Essay 2 Modeling Multi-category

Purchases in Travel

Ciju Nair Washington University in St.

Louis

WEBSITE CHOICEBASKET CHOICE

2

Online Basket Purchase Process

START BROWSE BUY

Priorexperienc

e

3

Motivation An extension of the work in the first essay w.r.t. to factors

impacting browsing and purchase as applied to basket purchases

Explore differences between Portals and service provider sites for basket purchases and quantify choice of same site basket purchases (methodological contribution)

Address the gap in literature as no known prior work exists that helps us understand

Travel category purchases better Multi-category or basket purchases in the online environment

Extend choice literature research to the online environment. Very little work in multi category purchases even in traditional choice literature

4

Motivation Though basket purchases constitute approx. 20% of

transactions they are associated with higher revenue (3-5 times) as they comprise of 2 or more products on average for each household

Travel Category Purchases

Unique Households

Transactions

(6 Mos)

Transactions

(Last 3 Mos)

Transaction sets

Airline Only 6029 8074 3754 3754Car Rental Only 1072 1578 734 734

Hotel Only 2921 4054 1799 1799Car and Hotel 145 364 181 76Air and Hotel

856 2620 1233210

Air and Car Rental 158Air, Car and Hotel 65

Total 8937 16690 7619 6796

5

Do travel portals have a significant advantage when it comes to basket purchases?

Do websites differ in their attractiveness and conversion effectiveness for basket purchases?

Do demographic and behavioral factors impact basket purchases?

Which basket combination has a relatively stronger base level preference?

What we find

Yes, we find demographic and behavioral factors have an impact in determining basket purchases

Websites differ in their strengths, relative attractiveness and conversion effectiveness

Travel portals do not have a relative strength over service provider websites when it comes to basket purchases

Car and Hotel indicating preference for road travel. Maybe due to post 9-11 effects as period of analysis is Q3/4 of 2002

6

Research Objective Analyze the difference between travel portal and

vendor website choice wrt basket as well as single product purchases

Understand factors that affecting website choice when it comes to basket purchases and their relative comparison to single product purchases

Investigate demographic as well as behavioral factors affecting basket purchases in the travel category.

Prior browsing experience translates into “learning effect” and prior purchase experience translates into “inertia effect”

7

Clickstream Prior Research

Traditional multi category choice

models

Online Browsing and Purchase of

Airline ticketsOnline Browsing and Purchase of basket and site choices on multiple websites

Bucklin and Sismeiro 2003Park & Fader 2004

Nair, Chan and Cheema 2009

(working paper)

This paper

Modeling Online Browsing or

Purchase

Single or multi -category

Single category

Multi category

Multi category

Traditional choice models

Single category Gudagni & Little 1983

Harlem & Lodish 1995Seetharaman et al. 2005

8

Determinants of Basket choice

Basket preference Limited information processing and

consideration set (Shocker et al. 1991, Roberts and Lattin 1997)

Demographics Younger consumers search more in general

(Ward and Lee 2000) Broadband users search more (Yonish, Delhagen

& Gordon 2002)

BASKET CHOICE

9

Determinants of Basket choice

Prior Category Experience reduces search Prior product & category experience (Srinivasan

and Ratchford 1991, Brucks 1985) Inverted U relationship (Bettman and Park 1980,

Johnson and Russo 1984)

Cost and benefits of search Perceived financial risk / benefit increases

search (Punj and Staelin 1983)

Prior Purchase increases likelihood State dependence and variety seeking

literature

BASKET CHOICE

10

Determinants of Site Choice for Basket Purchase

Site Preference Primacy effect, consideration set and search

costs (Anderson 1965) Store choice literature (Keng & Ehrenberg 1984, Rust

& Donthu 1995, Bell and Latin 1998, Bell and Lattin 1998)

Demographics Income dampens price sensitivities in online

markets (Degaratu, Rangaswamy and Wu 2000)

WEBSITE CHOICE

11

Determinants of SiteChoice for Basket Purchase

Prior Category Experience Product experience (Bellinger et al. 1978, Janiszewski

1998, Roy 1994) Frequent visits (Moe and Fader 2004, Brynjolfsson and

Smith 2001) Category knowledge (Brucks 1985)

Prior Purchase State dependence and inertia (Seetharaman,

Ainslie and Chintaguta 1999 )

WEBSITE CHOICE

12

6 months of browsing & purchases: July 2002 to December 2002 100,000 panel households 8937 households made travel purchases

Selection criteria

8937 households satisfy selection criteria

Comscore Data

July December

OctoberEstimation

(last 3 months) Prior Experience(first 3 months)

13

Modeling Approach Model the two stages of consumer decision process

Basket Choice Website Choice for Basket Purchase

STAGE 1: BASKET CHOICE

STAGE 2: WEBSITE CHOICE STAGE 1:

BASKET CHOICE

STAGE 2: WEBSITE CHOICE

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Basket Choice Set

Airline Only (49%)*

Car Rental Only (9%)

Hotel Only (24%)

Car and Hotel (2%)Normalized option

Air and Hotel (7%)

Air and Car Rental (5%)

Air, Car and Hotel (4%)

* Figures in brackets are purchase shares

15

Site Choice Set Expedia Orbitz Travelocity Hotwire Other Travel portals Other sites*

Normalized to “other sites” * (includes other travel portals and all other airline, car rental and hotel websites)

21 choice options considering all 2 way combos

Sampling of Other sites

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Website Type Product Category

Airline Car Rental Hotel

Travel Portals

Expedia Orbitz

Travelocity Hotwire

Other Travel portals Other sites*

* Sampling of other sites (includes other travel portals and all other airline, car rental and hotel websites)

Southwest Avis Hilton Delta Budget Sixcontinentshotels.com

American Hertz Hotels.com Jetblue Alamo Choicehotels.com

US Airways Enterprise Mariott

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A Discrete–Discrete Model of Basket and Site Choice

STAGE 1 BASKET CHOICE Decide on

basket of travel products to purchase

based on needsDiscrete

STAGE 2 WEBSITE CHOICE Choose a single or

combination of websites to purchase basket of travel

products Discrete

Priorexperienc

e

18

* *

*

1 if and only if , cict ict idt

f f f fc ic

fict it it ict ict

B B B d

B SZ H I

Stage 1 : Discrete Choice of Basket Choice

Categoryexperience

Latent Variabl

e

DemographicsBasket specific

experienceRandom Shocks

Basket combinations c=1 to 7, Car and Hotel choice is normalized to 0

PriorPurchase

19

Estimation: Stage 1

* *

1

1

1

Pr( 's history of basket preference) Pr( , )

1

i

ff f f f fi c ic it c it ic ict

f f ff f fit it id idtd id d

T

ict idtt

T Z H S I

CZ H S It

c

i B B d

e

e

We then estimate the first stage of the model to understand basket preferences as below

Hotel

Travel Portal Other Site Air Travel Portal

, , , ,A H A Hj t j t t j t j tV V u , , , ,

A H A Hj t o t t j t o tV V v

Other Site , , , ,A H A Ho t j t t o t j tV V v , , , ,

A H A Ho t o t t o t o tV V u

20

Stage 2 : Discrete Choice of Website for basket purchase

Indirect utility from Air purchase

Indirect utility from Hotel purchase

Utility from making both

purchases on a Travel portal

Utility from making one purchase on a Travel portal and another from other site

2,

2,

2 2, ,

(0, )

(0, )

+ (0, )

Am t A

Hn t H

A Hm t n t A H

N

N

N

21

Stage 2 : Discrete Choice of Website for basket purchase

21

Categoryexperience

Latent Variable

DemographicsSite specificexperience

Prior Purchase

Randomshocks

* pj

p p p pijt ijtit i ij ijtV Z H S I

Hotel

Travel Portal Other Site Air Travel Portal

, , , ,A H A Hj t j t t j t j tV V u , , , ,

A H A Hj t o t t j t o tV V v

Other Site , , , ,A H A Ho t j t t o t j tV V v , , , ,

A H A Ho t o t t o t o tV V u

, 0 1 2

, 1 2

other indep variables

other indep variables

note: is an indicator variable that takes value 1 if both purchases are on same website is

mm t m j

mn t j

m

j

u loyalty loyalty

u loyalty

loyaltyloyalty

an indicator variable that takes value 1 if both purchases are on a travel portal

Probability of a consumer purchasing airline and hotel from website m and website n respectively can be written as

The likelihood is expressed as

Stage 2 : Discrete Choice of Website for basket purchase

i i iPr( | ).Pr( | ).Pr( | ) ( ; )i iL A B C dF , , ,where { , , ; ; ; }A H C

i j t j t j t t tj u v

23

As the likelihood is highly non-linear we use a simulated maximum likelihood approach to estimate this problem using Neadler-Mead optimization routines

To avoid complexity and ensure tractability we estimate stage 1 and stage 2 independent of each other

Estimation: Stage 2

1

1ˆ Pr( | ).Pr( | ).Pr( | )ns

s s si i i i

s

L A B Cns

24

Model Estimation : Stage 2 The algorithm used to estimate the second stage of

the model is as shown below Step 1: Take 1000 draws of (6x6) for each combination of

website choice Step 2: Evaluate A as

Step 3: Similarly evaluate B as

Step 4: Evaluate C for each ,

st

1000

, , , ,1

1 Prob( max( , ) )1000

H H H Hn t k t t k t n t tks

V v k n V u

1000

, , , ,1

1 Prob( max( , ) )1000

A A A Am t k t t k t m t tks

V v k m V u

1000s

1

1Prob(m,n)= [ Prob( ).Prob( ){ 1} Prob( ){ 1}]1000

s s

s

A B C

25

Basket Preference compared to Car and Hotel purchase (normalized option)

Air only and Hotel only purchases are most preferred Car only is least preferred compared to all basket purchases Combination of all three products is most preferred bundle

after car and hotel basket

Results: Base level preferences

BASKET CHOICE

26

We find directional evidence (not significant) that consumers who make basket purchases on average are more likely from a larger household, older, have a broadband

connection, higher income and have a child in the family

Results: Demographic factorsBASKET CHOICE

27

Prior basket specific browsing effects are more pronounced for purchasing a single product as opposed to a basket of products

Prior travel category browsing positively impacts purchase

We find directional evidence (not significant) that prior basket purchase doesn’t seem to increase the likelihood for repeat purchase of same basket/combo

Results: Prior browsing and purchase experience BASKET

CHOICE

28

Consumers who browse more have a higher propensity to make a purchase if they are either older or have higher incomes

Consumers who made a prior purchase were significantly predisposed to make a purchase especially if they were either older or have higher income

Results: Interaction effectsBASKET CHOICE

29

We find higher residual variance amongst consumer preference for

Air & Car rental basket combination (0.2472) Car rental only (0.1283) and Air, Hotel and Car rental combination (0.0132)

purchases We also find the covariance to be negative

indicating consumers could be considering these transactions as substitutes

Hotel only and Air & Hotel combo (-0.0040) as well as Hotel only and Air only (-0.0011) purchase

Results: Residual varianceBASKET CHOICE

All basket purchase on ORBITZ or

30

There is a higher likelihood for consumers to complete basket purchases on

a combination of Travel portal and other site(mostly airline) or Orbitz when compared to Other site only (normalized option)

Results: Base level preferences

+ Other Site

WEBSITE CHOICE

Consumers have a base level preference to make basket purchases from the same website (barrier to switch) and this effect dominates most other factors including loyalty or state dependence effects arising from a previous basket purchase

We also find that consumers have a lower base level preference of purchasing their basket from travel portals collectively as a group

31

Results: Base level preferences

WEBSITE CHOICE

32

A child’s presence in the household positively influences basket purchases across various site choice combinations (compared to outside option)

Consumers are less likely to complete basket purchases when they are from a larger household, older, have higher

income, broadband connections

Results: Demographic factorsWEBSITE CHOICE

33

Consumers who have a prior site specific browsing history on following combinations of sites are interesting Most Likely to make a basket purchase

Orbitz and Other sites (mostly airline sites) and Orbitz and Other travel portals

Least likely to make a basket purchase Expedia and Orbitz

Prior category browsing history in travel category does significantly and positively influence the likelihood of making a basket purchase from all site choice combinations

Results: Prior browsing and purchase experience

WEBSITE CHOICE

34

Older consumers or those with higher income had a significant difference in the way they influenced basket purchases across all site combinations decreasing the likelihood when the prior

browsing history was higher (learning effect) and

increasing the likelihood when prior purchase history was higher (inertia effect)

Results: Interaction effectsWEBSITE CHOICE

35

We find the largest residual variance on site preference for basket purchases associated with a single site to be on Expedia (24.791) indicating that either Expedia

attracts a diverse target audience or price discriminates amongst its audience better and

makes the right basket offerings to the right consumer. The residual variance was least pronounced for

basket purchases on Orbitz (0.748) indicating profile of consumers making basket purchases on

Orbitz to be very similar or those that knew exactly what to get and where on Orbitz.

Results: Residual varianceWEBSITE CHOICE

36

Methodology Proposed two stage model of basket and website choice

Helps us investigate cost of switching websites for basket purchases and quantify loyalty effects

Leverages browsing and prior purchase info to explain purchases Findings

Highlights impact of factors affecting consumer basket and website choice using a two stage model

Provides new insights on differences between travel portals and other sites for basket purchases

Managerial implications Provides insight on consumer targeting, basket and website

choice in addition to understanding the relative strengths of various travel sites

Can be used as a benchmark model to investigate effect of exogenous changes e.g. marketing mix or policy changes effects of covariates (e.g. dynamic impact of last purchase) using

simulation

Contribution

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Next Steps and Future Research

While we have demonstrated the importance of prior experience, purchase and demographic factors on basket purchases and website choice we believe our understanding would gain a lot if we could investigate the impact of

marketing mix variables i.e. media spend especially digital in paid search, banner displays, text links and

also differentiate impact of pricing and promotions within business and pleasure travel.

Thank YouA recent version of this paper is available online at:http://students.olin.wustl.edu/~NAIRC/Online%20Search%20MS%20draft.zip