MARTIN OMANDER: Hello.
My name is Martin Omander and I welcome you
to "Google Root Access," the show featuring
actionable startup advice.
My guest today is Mani Doraisamy,
founder of the startup Guesswork.
Mani, tell us a bit about your startup.
MANI DORAISAMY: We are a machine learning startup
that helps to qualify leads and increase customer conversion.
We do that by building predictive intelligence in CR.
MARTIN OMANDER: Predictive intelligence
in customer relationship management systems.
MANI DORAISAMY: Right.
MARTIN OMANDER: How come you decided
to work on that problem?
MANI DORAISAMY: We found this problem
that the leads from the internet marketing channel
doesn't convert into customers very well.
For example, if you look at real estate agents,
they get like a hundred leads per day.
And out of the 100 leads, 90 leads
are from internet marketing, like Trulia and Zillow.
And 10 of them are from traditional channels.
But the problem is, out of the 90 leads, only five of them
convert into customers.
On the other hand, out of the 10,
the same five leads convert in the traditional channel.
So very often, we see real estate agents
and the small business owners think that internet marketing
leads don't have serious inquiries,
and tend to ignore them.
MARTIN OMANDER: Oh.
And then they got rid of half of their serious leads,
right there.
MANI DORAISAMY: Exactly.
Even though it can double their sales,
they start ignoring them.
So that's how we decided to build Guesswork.
So we started building this machine learning service
that predicts which of them are serious inquiries
and which of them are casual inquiries, so that they
can focus on the serious ones.
And we desire to build it part of the CRM.
MARTIN OMANDER: I see.
So let's talk a bit about objection handling.
You are selling to CRM vendors, I understand.
And they are technically astute.
And you talk to them about machine learning.
Do they ever tell you that, hey, why should I
go with a small startup and their machine learning,
when there are big players like Google, and IBM,
and who knows who else, is doing machine
learning stuff with more resources?
Does that come up and how do you respond?
MANI DORAISAMY: Very often.
So in fact, you can't compete with Google
on machine learning.
They have years of head start on machine learning.
Have hundreds of engineers working on machine
learning every day, right?
So we don't compete with them.
We leverage them.
So we build on top of Google Prediction API.
Similarly, we build on top of App Engine, and BigTable
to scale for huge volumes of data.
So in fact, whenever we talk about using Google Prediction
API for machine learning, most of the objections
about technology already stop from the customers.
MARTIN OMANDER: Oh, good.
That's a good objection handling technique, if it just stops it.
So I could see a potential other objection coming up, then,
with somebody you're selling to.
The customer saying, oh, you're using Google Prediction API
and Google BigQuery.
Why don't I just do that myself?
MANI DORAISAMY: Exactly.
So our value comes from the rule engine
that we are built on top of, Google Prediction API.
For example, think about the same real estate example.
If a customer asks for an apartment in Palo Alto,
right, the machine learning algorithm
can come up with an apartment recommendation, right?
But then that apartment could have been sold out.
So the machine learning doesn't give that intelligence by
itself.
A rule engine which understands that business context,
and then decides to pick the next-best alternative,
is very important for such cases.
That rule engine is our IP that we have brought into the table.
MARTIN OMANDER: All right.
And so you're complementing the machine
learning with the rule engine.
MANI DORAISAMY: Exactly.
MARTIN OMANDER: And you are good at building rules engines,
because you've been doing that for a while.
And then there's something about focus
and the customer leads there, as well.
Tell me a bit more about that.
MANI DORAISAMY: Sure.
So we always know and talk about technology, because, I think,
there is part of the stakeholders who
are interested in-- I mean, like for example, [? CT1s ?]
in a CRM company-- who was interested in the value we
bring on in the technology portion.
But if you have to convince the business guys,
then we have to talk about what value we bring
and what business problems we solve.
So we always talk about how we want to transform CRM
from being a record-keeping system into a customer
conversion agent.
That business value is what convinces the stakeholders
in CRM who are business guys, right?
Who are focused on solving a business problem rather
then just a technology problem.
So you have a combination of both objection handling
for the technology stakeholders as well as
business stakeholders.
And that's very important when you look at a target market
where you have both stakeholders.
MARTIN OMANDER: Oh, I see.
So into a sales meeting, you come armed with here
is why this is good for your business.
And no technology discussion there.
And then when the technology-- the CTO
and so on, they kick the tires, you
can tell them that this is good stuff.
It will hold up.
MANI DORAISAMY: Exactly.
So I think it's always about getting the entry into a sales
cycle where you convince the business guys about the value
proposition.
And then later on in the sales cycle
where you talk about how good your technology is
with the technology decision-makers, right?
So we have both gatekeepers that you need to cross.
MARTIN OMANDER: Aha, right.
And either one could stop you.
So you'd better be prepared for both.
MANI DORAISAMY: Exactly.
MARTIN OMANDER: Great.
So, Mani, you've been doing this for a while with your startup
here.
What would your advice be for other startups building
on somebody else's technology?
And how to think about objection handling,
and how to handle objections in sales situations?
MANI DORAISAMY: I think if you look
at choosing somebody else's technology,
it has to be always based on how it adds value to the customers,
right?
Very often, we see people choosing a technology
because they get marketing mileage, right?
Typically, there is this business development guy
who is responsible for partnership.
And he finds that he'll get more customers
if you have a big-brand logo in their website.
MARTIN OMANDER: Oh, the logo in the website.
Yes.
I worked for a couple of startups like that.
MANI DORAISAMY: Exactly.
So it's this you scratch my back,
I scratch your back sort of thing.
And that's the worst way to choose a technology.
I think the best way to look at choosing others' technology is
to find out whether you would choose
that technology irrespective of the marketing or sales
mileage you will get out of the big brand that
provides you that technology.
I think that is the one that will provide
long-term benefit to the customers.
And that way you will win, irrespective
of what the other company does for you.
MARTIN OMANDER: And you'll be able to handle the objections
better in the sales situation.
MANI DORAISAMY: Exactly.
And also I think the objection handling is not just using
somebody else's technology.
It's also about bringing a complementary strength.
It could be technology [INAUDIBLE].
For example, in our case, we bring in that rule engine IP
into the table, right?
It helps because we have 14 years of experience
in building rule engines already.
During the initial stages of a startup,
customers don't buy the product.
They buy you.
Founders are the product, right?
MARTIN OMANDER: Yeah.
The product might not be mature, might not even exist, right?
MANI DORAISAMY: Exactly.
So you make a personal guarantee that you
will deliver the results, irrespective of
whether you have a product or not, right?
MARTIN OMANDER: Yeah.
MANI DORAISAMY: So I think this notion of founder to market fit
is quite popular in the investment community.
Chris Dixon popularized it.
But I think it's equally important
during the initial stage of the startup,
because you convince the customers based
on the founders' strength, and not just on the product.
MARTIN OMANDER: Great.
Well, thank you for coming on and sharing your experiences
with us, Mani.
MANI DORAISAMY: Thanks, Martin.
It's my pleasure.
MARTIN OMANDER: Thank you for joining us.
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