Follow up on my previous post discussing the key technologies around the conversational AI solution, I will be dive into the typical challenges the AI Engineer team would encounter when building a virtual agent or a chatbot solution for your clients or customers. Let firstly define the scope and goal of the conversational application. The conversational agents can be categorized into two main streams. The typical agents for Open Domain Conversation are Siri, Google Assistant, BlenderBot from Facebook, Meena from Google. Users can start a conversation without a clear goal, and the topics are unrestricted.
In this episode, we're going to discuss how Marketers can use Conversation Intelligence to convert conversations into sales. Our guest today is Natalie Severino, who is VP of Marketing at Chorus.ai Favorite AI Solution: Chorus.ai . Mark – explore our chatbot on Facebook marketing. BIO: Natalie Severino is the VP of Marketing for Chorus.ai., the #1 Conversation Intelligence platform for high-growth sales teams.
Have you ever wondered how chatbots can understand natural language and answer using the same linguistic code? The answer is simple: behind every chatbot there's a human being or a team of human beings (often) called Conversation Designers, who give them a human voice. The bases of any frictionless interaction are the ability to understand unambiguously and the ability to answer accordingly. Human-Chatbot communication makes no exception. A chatbot understands messages thanks to NLP technologies that analyze and interpret natural languages using complex Machine Learning algorithms.
Melbourne, AU, Sept 2019 – Companies are now embracing Artificial Intelligence (A.I.), not just a tool to improve service efficiency but as means to forge a deeper relationship with customers. It is now used to augment processes across the business value chain, resulting in increased productivity and more informed and effective decision making. There is however still a space for Human Intelligence – H.I. In the context of Conversation Analytics, A.I. is deployed to allow us to do things quicker, faster and smarter. Take Quality Assurance (QA) as an example – long the bastion of QA staff listening to calls to assess risk, misconduct, Customer Experience (CX) opportunities and missed sales. Using this approach, most QA functions in a business AT BEST, listen to and assess 1% of their customer interactions.
Amazon is encouraging us to put listening devices in every room of the house with executives from Amazon saying that Echo assistants don't listen to private conversations, they say the device will start listening to conversations only if the word Alexa was used, this is not always the case as a story from a user in Portland highlights. An Alexa user from Portland, Oregon has installed Echo and Smart bulbs in every room of their house thinking that nothing bad will happen, however when asking Amazon to investigate an issue about Alexa recording a private conversation between her and her husband that was sent to a random number in her address book without her consent. She didn't believe her friend at first, however when her he explained the conversation between her husband she finally believed them. "You sat there talking about hardwood floors." Danielle realised the colleague must have heard everything.