FEATURE ARTICLE
by SUSAN HASH
CONTACT CENTER PIPELINE
JUNE 2017
BLENDING AI WITH HUMAN SUPPORT
“Freeing CSRs from repetitive
manual tasks allows them to
tap into their critical thinking
and problem-solving skills,
and to focus on transactions
that require an emotional
connection.”
FEATURE ARTICLE | SUSAN HASH
Blending AI
with
Human Support
Practical applications
of AI in the
contact center.
BY
T
he future of work and the impact that
artificial intelligence will have on the
workforce has been a hot topic lately.
The publicity has been a bit unsettling, though, given the tendency to couple
the acronym AI with the word “replace”—as
in “AI Will Replace Half of All Jobs in the
Next Decade” or “Could AI Replace Teachers,
Susan Hash, Contact Center Pipeline
Lawyers, Drivers, Doctors, [fill in your job]?”
These types of headlines might lead
you to believe that call center agents will
soon become unicorns, along with other
support-type positions that include a lot of
repetitive tasks and activities that can be
automated. But exchange the word “replace”
with “enhance,” “augment” or “transform”
CAN AI MIMIC THE BRAND’S PERSONALITY?
Some businesses have invested considerable time, effort and
expense into developing a brand personality. It is infused into
marketing materials, logos, website design, policies and company
culture—and even contact center scripts. Can AI pick up on and
exhibit the characteristics and qualities associated with that personality?
Absolutely, says DigitalGenius’ Mikhail Naumov. It’s simply a matter of training,
he points out.
First, historical data—which includes email transcripts, chat logs, email conversations, etc.—is fed into the deep neural network. “The expectation is that the
brand’s tone of voice already exists organically within the historical
log,” he says.
Next, the training continues when the algorithm goes live. During
the initial deployment stage, the system provides suggested answers
to agents for approval. Agents can approve, personalize or modify
the answer to personalize it for a particular customer. “The algorithm
trains on both—the agent’s actions, as well as any changes or personalization they
make—to convey the messaging of the brand,” Naumov explains.
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and that may provide a better sense of how
customer-centric brands are leveraging AI to
support the human element in their service
operations.
Certainly, there are still companies that view
the contact center as a cost center, and for
these, the thought of replacing hundreds of
frontline workers with robots might seem like
a magical solution to control the costs associated with staffing and managing human
agents. But the reality is that, despite the
influx of digital channels in recent years, customers prefer to speak with a human when it
comes to service issues (confirmed by recent
studies from Verint and Accenture).
Separate the Hype from
Practical Applications
When considering how AI can be applied
in a customer service function, it’s important to separate fantasy from the practical
applications, says MIKHAIL
NAUMOV , Co-founder &
CSO at DigitalGenius, an AI
customer service solutions
provider. “There definitely
has been a lot of hype in this space,” he
says. “Hollywood’s version of AI may or may
not come to pass some time in the future,
but let’s focus on the application that is real
and practical today—deploying algorithms that
save time and help customer service employ-
ees to be more confident in their responses.
We all want the same things—happier customers and engaged employees.”
DigitalGenius’ Human+AI™ Customer
Service Platform is trained on historical customer service logs and provides AI-powered
macro suggestions, automation of ticket tagging, auto-triaging, as well as automation of
responses. “These are the types of tasks that
AI is good at,” he says, adding that the combination of human and machine intelligence
can cut average handling time by up to 32%
per message.
What is the ideal model for a customer
service operation? Naumov recommends a
blend where AI suggests content and humans
act as the administrators of the system. “A lot
of the work is done for them by the machine
but then, ultimately, when it comes to sending the final message or solving a complex
query, the human is still there to supervise
the machine to make sure that it’s doing the
best job possible,” he explains.
Freeing CSRs from repetitive manual tasks
allows them to tap into their critical thinking and problem-solving skills, and to focus
on transactions that require an emotional
connection. Take, for instance, TravelBird’s
approach to AI. The package holiday provider
uses the technology to empower their customer service representatives, deliver a better
customer experience and engage staff in an
evolving, higher-skilled role.
Eliminating Repetitive Tasks
Frees Agents to Connect
Maintaining a human interface with customers is a central element of TravelBird’s service
mission. “People travel with their hearts and
souls,” says Head of Customer Service & Care
FIONA VANDERBROECK .
“But travel sometimes can
be unpredictable. Things
occur that create questions,
doubt or stress for travelers.
Our core job is to manage our customers’
emotions by responding quickly and making
a personal connection.”
TravelBird’s customer service operation
handles approximately 900,000 inquiries
per year, which are answered in 11 countries
by email, phone, social media and SMS. The
company’s rapid growth has led to a considerable increase in message volume. Rather than
replacing its customer service staff with bots
or outsourcing its customer care, the company partnered with DigitalGenius to support
frontline associates with machine intelligence.
The AI assistant provided by DigitalGenius
relieves TravelBird’s frontline advisors of repetitive administrative tasks like categorizing
and tagging the types of questions that
customers ask via email. AI also saves
advisors time when replying to frequent
requests. “A travel advisor doesn’t have
to write the same response over and
over,” Vanderbroeck explains. “The AI
presents the best available replies,
which the advisor can select and tailor.
Technology can perform those types of
tasks better than a human, and therefore,
it enables our humans to do what they do
best—make that interaction a bit more special
and personal.”
In addition to the customer experience and
efficiency benefits, Vanderbroeck
says that feedback from the
advisors has been very
positive. Eliminating
repetitive manual tasks allows them to focus
on the part of the job that they enjoy—helping
customers.
Self-Learning System Provides
Fast, Personalized Resolution
Increasing complexity in products, devices,
applications and services has been making
it almost impossible for companies to keep
up with content changes or the support
collateral that they might
need, says JC RAMEY, CEO
of DeviceBits.
“Consumers are relying
more on the Internet to
find their solutions, which can lead to either
positive or negative outcomes—but more
importantly, companies have no way of
knowing whether it was a positive or negative
outcome,” he notes, adding that, in many
cases, CSRs also are turning to Google to
find the answers that they need.
How can companies regain control of their
self-service while also managing increasing
handle times as CSRs attempt to resolve
more complex issues? Ramey suggests a
hybrid approach that empowers both the consumer and the CSR with information that the
business can curate and validate as accurate.
DeviceBits’ Care Assist product is an agent
portal that allows agents to converse with
customers via SMS, chat, web and social
messaging. The software is powered by a
self-learning AI engine that pulls content
from the brand’s knowledge base, DeviceBits’
curated knowledge base, and from public
sources, like Google and Bing, to try to find
solutions to continually improve the agent’s
experience. Over time, Ramey says, the AI
“understands how end users are using the
product, how agents are using the product
and maps those user journeys through successful outcomes.”
Improve Content Consistency
Across Channels
eGain’s SVP Worldwide Marketing ANAND
SUBRAMANIAM believes
that delivering a consistent
content experience is key
to driving value for both
customers and agents.
According to a recent survey of 500 contact
center agents by the customer engagement
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FEATURE ARTICLE | BLENDING AI WITH HUMAN SUPPORT
solutions provider, agents reported the top
two obstacles to providing excellent customer
service were finding the right answer to customer questions (26%), and different systems
and information sources provide different
answers to the same questions (25%).
Those responses closely corresponded to
an earlier eGain consumer survey. In it, consumers were asked about the worst aspects
of getting help from contact centers. The
top three responses: (1) Different customer
service agents give different answers, 41%;
(2) customer service agents don’t know the
answer, 34%; and (3) can’t find the answer
on website, 31%.
The findings were not surprising, says
Subramaniam. “We have these experiences
fairly often as consumers. When you use
web self-service, you often get the dreaded
‘no results found’ or 100 search hits that are
only remotely related to your issue. Humanassisted service is equally challenging. Most
AI IS NOT NEW
A common misconception about artificial intelligence is
that it is a brand-new concept. That is far from reality, says
Anand Subramaniam. “eGain has been a pioneer in AI for
contact center customer service with many blue-chip clients
using it for years, some for well over a decade. He offers
the following examples of how its clients are using AI today:
To converse with and answer customer questions using a virtual assistant: Virtual
assistants can be useful in answering questions of low to medium complexity
while providing an engaging experience.
To guide service and sales interactions with AI reasoning: Where queries are
more complex, AI reasoning can help guide the end-customer (in the case of
self-service) and the agent (in the case of human-assisted service) through the
next best steps to complete the interaction successfully. Guidance can also help
to enforce compliance with regulations and/or organizational best practices.
Moreover, it can be bootstrapped with context, leveraging information such as
past customer transactions, current interaction context, IoT data, etc.
To provide decision support with AI reasoning: Reasoning can also be used to
help make decisions, where the decisions can be the output, or they can support
a larger service process.
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recently, when I had to get something fixed in
my house through my home warranty company, I had to contact them multiple times.
Each time, I received a different answer. To
complicate matters even more, I received
different answers through the call center,
digital and field touchpoints. This problem is
commonplace, in our experience.”
What can contact centers do to address
content-related consumer and agent pain
points?
“Looking at the root causes from our recent
surveys, it is clear that the biggest hurdles
for great consumer experience and agent
experience can be addressed with a robust,
omnichannel knowledge management system
infused with AI. This will provide consumers
and agents with fast, accurate and consistent
answers and intelligent process guidance,
regardless of touchpoint,” Subramaniam says.
“Moreover, to develop empathy with customers and agents, center leaders should
eat their own ‘gourmet food.’” he says. “They
should conduct mystery-shopping as a consumer and ‘mystery-serving’ as an agent in
their contact center to experience things for
themselves. Empathy helps drive action!”
Susan Hash is the Editorial Director
of Contact Center Pipeline and Blog.
ContactCenterPipeline.
([email protected])
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