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