Preriit Souda, PSA Consultants Ltd
For last 9 years, Preriit has helped organizations answer different strategic questions by unraveling explicit and implicit human expression through mining of social and digital data alongside other data sources like Consumer surveys, IOT (Internet of Things) data, CRM data, Mobile behavioral data, Weather data, Locational data, etc. Has consulted clients from a range of sectors including CPG/FMCG, Finance, Travel, Telecom, Public Sector, across different geographies like UK, US, China, India, Continental Europe, Asia Pacific, Oceania, Middle East, North Africa.
Preriit has won several awards including ESOMAR Best Paper (Global) 2017, MRS (Market Research Society UK) Grand Prix 2016, MRS New Insights Methodology 2016, MRS Best Research using Social Media 2016 & 2017, ARF (Advertising Research Foundation, USA) Rising Star-Gold 2014, ESOMAR Young Researcher of the Year (Global) (2011), Best Analytics paper at MRS (India) Annual Conference 2012.
Trains, Politics and Emotions
Preriit will talk about two of his cases showcasing use of techniques from data mining.
1- First case is around Learning from the past for guided in the moment communications. Case will show how an organization can strategize it’s in-the-moment communication strategy for unpredictable and frequently occurring reputation hampering events by linking past social and digital data with previous operational data. Case pertains to travel sector where people can have high fluctuating emotional outpours with very low threshold.
2- Second case is around superimposition of semiotics on digital media. Semiotics is a structural analysis of opposing sociological and psychological meanings. Semiotics creates a coherent model for mapping intangible meaning, while Digital Media Analytics harvests the hard data that corresponds to each meaning. Here Preriit will be showcasing an ongoing work wherein they have created a Semiotic map on British Politics and then superimposed on digital media which is then being analysed for its impact on popularity polls.