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The Next Frontier: Conquering the Unstructured Data Challenge

The Next Frontier: Conquering the Unstructured Data Challenge

The Next Frontier: Conquering the Unstructured Data Challenge

5/27/2004
By Donna Fluss
ContactCenterWorld.com

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Contact centers waste 90% to 98% of actionable customer insights because they lack the process, technology and applications to capture, analyze and leverage “unstructured” sources of customer communications, rich with information and feedback.

Phone conversations are often recorded but rarely analyzed for new revenue opportunities. The Internet opened online communication channels between customers and enterprises. But companies have struggled to exploit the unstructured customer data received over the Internet because existing data warehousing, business intelligence, and analytics systems understand only “structured” data. Customers, unaware of and unconcerned with these system limitations, freely share their needs and wants with contact centers and don’t understand why the information they communicate is ignored.

Conquering the “unstructured” data challenge is the next frontier in contact centers and one that will distinguish proactive and engaged service and sales environments from those that are merely reactive. Enterprises that build a support infrastructure that allows them to immediately convert unstructured customer communications into actions – whether the information comes from a phone conversation, online survey, web form, web-based cancellation request, or email, will have a distinct competitive advantage.

Real-Time Analytics Defined
Analytics is one of the most overused words in the technology market. Even worse, many of the supposed analytics offerings are really only reporting packages without online analytical processing (OLAP) capabilities – a fundamental component of any true analytics solution.

At the risk of defying prevailing wisdom, analytics is not reporting and not data warehousing, although it can use data from both these sources. Nor is analytics business intelligence (BI), decision support (DS), or personalization, although it may use these capabilities as well. Rather, analytics is a business strategy that uses enabling applications, including data warehousing, data marts, business intelligence, decision support, online analytical processing, modeling, personalization, and reporting to achieve its goals.

Real-time analytics applications collect information from customer interactions, analyze customer data patterns and preferences in real or near-real time, and enable agents to take action either while the customer is still on the phone or within 5 minutes to 24 hours. Real time analytics applications are action-oriented and include a transaction engine for initiating activities and a business rule engine that is seamlessly integrated with the transaction engine. Real-time analytics applications are capable of providing real-time decision support to facilitate immediate action.

Real-Time Analytics Applications Become a Corporate Priority
Real-time analytics is one of a new breed of technically sophisticated web-services-oriented applications that are helping to share customer insights collected in the contact center with other operating areas. It does so by capturing and structuring customer transactions and identifying embedded insights and new opportunities. As the success rates in large-scale consumer campaigns continue to decrease and Do Not Call (DNC) legislation limits the use of outbound marketing campaigns, sales and marketing departments now have little choice but to ask customer service for help in reaching and selling to enterprise customers. During the past 30 years, the lack of cooperation and interaction between sales, marketing and service departments have cost companies an unqualified fortune in lost opportunities. A major goal of the CRM movement was to get the three primary customer-facing organizations to work together, but this challenge remains unmet in the majority of enterprises.

Efforts are underway in many companies to open up the contact center, making customer interactions and feedback transparent to sales and marketing, so that all customer opportunities and insights can be exploited on a timely basis. The contact center is increasingly viewed as an excellent sales channel, but improved systems and best practices are needed to facilitate these efforts.

Enterprises need timely, useful and actionable information about their customers and they need it at ever-increasing speeds. By converting large amounts of raw and unstructured data into useful information in a matter of minutes, real-time analytics gives an enterprise an advantage over competitors who continue to waste manpower and labor with unwieldy customer databases or even larger data warehouses.

Enterprise Benefits of Real-Time Analytics
Contact center real-time analytics applications contribute to an enterprise’s bottom line and to all customer-facing departments and operational areas, including: the contact center, sales, marketing, technical support and operations. Real-time analytics increases revenue and decreases the cost of sales when used to up-sell and cross-sell and to segment offerings based on customer value. These applications are used by marketing organizations to decrease customer attrition and enhance brand loyalty by capturing and identifying the reasons why customers close their accounts and uncovering customer opinions about competitors; by leveraging this information at point of contact, agents are able to counter offer and retain customers instead of losing them and then having to win them back at a later time. Additionally, the highly valuable competitive intelligence can be analyzed to create proactive retention campaigns and/or to influence a product’s features and pricing. Customers have always been willing to share their thoughts freely about products and service, but only recently, with the introduction of real-time analytics applications, have contact centers been positioned to use this information systematically.

Real-time analytics applications are used to improve service quality and customer satisfaction while reducing support costs by functioning as an early warning system for operational errors. Capturing this information early on limits the damage, avoiding additional inquiry volume, production costs, and negative press. These applications are also empowering for customer service representatives as they can quickly qualify and quantify problems that previously generated large volumes of angry customer calls or e-mails. This results in reduced agent attrition. Lastly, real-time analytics increases first call resolution, identifies training opportunities, and highlights new system requirements and fixes by quickly capturing and identifying system bugs. The products also add value by capturing customer recommendations for enhancements without requiring agents to write down all of the details.

Real-time analytics applications yield great results for individual departments but their value grows significantly for the enterprise and its customers when sales, marketing and customer service share goals and objectives.

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