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UNDERSTANDING,
EXPANDING, AND PREDICTING
CUSTOMER ENGAGEMENT
A WCAI Research Opportunity
sponsored by an International Beauty Retailer
October 17, 2014
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Introductions
Data Sponsor Team
WCAI Team
•
David
•
Ben Adams
•
Adrien
•
Melissa Hartz
•
Mathieu
•
Colleen O’Neill
•
Delphine
•
Elea Feit
•
Gregoire
•
Eric Bradlow
•
Kristy
•
Peter Fader
•
Alicia
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A Few Operational Notes
This webinar is intended for researchers & scholars. It should not be published
or presented without permission from WCAI.
• Questions on program: [email protected]
• Press contacts: [email protected]
To get access to the data, research teams should submit a proposal to WCAI
and the sponsor for approval. More details at the end of this presentation.
This research opportunity is sponsored by an International Beauty Retailer.
While awarded teams will be introduced, the sponsor must not be named in
publications.
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how does
LOVE
evolve?
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How Does “Love” Evolve?
prospective
customer
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customer
high-value
customer
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How Does “Love” Evolve?
prospective
customer
customer
high-value
customer
At any point, a customer might exit “the flow”.
Any change in status is unobserved.
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How Does “Love” Evolve?
UNDERSTANDING
ACQUIRING
DEEPENING
PREDICTING
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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The Data: Four-Year Observation Window
June, 2010
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September, 2014
The Data: Four-Year Observation Window
June, 2010
September, 2014
Stores
Products
Customers
Transactions
Marketing
Surveys
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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The Stores
The Dataset Contains:

Information for 707
stores in five countries

Store category (“mall
store”, “outlet”, etc.)

City, country, and
postal code of store

Full text of store name
*Size of circle
represents number
of stores
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Sneak Peek: Store Data
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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The Products
Product Data Contains:
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More than 3,500 distinct SKUs across 37 categories in 8 segments
Product replacement history
Physical dimensions of products
Full product name and description
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Sneak Peek: Product Data
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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The Customers
The customer data contains:
• 65,000 customers pulled in a stratified random sample
• Age, gender, city, country, and postal code
• Flags designating whether or not the customer has opted out of
direct mail, email, and or telephone marketing from the firm
• The store ID of both the acquisition store as well as the store where
the customer most frequently shops
The customers are:
• Randomly sampled from five countries: the United Kingdom (20,000),
France (15,000), Germany, Spain, and Italy (10,000 each)
• Divided into two categories: customers (~82%), people in the dataset
who have made at least one purchase, and prospects, people who
have been identified but have yet to purchase
• NOTE: sample includes only self-identified, tracked customers &
prospects. Data does not include transactions from unknowns,
unidentified, or "walk-in" customers
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Customer Status Distribution
Percent Prospects
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Percent Customers
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Sneak Peek: Customer Data
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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Transactions
The transaction data contains:
•
•
•
•
•
~150,000 shopping trips (baskets)
All individual line items purchased during each trip
Spend in local currency, tax inclusive
Date and location of the transaction
Return/refund transactions
Baskets and line items are mapped to each customer. The dataset
contains all online and offline purchases for each customer for the
entire duration of the observation window.
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Sneak Peek: Transaction Data
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Sneak Peek: One Basket
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Aggregate Purchases Over Time
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Aggregate Purchases Over Time by Country
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Purchase Behavior
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Purchase Behavior
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*Size of circle represents sales
amount in local currency
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Purchase Behavior
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*Size of circle represents sales
amount in local currency
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Purchase Behavior
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*Size of circle represents sales
amount in local currency
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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Survey Data
Customer satisfaction survey data are available from a single
country in the dataset, and include:
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Store/date that triggered the survey
Client ID to link back to customer table
Full-text comments
Customer-facing survey instrument
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Survey Instrument
The survey instrument includes questions such as:
• How likely are you to recommend your last in-store experience to
your friend/colleague?
• Before entering the store, did you intend to visit it?
• Amongst the products that you purchased in the store, would you say
you knew what you wanted to buy?
• Once in the store, were there any specific products that you looked
for but that you did not find?
• Are you satisfied with the information you received about
discontinued lines?
• Have you purchased a product in one of our retail locations in the
past 12 months?
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Sneak Peek: Survey Data
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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Marketing Data
This dataset contains the most
extensive direct-to-consumer
marketing of any WCAI
Research Opportunity.
• 2 channels – email & direct
• Creatives included
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• 100% customer addressable
• Built-in experiments
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Marketing Data
Direct Mail
• 48 campaigns over the
course of 3 years
• Lists of all targeted
customers
• Promotional codes that are
able to be linked back to
transactions
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E-mail
• 535 campaigns spread
across 5 countries
• Each email addressable
by customer ID
• Activities/actions from email
• Opened/read email
• Clicked a link
• Clicked “opt-out”
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Email Marketing – Emails Sent
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Email Marketing – Activities/Actions
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Sneak Peek: Email Action Data
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Direct Mail – Promotion Redemptions
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Direct Mail – Promotion Redemptions by Country
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Sneak Peek: Email Creatives
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Sneak Peek: Email Creatives
*some aspects of creative redacted to protect Data Sponsor’s anonymity
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Sneak Peek: Direct Mail Creatives
*some aspects of creative redacted to protect Data Sponsor’s anonymity
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The Data
Store
Survey
Transaction
Product
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Customer
Marketing
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Research Areas from the Sponsor
The Data Sponsor is open to proposals and projects exploring any of the following
themes:
• Multi-channel attribution modelling
• Detecting and forecasting customers’ “engagement” with the brand
• Optimal product bundling
• Analyzing the attributes of advertising copy to understand what makes an ad “work”
• Understanding geographic differences in customer purchasing and engagement
• Customer response to advertising
• Understanding the role of customer satisfaction in engagement, purchase, and churn
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Research Areas from the Sponsor
The Data Sponsor is open to proposals and projects exploring any of the following
themes:
• Multi-channel attribution modelling
• Detecting and forecasting customers’ “engagement” with the brand
• Optimal product bundling
• Analyzing the attributes of advertising copy to understand what makes an ad “work”
• Understanding geographic differences in customer purchasing and engagement
• Customer response to advertising
• Understanding the role of customer satisfaction in engagement, purchase, and churn
Proposals are not limited only to these research areas – any topic utilizing this
dataset is welcome. However, all projects must demonstrate impact or potential
for impact to the Data Sponsor.
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Benefits of Participating in a WCAI Research Opportunity
• Access to unique data
• Assistance with data cleaning, preparation, and processing at any
point during the Research Opportunity
• Teleconference Q&A sessions with the research sponsor
• Opportunity to present findings to the Corporate Sponsor at the
closing symposium, to be held at Wharton one year from now
(note: attendance by at least one member from each team required)
• Potential for additional PR for your research
• Promotion of your research paper through the WCAI SSRN Research
Paper Series
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Proposal Format
Proposals should be in PDF format, no more than 2,000 words, and include the
following information:
• Title
• Author(s) name, title, affiliation and e-mail address: Please designate a corresponding
author.
• Summary information: a single “slide” that visually summarizes team & project.
• Abstract
• Introduction: Describe expected contribution(s), covering both the academic and practical
aspects. Please keep it concise, and cite relevant work as necessary to explain your academic
contribution. There is no need to include a lengthy literature review.
• Detailed project proposal: Please include enough detail that we can assess the feasibility &
merit of the proposed approach. For example, modeling projects should include at least a sketch
of the model. In addition, include a rough estimate of how long the project will take. Also include
the business relevance of your research and the impact for the sponsor as well.
• Data Needs: Bulleted list of data required for analysis not explicitly mentioned here, i.e.,
“account creation date” or “store open/close date”. While we can’t guarantee the inclusion of
these items, we are happy to investigate the availability.
• Biographies: Include up to a paragraph-long biography highlighting what each team member
will contribute to the project.
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Proposal Submission Process
• Read more about the proposal format at
http://www.wharton.upenn.edu/wcai/Proposals.cfm
• Submit proposals at http://www.wharton.upenn.edu/wcai/proposalform.cfm
no later than Monday, November 3, 2014, 12 noon US Eastern.
– Proposals will only be accepted online.
– A single PDF combining the written portion and the single slide.
• Proposals will be evaluated both on academic contribution and potential to
significantly improve the research sponsor’s marketing practice.
– Rajdeep Grewal (University of North Carolina), Sandy Jap (Emory),
Elea Feit (Drexel University), Eric Bradlow (WCAI), Pete Fader (WCAI), and
representatives from the Research Sponsor.
• Contact [email protected], if you have questions prior to
submitting your proposal.
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Other WCAI Opportunities for Researchers
If you registered for this webinar, you will receive regular announcements
regarding:
• Research Opportunities like this one
– Desktop Software Renewal Analysis
– Massive Online Advertising Exposure and Attribution
– 2-3 more Research Opportunities in the Spring
Also find us at:
• SSRN Research Paper series:
http://www.ssrn.com/link/Wharton-Cust-Analytics-Initiative-RES.html
• Announcements: http://wcai.wharton.upenn.edu
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KNOWLEDGE FOR ACTION
TRANSFORMING BUSINESS THROUGH CUSTOMER DATA
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