Improve Retention with Predictive Support Signals
Are you leaving valuable insights on the table? This session will change your approach to customer feedback, showing how SupportLogic can turn support data into actionable insights that drive retention and protect revenue. You’ll see why ignoring this data is no longer an option.
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Well folks we got good news we are the final session of the day give yourselves
a round of applause you made it to the final session amazing amazing please
stay
for the award session that we have happening at 5 30 in this room it's
gonna be great we're gonna give out these incredible awards to incredible
teams that have been doing amazing things do we have a clicker up here yeah
we do oh yeah I'll dry this middle button yeah there we go okay so I am so
thrilled to be joined by Max Green one of our ultimate customer success
managers
for support logic and we're gonna be talking to you about improving customer
retention with these predictive support signals that we've been kind of talking
about all day so let's start with a look at the market right CX is more
important than ever we all know this and I think these stats really say it you
're
looking at loyalty you're looking at unsatisfactory experiences you're looking
at the likelihood of customers staying with you right and these these stats
really paint a big picture Max wouldn't you agree yeah absolutely and you know
we don't want to beat a dead horse I think you'll have seen this slide a couple
times a couple times today right but customer experience and support is more
important than ever to customer retention because your support teams talk to
your customers more than anyone else that's what it comes down to we know this
absolutely so how do we make sure we're on the right side of those stats this
is
really our hypothesis as a company is that you can only grow if you're acting
and understanding on the unbiased signals from every interaction and this is
what's so exciting about NLP natural language processing for complex support
for the B2B support that we're all talking about today but this has not
been easy right Max right we see stats like this about AI implementation being
hard right CIO magazine is telling us that organizations are having a hard time
building these models getting the adoption they want what are you seeing
yeah it's it's it's definitely it's definitely a struggle right organizations
have been struggling to adopt AI in a scalable way yeah right and so how do
you kind of solve for that right you you do a you know you start with a
measured solution simple use cases right and that's what you can do with NLP
absolutely and looking at a few more stats and I promise I think these are the
only stats left we have to to throw at you today but building this stuff
internally is hard and and this is proving it right this is an IBM research
paper that we that we read that is showing how difficult this is as well
building it in house is taking longer than expected so where do you start and
this is our hypothesis for this presentation is this idea of unified
observability for all of what we're calling post sales customer interactions
right post sales CX and let's get into what that is so got a little bit of an
eye chart on here for you it's something that you saw this morning in Christian
is a keynote this is really showing what we mean by unified observability this
is
showing you that across these channels across these functional groups and
across
these systems of record you're getting a layer taking all of that raw data all
that messy data in reading it extracting it applying AI to it and then really
getting insights from it that's such an exciting thing when you look across
these
systems of record right yeah absolutely and and it's really just about once you
can tap into these signals and you can share them with other teams beyond just
support right that's what I mean we're we're here to talk about how they can
impact retention right how they impact success and sales and that's where the
value of these signals come in and now with AI you can actually categorize and
share very easily absolutely so I look we're gonna throw a couple of analogies
at you because I think they're really great for kind of understanding what we
mean by unified observability and looking at it in a couple different ways the
first way is looking at it as a safety right so often without being able to
look at these pieces of unstructured data by without being able to look at
the sentiment oftentimes your customer interactions are going from red to
green you've got sorry from green to red you've got a good situation and now
you've got a problem situation and wouldn't it be great if you could take a
middle situation and bring it back to green before it gets back and now I will
go to green sorry I had to had to throw the pun out there guys folks are awake
right the whole point of real-time sentiment analysis is that you are able
to get to the customer before they turn red yep right so you get to yellow you
bring it back to green ideally we saw we saw that in the in the earlier video
with regards to you sales force right you can turn that set sentiment from
negative back to positive before the end of the case absolutely and then one
more analogy for you we like to also think of unified observability as a
baseline right think of you're in the market for a house you may walk through
the door you see a bad floor you see a stove that's out of code but you know
that you don't start at those things that you see first right you need the
complete inspection you need to see the whole picture of the house what's the
roof like what's the foundation like that's the smart way of getting into a
house and figuring out what to do and with sentiment analysis on your on your
data you get to see that whole picture you get to establish that baseline for
your customer experience and then with that baseline then you can improve your
outcomes in your efficiency and dedicate your time to deflection or
knowledge base or the things that you want to install a chatbot all the time
we hear of companies installing a chatbot with no sentiment analysis right so
now you're almost flipping a switch on interactions with your customers through
a through an automated channel you got to have that sentiment analysis first
right you don't even have an agent or engineer who can tell you that the
interaction went poorly so the only time you're going to hear about it is if it
comes from a CSAT survey absolutely so what does this do for you this is this
is another slide that we've got here about unified observability being so
important for investment max when you look across these four elements what
jumps out to you right I think what jumps out at me most is you know we've
all been working out of siloed systems forever right and the whole idea behind
unified observability and an analysis of all post-sale interactions analysis of
all your support interactions is that you can use a single platform to
highlight
that information to you whether it be via be alerting or you know using the
support logic UI this all becomes possible this all becomes possible when
you're using a single platform to analyze and capture these these signals
absolutely so and these benefits are company-wide right we talked to a lot of
customers and we talked to a lot of prospects who are seeing these benefits
across the left side of this slide obviously the support folks also customer
success and then down the right side as well because now you're able to share
these insights with product IT now has a system that they don't have to support
as much because of the partnership that we provide and then executives are
getting a full view of customers is that right that that's absolutely right and
in addition to that the value of this of the of sentiment analysis and the
signals out to sales and success teams and then well that is very much what
we're talking about now with regards to using these for retention but for those
of you who weren't in the other session that we did in the other room about
identifying upsell opportunities we are about to launch two new signals one for
renewals and one for expansion that will be detected on your cases so beyond
just positive and negative sentiment we're now specifically going to call out
when customers are talking about renewal they're potentially a risk and
that capacity or or that there's a you know an opportunity to upsell or explore
up other opportunities with them right so these are two new signals that are
coming that are going to round out this experience even more for customer
success teams that's really cool to hear because I give an open demo every
Friday on the product one of my favorite things to show is the product signals
where a product team can come in and they can look across three months of any
part of the product any capability the product and see what the feature
requests
are and the documentation requests so now customer success teams people that
are
in charge of growth in your company can go into your support data and see those
upsell and cross sell opportunities easily because those tags happen across
your cases and they're always there yeah right exactly so we've talked about
unified observability starting with sentiment analysis and I don't think we
need to harp too much on this room about what sentiment analysis means what
these
tags mean yeah we've we've covered this in in detail so we won't belabor the
point absolutely and here's a quick shot of the original 40 signals that we
detect missing those two new ones of course and let's really get into some
of this area so max can you talk us through how this looks within support
logic yeah so customer customer health as we you know as we've spoken about
your support teams to speak to your customers more than any other individual
right and so the wealth of information within support tickets both in the
unstructured text and how you're there communicating with you and you're
communicating back with them but also customer health is kind of best
understood not just in the sentiment itself but also with the metadata
surrounding the cases right so is this customer right it's not necessarily a
good thing if a customer that's opening five to ten cases a month with you is
all of a sudden opening no cases right that's a sign of no engagement which is
you know could mean a lot of things it can mean oh maybe you know maybe the
admin has left of your platform has left the company right that's a disaster
as well right or maybe they've just stopped using your software right so
like being able to look at these things as part of a holistic picture of
customer health in addition to that like customers that are opening have a lot
of cases open with you that are how to cases versus have engineering issues
tagged at them right tag via a jeer or whatever the system of record customer
that has a lot of those tickets open is likely a higher risk than customers
that
most of the tickets they open are how to right so all of these things in
conjunction with also the sentiments that's being detected on the cases
themselves provides a holistic picture of customer health yeah this is
presented
within the support logic platform that's a great point and if you and if you
couldn't tell by now this presentation a lot of this is a real wrap-up and
culmination of a lot of what we do because it all kind of bubbles up to
retaining your customers getting better customer relationships and that goes
beyond the the product and being inside the platform and extends to some of
these great integrations that we have out of the box right yeah yeah absolutely
right your customer success teams they're probably not working working out of
your ticketing system right or not sometimes they might be in it occasionally
but the last thing that's really the last place that they want to be if you
know
to be honest right so with our combination of our alerting capabilities
which allowed you to meet your you know other stakeholders where they are
using using signals right and using our our alerts but also integrations into
other customer success tools and that's what we are we're about to show yeah
absolutely so this is our gain site integration and Max tell me how it works
yeah so our gain site our gain site integration looks for a couple a couple
key signals that are being detected on customer cases right so negative
negative sentiment cases that are likely to escalate churn risk signals soon to
include also the renewal signals and the expansion signals right and it
actually
just it's a very straightforward implementation it just leverages our
alerts API which is the same API that that fires our alerts to inject these
signals directly into gain site right the same the the same integration could
be relatively in a relatively straightforward way actually leveraged
to integrate into other other customer success platforms as well right so it's
just about getting those signals out of support and injecting injecting them
into other systems which is where your customer success teams are actually
spending their time and working because you want to augment their existing
workflows you don't want to add new workflows to those unnecessarily because
then you're not going to get any adoption that's what it comes down to
that's a great point I'm going to tee you up for this slide this is this is one
of my favorite slides that we have and this is such a point that you like to
talk about where we're taking these AI generated signals and these NLP
generated
signals and we're taking the metadata out of your cases and there's such an
opportunity when these come together right right yeah I mean the you know
the sentiment signals and all that that are generated off the unstructured the
unstructured text right and 90% of the conversations that you have with your
customers 90% of it is unstructured data but the structured data is really
important as well because by correlating the the signals detected on the
unstructured data with all of the metadata right with you know this
this amount of frustration being detected on cases associated with this
particular product feature that we have right or these confusion this amount of
confusion being detected on cases that are owned by this region of my support
organization right when you're able to look at these and how they correlate
together it creates opportunity not just you know for the confusion example
maybe
there are enablement opportunities for my team right maybe they are not you
know
they just need some additional training on how they're engaging with customers
on these support cases right or if frustration just happens to be associated
predominantly with a particular product feature right that recently had a
release
or even if it didn't have a release that's an incredible amount of information
that can be shared back with product and engineering teams right you can
actually
go to a product and engineering supported by data and kind of solves for or
answers the age-old question of is it a problem with the support I'm providing
or a problem with the product that I'm supporting right and for us here we
would
love to be able to always say that it's actually a problem with the product
we're supporting so wealth of information available in that data yep
thank you for that so wrapping up a lot of what we've talked about right these
are five quick ways and maybe you're a customer maybe you're interested in
support logic you know about the escalation prediction you know about
the case assignment that we do but when it comes to what customers success can
get out of this when it comes to what you can get from being able to retain
your customers grow your customer relationships these are five quick ways
right yeah that that can happen yeah and a simple example there right confusion
could also be an indicator of an opportunity to provide training to
customers right enablement up enablement opportunities for customers maybe
that's a paid offering that you do right in addition to that like positive
signals for cross-sells and testimonials right we always need more
testimonials from our customers so if we see a customer that is continuously
providing positive we're getting detecting positive signals on cases with
them maybe it's an opportunity to reach out and see if they're willing to do a
case study or a testimonial it particularly important that when you're
offering kind of scaled customer success digital customer success where you're
not meeting with your customers all the time then support is often the only
people talking to them right so finding those leveraging those signals to
create
to find these opportunities can be really valuable absolutely you did a
session about an hour ago all about upsell yep and I don't know if everyone
saw it that's a really interesting one right yeah yeah absolutely right and
that
ties into the you know the new renewal and expansion signals right and for
those of you didn't see it I believe all the sessions were recorded yes right
so
thank you for reminding me it's gonna take you know the the the team of elves
that work at support logic a little bit of time but we're gonna get all the
sessions up on SX live library dot SX live comm so you'll be able to see
everything we've recorded all the sessions today so those will be up and
we'll let you know obviously yeah so getting into one of my favorite subjects
here the hard dollar savings of preventing what we call this a revenue
leakage right you can look at this across a few different ways you're
getting these reactive predictors you're getting these proactive predictors
across these different scores right yeah yeah I mean it just ties back to we
want to move from reactive to proactive right so customers with lots of
escalations higher risk of higher risk a renewal risk and higher risk of
churn consistent for CSAT surveys absolutely higher risk of churn right but
leveraging sentiment account health all of these real-time indicators can
really
allow you to prevent the loss of that revenue or at least mitigate it before
yeah this is a slide that you saw this morning and what we're really showing
here is that this is not the kind of thing that you sign up for and that your
IT team has to deal with setting up themselves right what we're really
providing is that solution for serious enterprise customers right for folks
who want that business partner to make sure that the software they invest in
is a success and this happens across these four different areas here you can
see the flexible infrastructure that enterprises expect you can see the all
in one solution that enterprises expect they don't want to you know buy five
solutions for five different use cases across customer support the expertise
and what is built across these different areas like onboarding and customer
success and then the community and it's funny that we're bringing that up here
because I think it's self-evident of live events and best practices which we've
shown certifications and a library of content and opportunities to connect so
this really kind of runs the gamut right absolutely yeah and then this is kind
of where we close things off just showing a slide that you already saw
this morning if you were here of of what our customers are seeing and I'm sorry
the end of this presentation feels a little bit like a hard sell but you
know we're excited about these these results that our customers are getting
so Max do you have something to end with yeah just this is the thanks for
sticking it out with us throughout throughout the day right we'll give you
a little bit of extra time before before the awards the award session yep and
yeah thank you so much for being here absolutely it was a 20-minute session
that we did in 20 minutes.