How CX organizations are evolving with generative AI

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thank you
when we put AI in place really we begin
to morph the way that we're interacting
with our customers we gain a lot more
insight into the data than we
necessarily had before an example would
be in the support organization where
tickets are coming in and there could be
a wide variety of channels that we're
tackling here traditional channels like
voice or email it could also be newer
channels where we're actually embedding
chat within mobile devices or within
websites or social channels and as a
result of that you have a lot more data
and a lot more different types of
questions and interaction flows than you
would normally have in a traditional
service organization
what this allows for is for that
organization to be able to take
advantage of that data prioritize where
the biggest impact items are and where
they're coming from and then take action
in deploying the AI to reconcile those
issues the Paradigm that you want to put
in place from a support organization CX
organization standpoint is to understand
what are all the reasons that your
customers or users are contacting you
and then where can you get the biggest
impact from deploying Ai and where is it
synergistic and where may it not be in
which case you actually want to leverage
your legacy channels where that might
involve a support agent
foreign
ex organization prior to deploying AI
you see a lot of traditional roles roles
that are focused on Services
implementing customers onboarding we
generally see a support organization
that's dealing with inbound requests and
queries that are coming in from the
customer base and we often also see an
organization that's responsible for the
long-term impact value that comes from
that customer relationship it begins
within an organization by pulling
individuals directly out of the front
lines who are dealing with customers day
in day out and they have to direct
exposure they know what the interactions
are like and so they then are interested
in being able to use the AI technology
to begin to automate some of those
interactions and so that generally
begins with a bot Builder who is
responsible for being able to design
what the conversation and and
interaction flows look like and put them
into a tool like Ada to be able to
automate
when you look at generative and the way
that the industry is going and the Ada
is innovating that takes a lot of the
pressure out of the build part and it
really begins to morph it into the more
analytical part of things so it's not
simply about uh setting up and
generating initial questions and
responses like an FAQ it's about
actually analyzing
um what are causing those interactions
and what is a different type of flow or
interaction framework that could
mitigate these types of concerns and
questions that customers have then from
a resourcing and tooling standpoint and
skill set standpoint you're beginning to
bridge out of the bot Builder into a
true bot manager and then that bot
manager begins to leverage other areas
of of skills or individuals for instance
there's a a premium that's placed on the
conversational design that's going on
there's a premium that's placed on the
data analytics because in many cases you
want to integrate and pull in data
sources to personalized interactions
there's a premium on the data science
aspect which is looking at when we Force
rank all of those types of interactions
how do we ensure that we're getting the
the biggest return on our investment for
deploying AI so it really does begin to
morph and it's less about the
fundamental building and more about the
Analytics
you think about success metrics like net
promoter score or a fixation on customer
satisfaction and in often our clients
will be focused specifically on agent
handle times this morphs definitely when
you put AI in place and it's not that
those old measures necessarily go away
but you have a different lens that
you're applying I focus heavily on First
Response time and first Contact
resolution what that essentially means
is when someone reaches out regardless
of the channel in a truly omni-channel
environment it doesn't matter whether
they're contacting Us in voice chat
emailing us social channels ultimately
the goal is to be able to understand
what it is that they're contacting us
about and reconciling it in the shortest
amount of time where we have confidence
that actually we've resolved their issue
so they're not having to either go back
through another channel to get their
question answered or to re-contact or
get frustrated and have to get routed to
an agent with things that really AI
should be able to handle