Interview: Saikat Mukherjee, ShareThis on Why Marketers can no longer Ignore Social TV?
We discuss the role of Analytics at ShareThis, the emergence of Social TV, better user behavior insights through Social TV, major challenges with Social TV analytics, interesting insights, future trends, recommendation and more.

He obtained his Ph.D. from Stony Brook University and bachelors from the Indian Institute of Technology and is a frequent speaker in data science conferences.
Here is my interview with him:
Anmol Rajpurohit: Q1. What does ShareThis do? What role does Analytics play in the firm's strategy?
Saikat Mukherjee: ShareThis is a social media company. We provide social tools to publishers so that users can share their favorite content to social networks of their choice. Currently we integrate with more than 100 social channels and 2.4 million publishers. At the same time, we help advertisers buy

AR: Q2. How do you define "Social TV"? What are the popular channels for Social TV and how do they compare against each other?
SM: Social TV is typically defined as online social activity about TV shows. For example, you might be tweeting about the show while watching an episode of ‘Breaking Bad’. In this case, it is real time but it need not be real time activity and could be social activity before or after the show has aired.

while Twitter and Facebook have a lot of activity on sports, drama, and family genres, Pinterest and Tumblr stand out in comedy. Pinterest also has significant social TV activity on music genre shows — maybe an effect of that network being used more by women.

SM: We have looked at device usage (i.e. is the activity from an iPhone or a PC, etc.), distribution of TV show genres, demographics, and geographic location of users across social channels in our current analysis. While that itself gave us a lot of interesting insights about user behavior, we can go much further particularly on analyzing the impact of the social activity on other users.
AR: Q4. What are the major challenges in measuring and monitoring the user activities on Social TV?

AR: Q5. What are some of the most unexpected insights that you have obtained through Analytics based on ShareThis data?
SM: Mobile has been a surprise. While it’s commonly known how content consumption

Also, we found that while there are more android smartphones than iPhones even the US, but in terms of social activity iPhones are more popular than androids. Goes to say something about the differences between iPhone and android mobile users.
AR: Q6. What advances do you expect in the field of Social Analytics over the next few years?

AR: Q7. Based on your extensive research of users' social sharing habits, what recommendations would you give to marketers? What metrics should they focus on?
SM: I think it’s important not to fixate on any one particular social channel but have a mix in the bag. Different social networks tap into different demographics and the usage

AR: Q8. Data Scientist has been termed as the sexiest job of 21st century. Do you agree? What advice would you give to people aspiring a long career in Data Science?
SM: I agree that it’s a great job and very fulfilling!
To be good at it though, I think it’s not enough to be a good scientist. There is certainly the science part but arguably it could be less critical than being able to work with data (data engineering skills), being able to understand an abstract problem and solve it at scale, and communicate with peers and the community. So my advice to aspiring data scientists would be to also work on your soft skills and your engineering skills.
AR: Q9. What are your favorite books or blogs on Data Science?
SM: Again to be a good data scientist, you need to be very aware of your particular industry. I try to read as much as I can of adexchanger, adotas, adage which are blogs/publications in the advertising industry. As far as data science goes, I am a hadoop stack + python + linear models kind of guy so try to catch up as much as I can on books and blogs in these areas.
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