Originally posted on IBM Big Data Hub
TED@IBM Reimagining our World
IBM is coming together with TED to host a first-of-its-kind event exploring ideas, insights and personal stories with a broad cross-section of IBM clients, partners, friends and IBMers. At this event, I will be speaking on IBM’s big data approach to engagement analytics and how it can only be successfully achieved by implementing a privacy by design methodology.
I probably don’t need to tell anyone reading this post that engagement matters; be that employee, consumer or citizen. Gartner studies indicate that “organizations with a highly engaged workforce significantly outperform those without,” and Gallup research shows that “engaged customers buy more, stay with you longer and are more profitable than average customers, in good economic times and bad.” Additionally, the Open Society Foundations proposes that “active citizenship is one of the most important steps towards healthy societies.” Engagement is important, and brings to mind this question:
“How do we measure engagement patterns so that we can better understand, characterize, predict, incentivize and ultimately drive active engagement?”
Historically, engagement has been measured by surveys that ask a series of questions and infer sentiment from the answers. While this works, there are only so many questions that a survey can ask and this limits that amount of information we can gather when we we are researching engagement.