- “Also known as opinion mining or emotion AI, sentiment analysis helps a business understand the social sentiment of their brand, product or service by mining text that identifies and pulls subjective information from the source material.
- Listen, listen and listen. It’s all out there — billions of online reviews with details and sentiment at the product and feature level, ripe to be taken. You will be a fly on the wall in the largest consumer panel and will be able to know the sentiment about your offerings, as well as about those of your competitors.”
I read a lot of these articles on a daily basis and it’s easy to identify the ones that are repeating the same old story to build SEO; and, I scrub those out so that you’re not stuck reading the same thing every day.
This one is clearly different with the concepts of predictive routing and sentiment analysis…check it out.
“AI-powered predictive routing engines can use historical performance data and match customer and employee attributes to predict which contact center agent is most likely to achieve targeted business goals.
Next best action
Contact center platforms such as Genesys leverage AI to suggest the “next best action” to agents in real time. This recommendation is typically based on an analysis of the customer profile, the type of inquiry they are making, and keywords being used in the conversation.
In an attempt to keep their contact center agents focused on high-value transactions, many financial institutions have started to deploy chatbot applications for lower-value interactions. However, even as chatbot technologies are rapidly improving and can effectively address basic needs, they cannot establish a personal connection that can build confidence and drive customers to share more of their needs or invest more.
Having a reliable way to identify a customer is a fundamental step in closing a financial transaction remotely, and is almost always a compliance requirement. In most cases, it includes verifications such as asking customers for their account number and other questions including address, birth date, and social security number.
Real-time sentiment analysis
Analysis of the video and audio streams will also dramatically enhance the assistance that can be provided to the agents. Facial expressions, body language, tone of voice, and keywords all reflect underlying states of mind, and uncovering them in real time feeds more informed suggestions to agents, who can then act more effectively.
Speech recognition, automatic text translation, and speech synthesis are all making rapid progress. It’s easy to envision applications in the not-too-distant future that will combine these technologies with video interaction. This will enable participants to speak their own languages but see on screen or even hear a translation of what the other party is saying.
Last but not least, contact center executives are constantly looking for ways to better collect and analyze the content of interactions to improve the quality and effectiveness of their services, provide more value to customers, and identify relevant post-contact actions. With speech recognition, the audio content of a video conversation can be transcribed into text, stored, and analyzed like any other text-based interaction channel.”