TeamSupport, provider of a B2B customer support solution, today announced it has added to its platform a sentiment analysis capability powered by IBM Watson’s artificial intelligence technology, a feature that aims to provide deeper insights into how customers feel about their experiences.
“One of the most important things that we can provide to our customers is the ability to better understand their customers,” says Robert C. Johnson, CEO of TeamSupport. “What sentiment analysis allows our customers to do is both understand the individual comments that come in and look at the level of frustration, satisfaction, happiness, etc., on each one of those actions and at the customer level as well.”
The new tool will provide TeamSupport users with text analysis that identifies how a customer is feeling based on his email or chat responses, using categories such as “satisfied” and “frustrated” to enable customer service agents to respond appropriately in each of their customer interactions. Information gathered by IBM Watson’s AI can be used to score response data at the individual ticket level and overall customer level.
“When a ticket comment comes in, either an initial question or an answer to an ongoing conversation, we’re able to measure the level of frustration or dissatisfaction,” Johnson says. “The agent, of course, sees that, but we can do things around automation on that as well, so we can, for example, flag a manager or a C-level executive if a customer is clearly getting frustrated during the course of the conversation.…We also roll that information up on the overall ticket level, so if you have a brewing level of dissatisfaction or frustration, that becomes evident on the ticket level.”
He adds that the information collected from these interactions is compiled to provide an overall view of how the customer is feeling. “We take the aggregate of the conversations and bring that up to the customer level, so we can look broadly at customers and see their overall level of satisfaction, dissatisfaction, or frustration across all of the interactions they’ve had,” Johnson says. “That becomes very important to start measuring not just transactional sentiment but actually longer-term sentiment about the customer.”