Manoj Ramnani’s Secrets to Refine Your ICP
Manoj Ramnani shares his framework and insights on how to refine your ICP and optimize your sales funnel.
Thanks for tuning in to this exclusive edition of GTM News Desk, presented by
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This show is hosted by me, Nick Bennett, and my co-host Mark Killens.
Now let's get to the goods, on with the show.
Alright, Manosh, we're back.
Let's get into the deep, dark...
Maybe it's not too dark, but...
Deep, dark, secret sauce.
The mole, like the stuff that's just, you know, you're just, you're, it's on
the stove,
marinating, it's getting all the flavors.
So, what's one of your favorite ways to think about, I'll give you an option,
either to create
the ICP initially, or to update, hone it. Like, walk us through like a
framework or a model that
you think is very valuable for either of those things. Yeah, yeah. So, I'm
looking at creating an
ICP, if you're an early on, just starting out of business, it's the founder's
hustle, and the
frequency at which they're getting the market feedback in the signals. For a
company that has never
done it, but they have grown to being five to ten million dollars in revenue,
and now they're
being serious about, increasing the efficiency of their dollar, and improving
their
KPI, such as, you know, your LTV to CAC ratio, the disc, kind of the indicator
of your health of
the business, then it's all about how much input you give to a model, how
sophisticated the model
that you build, and what kind of data do you have available, right, to zero in
on your ideal customer
profile. So, let me just break down, you know, those those three things. The
first is a, is a model
that you use, you know, look, back in the days, there was a spreadsheet, we put
scores, and that was
your model. Now, with AI, you know, those models have become very, very
sophisticated, with very small
effort, you can pick up a model that is, you know, multi-variable, right, but
that model isn't going to work
if you don't have enough data sets. So, that's where the second dimension comes
in, that you really
need high quality data that you can trust, because it's going to define the
success,
all the failure of your go-to-market efforts, you know, over the next six to 12
to 18, 24 months,
right, and that's where, you know, picking the right data vendors that brings
the detailed
form of graphic data, the tech graphic data, the persona, right, the contact
buying center data
becomes super, super important, right, and the third element is, how good is
your data within
your CRM system within your marketing system, right, and the more cohort of
data that you bring to
these models and may that be the ground troops of data, the better these models
are going to be. So,
many times, companies just go with, hey, I want close one data and that's going
to do the magic.
I think, at the very least, you should take your close one data and you should
go to take your close
lost data, right, at the very least, but if you really want to go deeper and
have more precise,
then you take the cohorts of your close one, right, by the size of the business
, and then you feed
that to the model, and let the model spit out your ICP, right, and the best
models are the ones that
not only give you ICP, but they give you the math behind it, so that you have
an opportunity to go
in and tweak that math because no AI is going to know your business better than
you will, right,
this is face it. So, let the AI do that 90% of the lift is like Tesla self-
driving machine, right,
90% of the time my Tesla works just fine. It's that 10% when I'm taking the
turn when I just want to
accelerate, you know, and pass somebody, that's when I need to just take
control of my car.
I think the best models are the ones that have best of AI and customization.
Can you give us examples, like what's a model, like could you name one, that
someone could find in use?
We are working on the models, right, so there are companies that provide you
models, I think most of
the, most of the times you have the historical charts, right, the, like, Oracle
has weighted driven model,
where you go in, you pick, you know, 10 variables to say, my best customers are
the ones that
fall under this employee band 50 to 500 employees that are in the high tech
industry, karma,
manufacturing industry, karma, healthcare industry, you know, in US alone,
right, because I don't
do international and company sizes X, right, let's just say that is the model
and you put, you know,
point system and then your point, you score the remaining companies, right,
this is your 20,000 W
point, you score them and sort them in the, there was, you know, weighted order
and say, okay, here
my, if my capacity is 1000, then these are the top 1000 companies that I want
to go to market with,
right, that's a, that's a scoring model. The issue is, it's not taking
advantage of, you know,
the infinite variables that you have available, you know, in the AI model,
right, so I think the
way the world is going or the world is, is going to see success is, that you
have the hybrid model AI
superimposed by the GTM experts input. I'm curious. Do you have kind of like a
story of
one of these most successful moments related to that? Like, maybe you're tying
it to a specific,
like a deal that you've seen, you know, that, I don't know, propelled you in
further or something
like some type of success story, people love success story, I like success
story, that's been pretty
depressed lately. So, yeah, absolutely. So, you know, I'll give you our own up
until when we started
the business, you know, we kind of grew very, very fast. We went from a million
dollar first year
to three to six to 12, you know, so we didn't, we say like, and the segment
that we are in, everybody needs,
you know, high quality data, high quality intelligence to go to market and in
2019, when we started
the business to, you know, 2022, everybody was growing because VCs were pouring
money, we were all
buying each other's products and life was good. But then in the market kind of
slowed down, we were
forced to look into this whole ICP Intel by Z. You know, we can survive, we can
survive to
bring and customer where the customer acquisition cost is on or and or second,
bring a customer
that churns, right? So, we had to go focus and then we went to this exercise,
we went to this exercise,
we co-hosted our customers, we co-hosted our close one, close loss or pipeline
velocity data, and we zeroed
in on say, okay, for this year, right, for this year, our focus is on these 20,
000 companies,
right? We could go after 200,000, but you know, we'll be lost because of the
effectiveness of our limited
dollars, our go-to-market dollars, would be very low. So, we focused on, okay,
here are the companies
where if we put all our go-to-market efforts, we're going to have higher
success and we saw that,
within four months, we saw over 20% you know, increase in the pipeline, you
know, over 16% increase in
the wind rate, our ACV event from $14,000 to $17,000, right? And, you know,
those customers are much more
happier. We find out the churn numbers here, you know, as they come up for the
news, but we saw in
our own numbers and we use as a template for some of our customers and now we
are productizing it,
you know, sometime, you know, early next year we are going to bring the ICP and
tell us what we are
calling it. And our goal here is to make sure that every go-to-market team goes
to market
efficiently, right? By using the data-driven approach to focus on the ICP.
Officially and people first. People first. Like, people is business, businesses
people.
And it's interesting, we don't have time to unpack this, but like, you know, we
do say this and I
think actually, Nick and I may you say it too much like people always buy for
people, but it's
actually not the case, because there's so much of what we do even in B2B now
that we buy through a
screen thanks to product-led growth, right? E-commerce. So it's like, but you
could argue then, well,
someone influenced you to buy that. And that's where the whole idea of like,
you know, the rise of
influencers, thanks to social networks, all this other stuff. Anyway, that's a
conversation for another
day wrapping up. I know I'm gonna know you've given us a lot of time, so thank
you for that. A CEO
today. They're trying to up their game around ICP or just go-to-market. I'll
give you the choose
your own adventure question again. It could be ICP or later go-to-market and
maybe time together. Like,
what would you recommend to up their game as a CEO? Like, and so it's really
like, you know,
maybe not their game, but like the company's game, as it relates to the go-to-
market or ICP.
See things. Do it quickly, adopt a tool, be data driven, and do it more
frequently. Okay?
So you're saying I give you twice a year for a company that's over five million
I definitely use twice a year, you know, because depending upon your products,
like if you have a
PLZ motion and you can get the data points within 60 days, then, yeah, do it
once a quarter,
right? But for SaaS businesses, they're going to market with sales that motion.
Right? Then you need at least six months of time to see the proof point.
Okay? Manosh, thank you very much. We'll see you at an event coming up soon,
because if you didn't
know, Manosh travels a ton. He's a pilot. And, you know, if you're really nice
to him, he might
take you up on his plane. Next time I'm in Boston, people.
I love it. I love it. Manosh, thank you so much. Thank you.
Thank you for joining us for this exclusive edition of GTM News Desk. If people
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Keep the people first, everybody!