45 percent of customers say they’re more likely to visit businesses that respond to their reviewsOnline Reviews Survey
Why is a customer review more important than a customer rating?
That’s what we’re going to find out at SxSW 2017.
Chris Campbell, our CEO and founder, will join Troy Janisch, VP of Social Intelligence at U.S. Bank, and Rob Key, CEO of Converseon, at a panel at SxSW 2017. The special panel of experts will discuss “The Sexy Side of Sentiment.”
But it can only happen if you (the reader) click here and vote.
The Future of Unstructured Feedback
Customers are providing their deepest emotions about your product and service.
Your hostess is rude.
The loan officer was helpful.
This unstructured feedback is what your business needs to make drastic changes, improve operational efficiencies, and work to become more a more “customer-first” organization.
For organizations that are managing customer feedback at an enterprise scale, this poses a challenge. When you’re aggregating customer data from hundreds or thousands of locations, from thousands of online sources, how do you begin to understand it?
Where to Find Sentiment
It’s a mess out there. Customer feedback about your businesses is already everywhere on the social web. It can be difficult to understand if you don’t know where to start.
Where do you find sentiment among the customer voices online?
The information required to understand how customers feel is right in front of you…. but just out of reach. It’s on online review sites like TripAdvisor, Google, and Facebook. It’s in E-mails. It’s under the “additional comments” section in surveys. Processing all of this customer data becomes a chore beyond the scope of the average business and discovering actionable insights becomes a pipe dream.
Find out what customers truly need by using a variety of customer data sources already out there.
Big Data & Natural Language Processing
There are a multitude of techniques for mining relevant sentiment data already in existence. Using natural language processing, artificially intelligent systems are able to accurately predict the intentions of the human communication. Companies such as IBM, Microsoft, and Google are actively developing machines capable of deciphering online customer sentiment at scale.
Using thousands of online reviews, millions of social media mentions, and other online customer data-points, machines will continue to provide important insights for marketing departments, operations organizations, and executive suites who wish to better understand their customers.