Relationship Marketing at StubHub - Wharton Customer …...WHARTON CUSTOMER ANALYTICS INITIATIVE PAGE 25 MORE ABOUT WCAI The Wharton Customer Analytics Initiative (WCAI) is the preeminent

PAGE 1WHARTON CUSTOMER ANALYTICS INITIATIVE

Relationship Marketing at StubHub

Research Opportunity Webinar

25 March 2011

CUSTOMER ANALYTICS INITIATIVE


INTRODUCTIONS

Jeff SpauldingDirector of Relationship Marketing

Grace LauRelationship Marketing Manger

Ming TengHead of Information Analytics

Dan HarringtonSenior Information Analyst

Elea McDonnell FeitResearch Director, Wharton Customer Analytics Initiative

Eric T. BradlowK.P. Chao Professor

Professor of Marketing, Statistics, and Education

Vice-Dean and Director, Wharton Doctoral Programs

Co-Director, Wharton Customer Analytics Initiative


ABOUT STUBHUB


ABOUT THE STUBHUB RELATIONSHIP MARKETING TEAM

Organizational Mission

• Enhance the customer experience with StubHub to foster customer loyalty

Organizational Goals

• Know our customer!

• Improve value proposition to our customer

• Approach 1:1 marketing

• Provide guidance within StubHub to give customers an experience consistent with their CLV to StubHub

Organizational Objectives

• Increase number of active customers

• Increase repeat transactions/purchases per existing customer

• Reduce attrition

• Increase transaction cadence

• Improve CLV

• Improve customer satisfaction and influence other channels

• Reward our best customers


THE STUBHUB PURCHASE PROCESS

1

User reviews a list

of events, along with

the event date,

venue and the range

of prices for tickets

available for that

event.

User clicks “Buy” to

see what tickets

available to buy for

the event.



User reviews a list

of available lots of

tickets for the

particular event, the

seat location and

the price.

Supply is very

seldom constrained;

98% of event page-

views have tickets

available.

User clicks

“Go” to get more

information about

the lot of tickets.

2



3

User reviews

detailed information

about how tickets

will be delivered and

what the fees will

be.

The user clicks

“next” to purchase

the tickets.

At this point, the

user is forced to log-

in (or create an

account, if they don’t

already have one.)

Only user behavior

after log-in is

tracked.



After logging in, the user

reviews this page, which

summarizes the order and

payment information.

Discount offers are

displayed in the “Your

Discounts” area.

The user clicks “place order”

to purchase the tickets.

If the user fails to click

“place order”, the

transaction is recorded as a

near-buy.

4


DATA

• For each month from January 2007 to December 2010, we

randomly sampled 2,000 StubHub buyers from among those who

made their first purchase in that month.

• For each customer we observe:

o Every purchase made, the event and genre, the number of tickets, the ticket

price, and the venue.

o Every near-buy, the event and genre, the number of tickets, the ticket price

and the venue.

from their first purchase through December 2010

• In addition, for each customer we observe:

o Zip code

o Whether they have also sold tickets on StubHub (7.4% of sample)

o Explicit (user-provided) and StubHub inferred preferences for genres (e.g.

MLB, Concerts, NBA) and locations


SUMMARY OF DATA

Cohort Number of Customers

Number of Purchases

Number of e-mails

Number of Offers

Time Observed

Feb 2007 2,000 5,446 133,331 2,987 49 months

Mar 2007 2,000 4,994 125,426 2,075 48 months

Apr 2007 2,000 5,288 122,578 2,065 47 months

.

.

.

Sep 2010 2,000 2,551 19,801 1,761 5 months

Oct 2010 2,000 2,475 18,077 1,668 4 months

Nov 2010 2,000 2,498 15,948 1,249 3 months

Dec 2010 2,000 2,319 11,599 475 2 months

Jan 2011 2,000 2,297 7,986 425 1 month


STUBHUB’S RELATIONSHIP MARKETING

• StubHub’s communication with users is entirely through e-mails,

which they have been sending since their launch in 2000.

• In an effort to increase retention, they began also making

discount offers (usually via e-mail) starting in 2010.

o Offers include %-off discounts, $-off discounts and free delivery.

o Offers are targeted based on a user’s prior behavior (purchases, lapses, etc.)

o For every offer, there is a randomly-selected hold-out group of otherwise

eligible users who do not receive the offer.

o Users who have opted out of e-mail would only become aware of the offer

through site banners if they logged on to the site during the offer window.


DATA

• In addition to transactions, we also observe for each customer:

o Every e-mail sent, when the e-mail was opened and whether the customer

responded with a click-through.

o Every offer received, the time window it was available, and a description of

the offer (e.g., 5% discount on MLB tickets)

from their first purchase through December 2010

• In addition, for each customer we observe:

o Whether they have opted-in for e-mail (54.2% of sample)


EXAMPLE CUSTOMER TIMELINE

3/12/2008 Received, Opened and Responded to an ALERT e-mail

3/18/2008 Reopened and Responded to an ALERT e-mail

3/25/2008 Received, Opened and Responded to a MONTHLY TICKET UPDATE e-mail

3/30/2008 NEAR-BUY: Dallas Mavericks at Golden State Warriors Tickets



4/7/2008 Received and Opened a MONTHLY TICKET UPDATE e-mail

4/22/2008 Received, Opened and Responded to a MONTHLY TICKET UPDATE e-mail

7/8/2008 BUY: Los Angeles Angels at Oakland Athletics Tickets

2/5/2009 BUY: Carolina Hurricanes at San Jose Sharks Tickets

9/25/2009 BUY: Los Angeles Angels at Oakland Athletics Tickets

….

10/3/2010 OFFER: Thank you messaging to at risk Budget & Value Buyers

12/3/2010 HOLDOUT: Holdout Group - Active Buyers who have opted-in to email

Customer 34191042

lives in 94941, has opted-in for e-mails and is not a StubHub seller


POTENTIAL RESEARCH QUESTIONS

• What are the key drivers for retaining valued customers?

• How do promotions affect customer behavior, both in the short-

term and the long-term?

• Do discounts help revive dormant customers?

• Is there a downside to “communicating too much” with

customers?

• Do some customers come to “expect a discount”? Do some

customers seem to be delaying purchases and waiting for a

discount offer? Is there a risk to StubHub becoming perceived as

a “discounter”?

• How should “near purchases” be interpreted? Should StubHub be

reacting to these “near purchases”?


EXAMPLE TRANSACTION DATA

0

50

100

150

200

250

300

350

400

450

500

Near-Buys and Repeat Purchases (May 2007 cohort)

Purchases

Near Purchases

0

50

100

150

200

250

300

350

400

450

500

Near-Buys and Repeat Purchases (May 2009 cohort)

Purchases

Near Purchases


TRANSACTIONS DISPLAY STRONG SEASONAL PATTERNS

0

2000

4000

6000

8000

10000

12000

2011

Total Observed Transactions All Cohorts

MLB

Concerts

NFL

NBA

NHL

College Football

Theater

All Other Sports

College Basketball

Motorsports

Exclusives

Non Ticket Items


EXAMPLE E-MAIL CAMPAIGNS

Email Campaign Marketing Program

Name

Email ID Date Number Sent

Number Opened

Number Responded

Ticket Update TU-060109 6/1/2009 26,798 4,647 995Ticket Update TU-100608 10/6/2008 21,676 3,750 940Ticket Update TU-031008 3/10/2008 13,543 3,500 912Ticket Update TU-010609 1/6/2009 23,507 4,151 909Ticket Update TU-101909 10/30/2009 30,426 5,371 867Ticket Update TU-021609 2/17/2009 24,539 4,303 864Ticket Update TU-080309 8/3/2009 28,363 5,646 861Ticket Update TU-032408 3/24/2008 16,211 3,747 854Ticket Update TU-051809 5/18/2009 21,520 3,995 841Ticket Update TU-040708 4/7/2008 15,618 3,783 840


EXAMPLE OFFERS

OfferDescription

Offer Start Offer End Number Eligible

Purchases in the Offer Window

1071: 10% instant discount to MLB buyers in new york metro region

7/30/2009 8/14/2009 194 0

2105: Spend $300 or more on US Open Tennis tickets and get free delivery

8/11/2010 9/11/2010 568 19

2106: Holdout Group - No Email 8/11/2010 9/11/2010 466 10

2017: Control Group - Promo email with no offer

8/11/2010 9/11/2010 386 4

2952 - Active Top & Selective Buyers (V1) Coupon 2 of 3: Spend $400 or more and get 10% off (excluding MLB tickets)

11/11/2010 12/12/2010 1739 32

2953 – Active Top & Selective Buyers Holdout Group – No Email

11/11/2010 12/12/2010 178 2


LOCATION INFORMATION

0

20000

40000

60000

80000

100000

120000

NY CA MA IL PA TX FL MI OH MO NA DC AZ GA CO WI MN WA MD NC IN VA UT TN NV OK LA OR CT AL KY NJ NE SC MS

Purchases and Near-Buys By Event State

PURCHASE

NEAR BUY


USER PREFERENCES

0

10

20

30

40

50

60Explicit User Genre Preferences


DATA FORMAT

• Data is provided in a relational format with the following tables: o Data on each user

• Users (zip code, e-mail preferences)

• User Geographic Preferences

• User Genre Preferences

o Data on each transaction

• Transactions

o Information about e-mails and offers:

• E-mail Meta Data

• Offers Meta Data

o Information about which e-mails/offers each user received:

• E-mails (by user)

• Offers (by user)

• WCAI will provide a detailed data key, .csv files, and the Python script to load the files into a SQLite database.

• The files are also small enough to load into Excel (with the exception of the e-mails table)


Q&A


PROPOSAL PROCESS

• Review the WCAI FAQ for Researchers

• Submit a brief proposal to [email protected] by April 15,

2011. Proposals should be less than 2,000 words and should

include:

o Research team, affiliations and e-mail addresses

o Objectives & contribution

o Proposed methods

o Rough timeline

o Potential for managerial insights & impact

• WCAI and StubHub will evaluate the proposals and choose a

team

• Clean data can be in your hands by the end of April!

http://www.wharton.upenn.edu/wcai/dump/891.cfm

mailto:[email protected]


OTHER OPPORTUNITIES FOR RESEARCHERS

• Call for Proposals on Modeling Mobile Customer Behavior due

April 22, 2011

• If you registered for this webinar, you will receive regular

announcements about:

o Research Opportunities like this one

o Grant/funding opportunities

o WCAI Conferences

Announcements are also available at wcai.wharton.upenn.edu

• Watch for our SSRN Research Paper series which will launch

soon.

http://www.wharton.upenn.edu/wcai/files/Mobile_RFP_2011-2012.pdf

http://wcai.wharton.upenn.edu/


MORE ABOUT WCAI

The Wharton Customer Analytics Initiative (WCAI) is the

preeminent academic research center focusing on the

development and application of customer analytic

methods. Acting as "matchmaker" between academia and

industry, WCAI has had a broad impact on the practice of data-

driven business decision-making, and the dissemination of

relevant insights to managers, students, and policy makers.

Based in the Wharton School’s Marketing

Department and designed to capitalize on

Wharton’s longstanding strength in

conducting empirical research, WCAI is an

interdisciplinary effort that brings a passionate

data-driven perspective unmatched by any

other business school.

Documents

Relationship Marketing at StubHub - Wharton Customer …...WHARTON CUSTOMER ANALYTICS INITIATIVE PAGE 25 MORE ABOUT WCAI The Wharton Customer Analytics Initiative (WCAI) is the preeminent