Tamoco strengthen advisory board with the appointment of business analytics specialist
London-based proximity technology company, Tamoco has appointed American academic, Dr. Anindya Ghose to its advisory board, as the company seeks to continue its rapid growth.
Ghose joins the Tamoco advisory board at a time of rapid expansion for the business. Tamoco launched its network in 2015 and now covers an audience of more than 100 million people across 100 countries with a network of over 1 billion sensors in public locations, providing its partners with data insight. The company is said to be working closely with businesses such as Omnicom and ABI as well as brands like Starbucks and McDonalds.
The advisory board will be chaired by Victor Chu, CEO and chairman of First Eastern Investment Group. Chu is currently a foundation board member for the World Economic Forum, and he co-chairs its International Business Council.
Ghose will combine his expertise on digital trends and analytics with Chu’s business experience to help Tamoco monetise its real-time location technology.
Dr. Ghose is the Heinz Riehl chair professor of business at New York University’s Leonard N Stern School of Business. His primary research focuses on monetising the digital economy using data science and business analytics. He has been named by Poets & Quants as one of the “Top 40 Professors Under 40 Worldwide” and by Thinkers50 as one of the “Top 30 Management Thinkers” globally most likely to shape the future of how organisations are managed and led in the next generation. He is the author of TAP: Unlocking The Mobile Economy which is a double winner in the 2018 Axiom Business Book Awards and has been translated into five languages.
Ghose received his PhD from Carnegie Mellon University’s Tepper School of Business and has consulted for tech giants such as Apple, Facebook, Snapchat and Samsung, and collaborated with Adobe, China Mobile, Google, Microsoft, SK Telecom, and Alibaba. He will be advising Tamoco on how to monetise their real-time location and contextual data on users using techniques from data science and large-scale field experiments.