What Successful Brands are Doing to Improve Post-Sales CX at Scale
Scaling customer relationships is vital to recurring revenue and the health of the business. This panel will disrupt the conventional wisdom around customer engagement and explore how leading brands are using innovative strategies to build deeper, more meaningful relationships at scale. Expect to walk away with insights that will challenge the way you think about customer loyalty and retention.
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We're going to start our next panel discussion.
I am absolutely again blown away with the quality of my panelist.
I'm looking forward to this one.
And as we...
Hi.
You're all good?
Hi, Shilpa.
I didn't get to see you.
Is there an announcement?
Let me see your badge.
Oh, I need to.
You get hot.
I didn't know the name.
Is that how you want to be interested?
Yeah, I hadn't done.
Put it on LinkedIn yet.
But yeah, Kong.
You got it.
Go to the girl at Latin Kong?
So you're ready for that to be announced?
I mean, that's fine.
It's not too...
Okay.
So, okay.
All right.
All right, everybody.
We're transitioning now to post-sales relationships.
And I am joined by three people who absolutely impress me with all that they
are doing to
improve those post-sales relationships and how can successful brands scale
those
relationships?
Right?
We've heard a lot this morning around the fact that support and customer
success are
being impacted.
You know, when there's cost cutting, it's generally happening in those two
groups.
But we know the only way we are going to continue to renew and expand these
relationships
with our customers is to do it at scale, do it in meaningful ways, and be smart
about
it.
Right?
It costs a lot to land an initial customer.
And it's hard and painful to keep them very happy.
So with me today, some of these individuals need absolutely no introduction.
A read, you are the founder, CEO, and CCO.
Right?
Do I have that right?
Both titles?
I never say founder, but yeah.
Okay.
The CSM practice.
You have literally helped hundreds, if not thousands, of organizations in seven
years,
eight years?
Ten.
Ten years now.
Oh, you just aged me too.
I was good dropping those extra three years off.
We didn't need to bring that up.
Shilpa Verma is a senior director of CX Strategy at Kong, formerly with
companies like Salesforce,
Palo Alto, LinkedIn, Zscaler.
Absolutely one of the most impressive support operations.
Sure.
Sorry.
That hair is not easy to control.
Thank you.
Um, support operations executives that you'll ever meet.
And Brian, thank you for joining us.
Brian is vice president of customer support at SAP Data Cloud.
So thank you so much.
Did you guys get a chance to eat some lunch?
Not a little bit.
Lunch was great.
Okay.
Good.
All right.
So we're going to start with customer expectations.
We always have known.
Customers have high expectations.
But I'd say that we would all agree that they've changed, especially in the
last, let's say,
two, three, four years, right?
We heard this morning, you know, people don't want to call support.
They'll put it off for six and a half months, right?
Even though it's a simple call, but the expectations are there.
Tell me, what do you think how have customer expectations changed?
Well, first of all, I think that a lot more companies realize that if they don
't become
way more proactive and control the journey of their customers, their
competitors will.
And so the number one thing is that I see a lot of companies and it's nothing
new, but
I think what's different is when we design a customer journey, we really
identify instead
of, you know, when you go through the sales process, it's really very clear.
When you start with a discovery, then there's a, you know, like there's a bunch
of steps
and it's really very clear.
And then comes post sales and it looks like a complete spaghetti.
And I think that companies are realizing now, A, we need to control the
customer journey
and defining for our customers so that they can go through steps that makes
them more
successful a lot faster.
They feel taken care of.
They need to become more proactive than reactive and since this is a support
conference at
large, I would say that what I'm seeing most companies do is invest, not in
bots, but so
much so is AI chats.
And those who don't, you know, guilty as charge, I'm a user of some of those
companies like
Canva, for example.
You know, if I want to know how to do something in Canva, I just type it in the
AI chat and
I expect it to give me exact instructions that by someone how to do it and then
I go
to LinkedIn or some other solution that I'm using and they don't have that
solution and
I'm like, where's the chat?
And I get angry and I think this is my, I was like, where is it?
Why doesn't, why doesn't everybody have that?
And I think that's what our customers expecting us.
They're expecting us to tell us what steps they need to take in order to be
successful
with us from the start, from first value delivered.
And by the way, first value delivered is not when you deliver your systems.
It's when the customer gets a wow moment and they expect us to give us an A
plus support
experience, which means they just hop on a chat and the chat gives them the
exact steps
to complete what they need to do.
Absolutely.
Thank you so much.
I don't want to see you angry.
I don't, I just don't.
I think we want to just keep you in your happy place.
Thank you.
So everybody get it together because if she's using your software, you need to
have it together
for her.
Shilpa, tell me, what is the biggest change you've seen recently in customer
experience?
That's a great question.
I think that it's been touched upon all day today.
We've talked about sort of more proactive.
We just talked about, you know, customers want to help themselves, ideally not
pick up
the phone and call you.
The biggest change, I'll say 2022, we thought generative AI was going to be
like snapping
our fingers together and it was going to cure everything.
I think we're now backing up and realizing that just like anything we need to
invest,
we need to invest in the data foundations, we need to invest in the process in
the fail
safe, which is, you know, human.
It has been talked about earlier today.
So I'll tell you that the biggest change in customer experience is that they
will see
automation upfront, but then the companies who are smart about it will have the
human
failovers.
They will give you the support that you need to build something else.
And I think that user experience will take over the world.
This is all user experience, right?
It's not just UI or buttons or screens anymore.
It's the human fail-safes.
It's the, you know, educating them about the AI, like letting them know that
you're interacting
with AI and teaching them how to interact with AI.
So I think that will be the change that's soon to come.
Some companies are doing it and more of them will.
Yeah.
Okay.
I think we have the same question to you.
Yeah.
I think what we're seeing is companies are definitely expecting that proactive
support,
you know, versus our traditional reactive models.
Companies want us to identify their issues before they happen and take steps to
mitigate
those and to proactively reach out to them.
It's a much better customer experience if we can contact them and say, "Hey,
customer,
by the way, we've identified this potential problem and here's the steps we've
taken to
mitigate it."
And, "Oh, by the way, here's some additional advice and optimizations you can
take to
prevent further issues in the future."
That's a much better experience than having to pick up the phone when they're
calling,
you know, and, you know, the situation has devolved, right?
Right.
So definitely proactive support.
The second thing is customers really expect us to know them and have context
about their
business and their implementation of our solutions, how they're using them, and
the
issues that they've encountered in the past.
They want us to have that context when we're talking to them, whether it's our
support
managers that are having conversations and a business health review or our
support engineers
that are taking cases.
Having that context is really important and customers expect that.
Yeah.
I can remember in 2014 I was with TSAA.
And at that time we gave a very specific example about you would call in and
you were either
putting in your account number or your phone number, and then the very thing
that happened
as soon as you had a person on the phone was, "Can I have your account number?"
Right?
And you're like, "Well, wait a minute.
Was I just doing that for fun?"
And you know what?
Ten years later?
That is still a problem.
It's still something that happens.
But as soon as you enter it, you're still asked for it later, right?
And some of these simple things that you can handle, it will make the biggest
impression
on a customer.
Start removing some of the small stuff and you won't know how big of an impact
that
could be on just something that simple.
Right?
You're question for you.
Scaling, we talk about it a lot.
And we talk about the fact that teams are adjusting.
They're moving to, you know, maybe, I'll say reducing or right sizing headcount
, putting
a technology solution in place.
But it still has to be personal.
You still need that personalization to be there.
Krishna talked about it during his keynote, right?
It's more human than ever.
What, with all the organizations you work with today, what are one or two good
examples
of what you're seeing where personalization is helping and not being impacted
by the scaling?
Does that make sense?
Let's talk about short-term impact.
Two terms that some of you may or may not have heard of in the past and what I
think
is going to happen in the next two, three years from now.
So how many of you heard of dynamic segmentation?
Heard of it?
Yeah.
Not enough of you.
If you still have a high-touch model, and that's all you know, and then you're
thinking, oh,
pooled model, it's another cool engagement model that it's not as effective as
portfolio
customer success management.
And if you've never heard of it before, you should go check that out because it
's the
juxtaposition between high-touch and pooled model, high-touch and digital
engagement.
In order to do portfolio success management, well, you have to have dynamic
segmentation.
So what is dynamic segmentation?
Dynamic segment, as everybody knows here, customer success is customer outcomes
and an
appropriate customer experience.
Some of your customers might fall into a specific ARR, annual recurring revenue
, so you are
going to be bound to think that they need a higher-touch model.
Maybe they don't need it or they don't want it.
Dynamic segmentation calls out, what is the appropriate engagement model for
right now,
given how many support tickets they have, given where they are in their
customer journey,
given what is the upsell or expansion opportunity without account.
So if you're still segmenting by annual revenues, you're still stuck in 1984.
Okay, that's one.
Look into dynamic segmentation and portfolio success management.
What I think is going to happen, Judy, in three, five years from now, more
predominantly,
is that folks are going to start leveraging AI solutions.
And I think those are coming up and ready to just say, okay, let me feed off
what I know
about the customer from the different applications and our tech stack, meaning
our support tickets,
the way they use the system, et cetera, and then curate a sequence email that's
tailored
to their experience, tailored to what I know about them personally, maybe even
from LinkedIn,
so that it feels personalized.
I think that's what's going to come up for the lower customer segment.
I think the customer success management areas are going to leverage that type
of information,
even to curate emails and specific invitations.
And I'll give you an example.
How many of you do health checks?
Offer technical health checks to customers?
And yeah, some of you, right?
It's a great opportunity to offer quick value to a customer.
But there's different flavors of health checks.
There's one where you can look into the architecture.
There's one that can look into the way that they interact, the system with
existing processes.
There's one that, how do they leverage people?
Do they have the right admin and the right people and resources?
So you can actually tailor a specific health check to the customer's needs.
But it's really hard to do without AI.
With Gen AI, we have opportunities to actually curate different quick value
engagements with
customers that is tailored to their needs.
And it no longer requires a heavy lift off.
So those are a couple of things that I think we're going to start seeing in the
market in
terms of curating the right experience for our customers.
>> Right.
Thank you.
I almost feel like you just took us to school there.
You did a very good job of being very prescriptive with us about what we need
to be doing.
And I appreciate that.
>> Hello.
>> Shilpa, you've been with some amazing companies.
Can you give one example for us from any one of those organizations,
whether it was Salesforce or Palo Alto, LinkedIn, etc.
How did you scale customer relationships without compromising the customer
experience?
So we just heard examples, right?
What's an example of something that you've done that worked well for you?
>> Yeah.
I'm going to draw on everything that people have said, but
I'll kind of tie it together with this example, right?
So I think in LinkedIn for their sales navigator project, we did the product.
We did this one year journey of customer journey mapping, but
I'll be really precisely nailed on what made it a success.
I think there's really three things.
Number one was we took the time to interview everybody,
just the CSMs, the pre sales, the post sales, even the support people and
customers.
And we came up with a by persona journey with specific moments that mattered.
I think to its point sales does that, post sales does not do that so frequently
So we came up with things like, when to fix a bug,
we tell them to restart their sales navigator.
That's actually really bad because it takes down their Salesforce instance.
The vendors, their Salesforce instance, unusable.
And support just never knew that and support just kept saying reboot the plugin
And so we got down to these levels of examples.
So that was the one big thing,
it was really getting precise about the moments that either make an experience
or
really break an experience.
The second big thing was we had a sponsor.
And it doesn't matter what the title of that sponsor is in the company.
We knew that there's one executive leader that is invested in making the LSS
journey a success.
And she really demonstrated that.
She put the team together, she showed up for every check-in.
So we knew kind of what our beacon there was.
And the third thing I think is everybody knew what part they're playing.
So support knew that they're there for a successful implementation.
And they knew that they're there for issue resolution.
But they also knew when to tug on a CSM for support.
Support leaning on somebody else for support.
And they also knew the sensitivity behind some of these support issues and
how to deal with it.
So this is better or worse than the other issue.
There's surprising findings like we discovered that if you're going to reboot
overnight, even though all of our customers were in North America,
we needed support in non-America hours because that's where they were doing a
lot
of their setup and rebooting.
So I think that those three things are key to me really getting very
precise about the moments that matter, the journeys that matter,
the personas you're interacting with.
And then everybody knowing what their parts are and
doing good handshakes to really make it a success.
>> Thank you.
Very good advice there.
Brian at SAP, you're overseeing customer support at a massive scale.
Just last year, right about this time,
your executive was winning transformational executive of the year,
Muhammad Ajup.
And I remember reading that submission and there was so much going on.
There were so many moving parts at SAP to transform the experience.
What are you doing now in such a large organization?
Because sometimes that is the proverbial snowball up the hill, right?
To make change and make customers feel heard and seen.
What are you doing to make your customers feel heard and seen?
>> Yeah, so when it comes to support feedback,
this is part of that transformational change is we do case closed surveys,
right, customer satisfaction surveys.
And for a long time at SAP, our core metric,
the thing we really focused on is CSAT, asking customers, okay,
how do you rate your overall support interaction, right?
And it's a very important question and obviously we care about that very deeply
But there's been a shift recently for us on rating customer effort and
really focusing on that as a key metric in these case closed surveys.
So now the primary question that we are asking our customers is to rate the
level
of effort that it took them to solve their issue.
Because what we found is that level of effort,
if we can decrease the level of effort for customers to solve their problems,
it's going to lead to happier customers and customers that are more likely to
renew.
And so that's something that we're really focused on in our reporting and
our metrics and it really drives what we do from a support optimization
perspective.
Because we want to reduce that effort and going back to being proactive, right?
The best support case is the case that doesn't exist, right?
That's the prime example of the lowest level of effort.
But if a customer does have to reach out to us and they do interact with our
teams,
how do we make that as seamless as possible?
How do we equip our support engineers with the most knowledge about the issues,
about the information that's available to solve that customer's problem in the
least
amount of effort required?
>> Great, by the way, I love that you said that.
Because sometimes what I find is that companies are very focused on
reducing level of effort to solve a technical issue.
But they put a lot of almost barriers to make it super easy for
me to upsell, to get to another module, to get to more seats.
I literally have to talk to someone.
And so I think the age of AI, do I really need to talk to someone if I just
need to
do a quick upsell?
Do I really need to engage with my CSM to have a quick upsell?
I think the gen AI is now opening up a lot of opportunities for us to just
smooth a lot of processes.
>> Absolutely, without a doubt is.
Which takes me to my next question.
I'm going to start with you on this, because it all aligns with Brian's answer
and what you just added to it.
We are sitting on tons and tons and tons of data, right?
And we always have been.
And so what are you seeing effective organizations do now with this data?
You love this question, I can tell already.
So tell me about using that data to focus, to create offers, to remove barriers
Give us some examples of what you're seeing.
>> Well, first of all, I want to say that we are seeing greater number of
companies leveraging unstructured data like never before.
So I think they kind of cracked the code on structured data.
But unstructured data before you would have to have CS ops, support ops.
You'd have to have a list of predictive analysis done and
some geniuses to do a predictive model.
That's not no longer the case.
You could literally do a verbatim model or a verbatim analysis.
And then you could actually do a verbatim model on support tickets on the
weekend or
on every Friday if you wanted to just dump the data and you see a lot of things
So it makes it more incumbent on our executives to actually analyze faster and
change faster.
So I think that's the most exciting at a high level,
most exciting stuff that I'm seeing right now.
That being said, look, I worked a lot with executives to kind of figure out how
can you leverage an AI to increase strategies for
customer success in general.
And what I find is that I'll buy our ability to do verbatim analysis and
chat GBT.
Still, if we really wanted to do a mathematical analysis with chat GBT and
the likes, you still need to have some considerations on cleaner data and
structure the data.
So if you don't ask your customers, was it easy or not, your Gen AI would not
know how to analyze that.
So you still as an executive have to think about what data do I need to collect
in order to feed it to my AI model and get those amazing results.
So examples of what I'm seeing, I think more and more executives are now
getting way more excited that they don't need to have a large team to analyze
the data.
So analysis, creating quick pilots is much easier.
Defining processes for the team.
I mean, in today's world chat GBT can actually create a full form for you in
Google or Google Doc or Microsoft document to just give your team really
quickly.
So this lineage that you have to have a good ops team is not necessary anymore.
Not to say that they won't be needed, but I think those are the kind of
exciting
stuff that we can see in generating a better journey we can actually launch one
a lot faster.
I think that's a great point.
Data is king.
We need to have data for all kinds of AI.
I'll kind of introduce another aspect of it, which is that how can you leapfrog
if
you hadn't created that data years ago and you're not sitting on that data
already.
How do you do that?
I think that you can actually now use gen AI to create that data.
An example is you may have recordings of Zoom summaries and calls from CSMs.
They may be recording it, right?
But here you're sitting on a pile of gold and you don't know how to shift it.
There's software now that'll go through and you can say, tell me what
competitive products
that I lose this customer to.
And they will literally fill in your fields in CRM to generate that data.
So I would urge everybody to think outside the box.
The game is not lost if you haven't already.
Had your CSMs painfully notate this data, same for support, right?
Explore where AI can help you actually generate good, clean data and make some
structure out
of your unstructured data.
Yeah.
Absolutely.
Great point.
Right?
How about you?
Yeah.
I mean, data is absolutely king and at SAP we've invested in a support data
lake.
And one of the ways that we're using AI is as it relates to case categorization
So running an analysis, using AI to determine, you know, is this specific
support case a
how-to question?
Is it a product defect?
Is it a customer implementation issue?
Is it a problem with our documentation?
And so we're able to do that at scale, something that previously required a lot
of effort from
our support engineers, right?
A lot of involvement.
And those are the steps that we can help automate through the use of AI.
And we take that data to then feedback it into our product development teams,
right?
To show them, hey, you're the trends that we're seeing from a support
perspective and,
you know, patterns we can see across our different product lines and where we
have hot
spots that we need to address.
And so that's really been valuable for us.
I think to that point, your product team, your education team, your sales team,
your
services teams, right?
Everyone can benefit from what you're sitting on there.
You can create new offers based upon what you're finding.
You can create educational offers based upon seeing the number of how-to
questions.
Absolutely.
So that's super, super important.
Personal story here, when I was a customer of support logic at Salesforce, we
used our
closure codes and we generated these amazing reports for our product team
quarterly because
that's all anyone had the mental capability to want.
And Shilpa, you remember these times?
It was heavy and it was hard.
Well, when we brought support logic in, we actually found that the information
we were
giving to the product team was inaccurate for many, many, many, many quarters
because
our engineers were choosing in alphabetical order the first closure code.
Oh, gosh.
So no wonder product really didn't like us or trust us because we were just
picking that
first thing there because that helped us get through the other 20 fields that
we had to
complete to close the case, right?
And so support logic allowed us to look at that data very differently and then
product
became our friend, right?
Because now we really gave them information.
That was meaningful.
And we didn't have to--actually what we did is ended up changing processes,
getting rid
of a lot of the fields that our support engineers were completing that we weren
't doing anything
with anyway or not doing the right thing with, certainly.
So Shilpa, I'm going to come to you, customer facing teams.
We just talked about the operations team and maybe that operations can be
scaled differently,
different resources that are needed.
For instance, I'd see in operations today, ideally, I probably have more AI-
focused individuals.
I have maybe business analysts who can look at my data and work with it and
such.
So tell me about some of the resources in an operations team that will help you
build
loyalty.
What are some of those key that you're going to be looking at now in your new
role, right?
What do you want to see in a good operations team?
Great question.
I'll generally say all of support because I think everybody's job is going to
change.
Support's job is also not going to be the same, right?
So I think there's more and more vendor software that allows you to interact
better with AI,
tune it, help do better with the prompts.
And so when you remove the whole heavy development and data science skills out
of it, then really
what remains is somebody who's an SME in their field.
That's an SME/C SM or that's an SME support person that understands the product
, right?
And now they will be interacting with some of these very easy to customize AI
vendors
and having worked with a handful of the AI vendors last year.
What I realized was that you really just need people that understand the value
of reusable
work.
Like the mind shift needs to be away from transactional work.
It's not that you're just resolving the case.
You want to train your support folks as well as your operations folks into how
are you
going to create lasting knowledge?
That knowledge can either be changed or that knowledge can be, I wrote an
article or, you
know, so I think it's a mind shift.
Everybody needs to start thinking, how am I going to create lasting value?
I think this phrase has been used a lot in the CSM world but not so much in
support,
right?
I think it's time to start thinking about it that way.
So I really look for people that understand the value of doing this type of
work and I
think the rest of it can really just be taught, right?
I think everybody that's here, I would highly encourage you guys to train your
folks, operations
and support in the basics of AI.
What is generative AI?
AI has existed before generative AI, right?
How do you need to interact with it?
And so I'm looking for people with the basic understanding of that and then you
basically
any software can be taught.
It's all pointed click now and it's really easy.
It's English now.
You don't have to know code.
Yeah.
What about CSM?
She's fine with me.
I'm going to ask her to please wait in.
I'm just going to say as somebody that really dove into AI quite deeply and not
in
a sense of AI chatbots for support but just in general, how do you leverage Changibiti
to create strategies?
There is some method to the madness if you were to create top notch content
from Changibiti.
You have to know prompt engineering.
There's a method to the madness and there's a way to structure it.
So it's not just, that's why I was like giving that reaction when he said it's
just English.
But just like anything else.
Pointing and pointing.
Okay.
All right.
What pitfalls have you seen in CS Ops teams?
If people today are looking at, let's say, purchasing an AI solution, I know
you've seen
it.
You can probably write books on top of books on top of books about what you've
seen go
wrong or go right.
Tell me about some pitfalls that you've seen in success ops.
Well, one is doubling down on digital CS or digital experiences way too fast,
way too
hard or overly automate in general.
Who was it?
I think Sanjit said, you know, you have to keep the personal engagement, the
human touch
in mind.
And I think most CEOs are going to put a lot of pressure on you to do a pure
digital CS
engagement for your lower customer cohort.
And that's why I said at the beginning of the conversation, look up digital
segmentation,
sorry, dynamic segmentation, look up portfolio CSM.
Zen desk just doubled down on that.
They have over 70,000 customers if I'm not mistaken.
And it works out tremendously well for them actually.
And there's a reason why they do that for multiple years now.
Actually SAP started the portfolio CSM movement back way back when.
And they learned that the hard way.
Actually the first go around, I think it was 2016, so really early to market
with that.
And they said, well, we have so much digital assets.
We can actually take a bigger cohort from our longer tail customer base and
give them just
digital experience.
And what they noted, that was in a presentation I did at the SIA back then, and
they presented
their numbers.
So I just wanted to clarify before I get sued.
Is that in that year when they offered pure digital CS, the churn went up and
the add-ons
from their marketplace store, right?
Was lower as well.
So unless you want to increase churn and decrease upsell, I would say think
carefully
about digital CS.
That being said, I think with the right leverage of Gen AI, when you can
personalize the experience
to some extent where it actually feels genuine and exciting for the customer, I
think nowadays
there is a reopening of that window to re-explore that.
But are we there yet?
2024?
I don't know.
I think still a lot of people need to be educated on how to leverage AI will be
on
a support chat and how do we create that customer experience in a more
personalized humanized
way, even though it's generated based on a chat or an AI model.
Okay, thank you.
Brian, tell me SAP, we touched a little bit on predictive analytics.
You're probably similar to other support organizations dealing with escalations
, the dreaded thing,
right?
And for a while, I would say that a lot of leadership, we created escalation
teams,
red account teams, you name whatever that team name was, and escalations just
became
part of our life.
They were just a cost of doing business, right?
Tell me what SAP is doing about predictive escalations and your focus there.
Yeah, so when it comes to predictive and proactive support, one thing that we
look
at is from our applications trying to identify those issues before they happen.
And it really starts with the design of our products itself, right?
Do we have the data?
And so thankfully, in Customer Data Cloud, we have a good partnership with our
development
teams who have built great logging metrics and reporting metrics for us.
We're processing over a billion requests per month.
And it's something where we have built predictive analytics on top of that
application data
to be able to identify customer by customer when things are trending negative
from a
health score perspective so that we can step in and we can work with that
customer proactively.
So we use things like anomaly detection.
So it's not just looking at spikes and errors, but also unusual traffic.
That can lead us to have very helpful conversations whether a customer had a
new deployment that
might have caused a problem, or if there's a drop in utilization and we need to
have a
conversation with a customer about their changes to their roadmap.
So those are the things we're doing from a proactive perspective that help us
maintain
that healthy relationship with the customer and can reduce those reactive
interactions
which oftentimes are the ones that lead to those escalations.
I love the trending of the health score.
I also love the anomaly detection, right?
Those outliers, when they come out of left field and you're like, where did
that come
from?
But if you can identify those and get in front of those, that is fantastic.
That's good stuff.
Thank you.
All right.
We're close to running out of time and then I want to see if there's any
questions from
the audience to give the audience a little bit of input if they need, if they
want.
Irrita, I'm going to start with you.
You get one thing, just one thing.
That's it.
Just one.
No pressure.
Well, it's only pressure for you because you have a thousand things that you
would offer
to companies.
You do.
One thing that you would say, if you could leave here today and you are going
to improve
your customer relationships if you do this one thing, what is it?
I know this is hard.
No, I actually have an answer.
It's just going to sound maybe too trivial, but implement a relationship score.
And here's why.
If you do this right, you have a right formula for the relationship score and
you actually
score each account, what is the relationship score for that account?
Gives you a sense of your CX efforts and it gives your CSMs support, even
account managers,
if you have those two, sort of like a gold standard of what an A+ looks like.
You can hold them accountable if it's not there.
It's just a great way to provide a standard for what great looks like.
And I think that one of the reasons we don't have great relationships with our
large accounts,
meaning executive relationships, relationships that are the right depth and the
right breadth,
is because we don't as executives do a good job in specifying and holding
accountable to
what great looks like.
So just it's more of a cheat or a tip than a high level strategy, but it's so
easy to
implement, that would be my one thing that I would share here.
Okay, awesome.
She'll have the same question.
What would be the one thing that anybody could leave this room today and create
better relationships?
What would it be?
I'm going to pick something very unconventional outside of the support board.
Love it.
She's a freelance shame, guilt your product teams and engineering teams.
She doesn't mean you, Karen.
I think she's a Polish Jewish mom and she just doesn't know it.
A Polish Jewish mom and she doesn't know it.
Karen, I'm not listening to what she's saying.
I just want you to know that.
You are my chief product officer.
I would never shame you.
What is?
What is?
Shame.
What it takes to really help your product and engineering teams understand that
they
cannot leave support with less information than the customer has.
Like golden rule, right?
In this age of cloud computing, the customer can never know more about their
problem than
you do.
So product engineering teams, please build the telemetry, please digest your
own data
and make it readable for us.
That's the longest poll item because I think for all the leaders in here, other
stuff is
doable.
We all have the guidebook on that.
But this one, we often just kind of sweep under the rug and move on.
That's awesome.
Very, very good answer.
I mean, I feel indirectly like I'm going to leave this stage and I'm going to
pay for
that answer from Karen.
But that's okay.
I'm going to take that one for the team here.
But you are right, right?
You are absolutely exactly right.
You often say that's not, you know, I don't have enough influence here.
That's really not part of my job.
But at the end of the day, if they should doesn't happen or the incident gets
resolved
before it began, then things never even get to support.
Right.
For sure.
Brian, you're on the seat.
You get to say one thing.
What would it be?
Know your customer.
And so, you know, first off, obviously you have to have the data.
The data about your interactions, your touch points, how your customers are
using your
product, what are their challenges and what's the feedback they've been
providing to you,
whether it's through support interaction surveys, NPS or, you know, customer
events,
right?
And getting that holistic picture of the customer, right?
Whether it's health scoring or doing trend analysis with AI, right?
But getting that holistic picture is how you know, okay, what are my customers
that really
need my attention?
What are the ones that are in a good state?
And how do I leverage my resources, right?
Because, you know, resources are finite and we can't give everyone, you know,
all the
attention that we would like, right?
And so knowing your customer and knowing, you know, the challenges they face
can help
you be smart about how you dedicate those resources.
Very good.
Okay.
I want to make sure that the audience has some time.
Is there any questions in the audience?
We have three captive.
I think that I'm standing between you and the steps, right?
Or are there steps over there, too?
We've got steps.
Ignore those steps.
They don't work.
You have to pass me to get off the stage.
Anybody have a question since we have them here and they have been so beautiful
in sharing
their thoughts and views today?
Anyone with a hand up?
Karen, do you have any questions, maybe for Shilpa?
No.
I got a sound.
Super-offstage.
Offstage?
I am in danger.
Super-repressed that when we started, everybody were talking and now there's
complete silence.
So thank you for listening.
Well, we know the conversation.
Thank you.
Thank you so much.
Thank you.
That's the best compliment when everybody's just listening.
Yeah, I agree with you.
Thank you.
Thank you all so much for being so present with us today and continuing to give
your
time to this conference.
We are absolutely thrilled to be able to see all of you.
And for our first live conference, it really has been a pleasure hosting you.
And having the likes of you be willing to come to our first conference and
present with
us is very meaningful and we don't take it for granted.
Thank you.
Thank you for creating that opportunity.
Thank you.
Thank you.
[Applause] Thank you.