February 27, 2024 • 55 mins
Lane Hart of Contentsquare brings to CS a no nonesense approach to ensuring the renewal via strong data analysis combined with a very human approach of customer engagement. He has taken lessons learned from his years in management consulting at IBM forward into a rocketship trajectory in CS at Heap - now Contentsquare.
Be sure to grab a pen and paper for this one as we talk about:
- Scaling the Heap CS team and starting a CS Ops function
- The importance of knowing what Data is available and how it all correlates to drive customer outcomes
- Advice: Don’t get stuck because the data is not perfect
- Use data in change management by ‘showing your work’ and telling a story of how you got there.
- Service recovery philosophy: So much of CS is gracefully falling on our sword - and owning up to that can lead to some incredibly real and human moments.
- Effective interventions on negative sentiment customers can turn these situations into extremely healthy relationships
- Contact-level data is so often in very poor shape, not just in formatting but also in whether that contact is still at the company or what role they have
- Implementing in-app prompts for new users for them to self-identify what role they play
- Using bounced emails to adjust customer contact data - flagging contacts that have left - then reaching out to company to get updated contacts via active users
- Surveys are annoying and you have to be very careful not to bombard people
- Standardizing metrics, both product and commercial, across departments and then putting them front and center in front of the whole company to drive alignment
- Tracking champions after they leave a company - they can be incredibly valuable CSQLs to land new accounts with minimal effort
Lane's LinkedIn: https://www.linkedin.com/in/lanehart/
Resources:
- Lenny's Podcast: https://www.lennyspodcast.com/
- Scaling People: https://amzn.to/3wDVfVH
- Nudge: https://amzn.to/3wDVfVH
- App: OmniFocus: https://www.omnigroup.com/omnifocus/
Shoutouts:
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The Digital Customer Success Podcast is hosted by Alex Turkovic
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:03):
I mean, I will often submit people submit NPS on
products that I use, just to seewhat happens afterward, and me
too, like majority of them,there's no follow up, there's no
closed loop.
They're just collecting thedata for data's sake, and I
think that a huge missedopportunity for a digital CS or
a scaled CS motion.
That's what I think I mean.
(00:24):
In order to be successful indigital CS, you have to have
people who are just innatelysuper curious and willing to try
and fail a lot.
You'll find those breakthroughs, but you know they're always
diamonds in the rock.
Speaker 2 (00:38):
And, once again, welcome to the digital customer
success podcast with me, alexTrokovich.
So glad you could join us heretoday and every week as I seek
out and interview leaders andpractitioners who are innovating
and building great scaled CSprograms.
My goal is to share what I'velearned and to bring you along
with me for the ride so that youget the insights that you need
to build and evolve your owndigital CS program.
(01:01):
If you'd like more info, wantto get in touch or sign up for
the latest updates, go todigitalcustomersuccesscom.
For now, let's get started.
Hello, it's the digitalcustomer success podcast.
You've reached episode 41.
That sounded like an answeringmachine message.
For those of you who know whatanswering machines are, I'm
(01:22):
dating myself.
Anyway, welcome to episode 41.
Great to have you back.
As always, today we have afantastic conversation with Lane
Hart.
If you don't know who that is,he serves as VP of customer
success at content square,formerly heap, and has just an
insane amount of really goodinsight into building and
(01:47):
scaling digital programs or CSprograms in general.
He has a background in datadata science and, as he made
that transition into customersuccess a few years back, he
brings a lot of that philosophyinto what he does on a
day-to-day basis but brings alot of just common sense smarts
(02:08):
into his programs and shares alot of that advice.
On this episode, where we dotalk about data, we also talk
about service recoveryphilosophy, where you turn a
negative experience into anoverly positive one.
We talk about metrics.
We talk about the annoyance ofsurveys, in-app prompts, contact
(02:30):
level data.
We go all over the place, butget your note pad out, because
there's a lot of really greatinsight in this conversation
with Lane Hart.
Mr Lane Hart, I'm so happy tohave you on the podcast.
Welcome, welcome, welcome.
Thanks for having me.
Alex Been, looking forward tothis for a few weeks.
Yeah, it's good to have you.
(02:51):
I typically like to start offwith kind of an origin story
type question, but we'll be kindof pointed with this one,
because I do a little bit ofLinkedIn stalking for all of my
guests, as you should if you runa podcast.
One of the things thatintrigued me about your past is
(03:15):
your time as Speaker of theStudent Senate at University of
Cincinnati.
I want to know more about that.
What was that all about and howdid you get into that?
Speaker 1 (03:25):
You really went below the fold on the scroll there.
Yeah For sure we were chattingabout Cincinnati.
That was definitely a reallygood time.
It was our student governmentat the University of Cincinnati
and the role was basically justorganizing like 30 or 40
(03:46):
senators from all of thecolleges.
Each college would send twosenators and it was intended to
be a quote-unquote legislativebody.
As much as any legislation thatyou could pass in a university
would matter, but a couple ofthings that we did were
basically pass fundinglegislation to give funding to
student organizations and justhelp out with visibility.
(04:09):
It was definitely one of thosethings.
I feel like it set me up wellto wrangle a lot of people,
because you literally need tokeep order in a meeting with 40
people who all have their ownagenda or sometimes after three
hours of meeting are justtotally checked out.
It was a lot of fun.
You get to kind of banter backand forth and people get to test
(04:30):
their arguments and reasoningskills.
It was fun.
Then I moved on from that to dosome other student leadership
stuff at the university, whichalso was a lot of fun.
Made a lot of lifelong friends.
Speaker 2 (04:44):
That's cool.
Did you have a gavel?
Speaker 1 (04:47):
I did.
I actually have a ceremonialgavel that's sitting at my
parents' house in Ohio that ithas my name engraved on it.
Surprise possession.
Speaker 2 (04:58):
That's awesome.
The gap between your time asSpeaker of the Senate is that
correct?
Yeah, speaker of the StudentSenate to now you're in San
Diego.
You've been at Heap for fouryears, I think, recently into a
VP of CS role there.
Fill in the gap a little bit.
(05:19):
What's the story of you gettinginto CS and that role
specifically?
Speaker 1 (05:27):
Wow, yeah, it hasn't been that long, but it seems
like it's been a super long time.
I've been around 10 or 12 years.
After I graduated from theUniversity of Cincinnati, I went
into management consulting atIBM.
In that role, I was doing abunch of really interesting work
(05:48):
all over the world.
My focus was in data and datascience.
All of the problems I wasworking on solving were somehow
related to how can we use datato make better decisions.
Through that, I get to work onreally interesting stuff,
ranging from how do you useTwitter data to predict what
people are going to buy, or uselocation data to understand how
(06:12):
much revenue a store is going todo, or how to advertise the
right things at the right time.
We built a whole bunch ofmobile apps that were the Uber
for concrete and cement deliveryfor a really large cement and
concrete company Wow.
You have to do reallyinteresting things all over the
(06:32):
place Again made lifelongfriends.
I did that for around eight orso years.
That led me to wonder what elseis out there.
I was working with a lot ofconsumer-focused companies,
people that were either workingdirect to consumer or B2B2C-type
business models.
(06:53):
I always was intrigued bysoftware.
Of course IBM also madesoftware.
It was mostly B2B software.
I started looking around at thiscustomer success role.
I didn't really know what itwas at the time but I reached
out to a friend of mine,michelle, who's actually still
at Heap.
She and I had worked together.
I just thought, hey, I'mlooking to potentially leave.
(07:14):
Tell me more about customersuccess.
She said, hey, we're actuallylooking for somebody to scale up
the team in New York.
Why don't you consider this?
I'm like, well, I don't evenknow anything about this company
.
It was like a 100% company atthe time.
She and Veronica, who isrunning customer success at Heap
at the time, sold me on theidea of building the team from a
(07:36):
team of just a couple of peopleto a pretty large team over the
last few years.
It turned out to be honestly acareer-defining experience Met
so many interesting people,worked on a lot of interesting
problems.
Our software Heap is customeranalytics, product analytics.
What we're doing is trying tohelp digital builders understand
(07:59):
how users are traversingthrough their flows.
It could be to buy somethingonline.
It could be to do a transactioninside of B2B software.
It could be to do a financialtransaction Then understand
where the friction is so thatthose digital builders can go in
and fix and remove the frictionso their users have an easier
(08:19):
time doing what they're tryingto do.
It actually brings together theaspects of consulting that I
loved, which are around thechange management, as well as
the people side of things likehow do you actually compel
people to make decisions usingdata instead of just using their
gut, which turns out to be thehardest problem that we're
always faced with.
(08:42):
I've been doing a couple ofdifferent things at Heap over
the years Scaled up the customersuccess team in New York, built
a team in Europe.
Then I moved actually into arole that I was doing on the
side.
You end up with these roleswhere it's a passion project and
then it turns into an actualjob.
I created our customer successops team, which is just a huge
(09:06):
passion of mine because I lovegetting hands on with data and
then hire somebody else to runthat team and then came back to
run the customer success teamthat I'm running now.
That has been a lot of fun.
We've announced a definitiveagreement to be acquired by
another company called ContentSquare in the near future.
(09:29):
Really excited to join ContentSquare because there's a lot of
complementarity between ourproducts.
We're doing a lot of thequantitative side of analytics
and getting the structured dataand the funnels.
They're doing a lot on thequalitative side of analytics.
I'm really excited to blend thequant and call together as we
(09:50):
join forces.
Speaker 2 (09:52):
That brings me to today.
Speaker 1 (09:54):
If that was an elevator, we would have gone up
and down the World Trade Centerlike four times maybe more.
Speaker 2 (10:01):
Yeah, no, it's all good.
It's a cool story.
It's fun to hear how folks endup in these roles, because
everybody's path is so different.
It's not as cut and dry as asales leadership role or
something like that.
It's always circuitous, whichis a word I'm still working on.
Speaker 1 (10:22):
Yeah, I'm always trying to hire people too.
I'm always trying to findpeople that are the interesting
unicorns who have done enough tounderstand what we do and be
curious about it, but they don'thave to come from a traditional
CSM background or a traditionalmanagement background.
It just needs to be somebodywho's curious about data and
(10:45):
human behavior and how tofrankly, just how to make things
happen, because a lot of CS isjust getting things done and
building a coalition of peopleto care about your customer and
help them out.
Speaker 2 (10:58):
Yeah, and I would imagine you building that ops
function.
You probably saw a lot of that.
Obviously, we're talking aboutdigital CS on this podcast, but
I kind of view the ops functionand digital CS can be
interchangeable, can be separate, can be one, you know, because
there's a lot of kind of overlapin terms of, like, wrangling
(11:21):
data, wrangling systems to, youknow, accomplish kind of a task.
So so I guess in that, in thatvein, you know, one of the
questions that I do like to askall of my guests is essentially,
you know what, what theirdefinition of digital CS is,
because it does vary, right.
So I'd be curious to get your,your take on it, especially
(11:43):
given your background and youknow data and all that kind of
fun stuff.
Speaker 1 (11:47):
Yeah, I mean it's definitely a blurred line and
that is how I got into.
Like you know, at the time weweren't even calling it digital
CS, but it's how I got into whatwe would now call digital CS
and we've gone, as probablyeverybody has gone, through
several different you know sortof like revamps of it over the
past couple years.
Even it's still always changingevery quarter.
But I guess I mean one.
(12:09):
It's to drive more impact withour human resources which,
incidentally, in a softwarecompany are pretty much always
our largest cost.
So it's not to replace humans,really to assist them.
It's not exactly ops, becauseops is more for internal
purposes.
As I see it, of course, thereare a lot of things that we do
in ops that our customer facing.
(12:30):
If it's done right, it improvescustomer satisfaction because
you're giving them the resourcesthey want and need at the
moment when they need them, evenif they didn't know exactly
what they needed at the time.
So just having that, that'swhere you really marry the ops
and data with the execution sideof things.
So if I had to think about,like, digital CS is the
(12:52):
execution, the ops and analyticsside is understanding what we
should try to execute to improvecustomers lives and I think the
biggest thing is just like alot of testing and learning.
So in the in that one, ourproduct is always changing to
our customers.
Needs are always changing, thecompetitive landscape is
changing.
We have to be really flexibleto use the data that we have
(13:16):
like that I call it the digitalexhaust that's coming off of our
platform to understand likewhat are some unmet needs that
we might be able to help with todelight our users.
Speaker 2 (13:28):
I love that and I love that you blended kind of
the that enablement factor ofyou know enabling the team and
making sure the team is runningefficiently with, obviously, you
know why CS is here is to drivecustomer outcomes and make
customers successful and youknow, I think that my my hunch
(13:52):
anyway, after speaking with youand, and you know, chatting with
you a little bit, but alsolooking into your background a
little bit is that your historyand passion around data and data
science has, has, has probablybenefited you throughout kind of
the roles that you've had, butthen specifically in CS, because
(14:14):
I mean, if you ask me, one ofone of the most valuable and
probably looked over products ofa healthy CS organization is
like the data, into the datainsights that we can glean from
various data sources and thingslike that.
So my hunch is and I'm puttingwords in your mouth that that
(14:36):
you probably had a kind of akind of advantage going into
setting up a CS org, coming atit from that angle.
Speaker 1 (14:44):
Yeah, I mean it's definitely it has helped a lot.
I think it's you don't have tohave a background in data or
data science, but definitely acuriosity to know what's
possible.
I think one of your guests,whose name was also Lane, which
I was really fascinated by, fromGainsight she was she kind of
talked about how data relates todata and I loved that term
(15:06):
because it really is justknowing, like, what data is out
there, how might you tie ittogether to tell you to one to
come with a story of what it,what can you, what are the 20%
of things that you can do todrive the 80% impact Right, and
a lot of that like just comfortin working with data and working
with messy data definitely camefrom my time.
(15:28):
Like dealing with you knowtweets and social media data, or
dealing with you know trying tojoin together data sets from
different back end systems andthat kind of stuff.
In a growing company like oursor, like you know, probably most
of the people listening to thispodcast large companies or
growing companies Most of thedata is messy.
You have to get supercomfortable with it being mostly
(15:51):
accurate or directionallyaccurate and then having some
backup plans in place.
So I think that comfort withthings not being perfect
probably went a long way.
I see a lot of people or talk toa lot of people are trying to
start a digital CS program andthey're you know, they basically
get stuck because they the datais not perfect and they're
(16:13):
stressed out that they're goingto mess something up.
Or, you know, like the everdreaded thing where you know you
send the wrong email to thewrong person, or for a long time
we were worried about our youknow, entitlements database
being like slightly inaccurate,and then we would send messages
to people saying, hey, you'renot using this thing or you're
not entitled to this thing, whydon't you go check it out?
(16:33):
And then they respond back andthey're like wait a second, we
already have this.
But I mean, ultimately you aregoing to make some mistakes like
that, and when that happens, Iusually just reach out to the
customers and just say, hey,like you know, we're trying to
improve right now, we're tryingto do things at scale, and
everyone I've never had someonewho is not understanding about
it creates a nice human moment.
(16:54):
So yeah, I think that that pieceof it probably helped in terms
of starting out in CS andstarting out in digital CS.
I would say the other piecethat really helped is most
people and I mean I work likerun a customer success
organization for a company thatis all about data Most of the
people that we work with are notcomfortable working with data,
(17:18):
it's their first time doing itor they're making really
consequential decisions, and soa lot of the job is how do you
compel people to care aboutusing data?
And that's really like a changemanagement exercise.
So what I found in my careerworking in data science is that
you really need to explain howyou got to the answer like that.
(17:39):
You know that when you're yourmath test gets graded and you
get like bad marks for not notshowing how you showing your
work on how you got there.
If you can show your work andyou bring everybody along, it
goes a really long way to thechange management and getting
people to use data and, morethan just using it, get curious
about what more could we do,because everybody has some great
(18:02):
idea.
They just may not know exactlyhow to execute on it.
So if they see what's possible,they see the work that you did
to get there, then you know, allthe time I have people come to
ask you some ideas.
Like somebody said hey, can wepull in our community data and
then use that to ping peoplewhen questions don't get
answered by one of their peers,and then how can we build that
(18:24):
into our health score?
So it's, you know, different.
Three different people camewith three different ideas, all
relating to the same data, thatall make our customers lives
better.
Speaker 2 (18:34):
Yeah, and that kind of stuff is lurking everywhere.
You just got to kind of go lookfor it and think about it
creatively.
And I really like what you saidyou know about just not being
able, not being afraid to jumpin, because so much of kind of
what we do in CS is gracefullyfalling on our heart a little
bit not being afraid to do so,because like.
(18:55):
Honestly, it is those humanmoments that actually make a
huge difference versus you know,if everything's kind of hunky
dory and by the book and by therecipe or whatever, you're
probably missing some greatopportunities to connect, you
know, with your customersorganically and and it also
shows that you know you'reyou're, you're trying to do
(19:17):
things and and you know toimprove, improve upon the
experiences.
It's not like we're purposelygoing out of our way to like
send extra emails, but yeah, Imean I think there's like the.
Speaker 1 (19:31):
I'm sure a lot of people have heard of the service
recovery philosophy.
It's basically like you know,you have, you have enough.
If something is broken, youactually have an opportunity to
not only fix it and do the rightthing but dramatically improve
the relationship.
And this is like one of myfavorite things.
With digital CS.
This is actually one of thefirst now that I think about it
(19:51):
like one of the first things.
Before even add digital CS as afunction, one of the first
things that I did at he wasreally use our NPS program as a
way of driving those servicerecovery moments.
So I mean, yes, we definitelycare about having a high NPS
score, but what I care a lotmore about is finding the
(20:12):
specific people who arestruggling and then turning
their moment of frustrationbecause usually they most people
as an in product survey they'll, like rage, submit a negative.
So you see the ones that are,like you know, under, like their
two or three or four.
Those are people who are reallystruggling right now and if we
can figure out exactly whatthey're struggling with and
(20:33):
reach out with some help andthen just offer, you know, an
olive branch, say, okay, cometalk to us, we truly want to
help you, that often turnsthings around and I, and then we
measure how did they respond tothe next time they responded,
and if we're able to close thoseloops live, our response rate
goes, you know, more than likeor sorry, our.
(20:54):
Our NPS for those people whoresponded negatively goes up,
like typically people willbecome, you know, go from being
a detractor to being a passiveor promoter over time if we've
done effective interventions andthat's kind of like really.
I mean, that's been done for along time since NPS has been a
thing.
But I mean I will often submitpeople submit NPS on products
(21:18):
that I use, just to see whathappens afterward, and me too,
majority of them.
There's no follow up, there'sno close to what.
They're just collecting thedata for data's sake, and I
think that a huge missedopportunity for a digital CS or
a scaled CS motion.
Speaker 2 (21:34):
I was going to say exactly the same thing massive
missed opportunity and NPS comesup quite a bit on the show.
Speaker 1 (21:41):
I mean because most of the people love to hate NPS.
Speaker 2 (21:47):
And exactly, I think for me, the two most valuable
bits of NPS are what we weretalking about the score, okay,
fine, but the goal is in thecomments.
The goal is in the commentsthat you can then distribute
internally and try to make someimprovements.
The real goal is when youactually respond and actually
engage on the back of thoseresponses, because, a it shows
(22:13):
that you're listening, but, b itdrives engagement down the road
.
It's one of those touch pointsthat can really help secure a
renewal, quite frankly, or makea customer, even if things
aren't hunky-dory, they knowyou're listening, they know
(22:35):
they've got a window into theorganization and so, even though
they may be evaluating someother solutions or whatnot, at
the end that could be one of thethings that makes them stick
around, because, oh yeah, I meanjust knowing ahead of time and
just getting a lay, especiallyin our primary.
Speaker 1 (22:57):
We have a traditional CS motion which is pretty
high-touch to very high-touch,and then we have a pooled motion
.
That digital is an overlayacross all of these, but within
the pooled accounts we're oftenpushing out content as you would
from a digital standpoint,trying to get users to come in
(23:19):
and say, hey, this is the thingthat I care about.
Or, based on our signals,here's something that we see it
looks like you're strugglingwith or you haven't done yet
that you should have done by now.
And within that base, theseinterventions are super
important because it givespeople a chance to just raise
their hand and say, hey,something is not quite right.
It doesn't matter what thething is, but if we can just
(23:39):
talk to them or just evenexchange email messages with
them, it goes a really long wayto understanding more about
their context, diffusing anypotential risk or frustration
for that person and the accountand many times often leads to an
upsell because they'refrustrated that they can't do
something that they could do ifthey had one of our products
(24:01):
that they didn't even know thatwe sold.
Speaker 2 (24:04):
Yeah right, exactly what.
On that topic, what are some ofthe, I guess, your favorite
motions that you have in placethat are either particularly
effective or things that arejust cool, like from a CS nerd
perspective?
Speaker 1 (24:25):
Yeah, one of the challenges I think on your
podcast and on all such podcaststhis is often discussed just
the lack of data, cleanliness oncontact level data.
So you have all the issues thatI'm sure have been talked about
ad nauseam, where people put inthe wrong name.
They combine their namestogether and then all of a
(24:46):
sudden you're saying hi laneheart, instead of just saying hi
lane, or the caps was on, andso it's all.
Speaker 2 (24:52):
Yeah, caps on, or they put it in all lower cases.
Speaker 1 (24:55):
Obviously, everything is messed up in our systems, or
I mean that's like you know.
That's pretty recoverable andwe have algorithms that you know
, scripts that will run to tryto fix that.
But the other thing that ismost difficult actually is see
right there, with that statement, you're already above.
Speaker 2 (25:11):
Above, where a lot of people are like you're fixing
the casing.
Yeah, totally.
Because I think a lot of folksyou know they'll have these,
they'll have user databases orwhatever, and it's just like
whatever it was put in by so andso and that's just what it is.
And then you know it's like amanual or an outsourced type of
(25:36):
situation to go fix it.
So that right there is actuallyquite interesting, because I
think a lot of people strugglewith that exact thing.
Speaker 1 (25:44):
Yeah, I wonder if there's like a Salesforce mini
app idea, or maybe this alreadyexists and somebody should write
it to us and tell us where.
You just plug this thing in andit just fixes the bad contact
data that's coming into your CRM.
Speaker 2 (25:57):
Yeah, if you have, if you out there, if you, the
listener, have something likethat, like an app or something
that automatically goes throughand cleanses your Salesforce
contact data?
Comment down below.
Speaker 1 (26:09):
Yeah, that will be your next guest, and definitely
call me as well, because then wewon't have to do all this stuff
manually.
But so that one of the thingslike that is one of the
challenges that we have.
That and just knowing who'sstill at the company, who's a
decision maker at the company,how are people related to
departments within the company?
Because I could go on a littlebit of a tangent here about the
(26:32):
departments and the breadth ofadoption.
So one of the things that wecare a lot about is that
multiple teams, differentdepartments, are using heap to
make decisions.
Reason why is that it reducesconfusion within their
organization, ultimately reducescost of people using different
data sets to try to makedecisions, and of course it
(26:53):
makes our platform stickier,because now you're making
decisions using the data thatyou collected from heap and
using charts and heap.
So we actually started.
This is kind of like a crawl,walk, run thing.
So I started off with just anapp queue in our product that
would just ask people when theywere signing in for the first
time, which department are you apart of?
Speaker 2 (27:14):
What do you use?
Speaker 1 (27:15):
Yeah, like what do you do and what are your goals
Like?
Why did you come here today andyou had to keep it really short
?
Because we were afraid ofadding undue friction in our
sign up process and in fact thisis actually why we ended up
with kind of shallow data in thefirst place, because we wanted
to make it very frictionless tosign up.
Remember, our company is allabout removing friction and we
(27:37):
looked at OK, if you ask toomany questions, people will drop
off in the beginning of theflow.
There's a really interestingLenny's podcast from a few
months back about someonetalking about PLG and how they
were actually saying it's fineto ask the questions you need to
ask, because if people drop off, they weren't very high intent
anyway and B2B software is theexpectation.
(27:59):
Is you're going to give up thatkind of information?
Anyway back to the thing.
So we collected thatinformation just using an app
queue, fed it into Salesforceusing Zapier and then use that
to basically say, ok, how are wedoing from a breadth standpoint
across accounts?
Do we have people in product,in marketing, in customer
(28:20):
success, in data and engineeringall using Heap?
And if not, how do we get morepeople across those teams using
it?
Or how do we get people toidentify themselves?
So, then what we did is wecreated just basically a
feedback loop where we look atwe use Marketo to send emails,
so we look at when we send outemails, are those emails being
(28:42):
delivered or are they bouncingWith all the turnover that you
have in companies today, peoplestick around, for there's some
different numbers out there, butit's under two years on average
.
So people are leaving and weneed to know are these people
dormant or did they just leavethe company?
Oftentimes their email balanceis, like you know, probably 70%
accurate at saying they left thecompany.
(29:02):
So that was one of the coolthings is just flagging contacts
that had left and then usingthat to flag accounts where we
don't have any relationshipcontacts or we don't have any
contacts in a certain department, and then just team up a
message that goes out to thoseaccounts through Catalyst, which
is our customer successplatform, to say, hey, it looks
(29:24):
like this person left and theywere in such role at your
company.
Did this person actually leave?
If they did, who is the newperson that's taking over?
One of the challenges that wehad was OK, we you know if
you're trying to reach out topeople by email, and they're no
longer there obviously you'renot going to get a response.
So, there's different levels toit.
(29:44):
We just send this message tosome of the top users in the
account, based on who's loggedin most recently, and it
actually is very effective atgetting those people who are top
users care a lot about theplatform continuing to exist at
their company and you know usbeing able to reach out to the
right people there, so usuallythey give us the information
(30:05):
we're able to update things sothat when we send out messages
we're sending them out to theright decision makers in each
department, and that has reallyhelped us with the dormancy
problem where you know, if wedon't have that top level
alignment, the account will overtime just sort of erode because
no one is administering theaccount.
Speaker 2 (30:26):
Yeah, it's so interesting because I feel like
I don't feel like I know that alot of times we're just afraid
to send those kinds of messages,you know, because we're like
hey, we don't know you that well, can you help us out?
But I think that is where,whereas that can be viewed as
(30:49):
something that is negative, Ithink also, on the flip side,
it's a point of engagement andyou're asking your most avid
users to say hey, help us out,keep us up to date so that we
can serve you better.
I think it's all in thesemantics and it's in how you
message that.
Going back to something thatyou said earlier which I thought
(31:11):
was interesting was almost thisnotion of, in PLG, using survey
completion like the amount ofcompletion of a survey as almost
like an engagement metric,which I think is interesting.
If somebody goes through andcompletes five out of the 10
(31:35):
questions in your survey versussomebody who completes the 10
out of the 10 questions, youcould almost say that, hey, this
person is a little bit moreengaged with your company much
less the software, but maybe thecompany and therefore is
somebody that you could use asan advocate or something like
that.
I thought that was veryinteresting and one of the side
(31:56):
benefits of surveying perhaps.
Speaker 1 (31:59):
Yeah, and I think you have to be careful.
The big thing with surveys isthey're so annoying.
You know when it's the end ofthe quarter because people have
some goal in their company goalsto send out a survey or get a
certain response rate or just acertain score.
I will always see it at the endof a month just a bunch of
messages piling up.
You have to be really carefulnot to bombard people.
(32:22):
We have a bunch of prettysophisticated logic that keeps
us from over surveying or askingtoo much of too much feedback
without a direct benefit.
We do a lot of surveying.
Our product team does a lot ofsurveying, especially our long
tail of customers to getcustomer interviews of people
(32:42):
that are doing specific thingsin our product.
Usually people are reallywilling to participate in those.
Sometimes they'll becompensated, Sometimes it's just
product people love talking toother product people and those
are our users or userresearchers, UX people.
Speaker 2 (32:59):
Yeah, interesting.
How do you coordinate that?
Because one of the epicproblems is like, hey, marketing
wants some information andsales wants some information and
CS wants some information, andproduct is like do you write
exactly?
Okay, question answer.
Speaker 1 (33:20):
Yeah, I think the good thing is, if you have a
small enough team or a team thatis cohesive enough, you can
strike that balance betweensomeone is the human router or
traffic cop to make sure thatyou're not inundating a specific
base of people, but you alsowant to just leave it open and
let people tell you if it's toomuch.
(33:42):
So we're more laissez-faireabout it than other places.
I've seen where, if somebodywants to reach out to customers,
we're not going to say, go sendthis to 1,000 users at once,
but if you have a list of 100people you want to reach out to,
maybe five or 10 of them willend up responding.
We've been pretty much willingto do that.
(34:02):
We haven't seen any majorrepercussions.
Where we do have issues is it'snot an issue, it's just a thing
that happens.
We have multiple differentteams that are all.
They all have the same goal,which is to engage our user base
.
That comes from sales, it comesfrom customer success.
It comes from product, it comesfrom product-slash-product
(34:23):
marketing, it comes frommarketing and from our scaled
adoption team.
So we do have a process wherewe just say, hey, these are the
sends that are happening andthis is the relative size of
those sends to make sure that wedon't send two messages per day
about totally different topics.
Then the metrics that we lookat to monitor that are really
(34:46):
the unsubscribe rate, to makesure that we're not overlapping
too many sends and then annoyingpeople because they got three
messages that didn't seemcoordinated at all.
Speaker 2 (34:58):
Totally, yeah, absolutely.
Speaker 1 (35:00):
I had probably-.
I think there should be an appto solve that problem as well,
just like there probably is also, we're just not using it.
Put all of your campaigns andthen prioritize them smartly, so
that the ones that are going todrive the highest impact will
get sent first and the rest justgo into a backlog Exactly like
a Q kind of deal.
(35:20):
Yeah.
Speaker 2 (35:23):
Obviously, there's some folks who use different
systems to send different emailstoo, and that exacerbates the
problem because there's nocommunication between the two.
I had a horrid experience withthis kind of stuff recently.
I won't mention the company,but it was like pre-sale they
(35:44):
were very aggressive in theiremails and calls to drive the
close.
Then post-sale, they wereincredibly aggressive.
I probably heard from six orseven different people like
texting, calling, emailingmultiple times.
Speaker 1 (36:04):
Texting is pretty amazing To drive an upsell
Totally.
Speaker 2 (36:09):
I didn't respond to any of them and then they start
sending me experience surveysand I gave it to them.
I was just like this is notcool, no, Stop, because it was.
Obviously it was very obviousthat it was like an outsource
type situation.
It wasn't a coordinatedoutsource situation, it was like
(36:29):
20 different people got a lead.
For hey, if you can upsellthese people, it's just so
stupid.
Anyway, it was like the epitomeof what not to do.
Speaker 1 (36:42):
Yeah, it's tough because, if I think about our
tech stack, we have a prettyrational tech stack.
We use Marketo for the majorityof our email sends, across
marketing and product marketing.
We use SendGrid to sendtransactional emails from our
product.
We use Catalyst to send O-Salecustomer success emails.
Our sales team uses Outreach tosend prospecting emails and
(37:06):
some sequences for even O-Salecustomers that they're managing.
Then, of course, we have Gmail.
That's going back and forthwith customers.
What I've found is that, eventhough Salesforce is far from
perfect for this, we bring allthe data into the activity feed
in Salesforce and into our ownproduct heap.
We basically have all thesetouchpoints streaming into those
(37:29):
two platforms, and then we canuse those to build suppression
lists.
It's far from perfect, though,because you don't really get the
priority of every message.
You can just look at thesaturation of messages per
recipient or per account, but ifyou look at the source, you can
infer what the message wasabout based on which system it's
being sent from, but there'sdefinitely not a
(37:52):
one-size-fits-all thing, andI've had several different
companies try to sell them, andI just don't believe it, because
some of these systems are soentrenched that we're not going
to get rid of them.
Speaker 2 (38:02):
Yeah, totally Absolutely.
That's cool, though.
I like that notion ofcollecting everything and then
throttling a little bitdepending on the volume.
That's super smart yeah it'sdefinitely not perfect.
Speaker 1 (38:17):
If anybody's listening to this and they're
like that's BS, they'redefinitely not doing that.
I apologize, let me know whatwe did.
Speaker 2 (38:26):
One of the things that we spoke about previously
was this notion of juststandardizing metrics across
departments and really trying toget on the same page,
cross-departmentally, with thegoals and what you're really
trying to drive.
Can you chat a little bit moreabout what that looks like at
(38:47):
Heap and what you're drivingspecifically?
Speaker 1 (38:50):
Yeah, we have a company value called Taste the
Soup, which might be like eatyour own dog food or drink your
own champagne somewhere.
Sure, we really try to livethis every day because, since we
are a product analytics company, we have lots and lots of data.
We are a self-serve platform.
Everybody in our company isusing Heap for various things.
(39:12):
One of the age-old challengesthat we've had is just what is
the definition of active usageThen what's the definition of
value driving usage?
Because you can have activeusage without value driving
usage.
It's easy if you don't know whatvalue looks like for your
(39:34):
customer, but if you don't knowwhat value looks like for your
user, you're going to end upinferring that they're fine when
they're not, and then you'renot driving some of the most
important interventions.
One of the things that we did afew quarters ago is just launch
a cross-functional team whichis spearheaded by Daniel, who
leads our product analytics team.
Who's amazing.
Huge shout out to Daniel to getalignment on these definitions
(39:57):
of basically our version ofMalWow and Dow basically our
users and daily users.
Then we have a few others thatdrive what we infer is value
driving behavior, like repeatingcertain actions within the
platform For the longest time.
For a couple of years, we wereall customer success was using
(40:21):
our own definition, product wasusing a definition, our
analytics team was using adifferent definition.
We just created thiscross-functional team and
basically said we need to figureout what these metrics are, and
then we're just going to blessthese and lock these down and
we're only going to use acertain set of events to
calculate them, so that when youare driving interventions,
(40:42):
we're not driving interventionsto the wrong people.
I guess communication isprobably the number one thing.
We're awash with data, but it'sreally just communicating on
the metrics that matter, or themetrics that we're going to
decide matter together.
Then I think the other bigthing that helped with
sanitization is just puttingthose metrics on display in
(41:03):
front of the entire company.
We have a system where we trackall of our OKRs as a company.
These are always metrics thatare what we call like top-line
metrics, so metrics that we justtrack all the time, even if
they're not at a specific OKRfor that quarter.
That has really helped justwith the visibility, because it
gets everyone thinking about howcan I drive those metrics?
(41:26):
And it also gets peoplethinking okay, I have an idea
how we could sort of rev on thismetric together, bring it to
the right people, or, oh wait, Iwas actually using a different
metric to measure success of myOKR.
I need to make sure it's tiedback to this one.
We don't really have anyonepolicing it, but organically, by
setting the definitions withthe department leads and then
(41:50):
making them widely available inour own platform and in our data
systems, we've pretty muchdriven a way the behavior of
people using different metricsor just random metrics all the
time.
That's from a product usagestandpoint.
I would say that actually, oneof the things that we have more
trouble with now that we'vemoved on from that challenge is
(42:14):
our commercial data andsegmentation.
Everybody wants to know whatsegment is this customer in in
terms of how we cover thataccount and then what motion are
they in in terms of the type ofservicing that they get from us
?
Getting that data accurate,maintaining it based on our
(42:35):
contractual commitments and thenpropagating it out across our
systems is an ever-presentchallenge.
I think, as with any dataquality, it's never really going
to go away, but that is thecurrent challenge that we're
focused on.
If anybody has great ideas onall years, again it goes back to
communication and justcommunicating.
(42:55):
Who owns that piece of data?
We had a whole cross-functionalteam for Salesforce to just say
let's list out all of the topdata elements that we have.
We had this spreadsheet thathad 500 rows.
Does anyone even know what thisone means anymore?
If not.
Speaker 2 (43:12):
Let's get rid of it.
Speaker 1 (43:14):
If people do know what it means, then who owns it?
If somebody owns it and it'ssimilar to another one, let's
call that person or just have abig call where it's a
clearinghouse.
That is the way that we've beensolving it so far and it's
helped us make a dent in thosestandard metrics.
My overall advice is put themetrics in public for everyone
to see, make it easy to know whoto go to when something doesn't
(43:38):
look right or when someone hasquestions, and then patiently
deal with all of thediscrepancies.
To encourage people to come tothe table when they have data
problems instead of reinventingthe wheel on their own and
trying to make their own thing,because it'll save them time for
that one thing they're tryingto do and then it'll create 10
times more problems in a quarterfrom now.
Speaker 2 (44:00):
That's great.
Yeah, I love that advice.
I think data hygiene issomething that everyone
struggles with.
Show me somebody who doesn'tstruggle with data hygiene and
I'll show you a liar yeah, everycompany, from the tiniest
companies to the biggestcompanies.
Speaker 1 (44:15):
Absolutely.
I think the other thing, too, isjust taking a really and this
is something that I do and myteam does with our clients all
the time trying to figure outwhat are those value driving
actions or moments, andsometimes they're a specific
action that you repeat over andover.
Sometimes it's a threshold of acertain number of times that a
(44:36):
user has done a thing, or acertain number of users on an
account that has done that thing.
For us, it's like savingreports and pinning them to
dashboards and then sharingthose dashboards with other
people to drive that virality.
What I find is that most of theteams that we talk to don't
know what those secondarymetrics are that drive the
(44:58):
Mao-Wao Dow type metrics.
And figuring those out is thebiggest unlock for digital
customer success, because itallows you to intervene at those
moments that matter or whenpeople are on one side or the
other of that threshold.
You're not telling themsomething that's really pedantic
that they probably don't careabout or they're already past it
, and so that you're not goingway over their head with the 103
(45:22):
course when they need the 101level.
Speaker 2 (45:25):
Yeah, exactly yeah.
All this stuff is reminding meof a conversation I had several
weeks ago with Dan Ennis, who isfairly well known and CS
circles for being.
Yeah, one of the things that hedoes really well within his
organization is using usage datato figure out what persona
(45:47):
somebody is likely to be withina customer, which I think is
fascinating to do those kinds ofthings as well.
But, yeah, it's really awesometo hear that is next level.
Speaker 1 (45:58):
If someone is doing that, they're probably in the
top 10 or 20 percent ofsophistication, which is amazing
, but this is one of my personalprinciples.
It doesn't have to be perfect.
If you're listening to this andyou're like holy cow, how am I
going to figure out, inferpeople's persona based on their
(46:20):
behavior?
Just start with something.
Just try to find that oneactive usage metric that is not
just like they logged into theplatform and then just run a
test around that and eventuallyyou'll figure it out.
Speaker 2 (46:32):
Totally, absolutely.
Do it, see if it works.
If it doesn't, go back and doit again, figure something else
out.
Speaker 1 (46:42):
Yeah, it's just those learning loops.
That's what I think.
In order to be successful indigital CS, you have to have
people who are just innatelysuper curious and willing to try
and fail a lot.
You'll find those breakthroughs, but they're always diamonds in
the rough.
Speaker 2 (47:01):
I think so too.
Well, cool, as we start toround out our Convo because
we're getting towards the top ofthe hour here and I want to be
respectful of your time I'd lovefor you to give us a quick
download of what's in yourcontent diet.
What do you pay attention to ona regular basis?
Speaker 1 (47:18):
Yeah, I mentioned it earlier.
Of course, I listened to yourpodcast.
There are a bunch of other goodCS podcasts out there, but I
also really like to expandbeyond CS and really think about
what is the persona of peoplethat we are serving, which are
largely product people ordigital builders.
Lenny's podcast is one that Imentioned earlier.
(47:39):
That's amazing for that,because he has a lot of guests
who are just top practitionersin their field and they're often
talking about product-ledgrowth or how do you make the
product just easier to use.
At the end of the day, that'sreally the nexus of digital CS.
It's like how do you make theproduct and the people work
(48:01):
together and get the people todo the things that your product
is intended to do?
There are a bunch of goodepisodes that I could share on
that topic and just also goesinto aligning active usage
metrics and stuff I also tend tolike.
My wife always gives me a hardtime because I'm always reading
what she calls businessself-help books.
(48:21):
There's one that I readrecently which is I have it
sitting here on my desk ofScaling People by Claire Hughes
Johnson.
She was the COO of Stripe.
I'm sure many people have readthat Fantastic book for anybody
who is leading a largeorganization or relatively small
organization, because she givesvery digestible, very specific
(48:43):
tips and frameworks.
There's a great book offrameworks Then, one that I read
recently actually listen to itwhile I was running on the
audiobook.
It's called Nudge.
It's about behavioralpsychology.
That is really interesting justin terms of what motivates
people to take certain actions.
And also when you think aboutdigital CS.
(49:04):
What we're doing all day istrying to motivate people to
care about a thing or to nudgethem into doing something and
connecting with what they see asvaluable and what we offer.
Then the last one, which isdefinitely a personal self-help
book, is Getting Things Done,which is a pretty old book.
Some of the stuff in the bookis outdated now because it's all
(49:26):
paper process, but there's anapp called OmniFocus that is a
task management app For anybodywho has a lot of things going on
.
I would definitely recommendthat one.
Speaker 2 (49:37):
Cool, I love it.
Amazing little tidbits.
Any folks that you would wantto give a shout out to Digital?
Speaker 1 (49:45):
CS related?
Yeah, a couple.
Recently, somebody that I'vebeen working a lot with is a
co-founder of an app calledAthenaai, mike Molina and his
team, jared and Sid and a bunchof other people over there.
What they're doing is basicallyhelping us scale Slack.
We're introducing customerSlack channels to many of our
(50:09):
customers and they help withbridging the.
When people ask questions, howdo we make sure those questions
get answered in a timely waythat doesn't overwhelm people
from being in a bunch of Slackchannels, and then how can we
use that for customer marketingas well?
It's definitely just an amazingteam, but also really useful
(50:29):
app for the next iteration andgetting out of just email as the
only channel that we email orin app that we use to
communicate with people withoutbeing super invasive and trying
to send people text messages,because I think that's one step
too far.
Yeah, the story that you toldis like wow.
Mike is only one great person toreach out to and to follow.
(50:53):
They put out lots of greatcontent.
This in the vein of scaled CSas well.
I don't know if anybody has evermentioned Mark Costaglow, who's
the CRO at Catalyst.
He runs all of theirgo-to-market functions,
including Postsale.
He has a framework that heshared with me a couple of times
recently, actually calledMoments of Impact, and it's
(51:15):
basically how do you get tothese specific moments of impact
that are going to drive, likethe customer say, wow, this is
valuable and I love this product.
The reason why I really lovethat framework is because it
relates really well to justreaching the next stair step
with customers, and it can beapplied digitally or through a
(51:38):
higher touch motion.
Then, actually, wes is theperson who runs Scaled CS at
Catalyst.
Wes has been doing a lot of thatorchestration of where the
rubber hits the road.
How do you help the CSMs aswell as the long tail with
reaching those moments of impactwithout being annoying and just
(52:00):
sending the same webinarcontent over and over.
I think they both work reallywell together in doing a pretty
job of deploying that content.
Of course, one of the things Ilove using their product is that
they're also tasting their ownsoup in making the product
better by using it for digitalCS, that's amazing, awesome show
.
(52:21):
Last shout out is a buddy ofmine, todd Bustler, who he and
Steven Ruff started a companycalled Champify which helps you
keep track of contacts as theymove on.
This has been a huge challengefor us and part of that motion
that I mentioned earlier, whereyou have people who are leaving,
we send alerts to the CSMs andsay, hey, these people are
(52:43):
leaving, let's figure out whothe new economic buyer is on
this account.
We can do that at scale.
We also turn around and usethat for sales as well, because
if somebody was a really happycustomer and they moved to a new
company, we can sell to themthere.
Todd puts out a lot of greatcontent just in terms of little
tidbits on LinkedIn that reallyare catered a lot towards sales,
(53:06):
which is their main audience,but much of it is relevant to CS
as well just how to getpeople's attention.
Speaker 2 (53:13):
Yeah, I had a conversation with someone
recently not on the podcast, butabout this notion of CSQLs and
how a CS qualified lead doesn'tnecessarily need to come from an
account that you have.
It can come from someone whoyou used to work with, at an
(53:33):
account that has moved on orwhatever.
I think there's a lot of valuein tracking those people and
where they go within theecosystem of potential clients.
Speaker 1 (53:48):
Yeah, we typically find the close rate.
On those accounts the time toclose is three or four times
faster than it is, which issomebody who's never talked to
us or used our platform before.
From a customer successstandpoint, they get it.
They struggle with some ofthese challenges before, so
their onboarding is always much,much smoother than somebody who
(54:09):
we haven't worked with.
We're always happy to havethose repeat customers and users
.
Speaker 2 (54:14):
Exactly, yeah, cool.
Well, lane, I've really enjoyedour conversation.
It's been great spending timewith you again.
Good to have you on the show.
Where can people find you,engage with you and reach out to
you?
Speaker 1 (54:28):
Yeah, I'm on LinkedIn .
You can definitely find me onLinkedIn Lane, hart, l-a-n-e,
h-a-r-t, and on the heapcommunity, which is
communityheapio, or you can justreach me by email Lane at
heapio Pretty easy to get intouch with, easy.
I always try to respond tofolks on LinkedIn.
I'm truly curious to connectwith people who are doing things
(54:51):
even that are totally differentor adjacent to the space.
Definitely don't hesitate toreach out.
One of the things I'll often dowith folks who reach out is
talk about health score.
How can you build an actionablehealth score?
You can find some stuff on ourheap community that I published
there about that as well, that'scool.
Speaker 2 (55:11):
Okay, we'll have to hit that the next time you're on
the show.
Speaker 1 (55:14):
All right, we'll love to come back in the new year.
Speaker 2 (55:18):
Sounds good.
Thanks for the time.
Speaker 1 (55:20):
Yeah, thanks so much, Alex.
Have a good one.
Speaker 2 (55:23):
Thank you for joining me for this episode of the
Digital Customer Success Podcast.
If you like what we're doing,consider leaving us a review on
your podcast platform of choice.
It really helps us to grow andto provide value to a broader
audience.
You can view the DigitalCustomer Success Definition Word
Map and get more details aboutthe show at
digitalcustomersuccesscom.
My name is Alex Turgovich.
(55:44):
Thanks again for joining andwe'll see you next time.
I mean, I will often submit people submit NPS on
products that I use, just to seewhat happens afterward, and me
too, like majority of them,there's no follow up, there's no
closed loop.
They're just collecting thedata for data's sake, and I
think that a huge missedopportunity for a digital CS or
a scaled CS motion.
That's what I think I mean.
(00:24):
In order to be successful indigital CS, you have to have
people who are just innatelysuper curious and willing to try
and fail a lot.
You'll find those breakthroughs, but you know they're always
diamonds in the rock.
Speaker 2 (00:38):
And, once again, welcome to the digital customer
success podcast with me, alexTrokovich.
So glad you could join us heretoday and every week as I seek
out and interview leaders andpractitioners who are innovating
and building great scaled CSprograms.
My goal is to share what I'velearned and to bring you along
with me for the ride so that youget the insights that you need
to build and evolve your owndigital CS program.
(01:01):
If you'd like more info, wantto get in touch or sign up for
the latest updates, go todigitalcustomersuccesscom.
For now, let's get started.
Hello, it's the digitalcustomer success podcast.
You've reached episode 41.
That sounded like an answeringmachine message.
For those of you who know whatanswering machines are, I'm
(01:22):
dating myself.
Anyway, welcome to episode 41.
Great to have you back.
As always, today we have afantastic conversation with Lane
Hart.
If you don't know who that is,he serves as VP of customer
success at content square,formerly heap, and has just an
insane amount of really goodinsight into building and
(01:47):
scaling digital programs or CSprograms in general.
He has a background in datadata science and, as he made
that transition into customersuccess a few years back, he
brings a lot of that philosophyinto what he does on a
day-to-day basis but brings alot of just common sense smarts
(02:08):
into his programs and shares alot of that advice.
On this episode, where we dotalk about data, we also talk
about service recoveryphilosophy, where you turn a
negative experience into anoverly positive one.
We talk about metrics.
We talk about the annoyance ofsurveys, in-app prompts, contact
(02:30):
level data.
We go all over the place, butget your note pad out, because
there's a lot of really greatinsight in this conversation
with Lane Hart.
Mr Lane Hart, I'm so happy tohave you on the podcast.
Welcome, welcome, welcome.
Thanks for having me.
Alex Been, looking forward tothis for a few weeks.
Yeah, it's good to have you.
(02:51):
I typically like to start offwith kind of an origin story
type question, but we'll be kindof pointed with this one,
because I do a little bit ofLinkedIn stalking for all of my
guests, as you should if you runa podcast.
One of the things thatintrigued me about your past is
(03:15):
your time as Speaker of theStudent Senate at University of
Cincinnati.
I want to know more about that.
What was that all about and howdid you get into that?
Speaker 1 (03:25):
You really went below the fold on the scroll there.
Yeah For sure we were chattingabout Cincinnati.
That was definitely a reallygood time.
It was our student governmentat the University of Cincinnati
and the role was basically justorganizing like 30 or 40
(03:46):
senators from all of thecolleges.
Each college would send twosenators and it was intended to
be a quote-unquote legislativebody.
As much as any legislation thatyou could pass in a university
would matter, but a couple ofthings that we did were
basically pass fundinglegislation to give funding to
student organizations and justhelp out with visibility.
(04:09):
It was definitely one of thosethings.
I feel like it set me up wellto wrangle a lot of people,
because you literally need tokeep order in a meeting with 40
people who all have their ownagenda or sometimes after three
hours of meeting are justtotally checked out.
It was a lot of fun.
You get to kind of banter backand forth and people get to test
(04:30):
their arguments and reasoningskills.
It was fun.
Then I moved on from that to dosome other student leadership
stuff at the university, whichalso was a lot of fun.
Made a lot of lifelong friends.
Speaker 2 (04:44):
That's cool.
Did you have a gavel?
Speaker 1 (04:47):
I did.
I actually have a ceremonialgavel that's sitting at my
parents' house in Ohio that ithas my name engraved on it.
Surprise possession.
Speaker 2 (04:58):
That's awesome.
The gap between your time asSpeaker of the Senate is that
correct?
Yeah, speaker of the StudentSenate to now you're in San
Diego.
You've been at Heap for fouryears, I think, recently into a
VP of CS role there.
Fill in the gap a little bit.
(05:19):
What's the story of you gettinginto CS and that role
specifically?
Speaker 1 (05:27):
Wow, yeah, it hasn't been that long, but it seems
like it's been a super long time.
I've been around 10 or 12 years.
After I graduated from theUniversity of Cincinnati, I went
into management consulting atIBM.
In that role, I was doing abunch of really interesting work
(05:48):
all over the world.
My focus was in data and datascience.
All of the problems I wasworking on solving were somehow
related to how can we use datato make better decisions.
Through that, I get to work onreally interesting stuff,
ranging from how do you useTwitter data to predict what
people are going to buy, or uselocation data to understand how
(06:12):
much revenue a store is going todo, or how to advertise the
right things at the right time.
We built a whole bunch ofmobile apps that were the Uber
for concrete and cement deliveryfor a really large cement and
concrete company Wow.
You have to do reallyinteresting things all over the
(06:32):
place Again made lifelongfriends.
I did that for around eight orso years.
That led me to wonder what elseis out there.
I was working with a lot ofconsumer-focused companies,
people that were either workingdirect to consumer or B2B2C-type
business models.
(06:53):
I always was intrigued bysoftware.
Of course IBM also madesoftware.
It was mostly B2B software.
I started looking around at thiscustomer success role.
I didn't really know what itwas at the time but I reached
out to a friend of mine,michelle, who's actually still
at Heap.
She and I had worked together.
I just thought, hey, I'mlooking to potentially leave.
(07:14):
Tell me more about customersuccess.
She said, hey, we're actuallylooking for somebody to scale up
the team in New York.
Why don't you consider this?
I'm like, well, I don't evenknow anything about this company
.
It was like a 100% company atthe time.
She and Veronica, who isrunning customer success at Heap
at the time, sold me on theidea of building the team from a
(07:36):
team of just a couple of peopleto a pretty large team over the
last few years.
It turned out to be honestly acareer-defining experience Met
so many interesting people,worked on a lot of interesting
problems.
Our software Heap is customeranalytics, product analytics.
What we're doing is trying tohelp digital builders understand
(07:59):
how users are traversingthrough their flows.
It could be to buy somethingonline.
It could be to do a transactioninside of B2B software.
It could be to do a financialtransaction Then understand
where the friction is so thatthose digital builders can go in
and fix and remove the frictionso their users have an easier
(08:19):
time doing what they're tryingto do.
It actually brings together theaspects of consulting that I
loved, which are around thechange management, as well as
the people side of things likehow do you actually compel
people to make decisions usingdata instead of just using their
gut, which turns out to be thehardest problem that we're
always faced with.
(08:42):
I've been doing a couple ofdifferent things at Heap over
the years Scaled up the customersuccess team in New York, built
a team in Europe.
Then I moved actually into arole that I was doing on the
side.
You end up with these roleswhere it's a passion project and
then it turns into an actualjob.
I created our customer successops team, which is just a huge
(09:06):
passion of mine because I lovegetting hands on with data and
then hire somebody else to runthat team and then came back to
run the customer success teamthat I'm running now.
That has been a lot of fun.
We've announced a definitiveagreement to be acquired by
another company called ContentSquare in the near future.
(09:29):
Really excited to join ContentSquare because there's a lot of
complementarity between ourproducts.
We're doing a lot of thequantitative side of analytics
and getting the structured dataand the funnels.
They're doing a lot on thequalitative side of analytics.
I'm really excited to blend thequant and call together as we
(09:50):
join forces.
Speaker 2 (09:52):
That brings me to today.
Speaker 1 (09:54):
If that was an elevator, we would have gone up
and down the World Trade Centerlike four times maybe more.
Speaker 2 (10:01):
Yeah, no, it's all good.
It's a cool story.
It's fun to hear how folks endup in these roles, because
everybody's path is so different.
It's not as cut and dry as asales leadership role or
something like that.
It's always circuitous, whichis a word I'm still working on.
Speaker 1 (10:22):
Yeah, I'm always trying to hire people too.
I'm always trying to findpeople that are the interesting
unicorns who have done enough tounderstand what we do and be
curious about it, but they don'thave to come from a traditional
CSM background or a traditionalmanagement background.
It just needs to be somebodywho's curious about data and
(10:45):
human behavior and how tofrankly, just how to make things
happen, because a lot of CS isjust getting things done and
building a coalition of peopleto care about your customer and
help them out.
Speaker 2 (10:58):
Yeah, and I would imagine you building that ops
function.
You probably saw a lot of that.
Obviously, we're talking aboutdigital CS on this podcast, but
I kind of view the ops functionand digital CS can be
interchangeable, can be separate, can be one, you know, because
there's a lot of kind of overlapin terms of, like, wrangling
(11:21):
data, wrangling systems to, youknow, accomplish kind of a task.
So so I guess in that, in thatvein, you know, one of the
questions that I do like to askall of my guests is essentially,
you know what, what theirdefinition of digital CS is,
because it does vary, right.
So I'd be curious to get your,your take on it, especially
(11:43):
given your background and youknow data and all that kind of
fun stuff.
Speaker 1 (11:47):
Yeah, I mean it's definitely a blurred line and
that is how I got into.
Like you know, at the time weweren't even calling it digital
CS, but it's how I got into whatwe would now call digital CS
and we've gone, as probablyeverybody has gone, through
several different you know sortof like revamps of it over the
past couple years.
Even it's still always changingevery quarter.
But I guess I mean one.
(12:09):
It's to drive more impact withour human resources which,
incidentally, in a softwarecompany are pretty much always
our largest cost.
So it's not to replace humans,really to assist them.
It's not exactly ops, becauseops is more for internal
purposes.
As I see it, of course, thereare a lot of things that we do
in ops that our customer facing.
(12:30):
If it's done right, it improvescustomer satisfaction because
you're giving them the resourcesthey want and need at the
moment when they need them, evenif they didn't know exactly
what they needed at the time.
So just having that, that'swhere you really marry the ops
and data with the execution sideof things.
So if I had to think about,like, digital CS is the
(12:52):
execution, the ops and analyticsside is understanding what we
should try to execute to improvecustomers lives and I think the
biggest thing is just like alot of testing and learning.
So in the in that one, ourproduct is always changing to
our customers.
Needs are always changing, thecompetitive landscape is
changing.
We have to be really flexibleto use the data that we have
(13:16):
like that I call it the digitalexhaust that's coming off of our
platform to understand likewhat are some unmet needs that
we might be able to help with todelight our users.
Speaker 2 (13:28):
I love that and I love that you blended kind of
the that enablement factor ofyou know enabling the team and
making sure the team is runningefficiently with, obviously, you
know why CS is here is to drivecustomer outcomes and make
customers successful and youknow, I think that my my hunch
(13:52):
anyway, after speaking with youand, and you know, chatting with
you a little bit, but alsolooking into your background a
little bit is that your historyand passion around data and data
science has, has, has probablybenefited you throughout kind of
the roles that you've had, butthen specifically in CS, because
(14:14):
I mean, if you ask me, one ofone of the most valuable and
probably looked over products ofa healthy CS organization is
like the data, into the datainsights that we can glean from
various data sources and thingslike that.
So my hunch is and I'm puttingwords in your mouth that that
(14:36):
you probably had a kind of akind of advantage going into
setting up a CS org, coming atit from that angle.
Speaker 1 (14:44):
Yeah, I mean it's definitely it has helped a lot.
I think it's you don't have tohave a background in data or
data science, but definitely acuriosity to know what's
possible.
I think one of your guests,whose name was also Lane, which
I was really fascinated by, fromGainsight she was she kind of
talked about how data relates todata and I loved that term
(15:06):
because it really is justknowing, like, what data is out
there, how might you tie ittogether to tell you to one to
come with a story of what it,what can you, what are the 20%
of things that you can do todrive the 80% impact Right, and
a lot of that like just comfortin working with data and working
with messy data definitely camefrom my time.
(15:28):
Like dealing with you knowtweets and social media data, or
dealing with you know trying tojoin together data sets from
different back end systems andthat kind of stuff.
In a growing company like oursor, like you know, probably most
of the people listening to thispodcast large companies or
growing companies Most of thedata is messy.
You have to get supercomfortable with it being mostly
(15:51):
accurate or directionallyaccurate and then having some
backup plans in place.
So I think that comfort withthings not being perfect
probably went a long way.
I see a lot of people or talk toa lot of people are trying to
start a digital CS program andthey're you know, they basically
get stuck because they the datais not perfect and they're
(16:13):
stressed out that they're goingto mess something up.
Or, you know, like the everdreaded thing where you know you
send the wrong email to thewrong person, or for a long time
we were worried about our youknow, entitlements database
being like slightly inaccurate,and then we would send messages
to people saying, hey, you'renot using this thing or you're
not entitled to this thing, whydon't you go check it out?
(16:33):
And then they respond back andthey're like wait a second, we
already have this.
But I mean, ultimately you aregoing to make some mistakes like
that, and when that happens, Iusually just reach out to the
customers and just say, hey,like you know, we're trying to
improve right now, we're tryingto do things at scale, and
everyone I've never had someonewho is not understanding about
it creates a nice human moment.
(16:54):
So yeah, I think that that pieceof it probably helped in terms
of starting out in CS andstarting out in digital CS.
I would say the other piecethat really helped is most
people and I mean I work likerun a customer success
organization for a company thatis all about data Most of the
people that we work with are notcomfortable working with data,
(17:18):
it's their first time doing itor they're making really
consequential decisions, and soa lot of the job is how do you
compel people to care aboutusing data?
And that's really like a changemanagement exercise.
So what I found in my careerworking in data science is that
you really need to explain howyou got to the answer like that.
(17:39):
You know that when you're yourmath test gets graded and you
get like bad marks for not notshowing how you showing your
work on how you got there.
If you can show your work andyou bring everybody along, it
goes a really long way to thechange management and getting
people to use data and, morethan just using it, get curious
about what more could we do,because everybody has some great
(18:02):
idea.
They just may not know exactlyhow to execute on it.
So if they see what's possible,they see the work that you did
to get there, then you know, allthe time I have people come to
ask you some ideas.
Like somebody said hey, can wepull in our community data and
then use that to ping peoplewhen questions don't get
answered by one of their peers,and then how can we build that
(18:24):
into our health score?
So it's, you know, different.
Three different people camewith three different ideas, all
relating to the same data, thatall make our customers lives
better.
Speaker 2 (18:34):
Yeah, and that kind of stuff is lurking everywhere.
You just got to kind of go lookfor it and think about it
creatively.
And I really like what you saidyou know about just not being
able, not being afraid to jumpin, because so much of kind of
what we do in CS is gracefullyfalling on our heart a little
bit not being afraid to do so,because like.
(18:55):
Honestly, it is those humanmoments that actually make a
huge difference versus you know,if everything's kind of hunky
dory and by the book and by therecipe or whatever, you're
probably missing some greatopportunities to connect, you
know, with your customersorganically and and it also
shows that you know you'reyou're, you're trying to do
(19:17):
things and and you know toimprove, improve upon the
experiences.
It's not like we're purposelygoing out of our way to like
send extra emails, but yeah, Imean I think there's like the.
Speaker 1 (19:31):
I'm sure a lot of people have heard of the service
recovery philosophy.
It's basically like you know,you have, you have enough.
If something is broken, youactually have an opportunity to
not only fix it and do the rightthing but dramatically improve
the relationship.
And this is like one of myfavorite things.
With digital CS.
This is actually one of thefirst now that I think about it
(19:51):
like one of the first things.
Before even add digital CS as afunction, one of the first
things that I did at he wasreally use our NPS program as a
way of driving those servicerecovery moments.
So I mean, yes, we definitelycare about having a high NPS
score, but what I care a lotmore about is finding the
(20:12):
specific people who arestruggling and then turning
their moment of frustrationbecause usually they most people
as an in product survey they'll, like rage, submit a negative.
So you see the ones that are,like you know, under, like their
two or three or four.
Those are people who are reallystruggling right now and if we
can figure out exactly whatthey're struggling with and
(20:33):
reach out with some help andthen just offer, you know, an
olive branch, say, okay, cometalk to us, we truly want to
help you, that often turnsthings around and I, and then we
measure how did they respond tothe next time they responded,
and if we're able to close thoseloops live, our response rate
goes, you know, more than likeor sorry, our.
(20:54):
Our NPS for those people whoresponded negatively goes up,
like typically people willbecome, you know, go from being
a detractor to being a passiveor promoter over time if we've
done effective interventions andthat's kind of like really.
I mean, that's been done for along time since NPS has been a
thing.
But I mean I will often submitpeople submit NPS on products
(21:18):
that I use, just to see whathappens afterward, and me too,
majority of them.
There's no follow up, there'sno close to what.
They're just collecting thedata for data's sake, and I
think that a huge missedopportunity for a digital CS or
a scaled CS motion.
Speaker 2 (21:34):
I was going to say exactly the same thing massive
missed opportunity and NPS comesup quite a bit on the show.
Speaker 1 (21:41):
I mean because most of the people love to hate NPS.
Speaker 2 (21:47):
And exactly, I think for me, the two most valuable
bits of NPS are what we weretalking about the score, okay,
fine, but the goal is in thecomments.
The goal is in the commentsthat you can then distribute
internally and try to make someimprovements.
The real goal is when youactually respond and actually
engage on the back of thoseresponses, because, a it shows
(22:13):
that you're listening, but, b itdrives engagement down the road
.
It's one of those touch pointsthat can really help secure a
renewal, quite frankly, or makea customer, even if things
aren't hunky-dory, they knowyou're listening, they know
(22:35):
they've got a window into theorganization and so, even though
they may be evaluating someother solutions or whatnot, at
the end that could be one of thethings that makes them stick
around, because, oh yeah, I meanjust knowing ahead of time and
just getting a lay, especiallyin our primary.
Speaker 1 (22:57):
We have a traditional CS motion which is pretty
high-touch to very high-touch,and then we have a pooled motion
.
That digital is an overlayacross all of these, but within
the pooled accounts we're oftenpushing out content as you would
from a digital standpoint,trying to get users to come in
(23:19):
and say, hey, this is the thingthat I care about.
Or, based on our signals,here's something that we see it
looks like you're strugglingwith or you haven't done yet
that you should have done by now.
And within that base, theseinterventions are super
important because it givespeople a chance to just raise
their hand and say, hey,something is not quite right.
It doesn't matter what thething is, but if we can just
(23:39):
talk to them or just evenexchange email messages with
them, it goes a really long wayto understanding more about
their context, diffusing anypotential risk or frustration
for that person and the accountand many times often leads to an
upsell because they'refrustrated that they can't do
something that they could do ifthey had one of our products
(24:01):
that they didn't even know thatwe sold.
Speaker 2 (24:04):
Yeah right, exactly what.
On that topic, what are some ofthe, I guess, your favorite
motions that you have in placethat are either particularly
effective or things that arejust cool, like from a CS nerd
perspective?
Speaker 1 (24:25):
Yeah, one of the challenges I think on your
podcast and on all such podcaststhis is often discussed just
the lack of data, cleanliness oncontact level data.
So you have all the issues thatI'm sure have been talked about
ad nauseam, where people put inthe wrong name.
They combine their namestogether and then all of a
(24:46):
sudden you're saying hi laneheart, instead of just saying hi
lane, or the caps was on, andso it's all.
Speaker 2 (24:52):
Yeah, caps on, or they put it in all lower cases.
Speaker 1 (24:55):
Obviously, everything is messed up in our systems, or
I mean that's like you know.
That's pretty recoverable andwe have algorithms that you know
, scripts that will run to tryto fix that.
But the other thing that ismost difficult actually is see
right there, with that statement, you're already above.
Speaker 2 (25:11):
Above, where a lot of people are like you're fixing
the casing.
Yeah, totally.
Because I think a lot of folksyou know they'll have these,
they'll have user databases orwhatever, and it's just like
whatever it was put in by so andso and that's just what it is.
And then you know it's like amanual or an outsourced type of
(25:36):
situation to go fix it.
So that right there is actuallyquite interesting, because I
think a lot of people strugglewith that exact thing.
Speaker 1 (25:44):
Yeah, I wonder if there's like a Salesforce mini
app idea, or maybe this alreadyexists and somebody should write
it to us and tell us where.
You just plug this thing in andit just fixes the bad contact
data that's coming into your CRM.
Speaker 2 (25:57):
Yeah, if you have, if you out there, if you, the
listener, have something likethat, like an app or something
that automatically goes throughand cleanses your Salesforce
contact data?
Comment down below.
Speaker 1 (26:09):
Yeah, that will be your next guest, and definitely
call me as well, because then wewon't have to do all this stuff
manually.
But so that one of the thingslike that is one of the
challenges that we have.
That and just knowing who'sstill at the company, who's a
decision maker at the company,how are people related to
departments within the company?
Because I could go on a littlebit of a tangent here about the
(26:32):
departments and the breadth ofadoption.
So one of the things that wecare a lot about is that
multiple teams, differentdepartments, are using heap to
make decisions.
Reason why is that it reducesconfusion within their
organization, ultimately reducescost of people using different
data sets to try to makedecisions, and of course it
(26:53):
makes our platform stickier,because now you're making
decisions using the data thatyou collected from heap and
using charts and heap.
So we actually started.
This is kind of like a crawl,walk, run thing.
So I started off with just anapp queue in our product that
would just ask people when theywere signing in for the first
time, which department are you apart of?
Speaker 2 (27:14):
What do you use?
Speaker 1 (27:15):
Yeah, like what do you do and what are your goals
Like?
Why did you come here today andyou had to keep it really short
?
Because we were afraid ofadding undue friction in our
sign up process and in fact thisis actually why we ended up
with kind of shallow data in thefirst place, because we wanted
to make it very frictionless tosign up.
Remember, our company is allabout removing friction and we
(27:37):
looked at OK, if you ask toomany questions, people will drop
off in the beginning of theflow.
There's a really interestingLenny's podcast from a few
months back about someonetalking about PLG and how they
were actually saying it's fineto ask the questions you need to
ask, because if people drop off, they weren't very high intent
anyway and B2B software is theexpectation.
(27:59):
Is you're going to give up thatkind of information?
Anyway back to the thing.
So we collected thatinformation just using an app
queue, fed it into Salesforceusing Zapier and then use that
to basically say, ok, how are wedoing from a breadth standpoint
across accounts?
Do we have people in product,in marketing, in customer
(28:20):
success, in data and engineeringall using Heap?
And if not, how do we get morepeople across those teams using
it?
Or how do we get people toidentify themselves?
So, then what we did is wecreated just basically a
feedback loop where we look atwe use Marketo to send emails,
so we look at when we send outemails, are those emails being
(28:42):
delivered or are they bouncingWith all the turnover that you
have in companies today, peoplestick around, for there's some
different numbers out there, butit's under two years on average
.
So people are leaving and weneed to know are these people
dormant or did they just leavethe company?
Oftentimes their email balanceis, like you know, probably 70%
accurate at saying they left thecompany.
(29:02):
So that was one of the coolthings is just flagging contacts
that had left and then usingthat to flag accounts where we
don't have any relationshipcontacts or we don't have any
contacts in a certain department, and then just team up a
message that goes out to thoseaccounts through Catalyst, which
is our customer successplatform, to say, hey, it looks
(29:24):
like this person left and theywere in such role at your
company.
Did this person actually leave?
If they did, who is the newperson that's taking over?
One of the challenges that wehad was OK, we you know if
you're trying to reach out topeople by email, and they're no
longer there obviously you'renot going to get a response.
So, there's different levels toit.
(29:44):
We just send this message tosome of the top users in the
account, based on who's loggedin most recently, and it
actually is very effective atgetting those people who are top
users care a lot about theplatform continuing to exist at
their company and you know usbeing able to reach out to the
right people there, so usuallythey give us the information
(30:05):
we're able to update things sothat when we send out messages
we're sending them out to theright decision makers in each
department, and that has reallyhelped us with the dormancy
problem where you know, if wedon't have that top level
alignment, the account will overtime just sort of erode because
no one is administering theaccount.
Speaker 2 (30:26):
Yeah, it's so interesting because I feel like
I don't feel like I know that alot of times we're just afraid
to send those kinds of messages,you know, because we're like
hey, we don't know you that well, can you help us out?
But I think that is where,whereas that can be viewed as
(30:49):
something that is negative, Ithink also, on the flip side,
it's a point of engagement andyou're asking your most avid
users to say hey, help us out,keep us up to date so that we
can serve you better.
I think it's all in thesemantics and it's in how you
message that.
Going back to something thatyou said earlier which I thought
(31:11):
was interesting was almost thisnotion of, in PLG, using survey
completion like the amount ofcompletion of a survey as almost
like an engagement metric,which I think is interesting.
If somebody goes through andcompletes five out of the 10
(31:35):
questions in your survey versussomebody who completes the 10
out of the 10 questions, youcould almost say that, hey, this
person is a little bit moreengaged with your company much
less the software, but maybe thecompany and therefore is
somebody that you could use asan advocate or something like
that.
I thought that was veryinteresting and one of the side
(31:56):
benefits of surveying perhaps.
Speaker 1 (31:59):
Yeah, and I think you have to be careful.
The big thing with surveys isthey're so annoying.
You know when it's the end ofthe quarter because people have
some goal in their company goalsto send out a survey or get a
certain response rate or just acertain score.
I will always see it at the endof a month just a bunch of
messages piling up.
You have to be really carefulnot to bombard people.
(32:22):
We have a bunch of prettysophisticated logic that keeps
us from over surveying or askingtoo much of too much feedback
without a direct benefit.
We do a lot of surveying.
Our product team does a lot ofsurveying, especially our long
tail of customers to getcustomer interviews of people
(32:42):
that are doing specific thingsin our product.
Usually people are reallywilling to participate in those.
Sometimes they'll becompensated, Sometimes it's just
product people love talking toother product people and those
are our users or userresearchers, UX people.
Speaker 2 (32:59):
Yeah, interesting.
How do you coordinate that?
Because one of the epicproblems is like, hey, marketing
wants some information andsales wants some information and
CS wants some information, andproduct is like do you write
exactly?
Okay, question answer.
Speaker 1 (33:20):
Yeah, I think the good thing is, if you have a
small enough team or a team thatis cohesive enough, you can
strike that balance betweensomeone is the human router or
traffic cop to make sure thatyou're not inundating a specific
base of people, but you alsowant to just leave it open and
let people tell you if it's toomuch.
(33:42):
So we're more laissez-faireabout it than other places.
I've seen where, if somebodywants to reach out to customers,
we're not going to say, go sendthis to 1,000 users at once,
but if you have a list of 100people you want to reach out to,
maybe five or 10 of them willend up responding.
We've been pretty much willingto do that.
(34:02):
We haven't seen any majorrepercussions.
Where we do have issues is it'snot an issue, it's just a thing
that happens.
We have multiple differentteams that are all.
They all have the same goal,which is to engage our user base
.
That comes from sales, it comesfrom customer success.
It comes from product, it comesfrom product-slash-product
(34:23):
marketing, it comes frommarketing and from our scaled
adoption team.
So we do have a process wherewe just say, hey, these are the
sends that are happening andthis is the relative size of
those sends to make sure that wedon't send two messages per day
about totally different topics.
Then the metrics that we lookat to monitor that are really
(34:46):
the unsubscribe rate, to makesure that we're not overlapping
too many sends and then annoyingpeople because they got three
messages that didn't seemcoordinated at all.
Speaker 2 (34:58):
Totally, yeah, absolutely.
Speaker 1 (35:00):
I had probably-.
I think there should be an appto solve that problem as well,
just like there probably is also, we're just not using it.
Put all of your campaigns andthen prioritize them smartly, so
that the ones that are going todrive the highest impact will
get sent first and the rest justgo into a backlog Exactly like
a Q kind of deal.
(35:20):
Yeah.
Speaker 2 (35:23):
Obviously, there's some folks who use different
systems to send different emailstoo, and that exacerbates the
problem because there's nocommunication between the two.
I had a horrid experience withthis kind of stuff recently.
I won't mention the company,but it was like pre-sale they
(35:44):
were very aggressive in theiremails and calls to drive the
close.
Then post-sale, they wereincredibly aggressive.
I probably heard from six orseven different people like
texting, calling, emailingmultiple times.
Speaker 1 (36:04):
Texting is pretty amazing To drive an upsell
Totally.
Speaker 2 (36:09):
I didn't respond to any of them and then they start
sending me experience surveysand I gave it to them.
I was just like this is notcool, no, Stop, because it was.
Obviously it was very obviousthat it was like an outsource
type situation.
It wasn't a coordinatedoutsource situation, it was like
(36:29):
20 different people got a lead.
For hey, if you can upsellthese people, it's just so
stupid.
Anyway, it was like the epitomeof what not to do.
Speaker 1 (36:42):
Yeah, it's tough because, if I think about our
tech stack, we have a prettyrational tech stack.
We use Marketo for the majorityof our email sends, across
marketing and product marketing.
We use SendGrid to sendtransactional emails from our
product.
We use Catalyst to send O-Salecustomer success emails.
Our sales team uses Outreach tosend prospecting emails and
(37:06):
some sequences for even O-Salecustomers that they're managing.
Then, of course, we have Gmail.
That's going back and forthwith customers.
What I've found is that, eventhough Salesforce is far from
perfect for this, we bring allthe data into the activity feed
in Salesforce and into our ownproduct heap.
We basically have all thesetouchpoints streaming into those
(37:29):
two platforms, and then we canuse those to build suppression
lists.
It's far from perfect, though,because you don't really get the
priority of every message.
You can just look at thesaturation of messages per
recipient or per account, but ifyou look at the source, you can
infer what the message wasabout based on which system it's
being sent from, but there'sdefinitely not a
(37:52):
one-size-fits-all thing, andI've had several different
companies try to sell them, andI just don't believe it, because
some of these systems are soentrenched that we're not going
to get rid of them.
Speaker 2 (38:02):
Yeah, totally Absolutely.
That's cool, though.
I like that notion ofcollecting everything and then
throttling a little bitdepending on the volume.
That's super smart yeah it'sdefinitely not perfect.
Speaker 1 (38:17):
If anybody's listening to this and they're
like that's BS, they'redefinitely not doing that.
I apologize, let me know whatwe did.
Speaker 2 (38:26):
One of the things that we spoke about previously
was this notion of juststandardizing metrics across
departments and really trying toget on the same page,
cross-departmentally, with thegoals and what you're really
trying to drive.
Can you chat a little bit moreabout what that looks like at
(38:47):
Heap and what you're drivingspecifically?
Speaker 1 (38:50):
Yeah, we have a company value called Taste the
Soup, which might be like eatyour own dog food or drink your
own champagne somewhere.
Sure, we really try to livethis every day because, since we
are a product analytics company, we have lots and lots of data.
We are a self-serve platform.
Everybody in our company isusing Heap for various things.
(39:12):
One of the age-old challengesthat we've had is just what is
the definition of active usageThen what's the definition of
value driving usage?
Because you can have activeusage without value driving
usage.
It's easy if you don't know whatvalue looks like for your
(39:34):
customer, but if you don't knowwhat value looks like for your
user, you're going to end upinferring that they're fine when
they're not, and then you'renot driving some of the most
important interventions.
One of the things that we did afew quarters ago is just launch
a cross-functional team whichis spearheaded by Daniel, who
leads our product analytics team.
Who's amazing.
Huge shout out to Daniel to getalignment on these definitions
(39:57):
of basically our version ofMalWow and Dow basically our
users and daily users.
Then we have a few others thatdrive what we infer is value
driving behavior, like repeatingcertain actions within the
platform For the longest time.
For a couple of years, we wereall customer success was using
(40:21):
our own definition, product wasusing a definition, our
analytics team was using adifferent definition.
We just created thiscross-functional team and
basically said we need to figureout what these metrics are, and
then we're just going to blessthese and lock these down and
we're only going to use acertain set of events to
calculate them, so that when youare driving interventions,
(40:42):
we're not driving interventionsto the wrong people.
I guess communication isprobably the number one thing.
We're awash with data, but it'sreally just communicating on
the metrics that matter, or themetrics that we're going to
decide matter together.
Then I think the other bigthing that helped with
sanitization is just puttingthose metrics on display in
(41:03):
front of the entire company.
We have a system where we trackall of our OKRs as a company.
These are always metrics thatare what we call like top-line
metrics, so metrics that we justtrack all the time, even if
they're not at a specific OKRfor that quarter.
That has really helped justwith the visibility, because it
gets everyone thinking about howcan I drive those metrics?
(41:26):
And it also gets peoplethinking okay, I have an idea
how we could sort of rev on thismetric together, bring it to
the right people, or, oh wait, Iwas actually using a different
metric to measure success of myOKR.
I need to make sure it's tiedback to this one.
We don't really have anyonepolicing it, but organically, by
setting the definitions withthe department leads and then
(41:50):
making them widely available inour own platform and in our data
systems, we've pretty muchdriven a way the behavior of
people using different metricsor just random metrics all the
time.
That's from a product usagestandpoint.
I would say that actually, oneof the things that we have more
trouble with now that we'vemoved on from that challenge is
(42:14):
our commercial data andsegmentation.
Everybody wants to know whatsegment is this customer in in
terms of how we cover thataccount and then what motion are
they in in terms of the type ofservicing that they get from us
?
Getting that data accurate,maintaining it based on our
(42:35):
contractual commitments and thenpropagating it out across our
systems is an ever-presentchallenge.
I think, as with any dataquality, it's never really going
to go away, but that is thecurrent challenge that we're
focused on.
If anybody has great ideas onall years, again it goes back to
communication and justcommunicating.
(42:55):
Who owns that piece of data?
We had a whole cross-functionalteam for Salesforce to just say
let's list out all of the topdata elements that we have.
We had this spreadsheet thathad 500 rows.
Does anyone even know what thisone means anymore?
If not.
Speaker 2 (43:12):
Let's get rid of it.
Speaker 1 (43:14):
If people do know what it means, then who owns it?
If somebody owns it and it'ssimilar to another one, let's
call that person or just have abig call where it's a
clearinghouse.
That is the way that we've beensolving it so far and it's
helped us make a dent in thosestandard metrics.
My overall advice is put themetrics in public for everyone
to see, make it easy to know whoto go to when something doesn't
(43:38):
look right or when someone hasquestions, and then patiently
deal with all of thediscrepancies.
To encourage people to come tothe table when they have data
problems instead of reinventingthe wheel on their own and
trying to make their own thing,because it'll save them time for
that one thing they're tryingto do and then it'll create 10
times more problems in a quarterfrom now.
Speaker 2 (44:00):
That's great.
Yeah, I love that advice.
I think data hygiene issomething that everyone
struggles with.
Show me somebody who doesn'tstruggle with data hygiene and
I'll show you a liar yeah, everycompany, from the tiniest
companies to the biggestcompanies.
Speaker 1 (44:15):
Absolutely.
I think the other thing, too, isjust taking a really and this
is something that I do and myteam does with our clients all
the time trying to figure outwhat are those value driving
actions or moments, andsometimes they're a specific
action that you repeat over andover.
Sometimes it's a threshold of acertain number of times that a
(44:36):
user has done a thing, or acertain number of users on an
account that has done that thing.
For us, it's like savingreports and pinning them to
dashboards and then sharingthose dashboards with other
people to drive that virality.
What I find is that most of theteams that we talk to don't
know what those secondarymetrics are that drive the
(44:58):
Mao-Wao Dow type metrics.
And figuring those out is thebiggest unlock for digital
customer success, because itallows you to intervene at those
moments that matter or whenpeople are on one side or the
other of that threshold.
You're not telling themsomething that's really pedantic
that they probably don't careabout or they're already past it
, and so that you're not goingway over their head with the 103
(45:22):
course when they need the 101level.
Speaker 2 (45:25):
Yeah, exactly yeah.
All this stuff is reminding meof a conversation I had several
weeks ago with Dan Ennis, who isfairly well known and CS
circles for being.
Yeah, one of the things that hedoes really well within his
organization is using usage datato figure out what persona
(45:47):
somebody is likely to be withina customer, which I think is
fascinating to do those kinds ofthings as well.
But, yeah, it's really awesometo hear that is next level.
Speaker 1 (45:58):
If someone is doing that, they're probably in the
top 10 or 20 percent ofsophistication, which is amazing
, but this is one of my personalprinciples.
It doesn't have to be perfect.
If you're listening to this andyou're like holy cow, how am I
going to figure out, inferpeople's persona based on their
(46:20):
behavior?
Just start with something.
Just try to find that oneactive usage metric that is not
just like they logged into theplatform and then just run a
test around that and eventuallyyou'll figure it out.
Speaker 2 (46:32):
Totally, absolutely.
Do it, see if it works.
If it doesn't, go back and doit again, figure something else
out.
Speaker 1 (46:42):
Yeah, it's just those learning loops.
That's what I think.
In order to be successful indigital CS, you have to have
people who are just innatelysuper curious and willing to try
and fail a lot.
You'll find those breakthroughs, but they're always diamonds in
the rough.
Speaker 2 (47:01):
I think so too.
Well, cool, as we start toround out our Convo because
we're getting towards the top ofthe hour here and I want to be
respectful of your time I'd lovefor you to give us a quick
download of what's in yourcontent diet.
What do you pay attention to ona regular basis?
Speaker 1 (47:18):
Yeah, I mentioned it earlier.
Of course, I listened to yourpodcast.
There are a bunch of other goodCS podcasts out there, but I
also really like to expandbeyond CS and really think about
what is the persona of peoplethat we are serving, which are
largely product people ordigital builders.
Lenny's podcast is one that Imentioned earlier.
(47:39):
That's amazing for that,because he has a lot of guests
who are just top practitionersin their field and they're often
talking about product-ledgrowth or how do you make the
product just easier to use.
At the end of the day, that'sreally the nexus of digital CS.
It's like how do you make theproduct and the people work
(48:01):
together and get the people todo the things that your product
is intended to do?
There are a bunch of goodepisodes that I could share on
that topic and just also goesinto aligning active usage
metrics and stuff I also tend tolike.
My wife always gives me a hardtime because I'm always reading
what she calls businessself-help books.
(48:21):
There's one that I readrecently which is I have it
sitting here on my desk ofScaling People by Claire Hughes
Johnson.
She was the COO of Stripe.
I'm sure many people have readthat Fantastic book for anybody
who is leading a largeorganization or relatively small
organization, because she givesvery digestible, very specific
(48:43):
tips and frameworks.
There's a great book offrameworks Then, one that I read
recently actually listen to itwhile I was running on the
audiobook.
It's called Nudge.
It's about behavioralpsychology.
That is really interesting justin terms of what motivates
people to take certain actions.
And also when you think aboutdigital CS.
(49:04):
What we're doing all day istrying to motivate people to
care about a thing or to nudgethem into doing something and
connecting with what they see asvaluable and what we offer.
Then the last one, which isdefinitely a personal self-help
book, is Getting Things Done,which is a pretty old book.
Some of the stuff in the bookis outdated now because it's all
(49:26):
paper process, but there's anapp called OmniFocus that is a
task management app For anybodywho has a lot of things going on
.
I would definitely recommendthat one.
Speaker 2 (49:37):
Cool, I love it.
Amazing little tidbits.
Any folks that you would wantto give a shout out to Digital?
Speaker 1 (49:45):
CS related?
Yeah, a couple.
Recently, somebody that I'vebeen working a lot with is a
co-founder of an app calledAthenaai, mike Molina and his
team, jared and Sid and a bunchof other people over there.
What they're doing is basicallyhelping us scale Slack.
We're introducing customerSlack channels to many of our
(50:09):
customers and they help withbridging the.
When people ask questions, howdo we make sure those questions
get answered in a timely waythat doesn't overwhelm people
from being in a bunch of Slackchannels, and then how can we
use that for customer marketingas well?
It's definitely just an amazingteam, but also really useful
(50:29):
app for the next iteration andgetting out of just email as the
only channel that we email orin app that we use to
communicate with people withoutbeing super invasive and trying
to send people text messages,because I think that's one step
too far.
Yeah, the story that you toldis like wow.
Mike is only one great person toreach out to and to follow.
(50:53):
They put out lots of greatcontent.
This in the vein of scaled CSas well.
I don't know if anybody has evermentioned Mark Costaglow, who's
the CRO at Catalyst.
He runs all of theirgo-to-market functions,
including Postsale.
He has a framework that heshared with me a couple of times
recently, actually calledMoments of Impact, and it's
(51:15):
basically how do you get tothese specific moments of impact
that are going to drive, likethe customer say, wow, this is
valuable and I love this product.
The reason why I really lovethat framework is because it
relates really well to justreaching the next stair step
with customers, and it can beapplied digitally or through a
(51:38):
higher touch motion.
Then, actually, wes is theperson who runs Scaled CS at
Catalyst.
Wes has been doing a lot of thatorchestration of where the
rubber hits the road.
How do you help the CSMs aswell as the long tail with
reaching those moments of impactwithout being annoying and just
(52:00):
sending the same webinarcontent over and over.
I think they both work reallywell together in doing a pretty
job of deploying that content.
Of course, one of the things Ilove using their product is that
they're also tasting their ownsoup in making the product
better by using it for digitalCS, that's amazing, awesome show
.
(52:21):
Last shout out is a buddy ofmine, todd Bustler, who he and
Steven Ruff started a companycalled Champify which helps you
keep track of contacts as theymove on.
This has been a huge challengefor us and part of that motion
that I mentioned earlier, whereyou have people who are leaving,
we send alerts to the CSMs andsay, hey, these people are
(52:43):
leaving, let's figure out whothe new economic buyer is on
this account.
We can do that at scale.
We also turn around and usethat for sales as well, because
if somebody was a really happycustomer and they moved to a new
company, we can sell to themthere.
Todd puts out a lot of greatcontent just in terms of little
tidbits on LinkedIn that reallyare catered a lot towards sales,
(53:06):
which is their main audience,but much of it is relevant to CS
as well just how to getpeople's attention.
Speaker 2 (53:13):
Yeah, I had a conversation with someone
recently not on the podcast, butabout this notion of CSQLs and
how a CS qualified lead doesn'tnecessarily need to come from an
account that you have.
It can come from someone whoyou used to work with, at an
(53:33):
account that has moved on orwhatever.
I think there's a lot of valuein tracking those people and
where they go within theecosystem of potential clients.
Speaker 1 (53:48):
Yeah, we typically find the close rate.
On those accounts the time toclose is three or four times
faster than it is, which issomebody who's never talked to
us or used our platform before.
From a customer successstandpoint, they get it.
They struggle with some ofthese challenges before, so
their onboarding is always much,much smoother than somebody who
(54:09):
we haven't worked with.
We're always happy to havethose repeat customers and users
.
Speaker 2 (54:14):
Exactly, yeah, cool.
Well, lane, I've really enjoyedour conversation.
It's been great spending timewith you again.
Good to have you on the show.
Where can people find you,engage with you and reach out to
you?
Speaker 1 (54:28):
Yeah, I'm on LinkedIn .
You can definitely find me onLinkedIn Lane, hart, l-a-n-e,
h-a-r-t, and on the heapcommunity, which is
communityheapio, or you can justreach me by email Lane at
heapio Pretty easy to get intouch with, easy.
I always try to respond tofolks on LinkedIn.
I'm truly curious to connectwith people who are doing things
(54:51):
even that are totally differentor adjacent to the space.
Definitely don't hesitate toreach out.
One of the things I'll often dowith folks who reach out is
talk about health score.
How can you build an actionablehealth score?
You can find some stuff on ourheap community that I published
there about that as well, that'scool.
Speaker 2 (55:11):
Okay, we'll have to hit that the next time you're on
the show.
Speaker 1 (55:14):
All right, we'll love to come back in the new year.
Speaker 2 (55:18):
Sounds good.
Thanks for the time.
Speaker 1 (55:20):
Yeah, thanks so much, Alex.
Have a good one.
Speaker 2 (55:23):
Thank you for joining me for this episode of the
Digital Customer Success Podcast.
If you like what we're doing,consider leaving us a review on
your podcast platform of choice.
It really helps us to grow andto provide value to a broader
audience.
You can view the DigitalCustomer Success Definition Word
Map and get more details aboutthe show at
digitalcustomersuccesscom.
My name is Alex Turgovich.
(55:44):
Thanks again for joining andwe'll see you next time.
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