Many organizations are hungry to understand what customers
and prospects think of their brand, products, services, and unique
relationship. To this end, organizations are trying to move from reactive
responses to negative experiences to proactive real-time action at the time of
both positive and negative interactions. There is a movement to more sentiment
analysis by supporting this shift, leveraging emotion AI and other forms of
opinion mining to help spot, extract, and quantify subjective information around
the customer's voice in real-time. Leveraging natural language processing, voice/text
analytics, computational linguistics, and biometrics are becoming a strong
trend.
Maybe You Should be Listening:
The cost of not listening after the damage is evident is not
smart to do business today. When an organization hears phrases like "Can
you believe this?", "Shame on them," "Let's get 'em,"
or "Do the right thing" in social media streams, it's getting to the
point of damage. If there are positive responses, organizations would be
foolish not to take advantage of those beautiful gems of customer delight. It
is important to sense harmful and helpful responses in social media, tapping
into real-time sentiments in the middle of voice interactions happening in the
servicing channels.
What Should Organizations Listen to?
Organizations should be listening for brand health,
product/service satisfaction, and the overall relationship. Listening to
mentions of the competitor's names is essential and usually means you are under
pressure of some kind. The customer is either growing in frustration or is
beyond their tolerance for unsatisfactory service. Voice inflections will tell
you if it is just a need or a real frustration. It is essential to distinguish
between a want or a wish or a real need. Of course, listening for the good news
is just as important, so knowing if your customer or prospect is happy and
loves the service they are getting is a great thing. Listening for the positive
is particularly vital if you want to upsell or cross-sell a customer.
What are the Typical Indicators to Focus on?
There are everyday things to listen to for sentiment. If
there is a lot of customer silence, they may be learning or just controlling
their emotions. Listen for overtalk where the agent is pushing their script
over customer needs. Also, listen for impatient customers that feel that they
are not being heard; they overtalk the agent and their talking script. These
calls are great for training, but real-time action is the first prize.
It is also essential to listen to the drivers for the calls
to determine if there are positive or negative trends forming. Customers will
let you know what they want, so it is essential to focus on their goals, not
just the CPA driven goal of reducing time to apparent resolution. This kind of
listening helps in improving first call resolution and even net promoter scores
(NPS).
Net; Net:
It's crucial to spot bad customer experiences early in your
contact center. Voice and text analysis in real-time leveraging AI helps ferret
out real sentiment analysis. Finding the right combination of digital
technologies is much easier today than even a year ago. Many options will help
improve customer relationship metrics. Voice is the growing approach today as
it captures the real customer sentiments before the relationship breaks down
and organizations are trying to bandage a large wound without much success.
Additional Reading
Voice; Voice Baby
Got Customer Excellence?
Let Your Voice Be Heard
