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SmartData Collective > Big Data > Data Mining > Unifying Your Social and Private Data Analytics – Creating an Integrated Customer Data Hub
AnalyticsData MiningPrivacy

Unifying Your Social and Private Data Analytics – Creating an Integrated Customer Data Hub

Jennifer Roberts
Last updated: 2011/06/22 at 4:19 PM
Jennifer Roberts
4 Min Read
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Analyzing social media conversations, while critical to surfacing real-time customer considerations and preferences, represents only part of the equation to understanding your customer. It doesn’t include all of the potentially relevant details currently residing in your private data, which may provide important transactional details, customer service insights or support status updates that may influence how you engage with a specific consumer or audience segment.

Contents
Private & Social Data – You Need BothIntegrated Customer Hub

Analyzing social media conversations, while critical to surfacing real-time customer considerations and preferences, represents only part of the equation to understanding your customer. It doesn’t include all of the potentially relevant details currently residing in your private data, which may provide important transactional details, customer service insights or support status updates that may influence how you engage with a specific consumer or audience segment.

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Social is just one side of the story. Click image to enlarge.

Private & Social Data – You Need Both

Feeding your private data into a real-time text processing engine can help you categorize your data to begin mapping emerging themes and trends to defined key performance indicators (KPIs). A consistent approach to how your organization manages both social and private data can extend your understanding of both your individual consumer and clearly-defined audience segment.

Why did I mention categorization as a first step in analyzing your private data? Accurate categorization means that contextually-similar terms are grouped together; text about “Crocs” the shoes are separately categorized from “crocs” the reptiles. Sophisticate language processing techniques are able to disambiguate a term that is used in multiple contexts. Once you have a precisely filtered data environment, you can begin to isolate emerging trends, sentiment as it relates to specific KPIs or consumer profiles based on customer service transcripts.

Traditional Analytics. Click image to enlarge.

Integrated Customer Hub

Ultimately, creating a comprehensive view of your consumer requires integrating social and existing data. Whether the information comes from a survey, chat transcript or Facebook, the data can be analyzed and tracked to enable 1 to 1 or 1 to many engagements.

Integrated Consumer Hub. Click image to enlarge

For example, customer service chat transcripts could be analyzed and categorized to reveal common issues, product enhancement requests or emerging concerns. Details from product enhancement requests could be isolated and filtered to reveal the context of those requests. Resulting findings could be fed into a business intelligence system or workflow process to inform both other business units and strategic development efforts to work towards a solution.

Of course, how your organization ultimately shares and acts on this type of information is something that would need to be considered. Knowing how information is ultimately shared and managed is as important as organizing and correlating the data.

Ultimately, it’s recognizing that whether it’s social media or private data, each contains valuable insights that may not only provide your organization with a competitive advantage but also the ability to use the wealth of information you already manage.  Integrating both forms of data, however, is critical to providing a more complete view of your industry, your customer, and your competitors.  What type of text-based data would inform your integrated customer data hub?

Jennifer Roberts June 22, 2011
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