Understand Why Customers Are Calling
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The Times College, Lahore *
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101
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Information Systems
Date
Nov 24, 2024
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docx
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Uploaded by BaronMoon15417
Understand Why Customers Are Calling
Once data categories and goals are identified, the team needs to
consider what kinds of queries into the bank’s data will help it assess the
nature and circumstances of the customer support requests. At the
banks where I consulted, we focused on the contact centers, specifically
information from customers’ interactions with phone agents within a
given time period, and came up with the following questions:
How many customers spoke with a live agent?
Who were these callers, i.e., what were their profiles in
terms of service interactions across channels, transactional
activities across products, and customer value at the
enterprise level?
What percentage of those callers were digitally active?
What, if any, banking activities had occurred before the call?
If there had been a banking activity prior to the call, in which
channel did it take place?
What did the customers call about?
Did any of them call more than once? If so, how many
times?
How long did the calls last?
For customers who made multiple calls, how much time
elapsed between them?
While banks typically do track the number of calls fielded by contact
centers, they usually don’t delve into many of these ancillary statistics.
This is consistent with what I’ve seen more broadly in
financial services
:
Firms track events but do a poor job of measuring activities around
events that can explain behavior and help them make improvements.
Knowing that a customer spent 20 minutes attempting to resolve a
dispute or activate cash-back rewards before they called would give call
center employees helpful context and inform their interactions.
At the banks where I consulted, I worked with the strategy teams I built
to help the institutions document each call’s purpose through a system
of record. For example, we could see that one customer, whose identity
was anonymized, had gone online minutes before calling and tried
unsuccessfully to close their account—the experience that had prompted
the call. Then we assigned each call a label denoting its purpose and a
time stamp. We were also able to determine secondary and tertiary
reasons for the calls by identifying events that had occurred around the
primary catalyst, allowing us to map out a full picture.
We subsequently calculated a key metric known as call-to-contact
spread, which we used to assess the experience of the overall population
of callers. It also served as a benchmark for improving efficiency.
Call rate:
the total number of calls made, expressed as a
percentage of the entire customer base
Contact rate:
the number of customers who made calls,
also expressed as a percentage of all customers
Call-to-contact spread:
the call rate minus the contact
rate
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