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PAGE 1WHARTON CUSTOMER ANALYTICS INITIATIVE
Relationship Marketing at StubHub
Research Opportunity Webinar
25 March 2011
CUSTOMER ANALYTICS INITIATIVE
PAGE 2WHARTON 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
PAGE 4WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 5WHARTON CUSTOMER ANALYTICS INITIATIVE
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.
PAGE 6WHARTON CUSTOMER ANALYTICS INITIATIVE
THE STUBHUB PURCHASE PROCESS
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
PAGE 7WHARTON CUSTOMER ANALYTICS INITIATIVE
THE STUBHUB PURCHASE PROCESS
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.
PAGE 8WHARTON CUSTOMER ANALYTICS INITIATIVE
THE STUBHUB PURCHASE PROCESS
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
PAGE 9WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 10WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 11WHARTON CUSTOMER ANALYTICS INITIATIVE
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.
PAGE 12WHARTON CUSTOMER ANALYTICS INITIATIVE
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)
PAGE 13WHARTON CUSTOMER ANALYTICS INITIATIVE
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
3/30/2008 NEAR-BUY: Dallas Mavericks at Golden State Warriors Tickets
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
PAGE 14WHARTON CUSTOMER ANALYTICS INITIATIVE
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”?
PAGE 15WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 16WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 17WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 18WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 19WHARTON CUSTOMER ANALYTICS INITIATIVE
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
PAGE 20WHARTON CUSTOMER ANALYTICS INITIATIVE
USER PREFERENCES
0
10
20
30
40
50
60Explicit User Genre Preferences
PAGE 21WHARTON CUSTOMER ANALYTICS INITIATIVE
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)
PAGE 23WHARTON CUSTOMER ANALYTICS INITIATIVE
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!
PAGE 24WHARTON CUSTOMER ANALYTICS INITIATIVE
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.
PAGE 25WHARTON CUSTOMER ANALYTICS INITIATIVE
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.