One of the eternal problems in a call
center is getting an enquiry routed to the right agent. This is doubly true in
a mobile world that demands conversational support in near real time.
Add to this the fact that most customers
seeking support already failed to find an answer to their inquiry using an FAQ,
a community, or other self-services. In this situation customers expect an
answer within few minutes, if not seconds.
On top of this, the ability to make
engagements with the company easy, efficient, and ideally joyful, is becoming
more and more a distinguishing factor for companies. Customer experience is the
result of engagements, and for humans the experience gained from the most
recent engagement tends to have a higher influence than older ones. Consequently,
a positive customer experience matters, not only during marketing- and sales,
but even more so in situations that require active help of the company that
sold the product or service. So, getting a solution to an issue must be as easy
and as human as possible.
The challenge is that every support
organization needs to live and work with limited resources – human as well as
technical ones.
It is Like a Good Game of Soccer
11 players and a ball. There is a goal
keeper, are defenders, midfielders and attackers who play as a team against
their opposition, trained by their coach and guided by the captain. There is a
core team, and some players may be assigned to different roles, even within one
game. Depending on the opposition team, the coach and the captain change player
assignments, tactics and roles.
Together they play the ball with the
objective of scoring.
Like a soccer team call center agents are
organized around their strengths and like soccer players the agents are – or
should be – carefully trained and assigned to roles on their field: the queues
with which incidents are managed. Like the soccer players, agents can be
assigned to different positions on the field: different queues.
The incident is the ball and the scoring is
resolving the incident.
With all its intrinsics, soccer is a simple
game. It has a few rules that dictate the do’s and don’ts. Following these
rules, considering available players and their strengths, is the table stakes.
Yet, this doesn’t make for a game that the spectators may find exciting – nor
might it lead to scoring. There is an art to it, the art of how and to which
player to move the ball in any given situation.
This is the same in a call center
environment.
Yet, in some call centers, when receiving
the incident, the team stops and asks the spectator where to start. The user is
asked to qualify it and to route it into the right queue. This is a task (s)he
is obviously ill prepared for.
Doing so would lead to a heavily disrupted
game that no one would like to watch, not even talking of enjoying. Scores
would be rare and far in between.
In a call center environment, this leads to
unnecessary load. Load that is caused by re-routing the incident, delays in
handovers and resolution, and ultimately frustration on both ends: The end user
and the service agent.
In brief, it is causing a poor customer
experience, following another poor experience.
There must be a better way.
And there is.
Back to our in-app support world.
Why not using the incident itself to automatically
identifying the right queue and smartly routing it there? This is like the soccer
players using the ball’s momentum and the given situation to proceed to score.
There are two basic possibilities to
achieve this smart routing. One I would name the classic approach, the other
one the text mining approach.
The Classic Approach
Automatic routing to the right queue can
easily be achieved by using metadata that is provided by the app as part of the
incident report. Incidents are tagged based on this metadata. The tags are used
to route the incident to an appropriate queue or agent. A configurable
automation does both, tagging and routing, without explicit intervention of the
app user, who is already in distress enough as there is an issue that he or she
couldn’t resolve.
This is a proven approach that requires an
elaborate design of metadata and its collection within the app and the ability
to build rule sets on top of this metadata in the service back end.
With sufficient data and advanced analytics
tools this approach can also be used to offer pre-emptive
support, which further improves the customer experience by avoiding the
negative experience in the first instance.
This approach, however, finds its limits in
the ability of instrumenting an app so that enough situations can be identified
from the metadata for appropriate tagging. Not in the least because
instrumenting has an adverse effect on the app.
The Text Mining Approach
With more and more service center software
running in the cloud, massive improvements in AI, Natural Language
Understanding (NLU) and machine learning technologies, additional information
can be used: The description that gets submitted by the user as part of the
incident report.
Albeit the users do not always provide
accurate information, this is regularly enough to augment and improve the
tagging, therefore getting a better routing and ultimately faster resolution.
Given that in many systems the first line
service agents can resolve incidents by themselves consulting a knowledge base
the AI might be able to resolve the issue before escalating it to an agent.
Smart Routing is the Future
This paves the way. Currently leading
systems smartly queue and route incidents based upon an elaborate architecture
of metadata and tags that are automatically given based upon the metadata. This
already tremendously helps companies in providing good service.
The next step is including the descriptions
given by the users into the mix and to use it to suggest solutions to agents
until confidence is high enough to have the software independently suggest
solutions to the users or to route the incidents. NLU in combination with
machine learning / deep learning are nearly at this stage.
In either case, smart routing is reducing
the friction in the support process and therefore improving customer- and
service agent experience. The result of this concentration on positive
experience is a measurable benefit for the business – because of adding value
for the customer.
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