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Welcome to "Visionary Voices" the podcast where we dive into the minds of business owners, founders, executives, and everyone in between.
Each episode brings you face-to-face with the leading lights of industry and innovation.
Join us as we uncover the stories behind the success and the lessons learned along the way.
Whether you're climbing the corporate ladder or just starting your business journey, these are the conversations you need to hear - packed with visionary voices and insights.
Let's begin.
So welcome to the show.
Thank you so much for taking the time today.
Could you give us a top level view about what it is that you're working on right now and
your journey so far?
Yeah, Kail, thanks a lot for having me.
um So I am building Layer 5.
It's a marketing data platform that helps marketers improve their marketing operational
efficiency as well as improve their marketing ROI.
um
and it's been fun so far.
I would say that the journey, the founders journey is pretty stressful as well but at the
same time I wouldn't do anything else other than this so this is super fun so far.
Amazing, amazing.
know we're glad to hear it and the entrepreneurship journey is one of those where it is
painful at times, but again, we wouldn't swap it out for anything in the world.
I'd love to go back to the start.
What initially got you motivated to start a career in the marketing technology space and
what did that look like in the early stages?
Yeah, so if I take you all the way back to my career, I started my career as an electrical
engineer on a refrigerator plant uh assembly line, fixing assembly lines and keeping them
running.
But within very quickly like within nine months, I realized that well, you know what the
future is more intact rather than on the assembly lines and I switched my career at that
point to go in tech and I spent many years with Deloitte.
So my early career was software engineer.
I built out a number of products here in the Bay for the Bay Area startups.
But then I went to tech tech consulting with Deloitte and I was serving a lot
wide variety of clients, pretty large clients in public sector, tech, healthcare, etc.
And at one point of time, was really, basically, I got really fascinated with marketing
technology because I saw that the impact of marketing technology has a pretty wide radius
of impact.
ah
you basically marketing is something as a function, it touches every business, whether
it's small or large businesses.
And that got me fascinated ah about marketing and marketing tech.
And I had an opportunity, I was trying to get back into the Bay Area startup ecosystem
because I had my roots in the Bay Area startup ecosystem before I went to Deloitte.
ah
And I got an opportunity to come back to join an SEO startup in the Bay Area, BrightEdge.
And that pulled me into marketing and Martek ArtTech world.
And since then, I've been in the Martek ArtTech world.
I've worked for multiple companies before I started Layer 5.
But that's what got me pulled back into one Bay Area startup culture and then uh back into
marketing.
Yeah, no, no, definitely, definitely.
And then I guess, you know, when you started your career, well, you got back into the
marketing space then, like what was that key moment where you were like, I'm going to go
and do this myself, let's say, because I think it's quite a big decision, of course, you
know, going from working in a role in a job to then starting your own company.
And know a lot of people, they're always on the edge of doing that, but might not actually
take that leap.
So you obviously took that leap.
So what was the motivations then and what was the reasons for that?
Yeah sure, I'll probably give you a longer version of this answer but I started in this
SEO company and the first thing the challenge that I saw there was that the company was
trying really hard to get the um basically get the credit for their platform.
So in SEO the typical problem is the challenge that SEO guys have is that
They will make the effort, but they think that all their credit is being taken by the ads
because people do branded ads.
And if you search for a brand name, you might see a brand ad first before the SEO results.
And SEO guys will always complain about how we are not getting the credit for our efforts.
And then I went to an ad tech company and there I saw that pretty large retailers uh were
spending tens of millions of dollars and some of them even hundreds of millions of
dollars.
on advertising, these retailers were basing all their decisions based on what they were
seeing from the platform.
So if it's Google or Meta, the results that they saw from the platform, they were basing
all their spend decisions and performance decisions based on that.
and as a tech having a tech background and as a tech guy I could see the fallacy in that
that well you really do not know if that particular platform provided you that kind of
return because you are not seeing a user's full journey you do not know if somebody may
have come from a google ad but then they may have come from an email they may have come
from a text before they converted and you are you really are not seeing the full journey
there
uh It bothered me there as well.
I saw that one retailer was spending uh like giving us 30k a month for a so-called
omni-channel attribution where we knew that we are only doing attribution between two
channels Google and Meta but we called it omni-channel attribution and the retailer was
paying 30k a month for that.
So obviously I saw that people are paying a lot of money for a very flawed solution.
And then I went to another company where I was serving pretty large financial services
clients.
And there I was in a more of a marketing consulting role.
I was helping this one really large US financial services client where they were trying to
identify individuals who were visiting their site so that they can do better retargeting
and can do on real time onsite personalization.
And in that case as well,
this uh company was struggling to identify even those people who they should have
identified because they logged in onto their site.
uh They were not even able to identify all of them for some reason.
So there was this data problem going on in their own data sets.
So that gave me another data point that there is a huge problem in the industry where the
retailers are basically the advertisers.
They are not...
They're making decisions on half cooked data.
when it comes to their ad spend decisions.
Plus, they are not being very effective in their retargeting or their onsite
personalization, et cetera, because they do not understand who are the visitors who are
visiting their site fully.
So I saw that as a white space, and that's what got me to start Layer 5.
Layer 5, basically, I started as an ID resolution company, that if I can just solve these
two problems by better ID resolution, I got a product that I can sell.
Yeah, yeah, no, definitely.
mean, it's such an interesting, space to be in because it's definitely something we see as
well is, you know, the problem with attribution is, is how do you actually properly
attribute, you know, as you mentioned before, right?
If it's like ads, if it's SEO, et cetera, like how does that all work together?
And cause you know, to a point we rely on these platforms to get the data out and to make
the data driven decisions.
But if that data is flawed from the get-go, then ultimately any decision we make is not
based on any, any grounds.
that we should have any confidence in really.
And so it's such an interesting space.
And I guess when you started, know, later five, like how did you get that business going?
Because obviously with that, there's a technology aspect to it.
So obviously the development of those systems, those softwares, like how did that all come
into play at the very beginning of your journey here?
And how do you start developing those systems and tools internally?
Yeah, so again, being a tech guy and having that software development background from my
early career back in the Silicon Valley startup, ah that helped quite a bit.
I was already looking at some of these idea resolution problems and I was trying to figure
out what could be a better way.
I was talking to a couple of colleagues at that time I was working in a company and some
of the AI ML engineers and we kind of hashed out something we thought was interesting, one
interesting way to look at idea resolution and.
And then it was a matter of just putting some money, developing a product, developing a
POC on that and see how it goes, ah which I was able to do based on with, so I put
together the design for the product.
I put together some of the architecture stuff, did some research.
ah And this one AI engineer, my colleague and another one person I hired in India with two
people, we took about four to five months to build out something ah that was ready for at
least show as a POC.
And that's what got me going.
But my target market at that time was very different than what I ended up doing with the
startup.
or what kind of target market we use today.
Yeah, yeah for sure.
So four or five months of development before you really had kind of something you could
push out, is pretty quick, right?
But for sure, like getting something out like that is, you know, like that is very quick
to get something out, which is working and it's functional as we've said before.
So obviously you had quite a lean team, I guess, in the initial phases.
uh How big is the team now, if you don't mind me asking?
We are about 20 people.
Oh, wow.
Okay.
So, you know, over the last few years, I then scaled, obviously from, from just a couple
of you building out to then obviously a team of 20 now, which is, which is cool.
Um, and how did you find that transition?
You know, being an entrepreneur and like a leader, um, building out that team, because I
think that's something that I'm going through right now, right?
Where we started to really build out the team, um, a lot more than it has been right now.
It's been like three of us, super lean, which is great, but we started to really add that
head count.
um,
How did you find that transition going from, I guess, working with someone else to then
leading a team?
And what did that transition look like for you?
uh So I led teams, I led pretty large teams in my job, in my career.
Building out a team was not a big challenge for me.
What was really challenge, big challenge was that how do I build out on a shoot string
budget?
Because earlier in my career, I could go and hire the most expensive resource I can find
for a job.
But when you are bootstrapping a startup, you have to go find resources at the string
budget.
And that's the challenging piece.
ah We identified, we found first of all I built out most of my based on initial team was
based on referrals based on like people giving references to others who they knew uh is
good resource and
Most of my engineering team was built out in India.
So that turned out to be a cheaper place to build out.
Of course, there are challenges with that as well in terms of like the kind of resource
you find, how do you figure out the coordination stuff and all, and there are things that
get lost in translation.
But.
um
It's been, it's been, it has been its own learning moments, but I had worked with offshore
teams in the past in my career as well.
So I was able to navigate that.
Yeah, yeah.
So it's one of those things, I think, in entrepreneurship where you've got to use what you
got, right?
Where if you have that experience and everything, then you can leverage those skills and
you can use those skills to do what you need to do.
Okay, cool.
And then you mentioned about your ideal clients, right?
So initially what was or who was your ideal client and how's that transition now?
Because it'll be interesting to see how that change over time.
Yeah, so like I was saying that when I started I saw this problem with large companies,
right?
So pretty large retailers large financial services companies And my initial ideal client
was going to be these pretty large retailers or pretty large companies that I've got like
Maybe over a like five million visitors on on their sites every day or every month and
they're spending tons like millions and millions of dollars on Mardic Artic.
The problem that I ran into and I had connections in the industry and I thought that yes I
will be able to sell this to these large clients.
The problem that I ran into is that if you are a bootstrapped startup for these large
clients they have pretty long procurement process and for a startup like layer five it was
impossible to break through all those all that procurement process.
ah unless I was ready to like put a few million dollars behind it and get some kind of uh
scale and name behind it.
So then I had to change my strategy to go after smaller clients first and then say, all
right, I'll have to build with the smaller clients and then go back to large clients.
And initially I got some e-commerce retailers as my client through references.
And those e-commerce retailers were small, but that's what became my initial list of
clients.
And that helped me grow the product where we are today, where we actually serve a lot of
e-commerce customers.
Right.
It's interesting how, how things progress over time, right?
When you start your company, you have this vision of, of what it's going to do and how
it's going to work.
And then, you know, you get a few years down the road and you look back and it's, it's, it
is vastly different.
Right.
And I think it's one of those lessons again, that we can extract through this journey of
entrepreneurship where, you know, you have like these feedback loops, I guess you could
say where, you know, these things are happening in the business and you kind of take those
lessons and then you can evolve the business, you know, even more in that direction,
right.
Based on those learnings.
And I think having
those types of processes in the business is so important.
uh And for yourself where you start to see that success in the EECOM side of things and
just like, cool, let's double down on this side of it because it's working clearly, which
is amazing.
Yeah.
Okay, cool.
And then I remember mentioning that in the previous kind of conversation that you also
work in the B2B space as well.
So like Econ Plus also a bit of B2B.
So do want to talk me through that and like how that side of the business works?
Yeah, so we got in terms of our target customers, we got three different target customers,
you can say groups.
ah The first one is marketing agencies.
We are working with marketing agencies that have and the problem that marketing agencies
have is that their marketing ops, ad ops generally.
ah
is not very efficient even though that's where the agency business is based off of like
their profitability and their success is based off of their marketing and ad ops but ah
it's not very efficient today.
And we are helping these marketing agencies make their overall marketing and ad ops more
efficient by unifying marketing data, providing them immediate insights that they can
utilize then to serve their clients.
And doing that in a very effective manner.
So that's our one target client um group.
The other one, of course, we talked about e-commerce.
are serving number of mid-size e-commerce retailers.
And then SAS.
uh SAS is an interesting one.
The product that we have, works for SAS as well.
We got some SAS clients as well.
ah They are the challenges that they have the same attribution problems challenges.
They have the same retargeting or lead scoring challenges where they can figure out which
lead to go after.
uh
But their challenge is a little bit more involved compared to e-commerce where I can just
do a Shopify integration and I got like 100,000 e-commerce customer market that is open
with that one integration.
But in the B2B SaaS, every client has got a little bit different way of managing their
funnel, ah how they are bringing somebody into their funnel, and then how that funnel is
progressing, whether it's a PLG, product-led growth SaaS, or it's a sales-led growth, or
both in the same company.
ah And everybody has got somewhat different, ah you can say, funnel, or their own
definition of funnels.
ah That's the interesting problem and we solved that as well.
So that's been pretty cool.
Yeah, yeah, no, definitely.
And, you know, I was just thinking back as you said that to the clients I work with and
like the funnels that I've seen in the B2B space and yeah, they all are very different.
They all have very different, maybe client acquisition strategies, channels and ways of
doing things.
And so it will be interesting to dig into the technical aspects of the technology itself.
So how does the technology work and how does it actually improve that marketing
attribution?
Because
Obviously it's huge problem that we're seeing, right?
And that I still see in the marketplace, but it's interesting how, you guys have built
this technology.
So how does it actually work on a, technical level?
Obviously not too technical, otherwise might go over my head.
But it'd be interesting to know like how, how does this technology work?
Sure, let me give you an analogy first and then we'll go a little bit technical.
think about, let's say if you've got a neighborhood mom and pop store in your
neighborhood, ah that mom and pop store owner probably knows you.
If you walk in, ah that owner is greeting you with your name or that owner already knows
what you typically buy, don't buy.
ah And that owner knows pretty much everybody in that neighborhood.
ah And it also knows if somebody, if they see somebody new in their shop, that okay, this
person is new and I need to go, I need to know this person.
Now, even if you, let's say, if you go to that store in a Halloween costume, the chances
are that the owner is gonna recognize you and will again greet you.
That's what's going on when you take this into the online world.
ah You go to a website.
Let's say I go to Macy's.com.
ah If I visit Macy's.com, often if I purchase something from Macy's.com, I'm a regular
visitor.
The ideal experience from my perspective, using that mom and pop store analogy, will be
that if Macy's.com recognizes me every time I get there, can...
uh
personalized experience for me like show me the products that I usually buy that I will be
interested in ah as well as basically if I leave then it knows that I came and I didn't
purchase anything but I might be interested in something and if they are using any of the
retargeting techniques then again they can personalize that retargeting message ah back to
me based on my preferences my journey so far on Macy's.com.
is what is
hard on the online world because I could use the same browser multiple times but my
cookies may get wiped out which is the case with all the privacy the browsers getting
stricter on privacy or I may use different browsers on the same device or I may use
different devices so this problem uh the mom and pop store problem that that I'm talking
about identifying somebody who is visiting your store becomes really acute on the in the
online world
And that's where ID resolution technique solves for that.
So the technology that we have for ID resolution is that we identify an individual who is
visiting a site.
We will drop the same thing, a cookie.
We'll understand if that individual logs in onto the site, if that individual gives their
email on a pop-up, or if they're coming in through an email click or an SMS click.
um
we will try to use all the techniques to identify that individual or attach an email to
that individual, to that visitor.
Then we, on top of that, then we utilize additional techniques where if the individual is
coming from a different browser or different device, which happens quite a lot in today's
day and work, the day and time.
So we will utilize additional techniques to say, this individual is coming from a
different browser.
So.
But it's the same individual based on the behavior that we see or based on some of the
parameters that we see from that browser.
So that helps us identify the individual when you are returning.
So first time, let's say somebody comes in through a Google ad, did not buy anything.
Now later in the day, that same individual is coming back but on a different browser, ah
and this time directly, and buys something.
Now in a typical, if we did not connect these two different journeys together, for any
system it will look like this individual came direct and purchased.
The credit back to the Google Ads is lost.
ah But a good ID resolution will resolve these two journeys back to the same person and
will be able to attribute that particular purchase back to Google Ads.
Right, okay.
That makes sense.
That makes sense.
And it's really cool how it all works.
It'll be interesting to know on your side then with AI and the intuition of like this
technology that we're seeing, because I have seen obviously, know, Jack GPT is looking to
implement kind of e-comm and like being able to buy products directly through their
platform.
So how do you think that's gonna maybe shift and change like this landscape of, you know,
of attribution and IDing?
you know, these, these visits to to the site and to the, you know, looking at the
products, that type of, that type of industry.
So I'll come to attribution, but IDing somebody is going to be even more important.
So the reason being that AI is hungry for context.
If I go back to just a recent study that came out from MIT about the state of GenAI in
2025, back in July, they came out with that said that 95 % of the GenAI implementations
today in the enterprises is failing.
only 5 % are being successful.
And the main reason they are fighting there is that the AI that are being put in the
enterprises, they are lacking context.
They cannot adapt to the workflows that the companies have today.
So that's one of the biggest challenge with AI today.
in the enterprise context.
To solve that, you have to have highly accurate contextual data that you can feed to AI.
And to get highly accurate contextual data, you have to do ID resolution on that so that
you can connect the dots as much as possible that then you can feed to AI.
If I gave that, let's say that in that earlier example, if I gave AI that two journeys
steps, one from Google Ads, one from direct, but there was no connecting thread between
the two, AI will not be able to do anything about it.
It's not going to go and magically say that, yes, this purchase can be attributed to
Google Ads.
So you really need that good data for that you can feed to AI to make it work.
So that's where identity resolution is in fact even more important today in the world of
AI than it was earlier because you're going to start to feed data into all these AI gen AI
systems and they are gonna you will give them crap they are gonna give you crap.
that's where on the attribution side like you said that uh
chat gpt you can you can go buy stuff directly into chat gpt that's something that has
been there today as well you can buy stuff in metashop like in facebook ads or instagram
shops or tiktok shop uh the headless what we call headless client that is already there so
um the overall purchase funnel has been decoupled from the retailer's website where you
can go and purchase on any surface um
But that does play a role into uh making attribution really hard.
uh And that's where, even though I'm saying that attribution needs the ID resolution,
attribution does have a limited role.
have to utilize attribution not as a singular thing, but attribution with some additional
models that can give you little bit better perspective.
Right.
Okay.
Yeah, it makes sense.
And it's going to be interesting to see how, how that evolves, I guess, over the next, the
next few years, but it's interesting.
You'll take on, you know, we already have platforms like, as you said, doing a meta, you
know, shop, for example, and you can go and buy products directly through there.
Um, it's kind of the same thing, right?
Just package it up on, on track GPT on open AI, um, rather than obviously on meta.
So, no, it's interesting that that's already, already there.
So I guess in terms of like a shock to the system, it's not quite a shock because again,
you, you, already have experience in.
in that realm of things through through matters and we said before, I'd love to switch
gears a little bit and talk more about the entrepreneurial journey and just some things
that, you know, have obviously happened in the last, the last few years.
So it'd be interesting to know how or who has been some of the, I guess, the biggest
mentors that you've had like over this, entrepreneurship journey.
Cause I know for myself, like, you know, I've had like two really, really amazing mentors,
which really pivoted and shaped the way I see
entrepreneurship in the direction I've gone in.
on your side, like who have been mentors oh or influences, let's say, on your
entrepreneurial journey.
There are a number of them.
ah When I started, there was one, my uh boss from one of the previous companies um who
helped me quite a bit in terms of getting going and trying to introduce two different
potential customers.
There ah is another person that actually I did a sales masterclass with him.
And this person has been amazing in terms of making a change in my mindset in terms of how
do you go out and sell.
um So of course I'm not naming people, there has been a few mentors who have helped me
quite a bit.
There has been another one who was very successful on the agency board.
uh
He helped me, actually he asked me early on, he asked me very hard questions.
as any founder, you think that you got the best mousetrap in the world.
I mean, this is the best thing.
Why will this not sell?
And you really need some mentors who can actually ask you the hard questions and.
kind of tell you like, all right, this is, you really need to think what your
differentiator, differentiators are.
So I, early on, I found an agency owner who had actually built an agency and sold.
um He made me think that what I'm trying to do, it really make, does it really work?
Does it make sense?
Am I making it too technical?
Things like that.
Yeah, yeah, no, definitely.
And it's interesting as well, because I think a lot of the time, you know, people listen
to this, they might be wanting to start a business or maybe they've started and they are
looking for mentors.
And the thing I always tell people is, you know, like look into your network on people
that you've worked with in the past or people that you know already, because there's a lot
of people in there that could help you and shape, obviously help you shape your business.
And to your point is finding someone who can ask those hard questions or really challenge
you on it.
uh
It's painful sometimes because obviously, you know, it's like your little baby, right?
Your little idea that you have and you want to protect it as much as possible.
of course we think it's the best thing, best thing in the world.
But of course we do need to hear some of the truths about it, right?
And sometimes we're not wanting to have a look at that until we're told it.
So I completely agree with you on that side of it.
Okay.
Amazing.
Well, one of the, one of the final questions we always ask guests in the show is if you
can go back to your 18 year old self,
and only take three lessons with you, whether it's some philosophical knowledge, some
business knowledge, some general advice, what would those three things be and what would
be those three things?
All right, that's a tough one.
So I think that the first thing will be that I'll tell my 18 year old self that everything
is gonna be much better than what you can even imagine today.
So do not stress out on small things.
Look at the bigger picture and everything will be all right.
ah I would second thing I will say that take risk now you have the age on your side.
you wanted to build out something on your own, go do it now rather than waiting for like I
need to get more money, I need to get a career before I can do something.
So if you got an idea, work on it now and I know that my 18 year old self uh
Maybe not 18 year old, but my 21 year old self had ideas that did not work on, which I
regret even now.
So that's what I'll say.
I think the third thing I will say that is spend time on relationships.
As an 18 year old, I was probably too, I would say cocky or not really paying attention to
all the relationships in the life.
whether it's family, friends, mentors, ah and I will say that spend time on those, nurture
those, treasure those.
Amazing, amazing.
Well, thank you so much for taking the time today.
I really enjoyed the conversation, learned a lot myself and I'm sure other listeners have
as well.
So yeah, thank you so much for joining us today.
Thank you, Akhil.
This was a really great conversation.
Thank you.