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Uniphore and Behavioral Signals Executive Interview

Sheri Greenhaus, Managing Partner, CrmXchange, conducted a Q&A with SVijai Shankar, VP of Product Marketing and Growth at Uniphore Rana Gujral, CEO at Behavioral Signals to discuss their AI-first approach for Contact Centers.

1. In a few sentences each, tell us a bit about Behavioral Signals and Uniphore. 

Vijai (Uniphore):

Uniphore offers the most comprehensive conversational automation platform combining conversational AI, workflow automation, and RPA (Robotic Process Automation) with a business user-friendly-UX in an integrated platform to transform and democratize customer experiences.

Rana (Behavioral Signals):

Behavioral Signals bridges the communication gap between humans and machines by introducing emotional intelligence, from speech, into conversations with AI. Our AI technology, offers a rich variety of emotional and behavioral metrics and allows both real-time and batch audio processing, and can readily support heavy-duty applications. An example of that is our AI-first approach for Contact Centers, AI-Mediated Conversations, a behind-the-scenes service that automatically matches each customer to the best-suited agent using voice data and emotion AI. AI-MC raises performance and outcomes —like revenue recovery and customer satisfaction— all through the call center.

2. Please explain what you mean by AI-Mediated Conversations.

Rana:

Within call centers, calls are usually randomly paired between an agent and the customer or prospect, regardless of the customer behavioral profile or employee skill set. AI-Mediated Conversations (AI-MC) is an automated call routing solution that uses emotion AI and voice data to match the customer to the best-suited agent to handle the specific call. This match is based on behavioral profile data extracted from previous voice interactions and our superior algorithms developed from years of research and experience in NLP and Behavioral Signal Processing. Whatever the objective, there is always a catalyst that allows the two parties in a conversation to reach the desired result. That contributing factor is usually a simple and naturally occurring human process: the affinity or rapport developed between people. Regardless of the type of business communication (sales call, support, collection), it will always be an interaction between real humans that eventually matters. We have specific behaviors and traits that help us get along with some people, better than with others. AI MC focuses on these specific behaviors and traits that are unique for each human to achieve the best possible conversation outcome.

Vijai:

AI-Mediated Conversations implies the use of AI to understand who the customer is, their intent, sentiment, and emotion, driving meaningful outcomes within the full context of the conversation. AI powers the ability of the machines to predict based on various parameters to derive the insights needed to deliver meaningful outcomes. This will apply for both customer service and sales conversations in both B2C as well as B2B environments. 

3. How is the partnership of Behavioral Signals and Uniphore creating a new experience for customer engagement?

Vijai:

People like to speak to people they seemingly relate to. The Behavioral Signals and Uniphore technology uses AI and ML to match each customer to the best-suited agent based on their respective behavioral profiles, leading to a more engaging employee experience. 

Rana:

Human communication is a complex process that depends on not just the words being spoken but also how they are being expressed. Behavioral Signals understands “How” something is being said in addition to “What” is being said. We understand human emotions, deduce speaking styles and assess behaviors from the “tone of” voice. We are excited to add these capabilities to the Uniphore product suite. 

4. How are you able to match each customer with the right agent?  What criteria do you use to determine the ‘right agent’? What if the right agent is not available?

Rana:

Our proprietary AI predictive model consumes behavioral profiles created for every agent and client using a variety of behavioral attributes, extracted from previous voice interactions. Here’s how this works: A customer call arrives in a contact center. Previous communications have allowed the creation of an interaction profile for this customer. In a split second, an AI predictive model determines which employees should be matched with the specific customer for the desired outcome. The customer is connected with her top match to discuss her issues or needs, contrary to today’s practices where customers are routed to the first available employee in an arbitrary manner. If the best-matched agent in the list is not available the client will be routed to her second or third best match and so on.

5. How is AI improving quality monitoring?

Vijai:

AI can be used to automate quality management and can enable the monitoring of 100% of calls against business rules to evaluate agent performance. Without the use of AI, quality analysts will be able to parse through just 4-5% of calls to monitor for quality management. AI makes it easier to map and deliver actionable insights against business rules. 

Rana:

Artificial intelligence is more than just a supplement to the existing processes. It can transform a Contact Center’s operations by allowing its operators to extract more meaningful insights from voice itself, in real-time. That combination of existing analytics with deeper insights from voice, like emotions and behavioral signals, can provide the kind of actionable intelligence that can boost revenue collection, sales, customer satisfaction, or help predict needs and outcomes. 

6. Your website states: ‘The technology captures this information from historical data related to the calls of both customers and agents, including talking style, positivity, emotional charge, and other elements of their voice and the outcome of those calls’.  What other tools are needed in order for your technology to quickly gather historical customer data? How do you match a first-time caller?

Vijai:

Our technology will integrate with existing CCaaS environments to deliver the system of intelligence required to drive better CX.  The CCaaS vendors from the basic call center infrastructure will route the calls to the right agents. Our tech will provide the intelligence required to drive next-best action, real-time agent coach, automating after-call work summaries, and analytics to help unlock the value in every conversation. First-time callers are matched with purely their intent, sentiment, and emotion to help guide the agent to deliver the best possible treatment.  

Rana:

AI-MC is a nimble solution that can be deployed in a matter of weeks via simple integrations with an audio source and a dialer. We typically require the last 3 months of call data to initially set up the system. Just a 2-minute audio interaction is all that is required to construct a high-quality behavioral profile for both an agent and a client. For a first-time caller, a behavioral profile can be constructed on the fly, in real-time by analyzing the interaction of the client with the IVR. Alternatively, we would route that client to a group of agents that fit a “neutral profile” category and are known to be matched with a broad variety of conversational profiles.