Cases: Science of Social Influence - HP Brandclout
Hewlett-Packard (HP) has been a 75-year-old technology leader with operations across 170 countries and an employee strength of over 3,20,000. In 2013, HP launched Actionable Analytics Services (HAVEn) - a Big Data analytics platform, leveraging the capabilities of Hadoop, Autonomy, Vertica, Enterprise Security, and applications. HP enterprise wanted to mobilize the prospective and existing customer base to embrace the HAVEn offering. Historically, large organisations had a fair coverage and influence on the entire sales cycle with them driving need identification all the way through to influencing the purchase decision and purchase. However, recent studies started showing that this was changing, and nearly 70% of the purchase decision was made before engaging a sales representative independent of the offering. The HAVEn team was aware of this shift in trend, and for an enterprise class product, with high initial investment needs and relatively new outlook to how businesses could extract value; the need to influence sales cycle right from stage-one to drive adoption was an important task. Pramod Singh, Director of HP Digital Analytics and Ayush Jain, Manager of HP Social Media Analytics were approached by the HAVEn team to help them identify the most relevant influencers in the Big Data space and help device a strategy of engagement with the same. Topic relevant influencer identification was tough considering the volume, velocity, and complexity of social media content. Quantifying the influence of the brands, thereby enabling comparison and competitive benchmarking was even more difficult. The problem of first defining influence, and then identifying influencers relevant to a topic of interest, in real time, using a data source that was high volume, high velocity with little or no structure, was a challenge that enticed Pramod and Ayush to group their best talent pool together.
Author’s Name: Srujana H M; Sudeep Chatterjee; Kratika Shakya; Dinesh Kumar Unnikrishnan
Publishers Harvard Business Publishing
URL: https://cb.hbsp.harvard.edu/cbmp/product/IMB515-PDF-ENG
Cases: Science of Social Influence - HP Brandclout
Hewlett-Packard (HP) has been a 75-year-old technology leader with operations across 170 countries and an employee strength of over 3,20,000. In 2013, HP launched Actionable Analytics Services (HAVEn) - a Big Data analytics platform, leveraging the capabilities of Hadoop, Autonomy, Vertica, Enterprise Security, and applications. HP enterprise wanted to mobilize the prospective and existing customer base to embrace the HAVEn offering. Historically, large organisations had a fair coverage and influence on the entire sales cycle with them driving need identification all the way through to influencing the purchase decision and purchase. However, recent studies started showing that this was changing, and nearly 70% of the purchase decision was made before engaging a sales representative independent of the offering. The HAVEn team was aware of this shift in trend, and for an enterprise class product, with high initial investment needs and relatively new outlook to how businesses could extract value; the need to influence sales cycle right from stage-one to drive adoption was an important task. Pramod Singh, Director of HP Digital Analytics and Ayush Jain, Manager of HP Social Media Analytics were approached by the HAVEn team to help them identify the most relevant influencers in the Big Data space and help device a strategy of engagement with the same. Topic relevant influencer identification was tough considering the volume, velocity, and complexity of social media content. Quantifying the influence of the brands, thereby enabling comparison and competitive benchmarking was even more difficult. The problem of first defining influence, and then identifying influencers relevant to a topic of interest, in real time, using a data source that was high volume, high velocity with little or no structure, was a challenge that enticed Pramod and Ayush to group their best talent pool together.
Author’s Name: Srujana H M; Sudeep Chatterjee; Kratika Shakya; Dinesh Kumar Unnikrishnan
Publishers Harvard Business Publishing
URL: https://cb.hbsp.harvard.edu/cbmp/product/IMB515-PDF-ENG
