Databases Reference
In-Depth Information
The case study shows how real-world organizations are using a combination of social media data
and structured data to create a powerful analytical platform. The business case in this situation tran-
scends beyond simple monetization—it is about brand value and market.
Case study 6: Customer-centric data integration
This case study is a representative of social media data integration in many large organizations. It is
based on implementing a customer-centric business transformation program, popularly called voice
of customer.
Overview
The world of social media and the revolution of mobile technology have changed the way we com-
municate and network forever. Prior to the advent of Facebook or MySpace and the smartphone, we
did have channels to voice opinions and feedback through forums (needed a laptop with Internet),
surveys, and call centers. The customer was important then, but more as a purchaser and a consumer
of products and services. The opinion of the customer was important but measured in terms of market
reach, wallet share, and overall brand presence. But the last decade has changed that landscape; the
customer is now an integral part of any organization, considered as an important stakeholder in the
business. The opinions of the customer across any channel and source are considered to be extremely
valuable.
Integrating customer data across CRM, sales, call center, forums, sentiment analytics, and social
media can benefit an organization to:
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Understand the customer.
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Understand the sentiments of a group of customers and apply the deviations to specific customers
to bridge the gap between happy and unhappy customers.
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Understand the sentiments and trends in the market as applied to their products and services.
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Understand how the customer evaluates them against the competition.
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Understand the needs of a customer based on their current life events.
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Understand what the customer wants from a social crowd perspective.
The challenge is how to build a solution, and determining what the best kind of data is and how
beneficial the analytics and metrics can be. The most important question is the measurement of ROI.
A large exercise like this has several critical phases of implementation:
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Data analysis
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Data architecture
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Data collection
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Planning the listening posts
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Implementing the listening posts
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Data quality
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Data processing
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Data classification
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Data integration
