Your customers are talking. Are you listening?
Can you? Traditional CRM analysis exposes only 20 percent of the valuable customer insight that your company captures today.
Enterprises have invested heavily in CRM solutions that collect tremendous amounts of information on their customers during product-support, service-request or transaction-processing interactions.
During these exchanges, a wealth of information is captured in call-center notes, or “verbatim,” such as the customer’s emotional state, sense of urgency or impatience, competitive insights and specific and complex issues associated with buying, using or configuring a product or service.
But it is only the “structured” data—the information that can be easily stored in the rows and columns of traditional databases—that is typically analyzed and mined. In many organizations today, the “unstructured” information such as call-center verbatim is only occasionally reviewed—usually one document at a time—and rarely used to identify trends, root causes of problems or opportunities for improvement.
In fact, there is even more unstructured information residing outside the enterprise. Web forums have gained in popularity, and customers are sharing their grievances and expectations through online product reviews, blogs and social networking sites. This consumer-generated content is growing rapidly in both volume and value.
The complete range of unstructured information—gleaned from both inside and outside the enterprise—must be thoroughly analyzed if a company is to acquire a complete understanding of its competitive threats and how to improve products and services to retain old and acquire new customers.
Traditional CRM analytics that leverage only structured data can tell a company how many customers called, average call durations, specific transaction amounts or products purchased during an exchange—and, perhaps, the broad category of issue discussed during a call. They cannot, however, answer the important questions that help a company improve product experiences, assess quality-of-service issues or proactively identify a competitive trend that might impact future corporate performance.
Text mining enables a company to leverage unstructured information and answer the provocative questions:
– What’s behind the trend in three-to-five-year customers canceling their policies despite steady prices?
– A new product that sold well after a marketing launch appears to be falling off precipitously, and returns are much higher than expected. Why? Product complexity? Quality? Installation issues?
– Another company just launched a directly competitive product that is impacting your sales. What are your customers saying about the competitor’s product?
– Anecdotally, you believe that angry/frustrated calls across a national chain of retailers are increasingly associated with product installations. Is the increase quantitatively measurable? What is causing the increase?
– You have a sense that a product-support issue that is hard to categorize is becoming more common, but the information is only being captured in the call center notes. Is the issue truly increasing in magnitude? Is you staff able to resolve the issue?
– What’s the must-have toy going to be for Christmas? How do customers expect to buy the product?
– Your competitor’s drug has just been pulled from the market because of safety concerns. How have perceptions of your product quality and safety been impacted? Is a campaign necessary to calm fears of your customer base?
Both structured data (which quantifies historical customer transactions) and unstructured textual information (which reveals customer feelings and desires) can provide meaningful insights that drive a variety of sales, marketing and customer-support decisions. Early adopters of text mining—including companies in consumer goods, retail, life sciences and financial services—are synthesizing all of the structured data and unstructured text available to them to dramatically enhance decision-making.
“Commercialized” text-mining solutions–the product of simultaneous development across business intelligence, data warehousing, CRM and natural language processing (NLP) technologies—integrate seamlessly with companies’ traditional reporting tools.
Familiar techniques such as score carding and creating “slice-and-dice” and drill-down reports can be applied for the first time to unstructured information, and new techniques of sentiment analysis and automatic categorization can be applied against customer information.
With a holistic view of internal information assets and external, consumer-generated content, companies can use commercialized text mining to answer any question of any internal or external data source, using any analytical tool. Text mining ultimately makes a company more agile and adaptive, capable of adjusting course at the onset of trends.
Enterprises have never had to available to them so many sources of information or such sophisticated tools for discerning the true sentiment of the market. Commercialized text mining tunes a company into its customers.
About the Author
Sid Banerjee is chief executive officer and co-founder of Clarabridge, Inc., which enables Fortune 1000 customers to transform text into valuable information to improve market research, customer care, product development, quality assurance and risk management.
