Successful Applications of Customer Analytics

May 8th – 9th, 2018

Inn at Penn

2018 Keynote Speakers

Headshot of a smiling person with shoulder-length blonde hair, wearing a dark blazer.
Headshot of a person outdoors with a red barn and greenery in the background.

Opening Keynote: Deborah Wahl, G’92, WG’92

CMO, Cadillac

A leading innovator amongst Chief Marketing Officers, Deborah has made a career of shaping and implementing transformative corporate strategy. She aligns customer and company objectives to drive success with revitalized brands and winning go-to-market strategies.

Past CMO experience includes positions at McDonald’s, PulteGroup and Chrysler. She also held senior-level marketing roles at Lexus, Toyota, and Mazda.

Closing Keynote: Victor Cho, W’93

CEO, Evite

Since joining Evite as CEO in June 2014, Victor Cho has re-directed the popular brand into a customer-obsessed company focused on bringing people together face to face. He has achieved revenue growth and taken the company into exciting new ventures, including text message invitations, donations for nonprofits, video, and sponsored content.

2018 Conference Highlights

Watch highlights from the 2018 Successful Applications of Customer Analytics conference. This video features key insight from a few of the guest speakers including Sajjad Jaffer, WG’01, Founder and Managing Partner at Two Six Capital; Dean of The Wharton School, Geoffrey Garrett; Keynote Speaker, Deborah Wahl, G’92, WG’92, CMO, Cadillac; Salman Mukhtar, Director, Microsoft together with Arun Shastri, Principal, ZS Associates; Kathy Koontz, Practice Director, Teradata; Keynote Speaker, Victor Cho, CEO, Evite and closing comments from Raghu Iyengar, Professor of Marketing, The Wharton School.

Pre-conference Workshops

1:30 – 2:00 PM
May 9, 2018
Wharton Campus

Workshop Registration

2:00 – 5:00 PM
May 9, 2018
Wharton Campus

Intro to Deep Learning and Sentiment Analysis

Instructor: Vikram Madan, WG’15, Sr. Product Manager, Amazon Web Services

Workshop Overview:
Deep learning plays a significant role in sentiment analysis, where algorithms can be trained to quickly learn and detect patterns in large volumes of data. In this workshop, we will start by providing an overview on deep learning and on the Apache MXNet deep learning framework. We will next discuss how to address sentiment analysis use cases with deep learning. We will finish by walking step-by-step through a demonstration on how to build a Long Short-term Memory (LSTM) model to perform sentiment analysis on the IMDB dataset, which includes 50,000 movie reviews.

Prerequisites:

  • Programming knowledge and basics of Python will be helpful to follow the hands-on part, but not required for the workshop.
  • No machine learning knowledge is assumed.
  • Basics of Linear Algebra will be good-to-have.

2:00 – 5:00 PM
May 9, 2018
Wharton Campus

Practical Recommendation Systems

Instructor: John Fox Ph.D., WG’13, Analytics Expert, Journey Analytics, McKinsey and Pascal Notin, Analytics Expert, Journey Analytics, McKinsey

Workshop Overview:
In this workshop, we will walk you through the various types of recommendation systems and discuss practical aspects of recommenders. By the end of the workshop, you will have enough knowledge to build a basic recommender and will be aware of the practical aspects of designing, deploying and maintaining a recommender. The workshop is approximately 50% theory and 50% hands-on.

Prerequisites:

  • Programming knowledge and basics of “R” will be helpful to follow the hands-on part, but not required for the workshop
  • No machine learning knowledge is assumed.
  • Basics of Linear Algebra will be good-to-have.