Guest blog by Jeff Sumner, Product Marketing Leader, IBM Content Analytics & Search

My colleague, Scott Blau in a previous blog mentioned that commerce has changed irrevocably. Main Street store owners knew their regular customers intimately, and created and sold products that met their individual tastes. They knew what the customers preferred and stocked those items, but more importantly they knew what other products to sell with them to increase the size of shopping basket.

Businesses ranging from retailer to telecom recognize that knowing your customer well leads to improved and personalized service for the buyer and results in a more loyal customer. In the effort to know their customers better, businesses have employed advanced IT systems to segment their customers into types and cohorts based on demographics, geography and more.

Although this type of segmentation helps, it often fails to define important differences between customers. For example basic mobile telcom segmentation might define a customer as part of a male, 30 years old, lives and works in Raleigh, and uses a data + long distance calling plan. A better approach is to classify by my choices, preferences and tastes based on all my interactions with the business.

To accurately micro-segment their customers, businesses need to recognize a broader range of customer characteristics many of which are found beyond the structured information like that found in order, service and billing systems. A rich set of additional information about customers can be found in customer interaction like emails, call transcripts, chat, SMS, social media and more. Businesses should have the ability to understand the meaning in customer dialog. For example when a customer expresses to a mobile provider “frustrated with experience of slow speeds when accessing the Android marketplace” – the provider can use that information to segment the customer as an Android phone user, prefers fast data connections, frequently downloads applications, tech savy, vocal, attrition risk”. When you ad that information to that of the structured data in the customer information systems it provides a richer more accurate description of the customer. When the mobile service provider this added level of insight it can plan more effective offers to this customer and ensure he remains a valuable customer for a long time.

In order to gain this level of insight about their customers, businesses will need to mine massive volumes of customer interactions and analyze unstructured content to understand what was spoken and in what context. Be it retailers, telecom service providers, banks, insurers or healthcare providers, every business can leverage the vast amounts of information available in their customer interactions to finely segment and maintain and grow relationships with their customers. It is commonly known that Big Data is a critical challenge and opportunity for businesses and having technologies designed to address the explosive growth of the volume, variety and velocity of information is critical for business success. In the end the big story behind big data may be very small – the capability to create and serve very Small- micro segments of customers.

To know more about how IBM addresses analytics of Enterprise Content at Big Data scale attend the IBM Content Analytics Meets Big Data and Beyond Watson: IBM Content Analytics Today sessions at Information OnDemand 2012 Global Conference at Las Vegas in October 2012.