What if you could revolutionize your sales process with just a few clicks? Join us as we sit down with Ashar Rizqi and Matt Cooley, the visionary co-founders of Bounti AI, who are on a mission to transform go-to-market strategies through the power of artificial intelligence. Ashar, formerly leading at Blameless, shares his intriguing journey from managing incidents to pioneering "outcome as a service," while Matt brings his seasoned expertise in scaling companies from his experiences at New Relic and Quip. Together, they weave a narrative of how AI can redefine the buyer's journey by marrying technology with human insight.
Our conversation with Ashar and Matt dives into the core of building a business from the ground up. They share the importance of trust, communication, and mentorship between co-founders and draw from their rich experiences in previous roles to shed light on managing sales, prioritizing leads, and understanding critical metrics like Customer Acquisition Cost (CAC) and lifetime value. We also explore their innovative approach to outbound prospecting and discuss the significant challenges founders face with hiring and scaling effectively. Listen in for their firsthand insights that are sure to inspire early-stage companies.
In this engaging episode, we also touch on the evolving roles within sales teams and the impact AI has on consumer experiences. Matt and Ashar discuss the crucial balance between automation and genuine human connection, highlighting the need for authentic interactions in high-stakes transactions. They reflect on their journey to increase deal sizes with strategic pricing models and reveal how Bounty AI is enhancing productivity for founder-led sales teams. Discover the future of AI in sales, where human elements remain indispensable, and learn strategies to elevate your go-to-market efforts with Ashar and Matt's transformative vision.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:00):
Number one was, as we were building this really
AI-first technology in adifferent space for a different
audience, developers andautomating like sort of the
human aspect of incidentmanagement using AI.
And then me having being afirst-time founder trying
founder-led sales, I was likeman, there's just so much in
go-to-market, just generallythat could be done in a similar
(00:22):
model with, like you know so, ai.
So that was kind of the veryearliest inspiration of starting
Bounty was to take a lot ofthose experiences and learnings
from a very different domain,different type of buyer,
different sort of problem space,and applying it in the world of
go-to-market.
Speaker 2 (00:40):
Thanks for listening to Seed to Exit.
As always, I'm your host, rhysKeck, and today I'm joined by
two exceptional entrepreneurswho have combined their
strengths to build somethingextraordinary.
First we have Ash Arrisky.
He's a serial entrepreneur whohas previously founded YC-backed
Blameless after leadingengineering teams at MuleSoft
and Box, and he's partnered withMatt Cooley, who is one of
Silicon Valley's mostaccomplished sales leaders
(01:05):
Valley's most accomplished salesleaders.
Matt's impressive careerincludes leading New Relic to a
multi-billion dollar IPO andQuip to a $750 million
acquisition by Salesforce.
Together, they've joined forcesto found Bounty AI and they're
combining Ashar's technicalinnovation and values-driven
leadership with Matt's provenabilities to scale companies.
I absolutely loved recordingthis episode.
We cover so many go-to-markettopics and each of these guys
drop some incredible wisdom.
I hope you enjoy it as much asI did.
Speaker 3 (01:30):
You're listening to the Seed to Exit podcast with
your host, rhys Keck.
Here you'll learn from startupexecutives, founders, investors
and industry experts.
You'll learn from the bestabout building amazing products,
scaling companies, raisingcapital, hiring the right people
and more.
Subscribe and listen in for newepisodes and enjoy the show.
Speaker 2 (01:54):
All right, usher and Matt welcome on.
Excited to have you guys.
Speaker 4 (01:56):
Thanks for having us Nice to be here.
Speaker 2 (01:59):
So, as I shared with you guys and so for the
listeners, this is a firsthaving two folks on the podcast
at once.
So I appreciate you guys beingmy guinea pigs, but definitely
excited for the upcomingconversation that we have here.
So, just to start things off,for anyone who's not familiar
with Bounty Usher, maybe if youwouldn't give us a quick
overview, yeah, sure, thanksagain for having us, rhys.
Speaker 1 (02:22):
A quick overview on Bounty we are basically a
platform that's using AI todeliver go-to-market outcomes as
a service, specifically aroundoutbound prospecting, inbound
personalization and so on, soyou can think of us eventually
in the future covering the fullbuyer's funnel and lifecycle
(02:42):
journey.
And what you're getting whenyou buy Bounty is both a AI
experience combined with a humanexperience.
Gotcha.
Speaker 2 (02:48):
Okay, maybe this is my ignorance, maybe this is a
term you made up, but what isoutcome as a service, because
I've not heard that before it isa pretty much made up term that
.
Speaker 1 (02:57):
I'm trying to market and get everybody else to think
about.
But in the simplest way, if youthink about just within sales
and marketing and customersuccess, do you care more about
revenue or do you care moreabout sales activity, right?
So the outcome is that, hey,are we booking meetings, are we
generating pipeline?
Are we generating revenue justwithin the domain of sales, so
(03:20):
all of those sort of leadingindicators.
And so when I say outcome as aservice, you know, imagine if
you could buy a piece ofsoftware or a service that
basically delivers on thatparticular outcome.
So that's the attempt atcalling it outcome as a service,
definitely more market-y madeup term.
And so but yes, that's what itwould be Cool All right, I love
(03:41):
it.
Speaker 2 (03:42):
So just in terms of the history of the company, so I
know that it was foundedapproximately three years ago
and you two were co-founders,but Matt, I know you came on a
little bit later.
So, usher, where did the ideafor the business come from?
And then, how did you and Mattmeet and have him decide to come
on as a later co-founder?
Speaker 1 (03:59):
Yeah, A lot of skeletons in the closet.
You're going to make me bringthose out, but no, no, just
totally kidding.
So just my quick backgroundvery, very quickly immigrant
founder, been in SaaS for thelast 15 years, worked at
companies like Boxcom andMuleSoft.
Started my first company calledBlameless, which was really in
(04:19):
the DevOps developer toolingspace, automating incident
management for SaaS softwareteams, right, and so it was also
venture-backed.
Recently exited.
I left before the exit happenedand started Bounty.
So my experience, a lot of whatthe story behind starting Bounty
(04:40):
was very, very heavilyinfluenced and colored by that
first experience of starting myfirst company as a first-time
founder and CEO.
So number one was, as we werebuilding this really AI-first
technology in a different spacefor a different audience,
developers and automating thehuman aspect of incident
management using AI.
(05:00):
And then me being a first-timefounder, trying founder-led
sales, I was like man, there'sjust so much in go-to-market
just generally that could bedone in a similar model with,
like you know so, AI.
So that was kind of the veryearliest inspiration of starting
Bounty was to take a lot ofthose experiences, learning from
a very different domain,different type of buyer,
(05:21):
different sort of problem space,and applying it in the world of
go-to-market I was justgenuinely.
The thing that I really reallyloved about the go-to-market
space is that when you'reselling to developers I love
developers too but there'sdefinitely a little bit of a
chip on your shoulder where it'slike, oh, I can build that, I
can do that, Whereas there'smuch more appreciation and
(05:42):
gratitude that you feel whenyou're selling to folks that
aren't equipped with those sortof the software development
skill set Right, it's like Ican't go build this myself.
So, wow, I'm so grateful.
So I just really love the buyer.
I love you know working withthat.
You know those kinds of folks Imet, Matt, you know, when
obviously I don't have the go tomarket domain expertise, you
(06:03):
know when obviously I don't havethe go to market domain
expertise, and so that wascritical when you're starting a
company, and so one of the waysthat the early, early strategies
at Bounty was to say, CMOs,chief, you know, customer
(06:24):
officers, and so just coveringthat full spectrum so that we
could kind of build this brain,this knowledge brain that could,
where we could sort ofproductizing ideas that are
coming out of those discussions.
And obviously Matt, you know,just given his experience, was
part of that early journey.
I met him through his brother,TJ, who was also, you know, a
good, a good, close friend, andMatt and I got to know each
(06:47):
other, became, you know, reallyreally good friends throughout
that journey.
And you know, it's like what Ilearned from my first experience
is like, you know, on one hand,you don't want to be starting
companies with like real, likefriends you've known since
childhood, right, Because you'llprobably end up killing each
other, and then, on the otherhand, you don't want to start
companies with like completestrangers.
(07:07):
So with Matt, like it was just amix of great chemistry, just
like really aligned in the waywe think about things, just
really complimentary experiencesand the way that we it's like
literally two sides of a brainin the way that we approach
problems, but we always end uplanding on the same kind of uh
place where we want to be.
So that was kind of like areally strong foundation to
(07:29):
restart a friendship.
And then, um, obviously, likejust his experience is just
phenomenal and what we're ableto turn into a product and then,
you know, turn into a bigcompany.
So that's how we, just veryearly, how we met um, how Matt,
you know, uh, you know, joinedthe company like as a late
co-founder, but it's just beenan amazing, incredible journey
(07:50):
ever since then.
Speaker 2 (07:51):
I love that.
So, matt, how has therelationship or partnership
evolved since starting andcoming on board with Bounty?
What would you say you two havelearned from each other?
Speaker 4 (07:59):
Yeah, so I invested like almost four years ago and
always been advising, and one ofthe things I love about us like
we became fast friends.
Normally I have a period like aspecific amount of time that I
can spend with the companies Iadvise for, but I found myself
like calling us on the weekendand we have just again.
(08:20):
We grew up in very similar waysin some aspects and the synergy
between the two of us isthere's no ego, because there is
a lot of focus around what hedoes and what he's great at and
what I do and what I'm great at,and there's a lot of trust
there.
But there's a ton ofcommunication around it too.
I think we talk two or threetimes a day, which is great
(08:46):
around it too.
I think we talked two or threetimes a day, which is great.
So, yeah, so that just continuedfor three and a half years or
so and I was available at thetime.
I loved what they were doingand decided to join as
co-founder right, and so, yeah,it's been an awesome ride and
the things that I've learnedfrom Usher like I've always
wanted to know more aboutproduct and engineering and you
(09:10):
know I sit in on those meetingsand, you know, at some point
maybe I want to be a CEO, whoknows?
But understanding the entirebusiness helps me be more
effective in my role, and Usherhas been very good about
informing me, and spending timewith the team has been helpful.
Speaker 2 (09:27):
Love that.
So, matt, you've obviously hadsome phenomenal experience in
go-to-market in both startupsand well-known companies, and,
of course, one of your biggestaccomplishments is you were able
to scale New Relic from zero orclose to zero to ultimately
through exit, and this couldprobably be the subject of its
own podcast by itself.
Unfortunately, we don't havethat much time, but can you talk
(09:49):
me through what that processwas like, how you scaled it at
different stages?
Speaker 4 (09:53):
Yeah, so when I joined New Relic, the founding
team had come from Wiley, whichwas on-premise technology
sales-led, and I came fromCitrix, online, which is really
go to meeting.
That'll date me a little bit,but it was very much inbound and
velocity type sales small,small transactions, but a number
of them.
(10:14):
So it was much more operationalin way that you know, I wasn't
a sales leader that was gettingon a plane and going and having
this good dinner, right.
It was all about like thefunnel and obsessing over the
funnel and making tweaks wherewe needed to, and like little,
small things like increasingyour average deal size by 10% at
scale made a really bigdifference, right, and that was
(10:36):
my first job.
I ended up leaving thererunning global commercial sales.
I took a 30,.
I was 30 years old and honestlyterrified.
I moved to Cisco and I've gotthis group of Dartmouth grads
that have done it before, thatare, you know, 10 years older
than me, and but they brought mein because I knew the product
(10:57):
led like.
However, the nice thing aboutNew Relic was I had great
mentors that would allow me tooperate in what I knew, but I
couldn't articulate well, right,and so they'd allow me to go,
make mistakes right and learn,and it just never made them
twice.
Right, I'd sit down with MarkSaclaban or Lou Cerny and you
(11:22):
know I deviated or made amistake, but I understood why.
I wrote it down and then thenext week I came back and
articulated it, and so the partof it was having great mentors
but also worked really hard.
Right, this was my firstopportunity at like a huge
success, right, and you know Ididn't have a lot of equity or
(11:44):
anything like that at CitrixOnline, so it was an opportunity
for me to create some, you know, outside opportunities for my
family as well, and, honestly, Iwas just so passionate about
the team I worked with and eventhough it was a totally
different technology, the modeldoesn't change so much.
(12:05):
Like you do have to adapt towhat the sales model is, but if
the product does a lot of theselling, like, the sales team is
transacting, right, and so youknow what is the sales assist.
Handoff was super important.
There was a lot of foundationalthings that they weren't privy
to, and I came in and there wasa thousand leads a month coming
(12:25):
in.
I had one sales rep and I'mlike Lou, what do I do here?
I don't know where to spend mytime.
And the interesting thing ishow it translates back to why I
invested and brought Lou over toBounty is the original product
was like this insights product.
So when I sat down with Lou andI said, look, we've got a
thousand trials, we have novisibility.
(12:47):
You know Lou will do this likehe'll look this side and be like
okay, and he comes back liketwo days later and he has this
internal CRM that we literallybecame a cheat code over time
and it would show you, you knowhow many servers were deployed,
what the application name was,what the throughput was, and it
would help us identify where toprioritize.
So it helped us run lean.
(13:09):
And so one of the biggestthings that I learned there was
how to optimize technology torun lean.
And when Patrick Moran joined,he was our CMO, our first CMO we
had this rhythm down of saleswas like demand.
It was trailing demand right.
We didn't hire heads to go anddrive sales.
(13:32):
It wasn't sales led.
We had a very strict algorithmfor it.
So every rep we knew that got300 leads in a quarter based on
the average deal size.
But the output would be theirquota right and not for
everybody.
It depends on level of skill,but we had it down and so we
(13:53):
didn't hire until we hadexceeded that amount.
Right, and so it was just likeit was.
It was a lot of it was how torun a business efficiently and
how to think about CAC andlifetime value and how important
those are to your business.
The one thing that I see with alot of the companies that I
(14:15):
advise they are concerned withCAC, right, they don't know the
next move and, especially withfounder led early stage, they're
doing all the selling.
Who's the first person I shouldhire?
How many?
What's the background they need?
And, honestly, if you boil downall the questions that I
normally get when I advise, itall results in how to manage CAC
(14:39):
, because you don't want that toget out of whack over time.
If you don't know what you'redoing, or doing it for the first
time, like in a couple of years, it's hard to come back from it
, right?
So what are the first steps youtake in order to build a
foundation that is conservativebut smart?
Speaker 2 (14:59):
Right, and how should founders be thinking about CAC
in your opinion when it's comingto the subject of early stage
startups, whether you'refounder-led or just starting to
build that GTM motion?
Speaker 4 (15:09):
Yeah, I mean, I think it depends on the stage right.
If you're at seed stage, it'sget as many people using the
platform as possible, right, andhire a couple people, but also
support that with technology,which is what Bounty does, right
.
But also, you know, supportthat with technology, which is
what Bounty does, right.
It is you have to lean into alittle bit of risk to figure out
(15:31):
like do you have product marketfit and beyond seed at A, you
don't necessarily need to havepredictability, like strong
predictability, but you need tohave, you know, customer growth,
like you know eyeballs on thetack right.
It doesn't need to be likenecessarily need to be ARR
growth.
It needs to be some level of achart that goes up into the
(15:54):
right.
Either it can be monetized orit already is monetized, but
usually it's not.
So how do you create some levelof like freemium that you can
monetize later and also showsome level of predictability in
upgrading those by B?
You better know dollar in,dollar out, right, the magic
number is a real thing and intoday's world it can't be sub
(16:20):
1.1, right.
In the growth market you couldmake $0.80 on $1.
1.1, right In the growth market, you could make 80 cents on a
dollar In today's market itbetter be 1.20,.
You know $1.20 on a dollar in.
So it really depends on themarket you're playing in.
But there are basic principlesyou got to be thinking about at
every stage.
But in the beginning there's afoundation that is necessary for
(16:41):
Series B.
If you don't start to operatethat way, you can't come back
from it.
It's really hard to come backfrom it unless you move up
market and then you're makingdecisions based on average deal
size to balance out CAC and themagic number and lifetime value
and companies can get lost inthat.
And so the foundational aspectsof building a business from the
(17:02):
beginning.
There are principles there.
Speaker 1 (17:05):
Yeah, risa, I wanted to just add to what Matt was
saying because it made mereflect back on my experience
with my first company, blameless.
I didn't even know what CACeven means.
Like, what is CAC, what is LTV?
And it's like, oh yeah, we'llworry about it when it's a
(17:27):
problem.
And I think that is the trapthat I think a lot of early
stage founders again it's aproblem, right, and I think that
is, um, the trap that I think alot of early stage founders
again it's a spectrum.
You can.
You don't want to overly obsessat the early stage to be like,
oh, we're going to have the mostperfect cac and ltv, and then
you know you don't want to bethinking about it too late.
But as matt was talking, it wasjust it was kind of like a lot
of my scars started to burnbecause I was like man, like if
we had this kind of awareness,right, it's almost like a
(17:50):
superpower.
And if you can start thinkingabout it early on and
understanding like these arefoundational plumbing, this is
foundational plumbing for yourbusiness long-term, like you
can't build a house withouthaving plumbing in it, right.
And so I almost see what Mattis saying with what he's talking
about CAC and sort of magicnumber and LTV, like all of
these numbers, all these metrics, is having a foundational
understanding really allows youto then figure out like, hey,
(18:13):
how am I going to start building, putting in the rest of the
pieces, like where do I want togo?
And I think I have in myexperience with other founders
is that it's just very, veryrare to see that at early stages
, early foundational companyforming stages, because a lot of
times the advice, like Mattsaid, is like, oh, growth at all
costs, just get as many usersas you possibly can.
(18:33):
Excuse me, because that'sbecome.
That has been the advice forthe last 15 years or so and I
think that's starting to change.
Speaker 2 (18:40):
And do we think it's just starting to change because
of the macro shifts in theenvironment and a greater focus
on profitability?
Speaker 1 (18:47):
I think that's a factor.
I also just think there's moreawareness around it now and I
think even just the venturecapital industry has become
better at articulating andcommunicating the asks around
that, the knowledge around thatamongst early stage founders.
You're just seeing more of that.
So I think it's just a functionof things.
I think definitely post-COVID2021, 2022, when things really
(19:11):
started to slow down kind ofreally made it, you know, really
brought it to light for peopleand unfortunately, there were a
lot of companies during thattimeframe early stage that
frankly had to wrap up justbecause they were not growing in
any kind of sustainable way,and it was just.
It was sad to see that.
Speaker 2 (19:29):
Yeah, it's certainly been a tough couple of years.
So the magic number that's beenreferred to a couple of times
is that, referring to the threeto one LTV, to CAC that's
usually referenced.
Speaker 4 (19:38):
The way that we look at it is sales and marketing
spend to revenue.
That's the way we look at it.
There's probably different waysthat people look at it, but
that's the way that we thinkabout it.
So it's an efficiency metricthat we combine with lifetime
value and net churn and all thatGotcha.
Speaker 2 (19:59):
Okay, and then with the freemium model, because Does
that throw off the LTV to CACequation?
Because you still had to havepaid to acquire those customers,
that ultimately never gave youany sort of revenue because they
just didn't go beyond the trial.
So then do you need morelifetime value out of the folks
who do actually convert, or howdo you approach that?
Speaker 4 (20:19):
Yeah, it's very much like there's a couple of things
to this.
So the land expand aspect ofthis is really important right.
We have this product now that'sout.
We have plans for gettingcloser to pipeline and the
customer um later.
So landing and expanding isreally important thing.
What we we basically obsess overour funnel right and there are
(20:43):
benchmarks for conversion ratesfrom visit to sign up, to sign
up to start trial, to engagewith sales and pipeline and then
close and the one thing you cancontrol is average deal size.
But it is, yeah, I mean it hasto come over time.
It has to come by growingcustomers right over time.
(21:04):
But if you can set it up in away that your cost per lead is
low which again we obsess overall of this on the front end and
this just comes from experiencedoing it Most companies don't
because they're thinking justgrow a customer on the
technology they have and that'swhere they start to fail is if
you set up the top of funnel andthe entire experience before
they become a customer, it makesit a hell of a lot easier for
(21:29):
you to sustain the lifetimevalue in CAC by growing those
customers right and the closeryou get to pipeline and revenue
and, you know, doing some levelof human and combination of AI,
people pay more for that becauseit's actually impacting further
down the funnel, and so we haveplans to go through the whole
(21:53):
customer journey.
Speaker 1 (21:55):
One thing I wanted to add to that, another way that
has helped me think about andframe things is the freemium
spend is almost like a marketingspend.
You can think of it as like oh,that could be my branding spend
, that's like the equivalent ofmy branding spend or marketing
spend.
Right, like it's like you canthink of it as like oh, that
could be my branding spend.
That's like the equivalent ofmy branding spend or marketing
spend.
So I think when you, when youthink of things that way, that
(22:16):
can change the dynamics a littlebit in that or in your
organization where you're likeoh, we have, like you said, we
have this massive freemium modeland we got to make up for it.
On the other side, or you couldjust be like, hey, that's just
branding, for example, likethere's awareness that we would
have spent anyways that it'shard to put place ROI on too.
Speaker 4 (22:32):
Yeah, that's a good point.
That's a good point, Usher, isit creates a community of users
and word of mouth and organicgrowth right.
So it does pay back, but youhave to know how to build that
and how to measure it, and weobsess over that stuff.
Speaker 2 (22:48):
That's a great way to think about it, matt, you
mentioned a couple of times thatthe easiest way to grow is
growing average deal size.
I know you mentioned you did itby 10% at New Relic and you've
referenced it a couple of timeswith Bounty.
How does one grow average dealsize other than the simple
answer of raise prices?
Speaker 4 (23:05):
Well.
So it's not raising price, it'sgrowing customer spend by
having a pricing model thatincrementally increases based on
the value you're getting right,so it's close them quick.
Acquisition so the way that Ibuild sales teams is there's an
acquisition team that transactsquick and that first transaction
should be easily digestible,right, you could go into a
(23:28):
starter pack and then you go toa pro pack and like it's all
pricing and packaging and thosebecome like sort of paid leads,
you know, paid trials for theteam.
Then the team will upgradethose based on the units that
you're selling.
So just in like one product,like you can do that.
And then, at the right time, youthink about what the adjacent
(23:49):
offerings are going to be andthen you're selling a platform.
Right, and you got to do thatin sequence, it can't be all at
once.
And that's another mistake I'veseen people make is oh, we got
our next product already, let'sgo build it.
But no, let's make sure thatour first product is honed in,
differentiated and we're winningthere and we know that we can
(24:09):
sustain customer, we can growcustomer and we can convert
prospects.
Let's do that first Strongproduct, market fit and
differentiation.
Then it's the way that I thinkabout it is it's almost like you
have an incubator on the sidethat's thinking about a year
from now right, and it's like aseparate team, maybe as a GM.
And it's thinking about a yearfrom now Right, and it's like a
separate team, maybe as a GM,and it's thinking about our
(24:31):
second product, and so by thetime, we need our second
products there right, but thecore company is focused on what
we do today, because when peopletry to do two things at once,
it's it all falls apart, right,they don't know what to do, and
so siloing that in a way isreally important.
But thinking about what do weneed a year, year and a half
from now to continue and sustainthe growth or accelerate, is
(24:55):
super important.
So it is upselling the currentproduct and it is adding new
products to the platform.
Speaker 1 (25:01):
Yeah, go ahead.
Sorry, one quick thing I wasgoing to add that this
highlights right, and you'reprobably seeing this, it's just
the rise of usage-based billingmodels.
Now, right, like just metering,and you're just seeing that
happen more across the board.
Because once you have meteringin place, that gives you
fine-grained control, refinement, understanding, and then that
(25:23):
becomes a really important andpowerful lever that allows you
to play around with the outcomebeing average deal size, right,
but you can actually start doingall sorts of creative uh things
when you have something likethat in place, right?
Speaker 2 (25:35):
yeah, that's a great point, because there's a lot of
companies, particularly on theuh, the ai side, that are using
tokens, because obviously weneed a certain amount of tokens
to generate ai responses, and sothat that, for example, is what
you'd be referring to whenyou're talking about usage, or
just one example.
Speaker 1 (25:50):
Yeah, exactly.
So tokens is an example, right,but what it allows you to do is
to really tie mentally in thebuyer's mind, psychologically,
like the, to the value that I'mgetting out of this tool, right?
So if I'm using it more, I'mgoing to pay more, but I'm
getting more value out of it.
That is hard to do, for example, in a seat-based pricing,
(26:10):
because you're like, oh, a seat,and then the seat has, like,
all these different things andI'm using two out of these 10
features, but I'm paying for all10 of them, right?
So that's what something likethis, you know, like you said,
token-based or usage-based, justhaving the ability to meter
gives you that ability to havemore flexibility on your deal
sizes.
Speaker 4 (26:29):
Yeah, I would agree with that.
I think I'll be provocativehere for a second.
But the seat-based pricing iskind of dying, right, it does
become shelfware at some point.
Right, and I totally agree withAsha, you're using two things
out of 10 things.
Is cost and value in lineanymore?
And like a platform, there'stwo types of customers, right,
(26:52):
some customers wantpredictability in what they're
spending every month, which isjust a flat rate, and then
there's some customers, likedepending on, like the company
size, really that want controlover the usage, right, so
there's a platform fee that'slower and then it's usage-based
and then at some point they useso much that they want to raise
(27:14):
the platform.
So it just becomes this likeoverage opportunity to continue
to upsell.
Speaker 2 (27:19):
And how do you approach that from a pricing
perspective at Bounty so today,we just have a platform fee,
right.
Speaker 4 (27:26):
We are moving in the direction of having multiple
ways of exporting, like anoutput from the core product
that we have today and alsoallowing people to import.
So you can either pay a flatfee or you can use tokens to
import more information orexport information in multiple
(27:48):
ways.
So that's a different modelthat we're looking at right now.
Speaker 1 (27:53):
Yeah, and the thing that is there today is that, you
know, instead of focusing onseats, we've moved the unit of
value around accounts orcompanies.
Essentially is what it is,which is again kind of step zero
or step one before you moveinto a more refined usage based
type of token oriented modelRight.
Speaker 2 (28:12):
Yeah, so I actually got into your guys' product last
night and signed up for thetrial and I was playing around
with it so I could have an ideaof what we were talking about.
What do you think of it?
I liked it.
I liked it it was, and itactually created a kind of a
couple of additional questions.
I think the automated researchportion of it works very well
and I love the different buyerpersonas, for and I, you know, I
(28:34):
gave it the folks that Itypically sell into, like for my
recruiting business, forexample, and the copy was good,
the ICPs were good.
But I did have a question injust the context of and I think
(28:54):
you've sort of alluded to thisin that I think this is more of
the beginning and obviouslyyou're going to continue to
expand.
But there's no, it really wasand correct me if I'm wrong,
maybe and this is just in thetrial, but it's like you can
send directly from the platformor like copy paste into a like
an engagement tool?
Speaker 1 (29:14):
is that generally correct?
Yeah, yeah, you're talkingabout the.
I'm assuming you're referringto integrations like having yeah
, yep, yep, yeah.
So that's exactly right andthat's intentional.
You know um, where we wanted tohave a limited trial experience,
where and if you think aboutour icp right, like um, which is
we're hyper-focused on earlystage, founder-led sales type
teams like that are just muchsmaller.
You know, for those folks,number one budget is tight.
(29:38):
So we know that, hey, it'sunlikely you're going to have
some kind of a sequencing tool.
It's going to be very limitedand you know we don't want to.
We want to be in a price pointwhere you can get all of this
value around research and data.
You know the contact databaseand messaging and all that kind
of stuff, uh, that you wouldhave to put together um at like
a pretty reasonable price pointand then if you are a bigger
(30:02):
team that has integrations, then, like, let's talk, like you
talk, to sales and then we canenable those integrations for
you.
Uh, the other piece that youdon't you can, you may or may
not have experience in yourtrial is but there is a human
API, human as an API elementbehind this, which is that you
know, most of the research isautomated, but if there are
(30:22):
things that are really hard forus to find, that the AI finds
hard to find, then it getskicked off to a human workflow
that will go and augment it, butto you it would be pretty
invisible, right, and that ispretty.
I would say just an approach ingeneral across AI that I think
you'll see more adoption of likehey, how are we, when we're
providing a service, how do wecombine both the AI, because AI
(30:45):
is not going to be enough.
You know this right, it's justwho wants to have the headache.
Is it you, reese?
Or is it like do I want to handthat headache off to someone
else?
So it's like, okay, I'd ratherhand it off to someone else to
deal with, and so that's kind ofcore to that experience.
Speaker 2 (30:59):
Okay, got it.
And so you've emphasized and Ido worry here a little bit that
I mentioned my own experiencewith the trial, but I don't
think it was really expanded onon really what the core product
of bounty does.
So maybe we could rewind alittle bit and one of you could
explain that just for thelisteners.
Speaker 1 (31:14):
Yeah.
So for the listeners it wouldbe that you are hiring a quote
unquote a bounty AI teammateexperience to help you outbound
prospect and what that meansspecifically.
If you think about prospectingand break it up into different
stages or tasks, it is having alist of companies researching
what's going on in thosecompanies, what are the key
(31:34):
events that I can reach out topeople for to tell them here's
how I can help you so, doing theresearch on the company,
finding the right personas basedon the product that you sell,
the capabilities and the usecases that you solve.
For Now, typically, if youthink about how long it takes a
human to do that about, and theoutput of all of that is some
kind of personalized messagethat you can either put in the
(31:56):
form of a PDF or an email orwhatever it is Like.
We're not explicitly in theemail business, but let's just
say you have a message thatyou've personalized Now that you
can choose to either send itout on your own or you can say,
hey, bounty, I want you to sendit out.
Sequence it on my behalf, right, and that's the outcome as a
service.
But essentially that wholeworkflow, if you think about it,
for one personalized messagecan take you know anywhere
(32:18):
between 60 to 90 minutes in abest case scenario, right
Whereas you get it within.
You know if you've tried it inthe trial experience you've got
a message ready to go withinless than five minutes.
So that's a pretty hugeproductivity gain that you get.
So that's what Bounty does todayfor you is really focusing on
outbound prospecting in twoforms.
(32:39):
One is you can use it on yourown, but you are responsible for
sequencing and doing the workand putting it into the
different tools and then promptengineering and keeping it up to
date.
That's on you.
If you buy our startup service,then you can say like hey, I am
an early stage founder, earlystage company that doesn't
really have the resources, but Ineed to build pipeline, I need
(33:00):
to build warm leads, I need tonurture them.
I want to hand it off to Bounty.
That's the second part of ourservice, which is like hand it
to us and we will run all ofthat for you, that whole
workflow for you, butspecifically today focused on
outbound prospecting using bothAI and humans.
Speaker 2 (33:14):
Yeah, does that give you a?
Speaker 1 (33:15):
little bit more clarity.
Speaker 2 (33:16):
That does.
Speaker 4 (33:17):
Super helpful, I'll add.
My experience in this BDR hasbecome this get up in the
morning, blast out 300 emails,hope for meetings because
incentives are off right.
Bdrs get compensated onmeetings and sales reps get
compensated on pipeline.
And then a gift card on top ofit, right Like now, you're
(33:37):
giving T-shirts and gift cards.
It's just like losingproposition today and then like
the world has changed right.
So you have really bright folksare graduating from college but
they're working from home forthe most part and they're asked
to do the most strategicoutreach in the company.
So you know.
Then you know they do all ofthis work.
They can't get it done at scale.
(33:58):
They've never done it before.
They don't know how to go outand, you know, tie their
solution to create a pitch tothe company.
They're trying to contact atthe buyer persona what that
person cares about.
That would take them all day toget three out that were good,
like even average, to be honest,and so they can't do it at
scale.
So it's become this mass emailthing.
It's this mass email and giftcard and get meetings and hope
(34:20):
and pray that people are showingup for value and not the gift
card.
And that's the world that welive in today.
And the other aspect of this,like what we've seen it was
unintended to be honest with youat first is we're creating
better salespeople.
We are literally telling you,we're showing you, how to do it
(34:44):
right.
The product does it, and thenyou read through it.
You understand what the valuedrivers are, the buyer persona
you're trying to sell to.
You understand how yoursolution ties to business and
public business objectives ofthe company you're trying to
sell to.
We're creating bettersalespeople, we're training and
enabling people and we're alsohelping them get out.
Like Asha said, the email andthe output is just like a
(35:04):
feature of what we do.
Just like a feature of what wedo, but it is this hub of
knowledge that can train peopleand also be manipulated in a way
that you can export it formultiple things in the future,
not just an email.
It can be a lot more than that.
Speaker 2 (35:20):
Yeah, you're not going to get any argument from
me that the role of the BDR haschanged, and I think
particularly you're right withthe work from home when you're
at that more junior level.
There's so much you learn justfrom osmosis and by sitting by
more senior salespeople and ifyou don't get to do that then it
kneecaps your growth At thesame time.
Is there also just to be alittle bit contrarian is there
(35:42):
also an argument that doing someof that work and doing some of
that struggle and maybe takingall day to send those three
meals is that a necessary partof learning and training and
growth is kind of figuring itout on your own, or not?
Is it more helpful just to say,hey, here's the right answer,
and then you learn by eventuallylooking at enough of the right
answers that this is how youshould do your customization?
Speaker 4 (36:05):
Yeah, well, it depends on how you trade off
enablement versus revenue, right?
So if the idea is that you'reenabling and training BDRs now,
then meetings are going tosuffer and pipelines are going
to suffer, right?
So I hear that, right.
So maybe it's like the firsttwo weeks of training you go
through that and do that.
But, um, if that's the purposeof it, I think every company is
(36:30):
going to trade off more pipeline, more meetings, for enablement
do we need bdrs with a tool likebounty?
you know what?
What?
I think there's two scenariosthat we see, right.
There's the early, early stagefounder-led sales who is
considering hiring a BDR thatmaybe doesn't, or maybe hires
one and then hires Bounty.
(36:50):
Then there is the more maturecompany that has 20, 30 BDRs.
We're not trying to replacethem, right, we want to help.
And it's almost like the oneperson's trash is another
person's treasure.
Right, if you can elevate a BDRto do more work, that's closer
to the customer, guess what?
The sales rep gets to move up,too, right.
(37:13):
And then everybody moves up.
And this is the problem that Isee today is there's too much
talking about calling andprepping to call a customer and
not enough calling the customer.
And if we can solve for that,this is why salespeople get into
sales.
They don't get into salesbecause they need to log
Salesforce tasks all day andhave forecast calls and do
(37:34):
prospecting.
No, they want to be on phonecalls.
That's why they're here.
They're social people, right.
And it's a declining thingright now where there's more
work in the day than there isactually doing the work.
Doing the work of talking tothe customer, prepping for the
call, has become the predominantuse of their time.
Speaker 1 (37:56):
You know sales is all about.
You know, if you think aboutyour superpower as a human being
versus AI, right, it is how youuse social intelligence and
judgment to manage complexproblems.
Right, that's really what itcomes down to and that is
something you know, what we'rereally really intentional about.
(38:19):
Because with AI, any kind of AI, right, it's all about, it's
what it is and it's a reflectionof what you put in.
You put in garbage, you getgarbage.
You put in good, you get good.
You put in bad, you get bad.
So we took a stance to say, likewe are going to inject good,
good behaviors, good outcomes,and we're going to get that
right.
That really means is when wethink about, in the context of a
BDR is like, hey, bdr, like youknow, this research, like Matt
(38:47):
said, like don't spend the timeprepping, spend the time in
figuring out what is theappropriate social engagement
and interaction that's going toget this person to have a
conversation with you about thepain and the problem that
they're facing right now,because after that, guess what?
You actually have to actuallyhelp them solve the problem,
which is okay.
So that requires you to learn,have the time, the mental
bandwidth, the emotionalbandwidth to go pick up new, new
skills, new technology.
(39:07):
So I almost see, you know, theBDRs becoming more what we call
AEs, for example.
But I think I would take it onestep further, which is that I
almost at a go to market levelit is.
You know, imagine a world inwhich the go-to-market folks are
becoming extremely, extremelyclose to the product.
They're shifting closer andcloser to the product, to how it
(39:28):
gets built and just picking upskills along the way and new
sort of neural connectionsforming, so that I think being
really super intentional aboutthat is really important, having
a viewpoint on it is reallyimportant.
But yeah, like you know, Icompletely, 100% agree with what
Matt is saying.
It's like it's just thatamplify the social intelligence
and complex problem solving.
That is the important piece,versus like, oh, we're going to
(39:49):
replace BDRs because it's like,well, replace them with what you
know.
That's the open question.
Speaker 4 (39:56):
Well, there are.
What we're doing is replacingthe title BDR and, like the
first entry level is juniorsales.
That's what it should be.
If junior sales can be doingthe demos, then sales folks can
be working on managing theirpipeline and being in front of
customers.
So that's the whole aspect ofmoving everybody up closer to
(40:17):
the customer.
And there's a reason why everycompany plans for a decline in
productivity every year, becausea lot of companies are throwing
headcount at growth and thenthe demand, right, the lead
generation has spread more thinright.
So every year you plan for adecline of 10%.
So you can make a number thatyou can report growth.
(40:37):
But you can also report hittingyour goal.
And the number of folks thatare making quota today has
declined right.
Like at New Relic, weintentionally set a goal.
We had this thing called themorale tax right, and Mark
Shackleben and I would work onit.
Mark's the CFO there now he wasthe COO.
When I was there We'd say look,you know what?
We're going to carve out amillion dollars for the year and
(41:00):
we're going to set quotas wherethey're attainable and 70% of
the team 75% of the team isgoing to make their number.
Well, guess what you just did.
You just improved moraleimplicitly.
And then you also recruitingbecomes easier because
everybody's making their number.
Culture is awesome and themillion dollars is now just like
(41:23):
become $3 million in soft costsacross the board.
People don't leave, people arehappy, people wanna work there.
We don't have to recruit, it'sall inbound right.
That is the thing.
People aren't like chasingquota the entire time.
Because what happens when youallow somebody to see beyond the
line of quota?
They work harder.
You actually get more out ofthem.
When they are have no chance ofmaking their quota.
(41:45):
Guess what they do?
They look for another job andthey sink and they, they, they
honestly poison the culture.
So it's just such an easy thingto think about.
Like combining that like thattype of thinking.
You can, you can augment thatwith bounty, like, like.
That is something that likewill make it easier.
So you don't have to have thatmorale tax.
You already have it built in.
Speaker 2 (42:08):
Right.
So from a consumer perspectiveI don't know if you'd seen this,
but Mark Mark Kosaglo, who isthe first employee outreach and
he scaled it up to 200 plus inrevenue he recently founded a
company called Operator which,as of this recording, they
haven't released their productyet, so not a hundred percent
sure what it is.
But the problem that has beendescribed is that contact
(42:30):
commoditization and AI outreachhas done damage to Outbound
because it's like when everyone,when everything is personalized
, it's no longer special.
How do you respond to that?
What are your thoughts?
Speaker 1 (42:43):
um, I think I think there's truth to that, right
like it's at some point it's.
Imagine a world where it's likebots talking to bots, right,
it's like that.
That's kind of.
I think the way that I see, um,this playing out is like okay,
so in that world where you'vegot bots that are generated and
it's like you can't really tellthe difference, you're starting
(43:04):
to like tune out channels, right, like email, like email is
already pretty tuned out forcold.
I would say.
You know, linkedin is becomingextremely, extremely crowded
with a lot of this stuff.
So people are starting to tune,starting to tune that out.
And I think the emphasis andimportance which I think is
we're talking about the problemis like OK, how do you actually
stand out, you know, how do youactually?
And the way again that I see itis like it's not going to be
(43:27):
just a standalone AI solution,that's just it's.
I don't.
I don't see a world where thathappens, where it's a standalone
AI solution.
I think the opportunity thereis like OK, how do you again
bring really bring forth thehuman in the loop element as
part of that consumer experience?
Now, right, where you're justlike, and, by the way, you know,
(43:47):
maybe there's a world wherepeople just get so attuned and
attached to that, with peoplebeing remote and post COVID,
where they're like I never wantto talk to a human and I just
love the fact that I'm talkingto a bot all the time.
I don't know, I could be wrong,but I think there's definitely.
I think there's going to bestarvation for human online
(44:08):
connection in in like sort of mypurchasing experience.
That, um, I think you have tofigure out.
We have to, collectively, allof the AI companies that are in
this space have to figure outlike, how do you bring that
forward, how do you bring thatto light, and so for that you've
got to have the right people,infrastructure, the right skills
you know in within your company, within your product, that you,
you know, are able to bringthat to light.
So that's that's how I wouldrespond to it, which would be
like, yeah, I agree, likecontact, monetization and AI
(44:29):
like has wreaked havoc andpeople have started to tune out,
but I think it's also createdan opportunity, which is like
okay, here's how we can bubbleup through the noise If you can
really figure out where is theright place to put the human in
that interaction.
Speaker 4 (44:42):
Yeah, we're seeing that.
First of all, I think humansare important very still, and I
think AI will not stand on itsown in this space for quite some
time unless a lot of thingschange.
Because there's got to be ajudgment call on the content,
right?
Someone has to make a judgmentcall, otherwise you just sound
like you're talking to a bot,right, and it's just as bad as a
(45:05):
generic email.
So the last 5%, we'll get you95% of the way there, and we
have our team that's tweakingbehind the scenes that's human
in the loop.
The sales reps and BDRs justhave to make judgment calls on
whether that is the rightmessage to send.
That's where I think we aretoday, is humans still make the
(45:29):
judgment on what goes out andwhat doesn't, but they don't
have to do all the heavy lifting.
Speaker 2 (45:35):
Yeah, because there's another company that just
recently raised a fairlysimilarly sized seed round that
is a fully AI BDR, as far as I'maware.
I haven't tried the product,but there's no human in the loop
, and my hesitancy about that isessentially what you just
described.
Do you think there will be apoint where a technology like
(45:55):
that is feasible, or do we thinkthere will always be a human in
the loop?
Speaker 1 (45:59):
I think it'll be, it's feasible from a like bill.
Can we build it?
And will people buy?
Probably, like you'll see thisspike, we'll see this like oh, I
want to try it, I want to seewhat it's like.
But I think, as we've seen witha lot of ai technologies that
launched in the last three tofour years, is that there's this
very extreme spike ofexcitement and interest and then
(46:19):
also an equally sort of uh ofdownward spiral in terms of
disillusionment that people feel.
So let's just say the example.
I don't know if you guys everwatched that movie I think it
was called Her with JoaquinPhoenix.
I've seen parts of it, right,but there's this really deep
emotional connection that youform with the AI, but then you
(46:40):
realize that there's like 10,000people that are also forming
the same kind of emotionalconnection and I just I just
kind of like I think that youknow, having a world where you
have people that are interactingthat way with AI is pretty
close to reality in my personalopinion.
And you know but would I be you?
(47:00):
You know there's got to besomething deeper, like there's
always.
That's like almost like step,stage zero in your sales process
.
Okay, I'm done with stage.
I booked a meeting.
Now, what right like?
So there's all this opportunityahead of like.
Okay, where is that deeperconnection that comes from
physical touch, that comes fromthe three of us?
Looking at each other's faces,you know, reading each's
expressions, making rapid,instant in time decisions around
(47:24):
oh, do I want to buy Reese'sproduct or not?
Or like, is he convincing me?
What's his tone of voice?
You know, that thing I feellike is is really going to be
hard to replicate and I feellike that is, you know, even
though it's going to be like yousaid, it's feasible and it will
be done and people will do it,even though it's going to be
like you said, it's feasible andit will be done and people will
(47:44):
do it.
But I think there's going to bea really, really high premium
on this.
What's happening right now.
Speaker 4 (47:49):
Really really high premium on that it's a long road
, in my opinion.
Based on your average deal size, either, the product can sell
itself, right.
Low price point, transactional.
I don't see AI selling 25,000plus average deal sizes.
I don't think people are goingto buy that way.
(48:09):
I do agree with ushers there'sa degree of trust when you're
spending a certain amount ofmoney.
You want to look somebody inthe eye, you want to hear their
voice, their tone, their bodylanguage.
You have to trust them, right?
Eye contact is a big thing,right, and it's I don't know.
You know, I just don't.
(48:30):
I think it's a long road tothat point that I don't see it's
just again, it's like peoplebuy from people or people will
buy from your product experience.
But it depends on the pricepoint, right?
Speaker 2 (48:39):
Yeah, dan from Stage 2 had mentioned that a few weeks
ago when he was on here.
Basically, the similar thoughtwas that, yeah, for PLG small
deal size stuff you can probablyget away with AI, but no one's
buying.
I mean you said 25.
I think he said a million.
Nobody's spending a milliondollars on an enterprise deal
without talking to severalhumans much less.
Speaker 4 (48:58):
One, nobody's spending 25,000.
To several humans, much lessone.
Nobody's spending $25,000.
I mean, it's a lower bar thanthat.
Right Like a million isoutrageous to think about, right
, unless they're two guystalking to each other.
Speaker 2 (49:11):
Never know.
So when we think about what thestructure of go-to-market teams
looks like in the future, youmentioned a little bit on the
sales side that you thinkeveryone will more or less
ratchet up a step and have themore junior folks doing the
demos and the more senior folksmanaging the pipeline.
How do you see that changing,if at all?
On the post-sales and customersuccess side, Ashi, you want to
(49:33):
touch on?
Speaker 1 (49:34):
Yeah, yeah, no, I think this is an ongoing debate
around this, right, and there'sa few ways to look at it.
There was a point in time inour life, at Bounty, where we
were like, oh, imagine a worldwhere you could just you
literally think about AIteammates as actual teammates,
right?
So you're thinking about it interms of you know, you've got a
(49:55):
CFO that's looking at headcount,building out a model, and then,
like you have a spreadsheetthat has like reese, um and matt
and usher, and then it's likeai teammate bob and ai teammate
karen, or whatever it is right.
Um, so I think it's it's it'sfanciful and romantic that
things think about things thatway, and maybe there's some
reality which is like, okay, I'mgoing to design my sales team
(50:18):
and I'm going to have, you know,three ai bdrs and two junior
sales reps and like four AEs andyou know an SE and stuff like
that.
So there's like one world thatcould possibly emerge that looks
a lot like that, just dependingon how buying patterns emerge.
I think the other world is justlike everything AI co-pilot,
like it's like, ok, you know,everybody gets an Ironman suit.
(50:39):
It's like, okay, everybody getsan Ironman suit.
Okay, everybody is Tony Starkon the team and everybody gets
an Ironman suit, which is thisAI co-pilot in post-sales,
pre-sales, whatever it is, andthat's a much more sort of
blended way of looking at AI andhow it plays.
And maybe in some places youwill see the Jarvis, the AI,
doing a lot more work on yourbehalf, which is on the BDR
(51:00):
prospecting side, and you'rejust kind of like sitting in the
suit.
And then on the AESC solutionengineering side, it's more like
, hey, tony Stark is doing mostof the work and the fighting,
but you've still got the AIthat's augmenting me in a bunch
of different places, likesolutions engineering is, I
think, is a really interestingone.
I was talking to my friend aboutthat use case yesterday, which
is, you know, that's whereyou're really looking at a
complex landscape, but youreally want to get information
(51:21):
about people's systems quicklyso that you can come up with a
reference architecture anddeploy it.
So you know that's a much moreblended AI model.
So that's how I see.
You know, those are the kind oftwo world views that I think we
are starting to look at and howsome of this stuff evolves over
time.
So yeah, we'll see, you knowit's hard to tell.
Speaker 4 (51:42):
I would take that.
If I want to step down to moretactical explanation, then Dosh
was very good at doing the highlevel.
But tactically, if you thinkabout enabling reps and DDRs to
be better with our platform butalso creating high quality value
meetings, the laws of averagetrickle down.
There's people coming to ameeting because they are
(52:05):
interested instead of getting agift card Handing over to the
sales team on the pipeline, amuch more highly qualified
opportunity.
Again, the laws of average istoday salespeople are
discounting by 40% to just get adeal done at the end of the
quarter because cost and valuearen't in line, because it
starts with the meeting they hadand it's like all right, well,
(52:26):
I'll buy it, but I'm going to doit month to month.
So they're selling month tomonth deals or 90-day outs and
they are discounting at 40% andso cost and value is already
misaligned and then handing itover to CS and CS ends up just
(52:47):
chasing cancellations instead ofmaintaining like solid
relationships, like that wholething is broken.
The whole customer journey isentirely broken and that's why
again I go back to whyproductivity is declining.
The more people you add, themore problems you get.
Like this problem gets biggerand bigger.
And so if you're discounting at40% to get a deal done on
average, well, what if you werejust discounting at 10%, cause
those opportunities were muchmore highly qualified?
Would you need to lowerproductivity every year?
(53:08):
Probably not.
That's a great point Superinteresting.
Speaker 2 (53:15):
Well guys, this has been awesome.
If someone wants to check outbounty or do a demo, what's the
what's the best way to do that?
Speaker 1 (53:21):
If someone wants to check out Bounty or do a demo,
what's the best?
Speaker 4 (53:24):
way to do that.
Go to our website.
Bountyai Watch your cell phone.
Yeah, just get a watch yourcell phone number.
Speaker 2 (53:26):
Publish it in the show notes, Cool guys.
Don't call me Awesome.
Thank you so much, reallyappreciate you coming on.
Speaker 3 (53:35):
Thanks for listening to See to Exit.
If you enjoyed the episode,don't forget to subscribe and
we'll see you next time.
Number one was, as we were building this really
AI-first technology in adifferent space for a different
audience, developers andautomating like sort of the
human aspect of incidentmanagement using AI.
And then me having being afirst-time founder trying
founder-led sales, I was likeman, there's just so much in
go-to-market, just generallythat could be done in a similar
(00:22):
model with, like you know so, ai.
So that was kind of the veryearliest inspiration of starting
Bounty was to take a lot ofthose experiences and learnings
from a very different domain,different type of buyer,
different sort of problem space,and applying it in the world of
go-to-market.
Speaker 2 (00:40):
Thanks for listening to Seed to Exit.
As always, I'm your host, rhysKeck, and today I'm joined by
two exceptional entrepreneurswho have combined their
strengths to build somethingextraordinary.
First we have Ash Arrisky.
He's a serial entrepreneur whohas previously founded YC-backed
Blameless after leadingengineering teams at MuleSoft
and Box, and he's partnered withMatt Cooley, who is one of
Silicon Valley's mostaccomplished sales leaders
(01:05):
Valley's most accomplished salesleaders.
Matt's impressive careerincludes leading New Relic to a
multi-billion dollar IPO andQuip to a $750 million
acquisition by Salesforce.
Together, they've joined forcesto found Bounty AI and they're
combining Ashar's technicalinnovation and values-driven
leadership with Matt's provenabilities to scale companies.
I absolutely loved recordingthis episode.
We cover so many go-to-markettopics and each of these guys
drop some incredible wisdom.
I hope you enjoy it as much asI did.
Speaker 3 (01:30):
You're listening to the Seed to Exit podcast with
your host, rhys Keck.
Here you'll learn from startupexecutives, founders, investors
and industry experts.
You'll learn from the bestabout building amazing products,
scaling companies, raisingcapital, hiring the right people
and more.
Subscribe and listen in for newepisodes and enjoy the show.
Speaker 2 (01:54):
All right, usher and Matt welcome on.
Excited to have you guys.
Speaker 4 (01:56):
Thanks for having us Nice to be here.
Speaker 2 (01:59):
So, as I shared with you guys and so for the
listeners, this is a firsthaving two folks on the podcast
at once.
So I appreciate you guys beingmy guinea pigs, but definitely
excited for the upcomingconversation that we have here.
So, just to start things off,for anyone who's not familiar
with Bounty Usher, maybe if youwouldn't give us a quick
overview, yeah, sure, thanksagain for having us, rhys.
Speaker 1 (02:22):
A quick overview on Bounty we are basically a
platform that's using AI todeliver go-to-market outcomes as
a service, specifically aroundoutbound prospecting, inbound
personalization and so on, soyou can think of us eventually
in the future covering the fullbuyer's funnel and lifecycle
(02:42):
journey.
And what you're getting whenyou buy Bounty is both a AI
experience combined with a humanexperience.
Gotcha.
Speaker 2 (02:48):
Okay, maybe this is my ignorance, maybe this is a
term you made up, but what isoutcome as a service, because
I've not heard that before it isa pretty much made up term that
.
Speaker 1 (02:57):
I'm trying to market and get everybody else to think
about.
But in the simplest way, if youthink about just within sales
and marketing and customersuccess, do you care more about
revenue or do you care moreabout sales activity, right?
So the outcome is that, hey,are we booking meetings, are we
generating pipeline?
Are we generating revenue justwithin the domain of sales, so
(03:20):
all of those sort of leadingindicators.
And so when I say outcome as aservice, you know, imagine if
you could buy a piece ofsoftware or a service that
basically delivers on thatparticular outcome.
So that's the attempt atcalling it outcome as a service,
definitely more market-y madeup term.
And so but yes, that's what itwould be Cool All right, I love
(03:41):
it.
Speaker 2 (03:42):
So just in terms of the history of the company, so I
know that it was foundedapproximately three years ago
and you two were co-founders,but Matt, I know you came on a
little bit later.
So, usher, where did the ideafor the business come from?
And then, how did you and Mattmeet and have him decide to come
on as a later co-founder?
Speaker 1 (03:59):
Yeah, A lot of skeletons in the closet.
You're going to make me bringthose out, but no, no, just
totally kidding.
So just my quick backgroundvery, very quickly immigrant
founder, been in SaaS for thelast 15 years, worked at
companies like Boxcom andMuleSoft.
Started my first company calledBlameless, which was really in
(04:19):
the DevOps developer toolingspace, automating incident
management for SaaS softwareteams, right, and so it was also
venture-backed.
Recently exited.
I left before the exit happenedand started Bounty.
So my experience, a lot of whatthe story behind starting Bounty
(04:40):
was very, very heavilyinfluenced and colored by that
first experience of starting myfirst company as a first-time
founder and CEO.
So number one was, as we werebuilding this really AI-first
technology in a different spacefor a different audience,
developers and automating thehuman aspect of incident
management using AI.
(05:00):
And then me being a first-timefounder, trying founder-led
sales, I was like man, there'sjust so much in go-to-market
just generally that could bedone in a similar model with,
like you know so, AI.
So that was kind of the veryearliest inspiration of starting
Bounty was to take a lot ofthose experiences, learning from
a very different domain,different type of buyer,
(05:21):
different sort of problem space,and applying it in the world of
go-to-market I was justgenuinely.
The thing that I really reallyloved about the go-to-market
space is that when you'reselling to developers I love
developers too but there'sdefinitely a little bit of a
chip on your shoulder where it'slike, oh, I can build that, I
can do that, Whereas there'smuch more appreciation and
(05:42):
gratitude that you feel whenyou're selling to folks that
aren't equipped with those sortof the software development
skill set Right, it's like Ican't go build this myself.
So, wow, I'm so grateful.
So I just really love the buyer.
I love you know working withthat.
You know those kinds of folks Imet, Matt, you know, when
obviously I don't have the go tomarket domain expertise, you
(06:03):
know when obviously I don't havethe go to market domain
expertise, and so that wascritical when you're starting a
company, and so one of the waysthat the early, early strategies
at Bounty was to say, CMOs,chief, you know, customer
(06:24):
officers, and so just coveringthat full spectrum so that we
could kind of build this brain,this knowledge brain that could,
where we could sort ofproductizing ideas that are
coming out of those discussions.
And obviously Matt, you know,just given his experience, was
part of that early journey.
I met him through his brother,TJ, who was also, you know, a
good, a good, close friend, andMatt and I got to know each
(06:47):
other, became, you know, reallyreally good friends throughout
that journey.
And you know, it's like what Ilearned from my first experience
is like, you know, on one hand,you don't want to be starting
companies with like real, likefriends you've known since
childhood, right, Because you'llprobably end up killing each
other, and then, on the otherhand, you don't want to start
companies with like completestrangers.
(07:07):
So with Matt, like it was just amix of great chemistry, just
like really aligned in the waywe think about things, just
really complimentary experiencesand the way that we it's like
literally two sides of a brainin the way that we approach
problems, but we always end uplanding on the same kind of uh
place where we want to be.
So that was kind of like areally strong foundation to
(07:29):
restart a friendship.
And then, um, obviously, likejust his experience is just
phenomenal and what we're ableto turn into a product and then,
you know, turn into a bigcompany.
So that's how we, just veryearly, how we met um, how Matt,
you know, uh, you know, joinedthe company like as a late
co-founder, but it's just beenan amazing, incredible journey
(07:50):
ever since then.
Speaker 2 (07:51):
I love that.
So, matt, how has therelationship or partnership
evolved since starting andcoming on board with Bounty?
What would you say you two havelearned from each other?
Speaker 4 (07:59):
Yeah, so I invested like almost four years ago and
always been advising, and one ofthe things I love about us like
we became fast friends.
Normally I have a period like aspecific amount of time that I
can spend with the companies Iadvise for, but I found myself
like calling us on the weekendand we have just again.
(08:20):
We grew up in very similar waysin some aspects and the synergy
between the two of us isthere's no ego, because there is
a lot of focus around what hedoes and what he's great at and
what I do and what I'm great at,and there's a lot of trust
there.
But there's a ton ofcommunication around it too.
I think we talk two or threetimes a day, which is great
(08:46):
around it too.
I think we talked two or threetimes a day, which is great.
So, yeah, so that just continuedfor three and a half years or
so and I was available at thetime.
I loved what they were doingand decided to join as
co-founder right, and so, yeah,it's been an awesome ride and
the things that I've learnedfrom Usher like I've always
wanted to know more aboutproduct and engineering and you
(09:10):
know I sit in on those meetingsand, you know, at some point
maybe I want to be a CEO, whoknows?
But understanding the entirebusiness helps me be more
effective in my role, and Usherhas been very good about
informing me, and spending timewith the team has been helpful.
Speaker 2 (09:27):
Love that.
So, matt, you've obviously hadsome phenomenal experience in
go-to-market in both startupsand well-known companies, and,
of course, one of your biggestaccomplishments is you were able
to scale New Relic from zero orclose to zero to ultimately
through exit, and this couldprobably be the subject of its
own podcast by itself.
Unfortunately, we don't havethat much time, but can you talk
(09:49):
me through what that processwas like, how you scaled it at
different stages?
Speaker 4 (09:53):
Yeah, so when I joined New Relic, the founding
team had come from Wiley, whichwas on-premise technology
sales-led, and I came fromCitrix, online, which is really
go to meeting.
That'll date me a little bit,but it was very much inbound and
velocity type sales small,small transactions, but a number
of them.
(10:14):
So it was much more operationalin way that you know, I wasn't
a sales leader that was gettingon a plane and going and having
this good dinner, right.
It was all about like thefunnel and obsessing over the
funnel and making tweaks wherewe needed to, and like little,
small things like increasingyour average deal size by 10% at
scale made a really bigdifference, right, and that was
(10:36):
my first job.
I ended up leaving thererunning global commercial sales.
I took a 30,.
I was 30 years old and honestlyterrified.
I moved to Cisco and I've gotthis group of Dartmouth grads
that have done it before, thatare, you know, 10 years older
than me, and but they brought mein because I knew the product
(10:57):
led like.
However, the nice thing aboutNew Relic was I had great
mentors that would allow me tooperate in what I knew, but I
couldn't articulate well, right,and so they'd allow me to go,
make mistakes right and learn,and it just never made them
twice.
Right, I'd sit down with MarkSaclaban or Lou Cerny and you
(11:22):
know I deviated or made amistake, but I understood why.
I wrote it down and then thenext week I came back and
articulated it, and so the partof it was having great mentors
but also worked really hard.
Right, this was my firstopportunity at like a huge
success, right, and you know Ididn't have a lot of equity or
(11:44):
anything like that at CitrixOnline, so it was an opportunity
for me to create some, you know, outside opportunities for my
family as well, and, honestly, Iwas just so passionate about
the team I worked with and eventhough it was a totally
different technology, the modeldoesn't change so much.
(12:05):
Like you do have to adapt towhat the sales model is, but if
the product does a lot of theselling, like, the sales team is
transacting, right, and so youknow what is the sales assist.
Handoff was super important.
There was a lot of foundationalthings that they weren't privy
to, and I came in and there wasa thousand leads a month coming
(12:25):
in.
I had one sales rep and I'mlike Lou, what do I do here?
I don't know where to spend mytime.
And the interesting thing ishow it translates back to why I
invested and brought Lou over toBounty is the original product
was like this insights product.
So when I sat down with Lou andI said, look, we've got a
thousand trials, we have novisibility.
(12:47):
You know Lou will do this likehe'll look this side and be like
okay, and he comes back liketwo days later and he has this
internal CRM that we literallybecame a cheat code over time
and it would show you, you knowhow many servers were deployed,
what the application name was,what the throughput was, and it
would help us identify where toprioritize.
So it helped us run lean.
(13:09):
And so one of the biggestthings that I learned there was
how to optimize technology torun lean.
And when Patrick Moran joined,he was our CMO, our first CMO we
had this rhythm down of saleswas like demand.
It was trailing demand right.
We didn't hire heads to go anddrive sales.
(13:32):
It wasn't sales led.
We had a very strict algorithmfor it.
So every rep we knew that got300 leads in a quarter based on
the average deal size.
But the output would be theirquota right and not for
everybody.
It depends on level of skill,but we had it down and so we
(13:53):
didn't hire until we hadexceeded that amount.
Right, and so it was just likeit was.
It was a lot of it was how torun a business efficiently and
how to think about CAC andlifetime value and how important
those are to your business.
The one thing that I see with alot of the companies that I
(14:15):
advise they are concerned withCAC, right, they don't know the
next move and, especially withfounder led early stage, they're
doing all the selling.
Who's the first person I shouldhire?
How many?
What's the background they need?
And, honestly, if you boil downall the questions that I
normally get when I advise, itall results in how to manage CAC
(14:39):
, because you don't want that toget out of whack over time.
If you don't know what you'redoing, or doing it for the first
time, like in a couple of years, it's hard to come back from it
, right?
So what are the first steps youtake in order to build a
foundation that is conservativebut smart?
Speaker 2 (14:59):
Right, and how should founders be thinking about CAC
in your opinion when it's comingto the subject of early stage
startups, whether you'refounder-led or just starting to
build that GTM motion?
Speaker 4 (15:09):
Yeah, I mean, I think it depends on the stage right.
If you're at seed stage, it'sget as many people using the
platform as possible, right, andhire a couple people, but also
support that with technology,which is what Bounty does, right
.
But also, you know, supportthat with technology, which is
what Bounty does, right.
It is you have to lean into alittle bit of risk to figure out
(15:31):
like do you have product marketfit and beyond seed at A, you
don't necessarily need to havepredictability, like strong
predictability, but you need tohave, you know, customer growth,
like you know eyeballs on thetack right.
It doesn't need to be likenecessarily need to be ARR
growth.
It needs to be some level of achart that goes up into the
(15:54):
right.
Either it can be monetized orit already is monetized, but
usually it's not.
So how do you create some levelof like freemium that you can
monetize later and also showsome level of predictability in
upgrading those by B?
You better know dollar in,dollar out, right, the magic
number is a real thing and intoday's world it can't be sub
(16:20):
1.1, right.
In the growth market you couldmake $0.80 on $1.
1.1, right In the growth market, you could make 80 cents on a
dollar In today's market itbetter be 1.20,.
You know $1.20 on a dollar in.
So it really depends on themarket you're playing in.
But there are basic principlesyou got to be thinking about at
every stage.
But in the beginning there's afoundation that is necessary for
(16:41):
Series B.
If you don't start to operatethat way, you can't come back
from it.
It's really hard to come backfrom it unless you move up
market and then you're makingdecisions based on average deal
size to balance out CAC and themagic number and lifetime value
and companies can get lost inthat.
And so the foundational aspectsof building a business from the
(17:02):
beginning.
There are principles there.
Speaker 1 (17:05):
Yeah, risa, I wanted to just add to what Matt was
saying because it made mereflect back on my experience
with my first company, blameless.
I didn't even know what CACeven means.
Like, what is CAC, what is LTV?
And it's like, oh yeah, we'llworry about it when it's a
(17:27):
problem.
And I think that is the trapthat I think a lot of early
stage founders again it's aproblem, right, and I think that
is, um, the trap that I think alot of early stage founders
again it's a spectrum.
You can.
You don't want to overly obsessat the early stage to be like,
oh, we're going to have the mostperfect cac and ltv, and then
you know you don't want to bethinking about it too late.
But as matt was talking, it wasjust it was kind of like a lot
of my scars started to burnbecause I was like man, like if
we had this kind of awareness,right, it's almost like a
(17:50):
superpower.
And if you can start thinkingabout it early on and
understanding like these arefoundational plumbing, this is
foundational plumbing for yourbusiness long-term, like you
can't build a house withouthaving plumbing in it, right.
And so I almost see what Mattis saying with what he's talking
about CAC and sort of magicnumber and LTV, like all of
these numbers, all these metrics, is having a foundational
understanding really allows youto then figure out like, hey,
(18:13):
how am I going to start building, putting in the rest of the
pieces, like where do I want togo?
And I think I have in myexperience with other founders
is that it's just very, veryrare to see that at early stages
, early foundational companyforming stages, because a lot of
times the advice, like Mattsaid, is like, oh, growth at all
costs, just get as many usersas you possibly can.
(18:33):
Excuse me, because that'sbecome.
That has been the advice forthe last 15 years or so and I
think that's starting to change.
Speaker 2 (18:40):
And do we think it's just starting to change because
of the macro shifts in theenvironment and a greater focus
on profitability?
Speaker 1 (18:47):
I think that's a factor.
I also just think there's moreawareness around it now and I
think even just the venturecapital industry has become
better at articulating andcommunicating the asks around
that, the knowledge around thatamongst early stage founders.
You're just seeing more of that.
So I think it's just a functionof things.
I think definitely post-COVID2021, 2022, when things really
(19:11):
started to slow down kind ofreally made it, you know, really
brought it to light for peopleand unfortunately, there were a
lot of companies during thattimeframe early stage that
frankly had to wrap up justbecause they were not growing in
any kind of sustainable way,and it was just.
It was sad to see that.
Speaker 2 (19:29):
Yeah, it's certainly been a tough couple of years.
So the magic number that's beenreferred to a couple of times
is that, referring to the threeto one LTV, to CAC that's
usually referenced.
Speaker 4 (19:38):
The way that we look at it is sales and marketing
spend to revenue.
That's the way we look at it.
There's probably different waysthat people look at it, but
that's the way that we thinkabout it.
So it's an efficiency metricthat we combine with lifetime
value and net churn and all thatGotcha.
Speaker 2 (19:59):
Okay, and then with the freemium model, because Does
that throw off the LTV to CACequation?
Because you still had to havepaid to acquire those customers,
that ultimately never gave youany sort of revenue because they
just didn't go beyond the trial.
So then do you need morelifetime value out of the folks
who do actually convert, or howdo you approach that?
Speaker 4 (20:19):
Yeah, it's very much like there's a couple of things
to this.
So the land expand aspect ofthis is really important right.
We have this product now that'sout.
We have plans for gettingcloser to pipeline and the
customer um later.
So landing and expanding isreally important thing.
What we we basically obsess overour funnel right and there are
(20:43):
benchmarks for conversion ratesfrom visit to sign up, to sign
up to start trial, to engagewith sales and pipeline and then
close and the one thing you cancontrol is average deal size.
But it is, yeah, I mean it hasto come over time.
It has to come by growingcustomers right over time.
(21:04):
But if you can set it up in away that your cost per lead is
low which again we obsess overall of this on the front end and
this just comes from experiencedoing it Most companies don't
because they're thinking justgrow a customer on the
technology they have and that'swhere they start to fail is if
you set up the top of funnel andthe entire experience before
they become a customer, it makesit a hell of a lot easier for
(21:29):
you to sustain the lifetimevalue in CAC by growing those
customers right and the closeryou get to pipeline and revenue
and, you know, doing some levelof human and combination of AI,
people pay more for that becauseit's actually impacting further
down the funnel, and so we haveplans to go through the whole
(21:53):
customer journey.
Speaker 1 (21:55):
One thing I wanted to add to that, another way that
has helped me think about andframe things is the freemium
spend is almost like a marketingspend.
You can think of it as like oh,that could be my branding spend
, that's like the equivalent ofmy branding spend or marketing
spend.
Right, like it's like you canthink of it as like oh, that
could be my branding spend.
That's like the equivalent ofmy branding spend or marketing
spend.
So I think when you, when youthink of things that way, that
(22:16):
can change the dynamics a littlebit in that or in your
organization where you're likeoh, we have, like you said, we
have this massive freemium modeland we got to make up for it.
On the other side, or you couldjust be like, hey, that's just
branding, for example, likethere's awareness that we would
have spent anyways that it'shard to put place ROI on too.
Speaker 4 (22:32):
Yeah, that's a good point.
That's a good point, Usher, isit creates a community of users
and word of mouth and organicgrowth right.
So it does pay back, but youhave to know how to build that
and how to measure it, and weobsess over that stuff.
Speaker 2 (22:48):
That's a great way to think about it, matt, you
mentioned a couple of times thatthe easiest way to grow is
growing average deal size.
I know you mentioned you did itby 10% at New Relic and you've
referenced it a couple of timeswith Bounty.
How does one grow average dealsize other than the simple
answer of raise prices?
Speaker 4 (23:05):
Well.
So it's not raising price, it'sgrowing customer spend by
having a pricing model thatincrementally increases based on
the value you're getting right,so it's close them quick.
Acquisition so the way that Ibuild sales teams is there's an
acquisition team that transactsquick and that first transaction
should be easily digestible,right, you could go into a
(23:28):
starter pack and then you go toa pro pack and like it's all
pricing and packaging and thosebecome like sort of paid leads,
you know, paid trials for theteam.
Then the team will upgradethose based on the units that
you're selling.
So just in like one product,like you can do that.
And then, at the right time, youthink about what the adjacent
(23:49):
offerings are going to be andthen you're selling a platform.
Right, and you got to do thatin sequence, it can't be all at
once.
And that's another mistake I'veseen people make is oh, we got
our next product already, let'sgo build it.
But no, let's make sure thatour first product is honed in,
differentiated and we're winningthere and we know that we can
(24:09):
sustain customer, we can growcustomer and we can convert
prospects.
Let's do that first Strongproduct, market fit and
differentiation.
Then it's the way that I thinkabout it is it's almost like you
have an incubator on the sidethat's thinking about a year
from now right, and it's like aseparate team, maybe as a GM.
And it's thinking about a yearfrom now Right, and it's like a
separate team, maybe as a GM,and it's thinking about our
(24:31):
second product, and so by thetime, we need our second
products there right, but thecore company is focused on what
we do today, because when peopletry to do two things at once,
it's it all falls apart, right,they don't know what to do, and
so siloing that in a way isreally important.
But thinking about what do weneed a year, year and a half
from now to continue and sustainthe growth or accelerate, is
(24:55):
super important.
So it is upselling the currentproduct and it is adding new
products to the platform.
Speaker 1 (25:01):
Yeah, go ahead.
Sorry, one quick thing I wasgoing to add that this
highlights right, and you'reprobably seeing this, it's just
the rise of usage-based billingmodels.
Now, right, like just metering,and you're just seeing that
happen more across the board.
Because once you have meteringin place, that gives you
fine-grained control, refinement, understanding, and then that
(25:23):
becomes a really important andpowerful lever that allows you
to play around with the outcomebeing average deal size, right,
but you can actually start doingall sorts of creative uh things
when you have something likethat in place, right?
Speaker 2 (25:35):
yeah, that's a great point, because there's a lot of
companies, particularly on theuh, the ai side, that are using
tokens, because obviously weneed a certain amount of tokens
to generate ai responses, and sothat that, for example, is what
you'd be referring to whenyou're talking about usage, or
just one example.
Speaker 1 (25:50):
Yeah, exactly.
So tokens is an example, right,but what it allows you to do is
to really tie mentally in thebuyer's mind, psychologically,
like the, to the value that I'mgetting out of this tool, right?
So if I'm using it more, I'mgoing to pay more, but I'm
getting more value out of it.
That is hard to do, for example, in a seat-based pricing,
(26:10):
because you're like, oh, a seat,and then the seat has, like,
all these different things andI'm using two out of these 10
features, but I'm paying for all10 of them, right?
So that's what something likethis, you know, like you said,
token-based or usage-based, justhaving the ability to meter
gives you that ability to havemore flexibility on your deal
sizes.
Speaker 4 (26:29):
Yeah, I would agree with that.
I think I'll be provocativehere for a second.
But the seat-based pricing iskind of dying, right, it does
become shelfware at some point.
Right, and I totally agree withAsha, you're using two things
out of 10 things.
Is cost and value in lineanymore?
And like a platform, there'stwo types of customers, right,
(26:52):
some customers wantpredictability in what they're
spending every month, which isjust a flat rate, and then
there's some customers, likedepending on, like the company
size, really that want controlover the usage, right, so
there's a platform fee that'slower and then it's usage-based
and then at some point they useso much that they want to raise
(27:14):
the platform.
So it just becomes this likeoverage opportunity to continue
to upsell.
Speaker 2 (27:19):
And how do you approach that from a pricing
perspective at Bounty so today,we just have a platform fee,
right.
Speaker 4 (27:26):
We are moving in the direction of having multiple
ways of exporting, like anoutput from the core product
that we have today and alsoallowing people to import.
So you can either pay a flatfee or you can use tokens to
import more information orexport information in multiple
(27:48):
ways.
So that's a different modelthat we're looking at right now.
Speaker 1 (27:53):
Yeah, and the thing that is there today is that, you
know, instead of focusing onseats, we've moved the unit of
value around accounts orcompanies.
Essentially is what it is,which is again kind of step zero
or step one before you moveinto a more refined usage based
type of token oriented modelRight.
Speaker 2 (28:12):
Yeah, so I actually got into your guys' product last
night and signed up for thetrial and I was playing around
with it so I could have an ideaof what we were talking about.
What do you think of it?
I liked it.
I liked it it was, and itactually created a kind of a
couple of additional questions.
I think the automated researchportion of it works very well
and I love the different buyerpersonas, for and I, you know, I
(28:34):
gave it the folks that Itypically sell into, like for my
recruiting business, forexample, and the copy was good,
the ICPs were good.
But I did have a question injust the context of and I think
(28:54):
you've sort of alluded to thisin that I think this is more of
the beginning and obviouslyyou're going to continue to
expand.
But there's no, it really wasand correct me if I'm wrong,
maybe and this is just in thetrial, but it's like you can
send directly from the platformor like copy paste into a like
an engagement tool?
Speaker 1 (29:14):
is that generally correct?
Yeah, yeah, you're talkingabout the.
I'm assuming you're referringto integrations like having yeah
, yep, yep, yeah.
So that's exactly right andthat's intentional.
You know um, where we wanted tohave a limited trial experience,
where and if you think aboutour icp right, like um, which is
we're hyper-focused on earlystage, founder-led sales type
teams like that are just muchsmaller.
You know, for those folks,number one budget is tight.
(29:38):
So we know that, hey, it'sunlikely you're going to have
some kind of a sequencing tool.
It's going to be very limitedand you know we don't want to.
We want to be in a price pointwhere you can get all of this
value around research and data.
You know the contact databaseand messaging and all that kind
of stuff, uh, that you wouldhave to put together um at like
a pretty reasonable price pointand then if you are a bigger
(30:02):
team that has integrations, then, like, let's talk, like you
talk, to sales and then we canenable those integrations for
you.
Uh, the other piece that youdon't you can, you may or may
not have experience in yourtrial is but there is a human
API, human as an API elementbehind this, which is that you
know, most of the research isautomated, but if there are
(30:22):
things that are really hard forus to find, that the AI finds
hard to find, then it getskicked off to a human workflow
that will go and augment it, butto you it would be pretty
invisible, right, and that ispretty.
I would say just an approach ingeneral across AI that I think
you'll see more adoption of likehey, how are we, when we're
providing a service, how do wecombine both the AI, because AI
(30:45):
is not going to be enough.
You know this right, it's justwho wants to have the headache.
Is it you, reese?
Or is it like do I want to handthat headache off to someone
else?
So it's like, okay, I'd ratherhand it off to someone else to
deal with, and so that's kind ofcore to that experience.
Speaker 2 (30:59):
Okay, got it.
And so you've emphasized and Ido worry here a little bit that
I mentioned my own experiencewith the trial, but I don't
think it was really expanded onon really what the core product
of bounty does.
So maybe we could rewind alittle bit and one of you could
explain that just for thelisteners.
Speaker 1 (31:14):
Yeah.
So for the listeners it wouldbe that you are hiring a quote
unquote a bounty AI teammateexperience to help you outbound
prospect and what that meansspecifically.
If you think about prospectingand break it up into different
stages or tasks, it is having alist of companies researching
what's going on in thosecompanies, what are the key
(31:34):
events that I can reach out topeople for to tell them here's
how I can help you so, doing theresearch on the company,
finding the right personas basedon the product that you sell,
the capabilities and the usecases that you solve.
For Now, typically, if youthink about how long it takes a
human to do that about, and theoutput of all of that is some
kind of personalized messagethat you can either put in the
(31:56):
form of a PDF or an email orwhatever it is Like.
We're not explicitly in theemail business, but let's just
say you have a message thatyou've personalized Now that you
can choose to either send itout on your own or you can say,
hey, bounty, I want you to sendit out.
Sequence it on my behalf, right, and that's the outcome as a
service.
But essentially that wholeworkflow, if you think about it,
for one personalized messagecan take you know anywhere
(32:18):
between 60 to 90 minutes in abest case scenario, right
Whereas you get it within.
You know if you've tried it inthe trial experience you've got
a message ready to go withinless than five minutes.
So that's a pretty hugeproductivity gain that you get.
So that's what Bounty does todayfor you is really focusing on
outbound prospecting in twoforms.
(32:39):
One is you can use it on yourown, but you are responsible for
sequencing and doing the workand putting it into the
different tools and then promptengineering and keeping it up to
date.
That's on you.
If you buy our startup service,then you can say like hey, I am
an early stage founder, earlystage company that doesn't
really have the resources, but Ineed to build pipeline, I need
(33:00):
to build warm leads, I need tonurture them.
I want to hand it off to Bounty.
That's the second part of ourservice, which is like hand it
to us and we will run all ofthat for you, that whole
workflow for you, butspecifically today focused on
outbound prospecting using bothAI and humans.
Speaker 2 (33:14):
Yeah, does that give you a?
Speaker 1 (33:15):
little bit more clarity.
Speaker 2 (33:16):
That does.
Speaker 4 (33:17):
Super helpful, I'll add.
My experience in this BDR hasbecome this get up in the
morning, blast out 300 emails,hope for meetings because
incentives are off right.
Bdrs get compensated onmeetings and sales reps get
compensated on pipeline.
And then a gift card on top ofit, right Like now, you're
(33:37):
giving T-shirts and gift cards.
It's just like losingproposition today and then like
the world has changed right.
So you have really bright folksare graduating from college but
they're working from home forthe most part and they're asked
to do the most strategicoutreach in the company.
So you know.
Then you know they do all ofthis work.
They can't get it done at scale.
(33:58):
They've never done it before.
They don't know how to go outand, you know, tie their
solution to create a pitch tothe company.
They're trying to contact atthe buyer persona what that
person cares about.
That would take them all day toget three out that were good,
like even average, to be honest,and so they can't do it at
scale.
So it's become this mass emailthing.
It's this mass email and giftcard and get meetings and hope
(34:20):
and pray that people are showingup for value and not the gift
card.
And that's the world that welive in today.
And the other aspect of this,like what we've seen it was
unintended to be honest with youat first is we're creating
better salespeople.
We are literally telling you,we're showing you, how to do it
(34:44):
right.
The product does it, and thenyou read through it.
You understand what the valuedrivers are, the buyer persona
you're trying to sell to.
You understand how yoursolution ties to business and
public business objectives ofthe company you're trying to
sell to.
We're creating bettersalespeople, we're training and
enabling people and we're alsohelping them get out.
Like Asha said, the email andthe output is just like a
(35:04):
feature of what we do.
Just like a feature of what wedo, but it is this hub of
knowledge that can train peopleand also be manipulated in a way
that you can export it formultiple things in the future,
not just an email.
It can be a lot more than that.
Speaker 2 (35:20):
Yeah, you're not going to get any argument from
me that the role of the BDR haschanged, and I think
particularly you're right withthe work from home when you're
at that more junior level.
There's so much you learn justfrom osmosis and by sitting by
more senior salespeople and ifyou don't get to do that then it
kneecaps your growth At thesame time.
Is there also just to be alittle bit contrarian is there
(35:42):
also an argument that doing someof that work and doing some of
that struggle and maybe takingall day to send those three
meals is that a necessary partof learning and training and
growth is kind of figuring itout on your own, or not?
Is it more helpful just to say,hey, here's the right answer,
and then you learn by eventuallylooking at enough of the right
answers that this is how youshould do your customization?
Speaker 4 (36:05):
Yeah, well, it depends on how you trade off
enablement versus revenue, right?
So if the idea is that you'reenabling and training BDRs now,
then meetings are going tosuffer and pipelines are going
to suffer, right?
So I hear that, right.
So maybe it's like the firsttwo weeks of training you go
through that and do that.
But, um, if that's the purposeof it, I think every company is
(36:30):
going to trade off more pipeline, more meetings, for enablement
do we need bdrs with a tool likebounty?
you know what?
What?
I think there's two scenariosthat we see, right.
There's the early, early stagefounder-led sales who is
considering hiring a BDR thatmaybe doesn't, or maybe hires
one and then hires Bounty.
(36:50):
Then there is the more maturecompany that has 20, 30 BDRs.
We're not trying to replacethem, right, we want to help.
And it's almost like the oneperson's trash is another
person's treasure.
Right, if you can elevate a BDRto do more work, that's closer
to the customer, guess what?
The sales rep gets to move up,too, right.
(37:13):
And then everybody moves up.
And this is the problem that Isee today is there's too much
talking about calling andprepping to call a customer and
not enough calling the customer.
And if we can solve for that,this is why salespeople get into
sales.
They don't get into salesbecause they need to log
Salesforce tasks all day andhave forecast calls and do
(37:34):
prospecting.
No, they want to be on phonecalls.
That's why they're here.
They're social people, right.
And it's a declining thingright now where there's more
work in the day than there isactually doing the work.
Doing the work of talking tothe customer, prepping for the
call, has become the predominantuse of their time.
Speaker 1 (37:56):
You know sales is all about.
You know, if you think aboutyour superpower as a human being
versus AI, right, it is how youuse social intelligence and
judgment to manage complexproblems.
Right, that's really what itcomes down to and that is
something you know, what we'rereally really intentional about.
(38:19):
Because with AI, any kind of AI, right, it's all about, it's
what it is and it's a reflectionof what you put in.
You put in garbage, you getgarbage.
You put in good, you get good.
You put in bad, you get bad.
So we took a stance to say, likewe are going to inject good,
good behaviors, good outcomes,and we're going to get that
right.
That really means is when wethink about, in the context of a
BDR is like, hey, bdr, like youknow, this research, like Matt
(38:47):
said, like don't spend the timeprepping, spend the time in
figuring out what is theappropriate social engagement
and interaction that's going toget this person to have a
conversation with you about thepain and the problem that
they're facing right now,because after that, guess what?
You actually have to actuallyhelp them solve the problem,
which is okay.
So that requires you to learn,have the time, the mental
bandwidth, the emotionalbandwidth to go pick up new, new
skills, new technology.
(39:07):
So I almost see, you know, theBDRs becoming more what we call
AEs, for example.
But I think I would take it onestep further, which is that I
almost at a go to market levelit is.
You know, imagine a world inwhich the go-to-market folks are
becoming extremely, extremelyclose to the product.
They're shifting closer andcloser to the product, to how it
(39:28):
gets built and just picking upskills along the way and new
sort of neural connectionsforming, so that I think being
really super intentional aboutthat is really important, having
a viewpoint on it is reallyimportant.
But yeah, like you know, Icompletely, 100% agree with what
Matt is saying.
It's like it's just thatamplify the social intelligence
and complex problem solving.
That is the important piece,versus like, oh, we're going to
(39:49):
replace BDRs because it's like,well, replace them with what you
know.
That's the open question.
Speaker 4 (39:56):
Well, there are.
What we're doing is replacingthe title BDR and, like the
first entry level is juniorsales.
That's what it should be.
If junior sales can be doingthe demos, then sales folks can
be working on managing theirpipeline and being in front of
customers.
So that's the whole aspect ofmoving everybody up closer to
(40:17):
the customer.
And there's a reason why everycompany plans for a decline in
productivity every year, becausea lot of companies are throwing
headcount at growth and thenthe demand, right, the lead
generation has spread more thinright.
So every year you plan for adecline of 10%.
So you can make a number thatyou can report growth.
(40:37):
But you can also report hittingyour goal.
And the number of folks thatare making quota today has
declined right.
Like at New Relic, weintentionally set a goal.
We had this thing called themorale tax right, and Mark
Shackleben and I would work onit.
Mark's the CFO there now he wasthe COO.
When I was there We'd say look,you know what?
We're going to carve out amillion dollars for the year and
(41:00):
we're going to set quotas wherethey're attainable and 70% of
the team 75% of the team isgoing to make their number.
Well, guess what you just did.
You just improved moraleimplicitly.
And then you also recruitingbecomes easier because
everybody's making their number.
Culture is awesome and themillion dollars is now just like
(41:23):
become $3 million in soft costsacross the board.
People don't leave, people arehappy, people wanna work there.
We don't have to recruit, it'sall inbound right.
That is the thing.
People aren't like chasingquota the entire time.
Because what happens when youallow somebody to see beyond the
line of quota?
They work harder.
You actually get more out ofthem.
When they are have no chance ofmaking their quota.
(41:45):
Guess what they do?
They look for another job andthey sink and they, they, they
honestly poison the culture.
So it's just such an easy thingto think about.
Like combining that like thattype of thinking.
You can, you can augment thatwith bounty, like, like.
That is something that likewill make it easier.
So you don't have to have thatmorale tax.
You already have it built in.
Speaker 2 (42:08):
Right.
So from a consumer perspectiveI don't know if you'd seen this,
but Mark Mark Kosaglo, who isthe first employee outreach and
he scaled it up to 200 plus inrevenue he recently founded a
company called Operator which,as of this recording, they
haven't released their productyet, so not a hundred percent
sure what it is.
But the problem that has beendescribed is that contact
(42:30):
commoditization and AI outreachhas done damage to Outbound
because it's like when everyone,when everything is personalized
, it's no longer special.
How do you respond to that?
What are your thoughts?
Speaker 1 (42:43):
um, I think I think there's truth to that, right
like it's at some point it's.
Imagine a world where it's likebots talking to bots, right,
it's like that.
That's kind of.
I think the way that I see, um,this playing out is like okay,
so in that world where you'vegot bots that are generated and
it's like you can't really tellthe difference, you're starting
(43:04):
to like tune out channels, right, like email, like email is
already pretty tuned out forcold.
I would say.
You know, linkedin is becomingextremely, extremely crowded
with a lot of this stuff.
So people are starting to tune,starting to tune that out.
And I think the emphasis andimportance which I think is
we're talking about the problemis like OK, how do you actually
stand out, you know, how do youactually?
And the way again that I see itis like it's not going to be
(43:27):
just a standalone AI solution,that's just it's.
I don't.
I don't see a world where thathappens, where it's a standalone
AI solution.
I think the opportunity thereis like OK, how do you again
bring really bring forth thehuman in the loop element as
part of that consumer experience?
Now, right, where you're justlike, and, by the way, you know,
(43:47):
maybe there's a world wherepeople just get so attuned and
attached to that, with peoplebeing remote and post COVID,
where they're like I never wantto talk to a human and I just
love the fact that I'm talkingto a bot all the time.
I don't know, I could be wrong,but I think there's definitely.
I think there's going to bestarvation for human online
(44:08):
connection in in like sort of mypurchasing experience.
That, um, I think you have tofigure out.
We have to, collectively, allof the AI companies that are in
this space have to figure outlike, how do you bring that
forward, how do you bring thatto light, and so for that you've
got to have the right people,infrastructure, the right skills
you know in within your company, within your product, that you,
you know, are able to bringthat to light.
So that's that's how I wouldrespond to it, which would be
like, yeah, I agree, likecontact, monetization and AI
(44:29):
like has wreaked havoc andpeople have started to tune out,
but I think it's also createdan opportunity, which is like
okay, here's how we can bubbleup through the noise If you can
really figure out where is theright place to put the human in
that interaction.
Speaker 4 (44:42):
Yeah, we're seeing that.
First of all, I think humansare important very still, and I
think AI will not stand on itsown in this space for quite some
time unless a lot of thingschange.
Because there's got to be ajudgment call on the content,
right?
Someone has to make a judgmentcall, otherwise you just sound
like you're talking to a bot,right, and it's just as bad as a
(45:05):
generic email.
So the last 5%, we'll get you95% of the way there, and we
have our team that's tweakingbehind the scenes that's human
in the loop.
The sales reps and BDRs justhave to make judgment calls on
whether that is the rightmessage to send.
That's where I think we aretoday, is humans still make the
(45:29):
judgment on what goes out andwhat doesn't, but they don't
have to do all the heavy lifting.
Speaker 2 (45:35):
Yeah, because there's another company that just
recently raised a fairlysimilarly sized seed round that
is a fully AI BDR, as far as I'maware.
I haven't tried the product,but there's no human in the loop
, and my hesitancy about that isessentially what you just
described.
Do you think there will be apoint where a technology like
(45:55):
that is feasible, or do we thinkthere will always be a human in
the loop?
Speaker 1 (45:59):
I think it'll be, it's feasible from a like bill.
Can we build it?
And will people buy?
Probably, like you'll see thisspike, we'll see this like oh, I
want to try it, I want to seewhat it's like.
But I think, as we've seen witha lot of ai technologies that
launched in the last three tofour years, is that there's this
very extreme spike ofexcitement and interest and then
(46:19):
also an equally sort of uh ofdownward spiral in terms of
disillusionment that people feel.
So let's just say the example.
I don't know if you guys everwatched that movie I think it
was called Her with JoaquinPhoenix.
I've seen parts of it, right,but there's this really deep
emotional connection that youform with the AI, but then you
(46:40):
realize that there's like 10,000people that are also forming
the same kind of emotionalconnection and I just I just
kind of like I think that youknow, having a world where you
have people that are interactingthat way with AI is pretty
close to reality in my personalopinion.
And you know but would I be you?
(47:00):
You know there's got to besomething deeper, like there's
always.
That's like almost like step,stage zero in your sales process
.
Okay, I'm done with stage.
I booked a meeting.
Now, what right like?
So there's all this opportunityahead of like.
Okay, where is that deeperconnection that comes from
physical touch, that comes fromthe three of us?
Looking at each other's faces,you know, reading each's
expressions, making rapid,instant in time decisions around
(47:24):
oh, do I want to buy Reese'sproduct or not?
Or like, is he convincing me?
What's his tone of voice?
You know, that thing I feellike is is really going to be
hard to replicate and I feellike that is, you know, even
though it's going to be like yousaid, it's feasible and it will
be done and people will do it,even though it's going to be
like you said, it's feasible andit will be done and people will
(47:44):
do it.
But I think there's going to bea really, really high premium
on this.
What's happening right now.
Speaker 4 (47:49):
Really really high premium on that it's a long road
, in my opinion.
Based on your average deal size, either, the product can sell
itself, right.
Low price point, transactional.
I don't see AI selling 25,000plus average deal sizes.
I don't think people are goingto buy that way.
(48:09):
I do agree with ushers there'sa degree of trust when you're
spending a certain amount ofmoney.
You want to look somebody inthe eye, you want to hear their
voice, their tone, their bodylanguage.
You have to trust them, right?
Eye contact is a big thing,right, and it's I don't know.
You know, I just don't.
(48:30):
I think it's a long road tothat point that I don't see it's
just again, it's like peoplebuy from people or people will
buy from your product experience.
But it depends on the pricepoint, right?
Speaker 2 (48:39):
Yeah, dan from Stage 2 had mentioned that a few weeks
ago when he was on here.
Basically, the similar thoughtwas that, yeah, for PLG small
deal size stuff you can probablyget away with AI, but no one's
buying.
I mean you said 25.
I think he said a million.
Nobody's spending a milliondollars on an enterprise deal
without talking to severalhumans much less.
Speaker 4 (48:58):
One, nobody's spending 25,000.
To several humans, much lessone.
Nobody's spending $25,000.
I mean, it's a lower bar thanthat.
Right Like a million isoutrageous to think about, right
, unless they're two guystalking to each other.
Speaker 2 (49:11):
Never know.
So when we think about what thestructure of go-to-market teams
looks like in the future, youmentioned a little bit on the
sales side that you thinkeveryone will more or less
ratchet up a step and have themore junior folks doing the
demos and the more senior folksmanaging the pipeline.
How do you see that changing,if at all?
On the post-sales and customersuccess side, Ashi, you want to
(49:33):
touch on?
Speaker 1 (49:34):
Yeah, yeah, no, I think this is an ongoing debate
around this, right, and there'sa few ways to look at it.
There was a point in time inour life, at Bounty, where we
were like, oh, imagine a worldwhere you could just you
literally think about AIteammates as actual teammates,
right?
So you're thinking about it interms of you know, you've got a
(49:55):
CFO that's looking at headcount,building out a model, and then,
like you have a spreadsheetthat has like reese, um and matt
and usher, and then it's likeai teammate bob and ai teammate
karen, or whatever it is right.
Um, so I think it's it's it'sfanciful and romantic that
things think about things thatway, and maybe there's some
reality which is like, okay, I'mgoing to design my sales team
(50:18):
and I'm going to have, you know,three ai bdrs and two junior
sales reps and like four AEs andyou know an SE and stuff like
that.
So there's like one world thatcould possibly emerge that looks
a lot like that, just dependingon how buying patterns emerge.
I think the other world is justlike everything AI co-pilot,
like it's like, ok, you know,everybody gets an Ironman suit.
(50:39):
It's like, okay, everybody getsan Ironman suit.
Okay, everybody is Tony Starkon the team and everybody gets
an Ironman suit, which is thisAI co-pilot in post-sales,
pre-sales, whatever it is, andthat's a much more sort of
blended way of looking at AI andhow it plays.
And maybe in some places youwill see the Jarvis, the AI,
doing a lot more work on yourbehalf, which is on the BDR
(51:00):
prospecting side, and you'rejust kind of like sitting in the
suit.
And then on the AESC solutionengineering side, it's more like
, hey, tony Stark is doing mostof the work and the fighting,
but you've still got the AIthat's augmenting me in a bunch
of different places, likesolutions engineering is, I
think, is a really interestingone.
I was talking to my friend aboutthat use case yesterday, which
is, you know, that's whereyou're really looking at a
complex landscape, but youreally want to get information
(51:21):
about people's systems quicklyso that you can come up with a
reference architecture anddeploy it.
So you know that's a much moreblended AI model.
So that's how I see.
You know, those are the kind oftwo world views that I think we
are starting to look at and howsome of this stuff evolves over
time.
So yeah, we'll see, you knowit's hard to tell.
Speaker 4 (51:42):
I would take that.
If I want to step down to moretactical explanation, then Dosh
was very good at doing the highlevel.
But tactically, if you thinkabout enabling reps and DDRs to
be better with our platform butalso creating high quality value
meetings, the laws of averagetrickle down.
There's people coming to ameeting because they are
(52:05):
interested instead of getting agift card Handing over to the
sales team on the pipeline, amuch more highly qualified
opportunity.
Again, the laws of average istoday salespeople are
discounting by 40% to just get adeal done at the end of the
quarter because cost and valuearen't in line, because it
starts with the meeting they hadand it's like all right, well,
(52:26):
I'll buy it, but I'm going to doit month to month.
So they're selling month tomonth deals or 90-day outs and
they are discounting at 40% andso cost and value is already
misaligned and then handing itover to CS and CS ends up just
(52:47):
chasing cancellations instead ofmaintaining like solid
relationships, like that wholething is broken.
The whole customer journey isentirely broken and that's why
again I go back to whyproductivity is declining.
The more people you add, themore problems you get.
Like this problem gets biggerand bigger.
And so if you're discounting at40% to get a deal done on
average, well, what if you werejust discounting at 10%, cause
those opportunities were muchmore highly qualified?
Would you need to lowerproductivity every year?
(53:08):
Probably not.
That's a great point Superinteresting.
Speaker 2 (53:15):
Well guys, this has been awesome.
If someone wants to check outbounty or do a demo, what's the
what's the best way to do that?
Speaker 1 (53:21):
If someone wants to check out Bounty or do a demo,
what's the best?
Speaker 4 (53:24):
way to do that.
Go to our website.
Bountyai Watch your cell phone.
Yeah, just get a watch yourcell phone number.
Speaker 2 (53:26):
Publish it in the show notes, Cool guys.
Don't call me Awesome.
Thank you so much, reallyappreciate you coming on.
Speaker 3 (53:35):
Thanks for listening to See to Exit.
If you enjoyed the episode,don't forget to subscribe and
we'll see you next time.
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