Surfacing Actionable Business Insights from Your Big, Private Data Source

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It’s estimated that 80% of business data is in an unstructured format. Inaccessible and untapped, your internal data may contain in the form of transcripts, surveys, or customer service records early signs of emerging issues, answers to development questions or even a customer’s first attempt at resolving an issue before they launch a tirade on a social media channel. (Laskowski, Nicole. "Avoid public relations issues by mining unstructured data from within" Business Analytics/Business Intelligence Information, News and Tips - SearchBusinessAnalytics.com. Web. 15 June 2011. ) Social is a critical component of business intelligence but it only provides a single view of a consumer. Applying the same analytical rigor to internal data can yield rich detail about a customer’s transactional behavior, customer service engagement efforts, or survey responses. What If….
  • You could filter and analyze survey information to surface how patients are using and responding to a form of treatment
  • Trend customer service issues to maximize allocation of corrective resources
  • You could identify a set of customers, who have cancelled their service, based on a set of shared characteristics.

Sources of Business Data

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There are probably multiple definitions of private, business data but some sources for unstructured, private data may include:
  • Survey/focus group - verbatim
  • Call Center
  • Email & chat transcripts
  • Private community conversations
  • Text-translated video
  • Private news

Identifying Shared and Unique Characteristics

MIT Sloan Prof. Erik Brynjolfsson estimates that “every 1.2 years, the volume of business data worldwide doubles”. Business data represents an enormous unrealized resource but also represents some challenges to surfacing that value. How your business approaches organizing and filtering large volumes of data will be based on unique business objectives and goals. Some areas you may want to consider for further analysis: Trends and Patterns. You may want to isolate common characteristics amongst consumers or users to achieve more precise audience segmentation. Identify common similarities between consumers but also allow for some flexibility for emerging trends and patterns. If you have a set of customers, who have cancelled their service, can you analyze your internal data for a pattern or set of shared characteristics of these consumers? Relationship Between Different Data Elements. Organize and filter business data to surface important relationships. For example, map buying behavior to a specific geography or demographic details. Analyzing business data is a critical element to better understanding your consumer, how they use your products or services, or it may hold valuable insights that can be used to optimize your organization’s workflow or product development.