Jetstar Airways: HOW MODELING GUIDED THE BRAND MIGRATION STRATEGY OF A LOW-COST CARRIER

Abstract

This article describes the application of a dynamic choice model of consumer preferences. It supported Jetstar, a subsidiary of Australia's leading airline, QANTAS, to effectively and profitably compete in the low-cost carrier marketplace. The evolution of the Jetstar strategy is traced from its initial position through to its efforts to attain price competitiveness and service parity. The model helped service design and pricing initiatives to shiftthe perceived performance of Jetstar relative to its competitors. It further indicated how the airline could move market preferences towards areas in which it had competitive advantage. The Jetstar market share went from 14.0 % to 18.1 % during the first five quarterly waves of the research, while profits went from US $ 79 million 2006 / 07, before the study was commissioned, to US $ 124 million in 2008 / 09. Today, Jetstar remains the only successful low-cost offshoot of a full service airline in terms of shareholder returns. [PUBLICATION ABSTRACT]

Headnote

This article describes the application of a dynamic choice model of consumer preferences. It supported Jetstar, a subsidiary of Australia's leading airline, QANTAS, to effectively and profitably compete in the low-cost carrier marketplace. The evolution of the Jetstar strategy is traced from its initial position through to its efforts to attain price competitiveness and service parity. The model helped service design and pricing initiatives to shiftthe perceived performance of Jetstar relative to its competitors. It further indicated how the airline could move market preferences towards areas in which it had competitive advantage. The Jetstar market share went from 14.0 % to 18.1 % during the first five quarterly waves of the research, while profits went from US $ 79 million 2006 / 07, before the study was commissioned, to US $ 124 million in 2008 / 09. Today, Jetstar remains the only successful low-cost offshoot of a full service airline in terms of shareholder returns.

Headnote

Keywords:

Positioning, Price Competition, Segmentation, Bayesian Statistics, Airline Marketing

Jetstar - Understanding Potential for Improvement Prior to Take off

Jetstar was established in May 2004 as a budget airline by QANTAS, Australia's foremost domestic and international carrier. Its purpose is to cover the low-cost segment of the market, which began in around the year 2000 with the launch of a competitor, Virgin Blue. Until the time Jetstar began operations, Virgin Blue had been successfully eroding the QANTAS market share by attacking it from below as a low-cost provider. In response, Jetstar was also designed to be a no-frills carrier, predominantly targeted at the leisure market.

Jetstar initially achieved some success in this role, reaching a market share of 14 % by the beginning of 2008. However, market research results suggested that Jetstar was not generally perceived as competitive in value to Virgin Blue. By the end of 2007, perceptions about Jetstar's lack of price competitiveness were inconsistent with its actual fares in the market. Moreover, service quality across the board was not perceived to be as strong as that of Virgin Blue. Surprisingly, Jetstar was perceived as more expensive than Virgin Blue, even though the actual airfares were nearly identical. This limited the effectiveness of Jetstar as a fighter brand, and retarded its financial results. To avoid the financial stress (and ultimate demise) suffered by low-cost brands of other major carriers, such as British Airways' "Go", United's TED, and Delta's "Song", Jetstar saw a need to improve by changing consumer perceptions, through focused pricing and service initiatives, together with a compelling communications strategy.

Finding Out What to Do Best

To improve its position, Jetstar needed new pricing formats, adaptive service design changes, and effective communications. To design such services, Jetstar management required information on the drivers of evaluation and choice amongst the target segment. They wanted to learn how Jetstar stood relative to its competitors, how drivers and perceptions varied across the population, and the relation of service design features to perceptual drivers. The Jetstar requirements were to understand the market on a continuous basis in order to firstly assess customer needs, then develop a strategy to address these needs, followed by subsequent monitoring to judge the degree to which the strategy had been successful. These strategies were expected to be adapted and refined over time in response to changes in perceptions and needs. Commonly used comparative statics do not allow a detailed study of the interaction of marketing activity and market analysis over time, therefore a new dynamic modeling approach was developed to meet a number of requirements in this situation:

(a) simultaneously accommodate global value attributes and micro process attributes that underlie the value attributes,

(b) link up consumer preferences, service performance improvements and share/profit,

(c) capture heterogeneity across the population, and

(d) represent how beliefs and preferences change over time in response to service and pricing initiatives.

Simultaneously handling these four requirements is rather challenging. Previously, two tiers of regression model, one at the global level, followed by a series of models at the micro levels or a LISREL approach to modeling multidi- mensional, hierarchical constructs were common for comparable tasks. In this study, on the other hand a Bayesian hierarchical model conceptually integrates macro level market share evolution with micro level attribute evaluation for service design into a single model and also captures individual-level heterogeneity, an important factor which has often been ignored in service management.

Applying a New Dynamic Choice Modeling Approach

In service research, one of the key management metrics is customer perceived value which forms the basis for consumer choice among alternative suppliers. It is determined by price and quality which in turn are linked to process attributes. For Jetstar, initial qualitative research found that consumers consider operational performance and reputation to be the key components of airline quality. They were therefore included in the model. To improve the value of quality and price, companies need to know how to improve their performance at an actionable micro process level. Consequently, such micro level attributes need to be included in the analysis.

Figure 1 depicts the model of global and micro process attributes relevant to this airline environment and the links between them. As mentioned earlier, Jetstar management expected customer perceptions and needs to change over time in response to their pricing, communications and service process activity. These dynamics are illustrated in Figure 1 for the model parameters that are re-estimated for each survey wave (e.g., ...).

Management Actions Based on Results

Activities and their consequent results during the 15 months within the time frame of the 5 waves of the survey are summarized in Table 1.

Estimating the Initial Position

Wave 1 served as a baseline measure of how far behind Jetstar was on price and quality (a combination of perceived operational performance and perceived reputation) perceptions. Figure 2 shows that at the beginning of the new strategic initiative, Jetstar had a 6.9% perceived price disadvantage to Virgin Blue (7.05 and 7.57 respectively on the 10 point scale). While this may not sound a lot, it is quite important at the price-conscious end of the market.

Figure 3 shows that the overall quality disadvantage for Jetstar is even greater, at 22.3 % (6.02 versus 7.75). This invites a naïve interpretation, namely, that Jetstar should focus on quality, since it lags behind Virgin by a much greater degree on quality than it does on price. However, the model reveals that price is much more important to customers. Additionally, since price is a search attribute and quality an experience one, Jetstar management considered the response function of price to be more sensitive to management activity in the short term than of quality. Table 2 shows that price is the most important global attribute, with an estimated coefficient of 4.464. This is followed by operational performance (3.392), and then reputation (2.973). The model further expressed these global attributes in terms of the constituent subattributes that drive them, showing management where the most traction can be gained with improved pricing and service design. Subattributes with the largest estimated coefficients were identified in wave 1 (and the subsequent waves) and these primary drivers of competitiveness could be addressed with corresponding actions.

Analyzing Individual Differences in Consumer Preferences

Furthermore, the model makes it possible to understand individual-level variation in the importance weights for the key global attributes of operational performance and price. Such an analysis is not possible with a simple regression model. Figure 4a plots the individual-level random effects for the importance weights for performance and price in wave 1. This analysis underlines the importance of acting on price. Two things are apparent. First, there is greater variation in the ... random effects, which range between - 1 and 1, while ... ranges between - 0.5 and 0.5. This indicates that the price attribute generates more extreme importance weights than performance. Second, the relationship between ... and ... is linear and negative, with a regression line fitted to these observations showing that price random effects are about twice those of performance. Indeed, those that place high importance on price place low importance on performance and vice versa. That is, for price sensitive customers, it is harder to compensate for poor perceived prices with improved performance, because of their lower quality coefficients. Although a price/quality trade-offis generally expected, Figure 4a depicts the strength of this trade-off, which very much favors price in this case.

Activities and Results Step 1: From "Everyday Low Prices" to a "Guaranteed Lowest Price"

At the time of wave 1 (January 2008), Jetstar was almost exclusively using a "low price" message in its communications, but the points of proof to make this credible were not evident to consumers. Based on these results the objective of management was to gain at least a perception of price parity and therefore it changed the theme of Jetstar communications and advertising to focus on a price guarantee. In its key messages, Jetstar promised that it would offer a 10 % price reward to any customer that found "a lower fare online on the same route for a comparable time".

As a result of the initiatives, the price perception of Jetstar relative to Virgin Blue improved dramatically (see Figure 2). From a 6.9 % deficit in March 2008, price perceptions of Jetstar changed markedly to a 2.5 % deficit in only three months (7.42 versus 7.62). In wave 4, Jetstar maintained its price perceptions, while Virgin Blue lost ground. By March 2009 (wave 5 of the quarterly tracking), Jetstar was within 1.3 % of price parity overall and well ahead of Virgin on the key pricing subattributes it was targeting.

Activities and Results Step 2: A Focus on Cost-Effective Service Quality

With the achievement of perceived price parity for a large percentage of the population, Jetstar addressed its perceived deficit in quality. Jetstar tackled that gap by focusing on a few specific subattributes which had high importance and offered good opportunity on which to achieve a point of difference over Virgin Blue at low cost. Interestingly, one criterion for attribute perceptions was that improvements should not lead to undue cannibalization of the flagship "QANTAS" brand name amongst its target market.

Service quality improvements also had a substantial effect on consumer perceptions. The overall quality gap was narrowed from 22.3 % to 17.9% (6.5 versus 7.9 in Figure 3 in wave 1) and continued to improve. By wave 3 in Q3 2008, on average some 31 % of the perceived service quality disadvantage for Jetstar was overcome (see Figure 3 where the difference declines from 22.3 % to 15.5 %), with particularly strong results on Jetstar's key target attributes. By the end of the period covered by this study, the average quality gap had narrowed by 45 % (see Figure 3, where a 22.3 % deficit in wave 1 had been reduced to a 12.2 % deficit in wave 5).

Activities and Results Step 3: Changed Preferences for the Whole Market

Given the success evident in phases 1 and 2, the strategy of maintaining price comparability and moving to focused differentiation, Jetstar saw no need to dramatically alter its marketing activity. Because of lags in consumer belief and updating importance weight, Jetstar could still gain further advantage by continuing its current message and service improvement, since Virgin had presented no effective response.

Given that Jetstar, and also Virgin, evolved from a low price strategy to one of good quality at a low price, it is interesting to see if this trend in price/quality trade-offis reflected in the consumer heterogeneity of tastes. Figure 4b plots the price and performance random effects in wave 5, thereby updating the wave 1 situation in Figure 4a. Here, the dispersion in performance importance has changed to a much more equal footing to those of price. The slope of the regression line has declined substantially from - 1.85 in wave 1 to - 0.56 in wave 5. This is evidence that the market has changed in terms of its preferences even over this 15 month period. No doubt the heavy Jetstar advertising combined with its tangible service quality improvements over this time period contributed to these revised customer preferences.

Assessing the Benefits of the Applied Model

The hierarchical model with parameters estimated at the individual level allowed a study not only of how service design and pricing initiatives shiftthe perceived performance of Jetstar relative to its competitors, but also how the airline could move market preferences towards areas in which it has competitive advantage. In particular, the following advantages over a traditional "sequence of models approach" were achieved:

* Adaptive management of marketing activities towards the long term vision

A marketing intelligence system that reflects the interaction between activities and results is of high value, especially in a dynamic and reactive environment like the airline business. The simultaneous handling of micro and macro level attributes provides a strong nexus between specific management actions and market outcomes, mediated by target market preferences and beliefs. As opposed to comparative statistics, this model helps to establish marketing actions that migrate customer beliefs in a cost-effective way. It helps to provide feedback between each stage on a series of actions over time and enables the adaptive management of marketing activities towards the long-term vision on an evolutionary basis.

Further, consumer differences and dynamics, both of beliefs and tastes, can be accounted for. Being able to monitor individual differences in consumer preferences and how they change helps to develop targeted marketing activities. It supported changing the organization from being efficient, safe, responsible and consistent, to one with a stronger customer service orientation. A major cultural transformation was undertaken, largely due to a service improvement program, supported by the CEO, who visited every Jetstar port to emphasize the expected behaviors. To cement the behavioral change, Jetstar redefined its key performance indicators (KPIs), with 40 % of executives' bonuses linked to the market research levels for the quality drivers chosen by Jetstar.

* Improved forecasting performance

Jetstar was also able to greatly improve on its forecasting performance, using the combination of consumerlevel and market-level techniques. The correlation between the model's share predictions for Jetstar and the actual share realized is very high, at 0.92. In an industry with an enormous cost of excess capacity, in terms of planes, crew, and ancillary facilities, the resultant better forecasts also had huge direct cost savings.

Flying High Based on Model Data

The market share for Jetstar has increased by 29 % (4.1 share points, unweighted by availability) in the first twelve months of this research/strategy initiative. Virgin has maintained its strong position on the price/quality combination, being "value for money". By contrast, Jetstar was initially in a poor position, with perceived mediocre price competiveness and low quality. However, by wave 5, Jetstar was in a position almost comparable to Virgin in the eyes of a large proportion of the target market. Moreover, Jetstar has improved its perceptual position while increasing its profit, while Virgin Blue has remained relatively stationary, but accrued major losses. The Jetstar revenue and profit contribution increased dramatically during the period of the study and remained on a strong upward trajectory, further on. By focusing in areas directed by the research and designing a migration path to its vision, Jetstar has reached the stage where in the first half of calendar year 2009, it provided over 100 % of the QANTAS group's profits. That is, without the contribution of Jetstar, the QANTAS group would have recorded a significant financial loss. It ascribes US $ 35 million of its improved profit performance to initiatives associated with the study.

The potential benefits have been realized by the commitment of top management to its results and the engagement of staffto the implementation of its recommendations through their new KPIs which were defined based on the data.

Sidebar

/ / / A model helps to establish marketing actions that migrate customer beliefs in a cost-effective way.

{ Box 1 }

Mode l Esti mati on

To capture differences in consumer tastes, as well as variations in their perceptions, a hierarchical Bayes model was developed. It consisted of two inter-related layers.

The first or top layer was a multinomial logit model for consumer choice of the probability that respondents chose a specific airline. At this top layer, the variables are respondent ratings for each airline on the "global attributes" of Performance, Reputation and Price. Therefore, the ßit are three dimensional vectors, showing the importance weight that individual i places on these attributes.

In the second layer, the global attributes are functions of a set of relevant micro process subattributes. For instance, the subattributes for Performance include "good route structure", "easy check-in" and "easy to reach airport." The complete list of subattributes is given in Figure 1, with 12, 10 and 7 subattributes for performance, reputation and price respectively. The Υ parameters are importance weightings placed on each subattribute corresponding to individual global attributes and subattributes.

Initially, the Υ were allowed to vary by airline, but the empirical results did not show significant variation across airlines.

The model captures unobserved heterogeneity in respondent preferences through the distributions around ßi and Υ.

Full technical details are presented in the web appendix of the original article.

» To improve the value of quality and price, companies need to know how to improve their performance at an actionable micro process level. «

{ Box 2 }

Sa mple and Questi onnaire Desig n

Domestic leisure travelers departing from Sydney, Melbourne and Brisbane in Australia form the target market for the 20 minute online survey. Respondents (between 1,600 and 2,000 per wave) were selected so as to be demographically representative of residents in New South Wales, Victoria and Queensland. The results of the first five quarterly survey waves, with the first quarter being January to March 2008, are reported in the study.

Of the five airlines operating in this market, Jetstar, Qantas, Rex (Regional Express), Tiger Airways (owned by Singapore Airlines) and Virgin Blue, respondents were queried about just two to avoid fatigue. These airlines represented a random selection from travelers that have flown in the past year but also allowed respondents to rate airlines that they had not flown, but felt they had sufficient familiarity to evaluate.

» The simultaneous handling of micro and macro level attributes provides a strong nexus between specific management actions and market outcomes. «

» Jetstar has improved its perceptual position while increasing its profit. «

{ Summary }

Jetstar Airways How Modeling Guided the Brand Migration Strategy of a Low Cost Carrier

John Roberts, Peter Danaher, Ken Roberts, and Alan Simpson

This article describes the application of a dynamic choice model of consumer preferences. It supported Jetstar, a subsidiary of Australia's leading airline, QANTAS, to effectively and profitably compete in the low cost carrier marketplace. The evolution of the Jetstar strategy is traced from its initial position through to its efforts to attain price competitiveness and service parity.

To improve Jetstar first wanted to learn its relative image-position compared to competitors, how drivers and perceptions varied across the population, and the relation of service design features to perceptual drivers on a continuous basis. Strategies were implemented based on quarterly results and these were then expected to be adapted and refined over time in response to changes in customer perceptions and needs.

A new Bayesian hierarchical model conceptually integrates macro level market share evolution with micro level attribute evaluation for service design into a single model. It also captures individual-level heterogeneity, an important factor which has often been ignored in service management. Global attributes are expressed in terms of the constituent subattributes that drive them, showing management where the most traction can be gained with improved pricing and service design. Subattributes with the largest estimated coefficients were identified in wave 1 (and the subsequent waves) and these primary drivers of competitiveness could be addressed with respective actions.

The model further revealed that consumers who place high importance on price place low importance on performance and vice versa. That is, for price sensitive customers, it is harder to compensate for a poor perception of prices with improved performance. Although a price/ quality trade-offwas generally expected, the strength of this trade-offvery much favored price in this case.

As opposed to comparative statistics had several advantages:

* It helped to establish marketing actions that migrated customer beliefs in a cost-effective way.

* It helped to provide feedback between each stage on a series of actions over time and allowed for the adaptive management of marketing activities towards the long-term vision on an evolutionary basis.

* Jetstar was also able to greatly improve on its forecasting performance, using the combination of consumer- level and market-level techniques.

* To sum up, the approach not only helped service design and pricing initiatives to shiftthe perceived performance of Jetstar relative to its competitors. It further indicated how the airline could move market preferences towards areas in which it had competitive advantage.

The Jetstar market share went from 14.0 % to 18.1 % during the first five quarterly waves of the research, while profits went from US $ 79 million in 2006/07, before the study was commissioned, to US $ 124 million in 2008/09. Today, Jetstar remained the only successful low-cost offshoot of a full service airline in terms of shareholder returns.

Keywords:

Positioning, Price Competition, Segmentation, Airline-Marketing

{ Deutsche Zusammenfassung }

Jetstar Airways: Sch ärfung des Markenprofils einer Billig -Airline mithilfe eines Positionierungsmodells

John Roberts, Peter Danaher, Ken Roberts und Alan Simpson

Dieser Artikel beschreibt die Anwendung eines dynamischen Entscheidungsmodells, das auf erfragten Kundenpräferenzen basiert. Es lieferte Jetstar, einer Tochter der größten Australischen Fluglinie "Quantas", die Datenbasis, um sich erfolgreich im Billigsegment zu positionieren. Die Evolution der Jetstar Strategie wird über mehrere Teilschritte hin zu einer wettbewerbsfähigen Preisstrategie und Serviceparität beschrieben.

Den Ausgangspunkt für Verbesserungen lieferte die relative Imageposition von Jetstar im Vergleich zu den wichtigsten Mitbewerbern. Die Positionsbestimmung lieferte Informationen über Erfolgsfaktoren und Kundenwahrnehmungen in unterschiedlichen Marktsegmenten. Auf der Basis der Ergebnisse entwickelte das Management Service-, Preis- und Kommunikationsstrategien. Man wiederholte die Erhebungen vierteljährlich, um - je nach den beobachteten Veränderungen der Kundenwahrnehmungen und -bedürfnisse - die jeweiligen Strategien zu adaptieren.

Das Besondere an der Datenaufbereitung besteht in der unmittelbaren Verknüpfung von Makro- und Mikroebene in einem hierarchischen Bayes Modell. Marktanteilsveränderungen stehen in direktem Zusammenhang mit Servicedesignaspekten. Globale Attribute werden durch entsprechende, sie beeinflussende Unterattribute beschrieben. Das Management sieht sofort, bei welchen Preis- bzw. Serviceaspekten die beste Hebelwirkung erzielt werden kann.

In der ersten Erhebungswelle wurden jene Aspekte aufgegriffen, bei denen die Daten das größte Wirkungspotenzial aufzeigten. Die Analyse verdeutlichte, dass ein Schwerpunkt auf Preismaßnahmen erfolgversprechender war als einer auf Qualitätsaspekten. Mit Maßnahmen wie einer Bestpreis-Garantie wurde deshalb vor allem die Wahrnehmung der Jetstar Preise verbessert.

Zusätzlich machte das Modell die Präferenz- und Wahrnehmungsunterschiede auf der individuellen Ebene der Kunden sichtbar. Das ist für Gestaltungsüberlegungen im Servicemanagement von großem Wert und war bei traditionelleren Regressionsmodellen so nicht möglich. Die Analyse ergab, dass Konsumenten, denen der Preis besonders wichtig war, auf die Ausgestaltung der Leistung weniger Wert legten und umgekehrt. Bei preisbewussten Konsumenten waren die beiden Aspekte so unterschiedlich gewichtet, dass ein als ungünstig wahrgenommener Preis mit verbessertem Service kaum zu kompensieren war. Das Ergebnis war zwar in diese Richtung erwartet worden, die Stärke überraschte aber und bestätigte die Fokussierung auf Preismaßnahmen.

Das Modell hat gegenüber herkömmlichen Absatzstatistiken bzw. Wellenbefragungen vor allem folgende Vorteile:

* Es ermöglichte an den Präferenzen der Kunden ausgerichtete Marketingaktivitäten und eine kostengünstigere Veränderung der Kundenwahrnehmungen.

* Das laufende Feedback ermöglichte die rasche Beurteilung der Aktivitäten im Zeitablauf und deren laufende Anpassung im Hinblick auf ein langfristig angelegtes Ziel.

* Die Verknüpfung von Kunden- und Marktdaten er- möglichte Jetstar darüber hinaus verbesserte Markt- prognosen.

* Es konnten nicht nur Qualitäts- und Preisaspekte gezielt angegangen werden. Das Modell half auch, die Marktpräferenzen der Kunden insgesamt in eine Richtung zu lenken, in der Jetstar Wettbewerbsvorteile genoss.

Der Marktanteil von Jetstar stieg während der ersten fünf Quartalsmessungen von 14,0 % auf 18,1 %. Parallel dazu gelang es, den Ertrag von 79 Millionen US-Dollar im Jahr 2006/07 (vor Durchführung des Projekts) auf 124 Millionen US-Dollar im Jahr 2008/09 zu steigern. Damit war Jetstar in diesem Jahr die einzige in Bezug auf Aktienerträge erfolgreiche Billigtochter einer Full- Service-Fluglinie.

Schlüsselbegriffe:

Positionierungsmodelle, Preiswettbewerb, Kundensegmentierung , Marketing-Mix-Gestaltung, Airline-Marketing