Transcript
WEBVTT
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A relationship with the right referral partner
could be a game changer for any BEDB
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company. So what if you could
reverse engineer these relationships at a moment's notice,
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start a podcast, invite potential referral
partners to be guests on your show
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and grow your referral network faster than
ever. Learn more. At sweetfish Mediacom
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you're listening to BB growth, a
daily podcast for B TOB leaders. We've
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interviewed names you've probably heard before,
like Gary Vannerd truck and Simon Senek,
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but you've probably never heard from the
majority of our guests. That's because the
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bulk of our interviews aren't with professional
speakers and authors. Most of our guests
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are in the trenches leading sales and
marketing teams. They're implementing strategy, they're
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experimenting with tactics, they're building the
fastest growing BB companies in the world.
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My name is James Carberry. I'm
the founder of sweet fish media, a
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podcast agency for BB brands, and
I'm also one of the CO hosts of
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this show. When we're not interviewing
sales and marketing leaders, you'll hear stories
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from behind the scenes of our own
business. Will share the ups and downs
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of our journey as we attempt to
take over the world. Just kidding.
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Well, maybe let's get into the
show. Welcome back to be tob growth.
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I'm Logan lyles with a sweet fish
media. I'm joined today by Robert
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Johnson. He is the cofounder and
CEO over at team support. Robert,
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how's it going today, Sir Logan? It is going gl gay. Today's
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so much fun of a chance to
talk to you today and talk about team
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support. Absolutely, sirs. So
we're going to be talking about how to
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take a data driven approach to customers
support. You know, as you and
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I were chatting offline, on this
show, we've taken a lot of time
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to speak about a data driven approach
to marketing, data driven approach to sales,
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but customer support, customer service and
success, I think, you know,
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maybe get the short end of the
stick when it comes to taking this
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data driven approach. So I'm really
excited for you to share some some tactical
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advice for folks and how they can
leverage a lot of the data. The
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good news is a lot of it
is is there for the taking in the
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in the platform that they may be
using. So we'll get into that in
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a second, but for some context, for a little bit of lead up,
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Robert, give us a little bit
on your background and what you and
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the team at team support are up
to these days. For some context.
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Sure. Well, we've founded team
support just about eleven years ago with the
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mission of being a BB focus customer
support platform and the primarily for technology companies.
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My background is running other software companies
and one of the things that I
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realized is that there really wasn't the
tool out there design for that type of
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company. I do think that the
customer support for the BB world is vastly
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different for the than for the BTC
world, and we created the industries leading
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be tob platform for customer support.
So it's going a great ride. We've
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got a lot of fun doing it
and we're growing like a weed. So
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life is good awesome. Well,
what you mentioned there actually, you know,
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you team me up for my opening
question for you is, you know,
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you mentioned that customer support in a
BDC environment is different from a b
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Tob Environment and you know we talk
a lot in the marketing world about how
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we can learn lessons from BBC and
approach it more like be Toc in a
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B tob environment, but when it
comes to customer support there are some very
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distinct differences that you like to call
out from B Toc to be tob.
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Can you speak to those a little
bit? Sure, I love to.
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As I said, it really is
there's some several fundamental difference, BUT DIFFERENCES
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BETWEEN BE TOB support and B Toc
Support, and my backgrounds always been be
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to be. Really never been to
B Toc Guys. So I really understand
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the B to be marketed very well
and I think it's absolutely important that we
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treated differently. So several things that
are different in the market places. Number
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one is that we are looking at
and this is going to sound obvious,
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but when we talk to a customer, we're not talking to an individual,
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we're talking to a corporation and a
customer really is that corporation. So we
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need to understand the relationship at the
corporate level, which is going to include
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a lot of different individuals across potentially
multiple divisions in a company. So understanding
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that relationship at a company level is
absolutely critically important. One of the things
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that really makes team support different goes
back to the very first architectural decision made
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in the product going back to two
thousand and eight. In most customer support
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systems the core construct is the ticket. In team support the core construct is
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the customer, because that's the single
more most important thing. Sold tickets is
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great, but understanding the relationship,
in improving the relationship with that customer really
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is the most important thing. A
couple of things that are important on the
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B Toc side seeing the Betb side
is that the volume of tickets generally in
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the BTB side is lower than the
BBC side, but the complexity is much
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higher. If you think about a
normal transaction in the BTC world, it's
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going to be high volume simple questions, repetitive questions that get get asked over
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and over again. Generally speaking.
In the BTB world it's not that way.
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It's going to be more complex questions
but a lower long of those quest
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questions. Finally, in a B
Tob side, each potential interaction has potentially
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a lot more value associated with it. Again, if you think about a
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BEDC transaction, one individual consumer for
most brands is not a material conversation.
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If the consumer walks from the brand
is says I'm never knew business with that
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company again. Most companies are going
to care too much however, in the
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BB environment, if a million dollar
recurrent run your client walks, that's a
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major and material event. So the
level of materiality on each interaction is potentially
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much, much higher on the BB
world. So again we shad on in
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two thousand eights and dollars for the
preminute be to be customer support tool and
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it had a great success doing that. Of the last love plusumers. Yeah,
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I love those three specific components that
you talk about there and the complexity
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and, you know, the stakes
being higher are two that really stand out
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to me because if you are going
to look at customer support being different in
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B tob you need to understand a
number of the dynamics affecting the relationship that
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can be there can be more dynamics
at play and, as you pointed out,
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more complexity. So what is some
of your advice, Robert, for
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customer service and customer support leaders when
it comes to managing all those different dynamics
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of the relationship and applying data to
it so that they can manage them effectively,
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because it is, you know,
so complex. At the same time,
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as I said, the in the
bdb world is much more about understanding
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the relationship with that customer as opposed
to the B Toc World, worth probably
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a more about personall resolution ticket times
and managing it very, very efficiently.
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Of course efficiency is important in the
be tob world from a support standpoint,
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but again it's go back to that
relationship. So as far as managing the
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relationship with data, understanding the potential
distress of that customer is key. So
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in team support we have a cool
tool, a well it's cool tool call
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the customer distress index, or CDI, and it actually measures the level of
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potential distress with a company. We
do that through a really cool algorithm that
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actually measures the average of all the
customers and looks of the standard deviation of
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one customer compared to the rest of
customer base on a whole bunch of different
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factors. In so from running that
algorithm we can rise up to the top
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the customers that we perceived to have
the most distress. And we call it
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the customer distress index because in the
customer support side we really never get a
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chance to look at customer happiness.
Nobody ever calls to the customer support department
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that says Hey, we let you
guys, things are going awesome. Just
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want to let you know that.
Thanks. Good by click. That phone
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calls never happened the history of customer
support. We always get the complaints,
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the issues, the questions. So
we always get the distress and our tools,
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CDI, allows us to measure that
and report on that, and then
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what most of our client companies do
is use that as a way to understand
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where to deploy resources, how to
best treat that client and potentially change that
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interaction with that client. So that's
one of many tools we use in team
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support to allow our customers to use
data to better understand, manage and improve
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the relationships with their customers. Today's
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know well, air BNB. When
they were trying to maximize growth among work
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travelers, are BNB new they needed
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reach multiple personas at different stages of
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marketing hub and spoke managed creative content
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that allowed airbnb to develop more content
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lot of content across multiple channels,
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Within the first six months, are
BNB nearly tripled the number of companies
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enrolled in their AIRBNB for work program
they also saw huge increases in user adoption,
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with work travelers booking longer stays and
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a content specialist today. That's hub
spoke dot marketing growth. All right,
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let's get back to the show and
I think the methodology there is worth pointing
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out because when you, you know, mention your index that you mentioned the
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the CDI customer and distress indexes,
you guys call it, you know,
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I think of other tools, other
reporting methods to gage customer satisfaction, like
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a net promoter score in ps,
those sorts of things, and you know,
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as you and I were talking offline, you know you mentioned that.
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Yeah, those, those things are
important. You want to measure those.
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Those have, you know, great
implications, but specifically in customer success,
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customer service and customer support, you
you're dealing with customers when they are at
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that distress point, and so you
want to manage the the ones that are
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in the greatest distress. So I
love the way that you guys are tackling
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that and I think that that mindset
shift of thinking about overall customer happiness but
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then looking at the other end of
the spectrum and and how can you,
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you know, improve both to move
the pendulum, you know, on both
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sides, I think makes a lot
of sense. You know, you mentioned
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a little bit there, Robert,
on reporting. I imagine that there's some
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regular advice that you guys are giving
to customer support leaders where they may have
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some lowhanging fruit of data that they
could just be looking at a different way
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or changing the way that they collect
it. That could give them some insights
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that might yield some specific changes that
could be big levers for either customer happiness
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or reducing that distress. Right.
What are some of those areas where you
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see folks can change the way that
they look at data or the way that
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they capture data and then leverage that
for a vast improvement in customer support?
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Sure, let me go back to
the last point is for one second,
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though. It's we talked about in
the CDI and we brought up the MPs
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and some other survey data as well, and that's all absolutely critical. It
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is, as I said, the
CD I really looks at this one section
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of that customer relationship, in we're
big believers, and also looking at things
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like MPs, things like transactional surveys
and getting that whole list of view of
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that customer. So it's the CDI
is really one data point there which we
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incorporate with a lot of other data
points to try to understand that overall relationship
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and it's there's no one tool that
gives you all the inside the customer.
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Were working on it. We love
that idea. Yeah, Robert, I
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mean it goes back to what you
said earlier is that, you know,
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the relationship in the BB environment is
more complex, and so what you're saying
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here about having multiple tools to be
able to capture data about different aspects of
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the customer relationship, you know,
just reinforces that point you made earlier.
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I'll let you speak to kind of
the the data question and some of the
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reporting things that customer support leaders might
want to be thinking about. then.
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Yeah, the data. Obviously,
having a lot of any customer support system
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you've got a lot of data locked
up in the system and hundreds of thousands,
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if not millions of interactions with customers
is a treasure trove of potential data
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right in the ability to look at
that and really mind that for intelligence becomes
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a very, very valuable tool.
So just a couple kind of basic examples.
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One thing that's fairly easy to do
certain INTA in support is to look
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at a histogram of the days of
week, in times of day when your
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customers are contacting you. So from
that it's becomes literally about three clicks to
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understand what time of day is is
very busy. So you can't, from
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a staffing perspectives, start understanding,
okay, we need to start the day
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earlier, start the day later,
or stagger lunches, for example. Let's
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say we have to spike at twelve
to one when we might want to move
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the lunches around so we have your
lunches earlier or later, as we don't
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have the whole staff gone when we're
seeing a big influxive tickets. Certainly,
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one of the things we've done is
we actually have a customer support operation in
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Tape Count South Africa, and we
use our own data to understand that.
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We had a lot of issues and
customer questions coming in from both in North
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America, in overnight, but also
in all our customers in Europe and Asia
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as well. So we are opened
up a will open up a customers port
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operation and take time to be able
to address those again based on the data
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that we have within team support.
Yeah, no, things we can do.
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Kind of going back to the survey
stuff, is we have the ability
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of doing a essentially a ticket closed
survey. So we can understand. There's
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lots of different ways to surveys.
Can Do MPs, we sort have the
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CBI, but this is a very
transactional survey. Every time a ticket closes
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we sent a very basic surveyor that
says essentially we said three faces, happy
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faced, neutral face and Friday face, and it's a snap shot gage of
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how that particular interaction went. But
we can do it. We can measure
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two things. Everyone that helps is
measuring the relationship with the client and actually
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that's a feedback into the CDI,
but also helps us to understand the agents
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as well. If we have agents
that have continually very very high percentage satisfaction
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from customers and Asians they have very, very low satisfaction of customers, that's
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obviously a point for management to go
on there and say hey, let's figure
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out what's going on here. Yeah, absolutely. I mean I love that
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example there of very tactically just looking
at a simple data point right of when
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our tickets coming in and then how
can we staff around those? Or,
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you know, in your case,
a little bit more extreme than moving lunches
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around, opening up a new office, but that can affect some large company
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decisions. If you look at the
data, and I love the way that
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you pointed it out that the data
that you have in your customer support platform
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is a treasure trove of intelligence and
if you're looking at it the right way,
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you can use it very powerfully.
Speak a little bit more to Robert.
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For Customer Support Leaders Listening to this
in looking at, you know,
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how they manage csms. Again,
it might be a little bit different if
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you know, maybe they come from
a B Toc background and now they're managing
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their agents in a Bob Environment.
Are there's some dynamics there that you think
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folks need to call out and be
thinking about when it comes to managing their
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customer Support Team in a beb environment? Very much so. So on the
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BBC, as we talked about,
as much more about volume, speed of
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closure, efficiency of agents and things
along those lines. In the Bab world
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it's much more about customer satisfaction the
relationship of those customers in ensuring that you
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are getting that customer to especially in
the subscription world, to stay and potentially
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expand as well. So in many
ways the skill sets from a manager but
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also from an agent themselves are different
between the two. Again, B Toc
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much more vally and much more rapid. Closing be to be much more relationship
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driven. So when you're looking to
hire in manage agents in the BB world,
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one of the things we really focus
on is that ability to drive that
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relationship and I think that's absolutely critical
in the Bab will yeah, anything else
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you want to add rubber in?
You know, some of the the new
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technology that folks are leveraging is,
as you and I were talking offline,
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you mentioned something about sentiment analysis in
a part of your platform that you guys
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are leveraging it. It seems like
you know not only the data but merging
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ai with all of this volume of
customer information, customer input, there are
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some opportunities to add some technology that
folks might not necessarily be thinking about yet
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in how they can improve those relationships. That coming back to the main point
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of managing relationships in customer support in
Feb that's been, you know, a
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common thread throughout this conversation. Sure
a hundred percent agree with what the data
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that we have in in a customer
support to long team sport should never be
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locked up. That data is absolutely
invaluable and IT Saddens Ministry we go to
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some potential clads of ours and they
don't have that data expose. I don't
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really understand what information they have.
So our ability to report them that understand
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that really is a key put different
differentiation for our tool. But one of
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the things you referenced was we've got
a great integration with IBM's Watson and what
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that does for us is allows us
to do cinnamon analysis so we can actually
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understand the intent and meaning of a
customers interaction with us. Obviously, as
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a human we going to look at
a email or chat in pretty quickly understand
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okay, they that or not,
and that's easy to do with one ticket
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or two tickets. The problem as
you get hundreds of thousands of tickets coming
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in and a thousand agents looking at
those interactions, the ability to categorize that
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numerically and use essentially turned sentiment data
into numerical old data, is immensely valuable.
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That allows to look at begin the
relationship with that customer. We can
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look at all their interactions across all
the tickets, potentially across all the different
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divisions, when maybe supporting, and
see if there's sentiment is broadly trending better
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or worse? Are they happy?
Are they frustrated? What is that look
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like? They can easier to do
for a human looking at one or two
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tickets. Very difficult to do when
you've got again, potentially hundreds or even
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thousands of agents across millions of tickets
to understand that. So again, going
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back to the thing of data,
the ability to use that idea of sindment
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analysis has been a great data tool
for us. Yeah, that's really cool
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that you guys have built that integration, Robbert, and it you know,
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it points to this common trend.
Right of you know we're swimming in data,
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but it's really we need it organized, we need it, we need
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the ability to analyze it and take
action based on the Organization of that data.
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And so, as as you were
talking, I was picturing, you
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know, kind of viewing customer sentiment
trending up or down, and that and
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low and behold. That's exactly where
you went with that. And so I
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think for customers support leaders, you
know, one of the big takeaways is,
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you know, how can how can
you get to that? How can
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you start to organize the data and
apply some analytics to it in some form
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or fashion so that you can look
at the key components and how they're trending?
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And it kind of came back to, you know, as you talked
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about, within customer support, distress
and not only just customer happiness, but
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looking at different key points along the
pendulum of that relationship with the customer become
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very, very important. Robert,
this has been a great conversation. I
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love the experience and the tactical advice
that you brought to customer support leaders listening
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to this today. If anybody listening
to this would like to reach out,
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ask any follow up questions with you
or just stay connected with you and your
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team, what's the best way for
them to go about doing that? All
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00:20:41.289 --> 00:20:45.650
gras a different ways, obvious.
The website team Supportcom you can reach me
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on twitter at team support CEO.
Email our Johnson at team, supportcom and
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linked in as well, so I
am agnostic value contact rd, so I
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appreciate it. Awesome. As you
said, make it easy lots of different
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ways. Robert, this was a
fun conversation. Thank you so much for
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joining us on the show today.
Logan, thank you so much. We've
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got a lot of fun and Gret
what has been twenty minutes or so.
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Thank you so much. We totally
get it. We publish a ton of
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content on this podcast and it can
be a lot to keep up with.
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00:21:15.269 --> 00:21:19.660
That's why we've started the BOB growth
big three, a no fluff email that
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00:21:19.779 --> 00:21:25.700
boils down our three biggest takeaways from
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today at Sweet Phish Mediacom Big Three. That sweet PHISH MEDIACOM Big Three