most important and
CCV 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 some
of customer data. These include the following:
attributes of a loyalty program as more important
Data aging: CCV considers the “aging” of than others.3 However, in most cases, there is a
customer data while calculating vector values. substantial gap between what customers want
Customer 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 to
the most recent actions compared with older a four-fold increase in the percent of customers
behavior. The rules for aging customer data are who will be willing to fly the airline more. Not only
defined for each vector and are uniform across all this, but if airlines offer products and services
customers. This process ensures that more recent that customers value more highly, then the cost
behavior 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 the
For example, if two customers both have an perceived value of a particular product, service
average frequency of three trips per month for or experience by a particular customer, the lower
the 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 be
vector values. The first of the two customers used captured as a CCV “strength,” which indicates
to average five trips per month, while the second the relative importance of that vector for that
customer used to average one trip a month. As a particular customer. For example, a customer
result, the vector value for the first customer will may travel three to five times per month, but
be different from the second. that may be the highest level the customer has
the potential to achieve; therefore, the strength
This is an important insight, because now the of the trip frequency vector will be ranked lower
airline knows the first customer is reducing the than other vectors. On the other hand, the
cognizant 20-20 insights 4

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 some
understanding 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. 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 will
rules should be defined only after thorough due be willing to pay a slight premium to travel on an
diligence and impact analysis. airline in which she is a member of the frequent
flyer program in order to
Application of CCV: Driving Behavior accrue additional miles and Creating too many
Airline operators spend millions of dollars on rewards. And so, the campaigns
promotions and campaigns to attract customers. and promotions that will drive vectors can make
They acquire new customers who often enroll in the customer’s behavior need analysis difficult and
their 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 other
customers in loyalty programs is important, the decide. hand, creating too
greater benefit comes from tracking customer
Learning from Retailers
few vectors will
behavior on an ongoing basis.
Airlines can also learn from compromise the
Setting the initial value of the customer’s CCV retailer loyalty programs, heterogeneity of
vector values is the essential first step in this
process. 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 market
behavior 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 out
values becomes the starting point of the air- targeted and highly individualized promotions for
line-customer relationship and should then be years based on their customer data and loyalty
subsequently used over the customer’s lifetime programs. Airlines should consider emulating the
to continuously change the CCV vector values, way retailers analyze in-store and online spend
depending upon different customer journey and behavior and attempt to increase the customer’s
lifecycle events. total spend. Retailers do this
by performing a market basket Every customer
Throughout 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-travel
enrich the understanding of the customer. This
then 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, call
call 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 preference
tion such as rival airline frequent flyer programs
of which the customer is a member can help in
It then uses that segmenta- and so on enriches the
tion to not only understand
understanding the airline consideration set for the customer but also influ- CCV. Even non-events
that customer. Studies show that while 9 in 10 of ence her behavior based on like not flying enough
business travelers belong to at least one frequent
flyer 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 they
Thus, in theory, all else being equal, the optimal
are likely to fly, how often they fly, which sectors
pricing strategy is not to be the cheapest
they fly, etc. All this information can potentially
among all airlines but to be the most attractive
be used by airlines in tailoring their relationship
in the customer’s consideration set. Similarly, a
with customers.
customer with two active frequent flyer programs
will 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. 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 kinds
as 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 and
into 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. 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 Evaluation
Figure 3
Again, CCV-based analytics can help identify the security screening7 to reduce waiting time at the
right audience for this offer, calculate the cost of airport. The vector of time or convenience is more
such a promise and compute the returns on such important to a certain set of passengers, and they
promotions. The econometric modeling of such are willing to pay extra for it. This indicates an
promotions is crucial to ensure that the incremen- opportunity for the airlines to charge extra for
tal 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 most
A one-size-fits-all approach does not work in most
industries, and the airline business is no exception.
It is important to treat different customers dif- traveler may value access to industries, and the
ferently 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. casual
traveler, frequent flyer vs. occasional traveler,
single traveler vs. travelers with family, long-haul that additional feature at the
traveler vs. short-hop travelers, etc. Each of these time of booking, even at an extra cost, may not
customer segments has its own characteristics, only increase the yield but also do wonders for
with significant implications for airlines. the long-term loyalty of the customer. Similarly,
for a traveler with family, providing discounted
For instance, a study shows that more than one vouchers for a restaurant at the airport might be
in 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. 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 airline
retail 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. opportunity at airports is the opportunity of the facturers and automobile companies are already
in-flight time spent by the customer. While this is doing this very effectively, and airlines would be
still an evolving space, a greater understanding wise to apply lessons learned from their digital
of customer behavior can be leveraged to enrich marketing strategies. CCV can help analyze the
the customer’s in-flight experience, which can impact of social media interactions and drive
not only augment ancillary revenue and increase airlines’ digital marketing and social media
profits per trip but also be a way for the airline to strategies. Airlines need to analyze the impact
differentiate itself. of such social media behavior and try and
understand the drivers for customers choosing a
For example, in 2010, Virgin America launched the particular airline over others.
first ever digital shopping platform on seat-back
video screens. Korean Air will roll out the world’s Malaysian Airlines, for example,
An airline’s digital
first flying duty-free store onboard its first A380 has launched an application
by the end of 2011.13 With technology making such (MHbuddy) on Facebook that marketing strategy
services possible, the key is to identify whom to allows users to book and check should primarily
offer what kind of service at what price point. in for a flight while sharing
serve digitally-savvy
their trip details with their
Thus, providing Internet access to business social network. While the digital customers, and CCV
passengers through an in-flight wireless facility world is in hyperactive mode, it vectors can enable
may be a very simple and effective way of not only
increasing revenue potential but also increasing
is also important for airlines
it to make this
to differentiate and segment
customer loyalty in a hyper-competitive market. digitally-savvy customers from distinction.
For instance, Delta offers a 24-hour pass for digitally-challenged ones. An
unlimited 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 CCV
such 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 much
have a higher propensity to accept them. by digital media and the most effective way to
reach him can help airlines make optimal use of
Online/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 and
that customers are increasingly using comparison/ Peer influence: CCV-based CCV vectors can
aggregation 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 impact
also becoming an increasingly important vector in of peer influence on a customer referral campaigns to
the customer’s decision-making process. Holiday and the ability of customers to help airlines reach the
and casual travelers increasingly rely on Web influence others who span their
buzz, 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 the
independent blogs. and their connections can help network of customers
analyze their impact on peers
Social media sentiment is becoming an important they already have.
(family members/friends/office
aspect, and hence it is crucial for airline operators
colleagues, etc.) and see which
to be proactive in the online space through
vectors have a higher correlation and identify a
effective use of advanced analytics. While the
greater influence. CCV vectors can help connect
ability to listen and analyze the sentiment of
this very important linkage among the peer
online chatter is crucial, it is becoming increas-
group, which can be used effectively in designing
ingly 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 network
ability to shape key opinion leaders’ views in the
of customers they already have.
social media space is crucial.
While ancillary revenue opportunities are
Advanced digital and social media analytics can
immense, it is important for airlines to ensure
go a long way in augmenting airlines’ overall
that customers are not inundated with numerous
marketing strategy to manage brand perception.
frivolous offers and are instead offered only a few
In fact many retailers, consumer goods manu-
cognizant 20-20 insights 10

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 identify
vectors 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. tomer, including the cost of incentives and assess- The third component required to implement
ing 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 inputs
CCV is an independent engine that can provide computed by the CCV Engine and CCV Business
customer vector values for any given customer Applications are optimally
to any system or program within the airline’s applied to different business From a technical
IT landscape. From a technical perspective, the scenarios and ongoing
CCV Engine is developed using a set of advanced decision-making exercises.
perspective, the CCV
statistical and mathematical techniques and CCV analytics can also be Engine is developed
algorithms. The engine is specific to each airline delivered as a business or using a set of
and must be built based on specific customer data knowledge process outsourc-
and core intellectual property. Once developed ing (BPO/KPO) service, in
advanced statistical
and matured, the CCV Engine can be operated like which clients entrust a third- and mathematical
a black box, with minimal maintenance overhead. party specialist to identify techniques and
However, persistent change in the business envi- and make customer-specific
ronment may necessitate continuous fine-tuning recommendations offers.
algorithms.
of the algorithms and logic inside the CCV Engine
from time to time. CCV: Approaching Take-off
It is a continuous quest for airlines operators to
The second component required to implement
increase customer yield in these economically
a CCV-based solution is a set of “CCV Business
challenging, highly competitive times. Advanced
Applications” that can be leveraged by different
analytics is the most under-utilized lever today
business groups and functions within each
and has significant potential to aid and optimize
airline’s business group to optimize their
decision-making at all levels. Analyzing customers
day-to-day decisions using CCV-based analytics.
along different CCV vectors
These could be across the business value chain,
can improve airlines’ under- CCV Business
such as marketing, promotions and campaigns,
standing of customer behavior
pricing and revenue management, ancillary Applications can be
patterns and enable them to
offer services, promotions developed specific to
revenue opportunities, partnerships with other
loyalty programs, etc.
and campaigns that are an airline or could be
customized for individual
CCV Business Applications could range from a set delivered as hosted,
of simple business rules, to complex algorithms customers. This, in turn, will
specific to a business function. And since these have a higher probability of managed services.
are pure business applications, they should be driving customer behavior
fairly flexible to changing market dynamics. CCV in the desired direction that will increase the
Business Applications can be developed specific customer trip yield and profitability and ultimately
to an airline or could be delivered as hosted, increase customer stickiness and loyalty, which is
managed 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 cost
of investment required to deploy and leverage
their benefits.
cognizant 20-20 insights 12

13. Footnotes
1
“Global Media Day, Geneva,” IATA Web site, Dec. 14, 2010,
http://www.iata.org/pressroom/speeches/pages/2010-12-14-01.aspx
2
“Airlines: Customer Loyalty and Retention has Most Positive Impact,” 4Hoteliers.com, Oct. 19, 2009,
http://www.4hoteliers.com/4hots_nshw.php?mwi=6466
3
“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).pdf
4
Philip Charlton, “Targeting: The Achilles’ Heel of Frequent Flyer Programmes,” The Wise Marketer, February
2004, http://www.thewisemarketer.com/features/read.asp?id=42
5
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.pdf
6
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/2
7
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/2
8
“Survey: What Passengers Want from Airlines,” eTurboNews, March 15, 2010,
http://www.eturbonews.com/14902/survey-what-passengers-want-airlines
9
“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.pdf
10
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/2
11
“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.ashx
12
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.pdf
13
“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.jsp
15
“Ninety Major World Airlines Surveyed,” eTurboNews, Nov. 29, 2010,
http://www.eturbonews.com/19795/ninety-major-world-airlines-surveyed
16
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.pdf
17
“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. About the Author
Siddhartha Tomar is a Director in Cognizant’s Enterprise Analytics Practice and is the global leader
of analytics for multiple industries, including travel, hospitality, manufacturing, logistics, energy and
utilities. 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 clients
across the globe by providing business-specific and enterprise-wide analytical services. EAP uses
advanced statistical, mathematical and econometric models, combined with deep domain knowledge to
provide predictive and descriptive analytic solutions to drive fact-based enterprise decisions. Cognizant
EAP’s philosophy is to extend the classical hindsight analysis by providing uncommon business insights
and 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 Cognizant
Cognizant (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 in
Teaneck, New Jersey (U.S.), Cognizant combines a passion for client satisfaction, technology innovation, deep industry
and business process expertise, and a global, collaborative workforce that embodies the future of work. With over 50
delivery centers worldwide and approximately 118,000 employees as of June 30, 2011, Cognizant is a member of the
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