The moment of truth: I hear that term often in the world of customer
experience. It describes when a customer makes a decision – to search for
an item, to look for options, to speak to a representative, to fill their
shopping basket or check out. But what if that moment of truth was the
moment they decided to leave your site? Will you know why?
They say that
the customers you should be worried about are not the ones who complain on
social media or leave a negative survey, but the silent ones. The ones who
leave out of frustration only to take their business elsewhere. No
feedback.
So, then, how does a brand get a true picture of customer sentiment or find
out what really needs to be improved in order to satisfy customers? Here
are some insights I’ve learned throughout my journey for gathering and
analyzing the Voice of the Customer data.
1. Starting Point
From the vast collections of
unstructured data gathered from ever-expanding omni-channel solutions, a
brand can end up with a byproduct of millions of conversations and chat
logs, millions of touchpoints. So you have to start with a macro-view of
the data — an unbiased point of seeing everything – and then mine and
extract insights to tap into the feedback in a very customer-centric way.
It is common practice for a business to analyze customer feedback by
starting with a taxonomy of questions or variables based on what the
company thinks is important or relevant. That’s all well and good, but the
outcome is going to be very narrow and skewed. They will be missing the big
picture, and therefore may not see a particular set of customer insights
that would be vital to the brand’s improvement and growth.
Or, if starting
with only an A/B comparison, you stand the risk of not getting the whole
story. For example, if comparing the performance of two different web pages
on the site, you might be dealing with two different kinds of visitors, so
of course you’re going to get different results-that don’t have anything to
do with each other. Therefore, the conclusions that are drawn may be
completely false.
2. To Survey or Not?
Surveys are helpful, but
certainly not the end-all of customer feedback. They are given to customers
after the fact – after the pain point has been addressed.
If you analyze
the real-time, actual customer conversations, you will see the customer’s
genuine feelings and see the heart of the matter. Two other drawbacks in
analyzing surveys: they tend to come from a company’s biased questioning,
so the real question at hand may not be addressed; and the customer takes
the survey with an impression that their responses won’t be read, thus why
spend much time on it?
With the understanding that surveys are inherently
biased towards respondents who are willing to participate in surveys (i.e.
self-selection bias), a brief analysis of a major telecom captures such
disposition. Survey respondents with deeper levels of engagement, measured
by the number of customer messages sent, were 233% more likely to
participate in surveys vs. respondents with lower levels of engagement. The
overall survey population was disproportionally representative of visitors
with deeper chat engagements. Thus, data driven decisions were made
alongside of alternate and more inclusive program metrics.
3. Critical Insights from Chat
Chat conversations arise out of pain
points when customer self-service experiences don’t give them the
assistance they need, so what transpires are a goldmine in terms of what
you should do to prevent those pain points in the future. When the brand
looks at the raw data that comes from the touchpoints of when the
experience has failed, then you will truly see what needs to be improved.
Without this knowledge, you’ll be missing the mark.
A major
subscription-based retailer that sells pre-built bundles online, leveraged
live chat to provide real-time, shopping assistance. Text clustering of
such digital conversations revealed that a certain percentage of consumers
expressed interest in acquiring a single product only. Based on this
feedback, this major retailer created a particular purchase flow only
accessible via live chat referral. This resulted in a 20% increase in
single product units, leading to the creation of a new pre-built bundle to
further drive measurable increases in subscription-based revenue
Additionally, a major telecom provider completed a website redesign to help
continue to drive customer experience transformation. A notable increase
was observed in the number of customers who inquired about the installation
fee, post redesign. A usability analysis was conducted and revealed that
the cost of the installation fee is now increasingly emphasized, using bold
font. Based on this feedback, targeted optimization was performed, applying
a different treatment to the display of the installation fee. This resulted
in a 36% improvement in issue deflection and a 6% increase in customer
satisfaction.
Learning from Moments of Truth
When customer feedback is viewed from the inside-out, the brand can learn
from agent-side analytics to automatically train, tune, and optimize
self-service channels, thereby creating moments of truth that lead to more
conversions and increased customer satisfaction.