Inspiring Healthy Habits: Data Science at WW
                                                                   Keynote

                                                              Carl Anderson
                                                   carl.anderson@weightwatchers.com
                                                           Data Science at WW
                                                              New York, USA
ABSTRACT                                                                     BIOGRAPHY
Our purpose at WW (the new Weight Watchers) is to "inspire                   Carl Anderson is the Director, Data Science at WW, the new Weight
healthy habits for real life. For people, families, communities, the         Watchers, in New York. His team builds predictive models and
world - for everyone." For 56 years, we’ve been a leader in weight           data products such as churn models, social network recommenders,
loss. Now, however, our mission is bigger and broader: drive health          search improvements, and food recommenders, all to inspire healthy
and wellness, making healthy habits accessible to all, not just a few.       habits among our millions of members around the world, as well
The question is, how do you deliver on that? Humans are notori-              as to positively impact their families and their communities. Pas-
ously fickle, stubborn, and irrational. They don’t always do what            sionate about all thing data, he is the author of the 2015 O’Reilly
is in their best interests. Moreover, behavioral change and habit            book "Creating a Data-Driven Organization".
forming is genuinely hard. It is all too easy to skip going to the
gym, to resist that extra cookie, or to take time for yourself and
reduce stress.                                                               HealthRecSys’19, September 20, 2019, Copenhagen, Denmark
In this session, we’ll discuss what’s involved in behavioral change          © 2019 Copyright for the individual papers remains with the authors. Use permitted
                                                                             under Creative Commons License Attribution 4.0 International (CC BY 4.0). This
and nudges, and how the WW data science team are working on                  volume is published and copyrighted by its editors.
personalized experiences, various recommenders, and other data
products at scale to aid our members’ success.




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