I have been doing research into customer relationship management (CRM), contact centers and analytics for seven years. Throughout that time some customer-related themes have remained constant: Companies say their top driver is to improve customer satisfaction; customer experience management (CEM) has overtaken CRM as a top priority; and companies still search for a 360-degree view of the customer (which now is often called “the voice of the customer”). For many companies these themes remain problematic. Most don’t really know how satisfied their customers are; many are not sure exactly what CEM is; and that 360-degree view of the customer remains elusive.
In my research into customer experience management, I discovered that the majority of companies rely on manual and thus subjective ways of determining customer satisfaction, such as contact center agents assessing how satisfied callers are with their handling of calls, flipping through completed customer surveys and “sensing” what customers are happy or unhappy about, or listening to a small selection of recorded calls. In reality customers are telling companies every day whether they are satisfied or not – the problem is that this information is tied up in call recordings and multiple kinds of written documents. Companies have vast volumes of documents: notes handwritten by contact center agents, e-mail messages, postal letters, completed surveys, instant messaging scripts and now comments posted on social media or other news sites and forums. If companies could unlock this information, they would find a fuller picture of their customers and their levels of satisfaction.
Clarabridge tries to help them find the key. Its Clarabridge Enterprise technology can capture and extract text from documents from all the sources above, as well audio sources that have been transposed into text and, in the company’s latest release, text from social media. Clarabridge also has a natural-language processing engine that can analyze and make sense of text. It can spot words, phrases and combinations of words, combine these with other sources of internal data such as CRM and then use rules set up by the user company to classify the interaction as being of a certain type. It can use similar techniques to attach a customer sentiment score to the interaction – for example, by picking out predefined words and phrases and applying sentiment rules, it can find parts of an interaction where the customer is expressing positive or negative views (perhaps the bed was too hard, my room was very noisy, checking in and out was easy, or the staff was very helpful). Finally it can produce reports, dashboards, trend analysis and early-warning alerts that include the information different users want to see from the analysis.
Pickup up on where I highlighted the importance of unlocking customer voice through text analytics the demand was just beginning to pick up steam. Clarabridge’s latest release is aimed at the social media space. Among other things, social media have become a key source of customer information and sentiment. Customers no longer tell only immediate friends and family of a bad experience with a company; now they can use social media to tell the world about their bad (or good) experiences. All of this communication is of course outside the company’s control and so is often a truer reflection of customer sentiment than in-house surveys. The Clarabridge extractors can pull data from a range of sites and feed it into the classification and analysis tool. This gives companies the power to do two things: respond appropriately to the interaction and more importantly change the root causes of bad customer experiences; that might include changing the bed supplier, making sure VIP guests get quiet rooms or training contact center agents how to handle certain customers.
Clarabridge makes it easy for companies to access these capabilities; the product is available either for on-premises installation or as software as a service (SaaS). It also provides professional services to help companies get up and running, but customers I have spoken to said they quickly got the hang of using the application and setting up classification and sentiment rules, and are able to produce personalized outputs.
For me the first purpose of CEM is to change the way interactions are handled, including while they are happening. To do this companies need up-to-date customer information based on as much customer data as possible. It is evident from my research into customer information management that the bulk of customer data is in unstructured forms such as text. Customer service in the social media age is no easy task as I have already pointed out and tools like that from Clarabridge can help significantly. Clarabridge allows companies to unlock the value of information and use it to improve the experience and thus satisfaction of your customers.
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Richard Snow – VP & Global Research Director