If you have been keeping tabs on new technology announcements in the realm of UC business communications, you will see more products and services that are focused on customer services. That involves more than the business processes themselves through traditional “call/contact centers”, but also the performance of customer support through customer-facing staff (live assistance from agents, subject matter experts, field support, sales contacts, etc.), increasingly from automated self-service applications, or a combination of both staff and automation. Under the label of "analytics," all aspects of operational performance are being captured and analyzed to improve customer satisfaction, efficiency, and productivity.
While there is no question about the importance of understanding how customers and support staff are performing in various business processes, most of the contact center technology announcements coming from traditional telephony-oriented providers still focus heavily on the voice conversations between people, and on using "speech analytics" as a key objective for customer service analysis.
On the other hand, there is increasing use of analytics to monitor and track all kinds of automated business process applications in order to improve the efficiency and ease of use of such activities. Information Week recently surveyed business executives on the shift to “innovation” in supporting end user needs and making business processes (which has to include communication contacts with people) more efficient. The study highlights the importance for UC and CEBP, showing CIO responsibilities outside of IT for telecommunications as the highest (64%) domain of responsibility and interest.
The study also describes how "innovation" is taking over automating business process applications, particularly in online/self-service activities, and is relying on more comprehensive analytics to monitor, evaluate, and improve such processes from an end user interface perspective. Since UC is not limited to just speech interfaces with automated self-service applications, it is obviously going to be a powerful element of any automated application process, as well as providing access to available live assistance when necessary. However, even as consumers rapidly adopt mobile, multi-modal endpoint devices (smartphones, tablets) for business contacts and interactions, the analytics world seems to be slow to integrate voice telephony contacts as part of the brave new world of seamless UC.
Business Communications--What We Say Is Only Part Of What We Do
Capturing what people say during a business call can be useful, especially if it helps describe the customer's state of mind and satisfaction with the business process. Analyzing conversations for keywords and emotions can provide insights into what the customer is doing and, if displayed in real-time to a customer-facing agent, can expedite better resolution of the operational issues involved. Thats like having a customer hooked up to a lie detector while discussing any problem that requires live assistance. But do we need that much "analytics" data all the time? UC, by definition, covers all forms of business contacts and interactions; so tracking all communication activities is an effective way to monitor all business communications, not just customer interactions. The practical definition of UC as a concept has been well stated for a number of years by UC Strategies, i.e., "Communications integrated to optimize business processes." After all, business processes involve internal staff, external business partners, as well as consumer/customers. So we really need to be looking selectively at key business processes as the starting point for what communication activities the analytic tools need to be tracking.
With the increased adoption of smartphones for all forms of contact with people, especially for text based messaging (SMS, social networking, email), voice conversations are slowly becoming less significant for analytics. So, even though the technology for capturing and analyzing voice has become very sophisticated, that does not mean that all other forms of business contacts should be ignored. In particular, automated business processes that initiate time-sensitive notification contacts with individual end users (CEBP), will not be having voice conversations with customers, and instead will exploit the visual interfaces of personal smartphones and tablets.
Self-service Applications and UC
I recently reviewed a report in Speech Technology magazine on contact center technologies that focused primarily on call management and speech analytics to evaluate and manage customer-facing agents as part of Work Force Optimization (WFO). The article describes the progress of speech analytics as key to evaluating both agent performance and customer satisfaction. While this perspective is certainly valid for customer contacts via traditional phones, it is definitely not adequate for exploiting multimedia self-service application access by customers through multi-modal mobile devices.
In talking to an old colleague, Jeff Schlueter, a marketing VP at Nexidia, a leading provider of Enterprise Speech Intelligence software, I raised the question of how speech analytics fits into the overall multi-modal mobile UC picture. His first response was that smartphones were all that he personally needed. Then I reminded him that UC is not just about person-to-person contacts and that enterprise applications needed to be integrated into the picture (CEBP). Obviously, the technology is still evolving and that perspective remains to be defined and developed.
Needless to say, speech analytics does become useful when speech is used for input, whether in a voice conversation or even when speech commands are used as self-service application inputs. Otherwise, tracking all user interactions is necessary for monitoring and evaluating end user communication activities. That's why business communications need the flexibility of UC as well as comprehensive analytic tools to track all interactions that may occur during the course of a business process.
