0:01

so , so build x . How , how was

0:03

that for you , chloe ?

0:06

uh , it was good , interesting

0:08

, we learned a lot . Um , probably

0:10

not a place we would head back to

0:13

, it's just not our audience , but uh

0:15

, it was really interesting to get

0:17

to know a bit more about the city of vancouver and

0:20

, um , get to know about

0:22

, you know , a lot of the sub trades

0:24

on the exhibition floor and

0:27

building product manufacturers . So , yeah , it was . It

0:29

was great to just honestly walk around and be

0:31

amongst the people . It feels

0:33

like been a while since COVID .

0:36

I have to say I really liked the fact that you are

0:38

a very motivated

0:41

entrepreneur . It's very cool . You

0:43

came up and you're like , hey , let's , let's talk

0:46

, let's do this , and you're like hey , let's talk , let's do this . I'm

0:48

like , yeah , why not ?

0:48

I've heard of you guys before . I mean you're the founder , right ?

0:51

Yeah , no that's awesome , that's cool

0:53

. So , yeah , I mean , buildx was awesome for us . We

0:55

were there , as you could tell . We had a lot

0:57

of interest . We've

1:00

going out and , yeah , it's too bad we didn't

1:02

know you sooner . We could have done one there

1:04

. But this is better , because I

1:06

shouldn't say better . Build x was awesome , but

1:08

it's better the fact that we can have a little bit of a longer

1:10

conversation and really dig

1:13

into stuff . I got a whole bunch of points

1:15

here to to chat with you about your business

1:17

and , uh , you know , so people can

1:19

really understand . You know benefits

1:21

etc . And you can take me through a platform and all

1:23

that kind of stuff . So , welcome

1:25

to the site . Visit podcast leadership

1:28

and perspective from construction

1:30

with your host , james

1:33

balkner . Business

1:37

as usual , as it has been for so long

1:39

now that it goes back to what we were talking about

1:41

before and hitting the reset button . You know , know , you

1:43

read all the books you read the evening . You read Scaling

1:46

Up , you read Good to Great . You know I could

1:48

go on . We've got to a place where we

1:51

found the secret serum . We

1:53

found the secret potion . We can get the workers in

1:55

. We know where to get them .

1:56

Once I was on the job site for a while and actually

1:58

we had a semester concrete and I ordered

2:00

like a green finishedished patio . How

2:02

fun did this HLH taste ?

2:04

I was down at Dallas and a

2:06

guy just hit me up on LinkedIn

2:08

out of the blue and said he was driving from

2:10

Oklahoma to Dallas to meet with me because

2:12

he heard the Faber Connect platform

2:15

on your guys' podcast . Own it , crush

2:17

it and love it , and we celebrate these values

2:20

every single day . Let's get down to it

2:22

, let's

2:25

do it All right . So here we are

2:27

with Chloe Smith . Chloe

2:29

, hello .

2:31

Hello , thank you for having me , James .

2:34

Well , you're very welcome . So you are in Calgary

2:36

.

2:37

We are . Yes , we are stationed

2:39

in Calgary . However , my team

2:41

is across Canada , into

2:43

the UK , into the States . We're all

2:46

over the place .

2:47

So you have a well-distributed

2:49

development team .

2:51

Yeah , we try and make sure that

2:53

I mean talent can come from anywhere

2:56

. We try and make sure to

2:58

hire talent locally because that's always important

3:00

, especially in a growing market , and

3:03

we're super long on Calgary , so that's

3:05

a , you know , that's a . That's

3:07

a big driver for why we would grow talent here

3:10

. But in a startup environment

3:12

, we try and pull talent from everywhere . It also gives

3:14

different perspectives , helps us make

3:16

sure we're not insulated , and especially

3:18

in the construction market where we're selling , you

3:21

know , cross Canada across states

3:23

. Uh , it's important for us to get

3:26

kind of a diverse perspective in-house , um

3:28

, so that we're not potentially alienating or

3:31

creating models that might have specific biases

3:33

that we're not aware of biases wow

3:36

, the b word .

3:37

So , uh , you got a little bit of a james bond

3:39

film villain thing going on . You're stro stroking . Yes

3:42

, we will take over the world .

3:45

Yeah , I have a cat . Is that your cat ?

3:47

Your cat just came by for a visit .

3:49

I have a little great cat , it's now the cat visit

3:51

everyone .

3:52

Okay , so this is cool . So how

3:54

do I pronounce the name of the brand ? Is it

3:56

Mercator ?

3:58

Mercator .

3:59

Mercator .

4:00

It comes from the Mercator projection . So

4:02

your Google map , the map that you're most

4:05

commonly seeing , is

4:07

a Mercator projection . So it's the

4:09

we kind of simplify it and make it instantly

4:11

usable for our users to find early opportunities

4:13

of new projects .

4:32

Cool . Ok , so without putting

4:34

you on the spot with the whole elevator pitch , you

4:36

know the whole startup thing , just just

4:38

give us , like if we were at a party

4:40

. I'm like , hey , so you know , mercator

4:42

, what does it do ? Like quickly , like

4:45

what is that ?

4:47

Yeah , so we do early project

4:49

detection . So we tracked land development

4:51

over time and then RAI stitches all

4:53

of that together so that we can detect

4:55

early project opportunities and put you in front

4:58

of projects at any

5:00

stage that you sell at . And so

5:02

the biggest value prop that we see

5:04

from our customers is that one it reduces

5:06

pursuit time dramatically . I

5:09

just was on a customer call today where

5:11

the customer said you know , something

5:13

that would have taken years , took 15 minutes , to

5:15

do in our platform All of that

5:17

research one place combined together . The

5:21

other thing that you know we seem to

5:23

generate a lot of value with our customers

5:25

is identifying projects that they would

5:27

have never known about , um , so getting

5:30

projects , new developments , um in front

5:32

of them at a stage where they can actually

5:34

build relationships , um and engineer

5:36

in value and trust instead

5:39

of constantly being compared to , uh

5:41

, their bottom line and and cost . And

5:43

so we primarily work with general

5:45

contractors today , but in the future

5:47

here we'll start to open up outside

5:50

of just the GC realm and serving more

5:52

stakeholders across construction .

5:54

Cool , okay , so I have to

5:56

ask the million dollar question . Why did

5:58

you start this ? Like

6:00

what , you're crazy . Like

6:03

, what was the ? What was ? Like ? What's the ethos

6:05

? Not the ethos ? What do you call it ? The Genesis story

6:08

? Like what , what made you think that there ? A

6:10

, there was an opportunity ? B why did you think

6:12

you're the person to do it ? And C

6:14

? Um , like

6:17

, who are you ? Like , where did you come from ? Like , what

6:19

is . What is this whole ? What's the Chloe Smith story

6:21

? Tell us .

6:23

Sure , sure , I mean probably very

6:25

similar to you , james . I mean , first off

6:27

, I believe the

6:30

statement is if

6:32

you're founding a company , it's usually because there's something

6:34

wrong with you , something like that . So

6:38

we're a little off our rocker to begin

6:40

with , no , but

6:42

I started , so

6:45

my background's in data strategy . So you come from brand

6:47

strategy . I come from the same space . I just come

6:49

from the marketing and advertising space .

6:51

Interesting Okay .

6:54

Working for some of the largest marketing

6:56

and advertising firms globally , working

6:58

on some of the largest brands in Canada

7:01

and the US and globally . And

7:03

specifically , I had the opportunity

7:06

to be a head of innovation at

7:08

a very young age , kind of given

7:10

carte blanche to build the ideas that

7:12

I wanted to build with the team I wanted to build . I

7:15

had restraints on budget so I had to be

7:17

creative , but one of

7:19

the products that we had developed kind

7:21

of sparked this concept of we

7:24

were working with our business development teams and we were bringing

7:27

in all of the data and insight

7:29

that we needed . Every single time we went and

7:31

pitched a new customer and keep in mind

7:33

, we weren't vertical

7:36

specific , so we would go automotive

7:38

to healthcare , to consumer brand

7:41

and back right , so we would be

7:43

constantly bouncing around different industries

7:45

and to have to learn those industries really

7:47

quickly to be able to pitch a really unique

7:49

brand strategy was quite difficult

7:52

, and so we ended up building a platform that

7:55

automated a lot of that work and that gave me , you

7:57

know , kind of pause for thought and , coming

8:00

from a construction family , I didn't think

8:02

I'd come back into construction . I've

8:04

never been in construction in the first place . I

8:07

remember my dad bringing drawing packages home

8:10

and marking them up at

8:12

the dining room table . But

8:14

I've never been in construction , and

8:16

so we ran a market research

8:18

study where we had the opportunity to

8:21

speak to agriculture , manufacturing

8:23

, transportation , healthcare

8:27

, insurance , finance , construction and construction

8:30

was really the group when we started talking about market

8:32

research and understanding your market , where the projects

8:34

come from . They're really the

8:36

ones that said , look , if the clients aren't working

8:38

with us and the spend isn't happening with us

8:41

, we really have no idea where

8:43

that work is or who to contact

8:45

, where to find it . And so we started

8:47

to break that problem down into okay

8:50

, could we stitch together the

8:52

entire construction process

8:55

, not looking at projects , because I think this

8:57

problem has been addressed before from

8:59

the perspective of let's have the industry generate

9:02

the data ? Well , can we have the data

9:04

generate the insights for the industry

9:06

? And so that's really where we said

9:08

, okay , well , let's take what we were

9:11

doing in the marketing , advertising space

9:13

and mapping different markets and

9:15

see if we can actually map the

9:17

construction market using the data that

9:19

it produces .

9:21

And you do this for a customer while you're

9:23

still in advertising . First , is that how

9:25

that works ?

9:25

Oh gosh , no , oh no , you

9:27

know , you take the big leap right .

9:29

Okay , so that's yeah . Okay , let's

9:31

look at the Grand Canyon leap here and just talk

9:34

about that part

9:37

. So you left the advertising company

9:39

and then how did you go

9:41

from there with zero tech

9:44

left over and you had to start

9:46

a whole stack yourself and then get this deployed

9:48

. Like how long did that take ?

9:52

Well , it took about a year

9:55

I

9:58

want to say maybe a year and a half

10:00

before we actually had something built .

10:03

So MVP was kind of like like took about a year and a half

10:05

Nice , and did you so ? Did you go and get funding

10:07

? Like how did all this work ? How did you pay for it ?

10:10

No , in fact , actually I had a really

10:12

great mentor , um , who is

10:14

still a mentor of mine today who said

10:16

if you're going to do this , make sure that

10:19

you can pay yourself for two years

10:21

, because your company will not pay you . You

10:23

will not make enough capital in order to pay yourself

10:25

. And so I started consulting

10:28

, and that was a huge leg

10:30

up , because the first milestone

10:32

was I needed to get myself financially

10:34

secure . The second milestone

10:36

was I needed to find

10:38

a market , build a product and get one

10:40

customer signed on , and then after

10:43

that it was I needed to go and figure

10:45

out how to get funded . And so those were

10:47

kind of big milestones that I'd

10:49

set in front of myself at the start .

10:51

So did you go into some accelerator program somewhere ?

10:55

No , I mean accelerator

10:58

programs work for some , but

11:01

at some point you

11:03

have enough industry experience . You have enough

11:05

experience building new things that

11:07

an accelerator will just tell you what

11:10

you already know , and there really

11:12

wasn't a lot of value for us to go down that

11:14

path . Now , if you're coming out of university and

11:16

you're going and you're building something , yes , absolutely

11:19

. You have no foundation . However

11:21

, if you're , you know , if you've been in industry for many

11:23

years , you understand how businesses work , you

11:26

know , you have you , you have an idea

11:28

on how to build something from scratch . They're

11:31

not going to tell you much more than what you already know .

11:33

Okay , so that could be a hot take so

11:35

so you went

11:37

to um to a

11:39

, to a like um , do you do

11:41

a friends and family round ? You know , you went got

11:43

a lawyer . You put your all your share packages together . You did all that . Do you do a friends and family round ? You know , you went got a lawyer . You put your all your share packages

11:46

together . You did all that . Do you do an offering somewhere

11:48

? Did you raise a little bit of money first ? How did that work

11:50

?

11:52

yeah , so we . So I would have quit my

11:54

my job in september

11:56

of 2020

12:03

. And we would

12:05

have . So we spent

12:07

about . I mean , we did all

12:09

kinds of stupid things . We thought we needed a website

12:12

first . We thought we needed to pitch and

12:14

raise money first . We didn't

12:17

really have a focus on a

12:19

proof of concept yet , so

12:21

we kind of meandered a whole bunch and

12:24

then , around kind of 2021

12:27

, the spring of 2021 , we

12:29

started raising money from friends and family . We

12:32

still hadn't had construction as a focus yet . It

12:34

was more of like a agnostic

12:36

, you know , market

12:38

intelligence platform that we were building off

12:40

of kind of a previous concept

12:43

we had raised . We

12:45

had raised 140,000

12:48

Canadian-ish

12:50

from friends and family . We got

12:52

our butts handed to us on a silver

12:54

platter by some investors that we approached

12:56

that will never talk to us again today . That

12:59

was a learning . But what we learned from

13:01

that was we needed to go talk to more people and

13:04

, specifically , we needed to find who

13:06

we were actually servicing . And

13:09

so that's where we ended

13:11

up running a market research study from

13:13

a good friend of mine who started her company

13:15

Cashew that does market research

13:17

studies for very affordable costs

13:19

for startups , and

13:22

they

13:24

helped us to find the construction

13:26

market . We needed the types of questions we

13:28

wanted to ask . We needed the space we wanted to be in . It was

13:31

business development , market

13:33

intelligence , and

13:35

that's really when we started to build POCs

13:37

for construction , so proof of concepts for construction

13:40

, and I tell you it was myself

13:42

only open

13:44

data and a bunch

13:47

of spreadsheets and some Tableau dashboards

13:49

and we would get our proof of concept

13:51

out there . And that's really when we started

13:53

to see traction . We started to see that we could generate

13:56

new opportunities

13:58

, new invitations to projects

14:00

for companies who would have never

14:02

had that relationship in the first place . And

14:04

so , from there , we then pulled

14:07

together a team . Over six weeks we

14:09

actually pulled together a team of contractors

14:12

from our past , so myself and my co-founder and

14:15

basically dictating the platform , and over

14:17

a solid three weeks

14:20

we worked from 8 pm to 4 o'clock in the

14:22

morning and managed to build the product

14:24

the first . And managed to build the product the

14:27

first MVP , so minimum viable

14:29

product , sold

14:32

it into our proof of concept customer

14:35

, who became our first customer . And then , all

14:37

of a sudden , we were facing the

14:41

fact that we had a first customer . We

14:46

had to make sure that the product could actually change and be modified according to what their needs

14:48

were .

14:48

Yeah , the customer customer led developments . It's

14:50

always interesting .

14:51

Exactly as well , as we were

14:53

like staring at $40,000

14:55

in our bank account , so we had to figure out how to raise

14:58

Right ? So , yeah , it was really

15:00

about getting thrown into the deep end .

15:01

Okay , so , and then , and then you did

15:03

you go to raise money after that ?

15:06

We did . We did . So I , I

15:08

actually took an approach that , uh

15:10

, learning or looking back now was , I

15:12

don't know what inspired

15:15

me . Um , but I

15:17

, I actually reached

15:20

out to the portfolio companies , the CEOs

15:22

of the portfolio companies , to

15:25

ask if they liked their investor

15:27

. And now , being

15:29

on the other side of that , that happened so

15:31

infrequently that it

15:33

was a pretty odd thing to receive

15:36

as another founder . And

15:38

so that ended up snowballing

15:41

a ton of introductions and

15:44

that momentum , and I learned how to create

15:46

, you know , a fear of missing out , some FOMO

15:48

while I was raising , and that

15:50

momentum helped us close a million just

15:53

a little over a million , uh , canadian for

15:55

our pre-seed round , and so we took that , built

15:57

a team out of that , and then yes

16:00

, so how many rounds are you in now , then ?

16:02

And then we can , then we can get onto the product .

16:05

Yeah , absolutely . So we just closed our

16:07

uh , we closed our seed round back in 2024

16:10

. Um , so we took that money .

16:12

Back in 2024 , this is 2024 .

16:14

Oh sorry , 2023 . Oh my gosh

16:16

, it's , still February .

16:18

See the problem with all you AI people . You're already in 2025

16:21

. So you're way ahead of all of us .

16:23

I know Um , we closed in 2023

16:26

in January , grew our team from five

16:28

to 15 and focused intently

16:30

last year on product market fit , and so , you

16:33

know , right now we are at a state where we

16:35

are delivering consistent value to our customers

16:37

and new customers in a

16:39

very reputable way , which is exciting for

16:41

us . I mean , it's one thing to have an idea

16:44

. It's

16:47

another thing entirely to see it grow and become something that is , you know , consistently valuable to

16:49

the people who are using it .

16:50

Okay . So for those who who haven't seen

16:53

Mercator work , so

16:55

essentially this is a you

16:58

focus in on a map and you figure

17:00

out exactly , you put in criteria

17:02

for what you're looking for I guess that's how that works

17:04

and then your

17:10

platform has aggregated , via

17:14

, I would guess , a whole bunch of APIs you've

17:16

probably implemented , and

17:19

then it brings that

17:21

into a machine learning model . Where

17:23

is this providing product , sorry , project

17:27

pins ? And then is

17:29

there , is there , is there basically a a

17:32

like

17:35

a profile ? So

17:38

how , how is each product sorry

17:40

, not product project categorized

17:43

, um in in the platform

17:45

for what a GC might want to see ? So I guess it's

17:47

a a developer's pull , developer

17:49

has , uh , uh , pulled a permit , and

17:52

then that gives them information

17:54

on do you know when a permit

17:56

is issued , Do you know when it's , when

17:59

it's , and all that kind of stuff . So just take us through

18:01

what that nugget of information would

18:03

be . The GC is like oh okay , good , I

18:09

can call ABC developer and say hey , do you guys have a GC for

18:11

this job ?

18:11

So imagine coming into a platform

18:13

that's already told you hey

18:15

, there's a project that is smack

18:18

dab in your wheelhouse .

18:20

Here is not only the information

18:22

Hang on a sec . So

18:25

when you say , do you create a profile for your like ICP

18:27

customer , as a

18:30

Mercator , like user , do

18:32

you ? So you put in , we look for

18:35

these types of projects . Let's say it's okay

18:37

, and then this will show

18:39

you your , your , your

18:41

ICP kind of projects within a map , and then also

18:44

other stuff that might extend your ICP to something else

18:46

very

18:59

much white glove , very hands-on , and we support them by building out kind

19:01

of their search criterias call them like a smart saved search

19:03

We'll really kind of detail up the type of profile

19:06

of projects that they have or that they're looking

19:08

for , and so that might be you

19:10

know what particular market are we interested in

19:12

or stage of the project that we're

19:14

interested in .

19:15

And keep in mind that we extend from like conception

19:17

through to pre-con , through to construction , then

19:20

post-construction , so really depends where

19:22

you want to sell into and

19:25

then we will help them get that

19:27

set up . They can do it themselves in the platform and

19:29

that starts to generate emails into their inbox

19:31

and so typically a Mercator

19:34

email . We target about

19:36

80% to 90%

19:38

relevancy in those emails of projects

19:40

that are actionable immediately

19:42

for you to start pursuing

19:45

. And so when you go from

19:47

your email to a project page so

19:50

basically you'll get a list in the

19:52

morning links to the Mercator

19:54

website that'll open up project

19:56

pages and in there you're seeing you

19:58

know who owns the land , you're

20:00

seeing any sort of permits that have

20:02

been pulled , you're seeing any real estate

20:04

information . You're seeing you

20:07

know other companies that are involved

20:10

, what role they're playing . You

20:12

can click through and actually see those entire company

20:14

profiles , other projects they've got going on

20:16

contact details . So we

20:18

usually say if it's not in your Rolodex . It's

20:20

usually in ours , because we

20:22

can take you from finding

20:25

out to seeing all

20:27

of the project details , as well as any

20:29

materials that have been created so far , like drawing

20:31

packages , for example , and

20:33

then into the company's profile . So if

20:35

I'm going out to lunch with someone , instead

20:38

of asking the question , hey , what

20:40

do you got going on , you're going , okay , you've

20:42

got these three projects going on , let's

20:44

chat about how we can help on these , and

20:46

you're having , you know , a more productive conversation

20:49

instead of just a discovery

20:51

one .

20:53

So how is this AI

20:56

? And not just , like you

20:58

know , categorized and

21:01

organized query searches Like how is

21:03

it AI ?

21:04

Yeah , so oftentimes I talk

21:06

about the fact that AI is . You either have it

21:08

above the surface or below the surface , and

21:11

we talk about that in terms of the

21:13

user experience . Right , it's either I'm

21:15

getting recommended something or I'm directly

21:18

interacting with a generative AI

21:20

tool , or it's

21:22

happening under the surface , in which case it is part

21:25

of what the like the data that's being created

21:27

. So keep in mind that we're in a space where

21:29

none of this data has been created . In

21:31

the past , when I worked in marketing and advertising , yeah

21:34

, we definitely had data sets that were

21:36

funneled to us via API . In this

21:38

instance , we're sourcing from

21:40

government , we're sourcing from regulatory

21:42

boards , we're working with some paid partners

21:45

. At times , we're also generating

21:47

that data ourselves . So , the amount of ocular character

21:49

recognition , we do image recognition

21:52

, we do natural language processing

21:54

basically stripping out the

21:56

meat of all of these different data sets that

21:58

technically have no relationship

22:01

across them , and then we have

22:03

to then cluster all that together or

22:05

stitch it all together to be able to detect these

22:08

are . All of these activities are related

22:10

to the same project and all

22:12

of these companies are therefore all working with

22:14

one another on that same project . Therefore

22:17

, there's a relationship not only within

22:19

the activities , but also within the

22:21

companies .

22:23

Okay , so that's pretty , pretty

22:25

cool . So what's

22:27

your , what's your understanding of like how

22:30

AI will be applied in construction

22:33

in general ? I mean , you're obviously this is , you

22:36

know , the the procurement side sort

22:38

of procurement or project opportunity side . You

22:41

know , this is not about the actual building itself . Where

22:43

do you see this kind of going in

22:47

terms of AI with project management

22:49

?

22:50

I think I mean , look , I

22:52

think a big part of where

22:55

this will go is how quickly

22:58

we can understand the pieces

23:00

that make up AI , and

23:03

I think something that's really valuable

23:05

to talk about is and

23:07

we can go into the examples of , you

23:10

know companies that are

23:12

doing amazing things . I can

23:14

name a couple off the top of my head here

23:16

that are doing some pretty amazing things from

23:19

a resource efficiency

23:22

standpoint , from an

23:24

optimization standpoint , from just

23:26

honestly , like Document Crunch , for

23:28

example , reading your own legal

23:30

on site so you can understand what

23:32

you can and cannot do in a contract .

23:34

Did you listen to our podcast that we did with them ?

23:38

Did you chat with Josh ? He's like

23:40

I call him my big brother .

23:41

Yeah , he's awesome .

23:42

We're part of the same portfolio under

23:45

Sequoia Ventures Great

23:47

, great team . But it

23:50

really comes down to how do you think

23:52

from the lens of AI and that'll really

23:55

direct where this industry goes with it and

23:58

really we talk about . You know

24:00

, oftentimes when I speak about AI , I'm talking about

24:02

the different components . Right , we need

24:04

to start demystifying the fact that this isn't magic

24:06

. Right , we aren't at a

24:08

space where you know , ai will take

24:10

over our jobs , but it's here to

24:12

enhance us and augment us . And

24:15

I think the way in which you can think about AI

24:17

is a

24:19

lot of the things like machine learning , computer vision

24:21

, natural language processing , which

24:24

are the subsets , a lot of the subsets

24:26

of AI are all

24:29

mass pattern recognition . We're

24:31

just recognizing patterns within

24:33

machine learning and this is a gross simplification

24:36

, a gross oversimplification

24:38

. But with machine learning , we're doing

24:40

that with numbers . We're pattern matching

24:43

on numbers , right . With computer

24:45

vision , we're pattern matching on pixels . With

24:48

natural language processing , we're pattern matching on

24:50

words , and then generative AI is

24:52

taking those patterns and creating something new out

24:54

of them . Yeah , right , and creating something

24:57

new out of them . Yeah , right , so when we can

24:59

start to just create that kind of foundation of understanding

25:01

, then we can look at our problems and go , oh

25:03

okay , I would love for

25:05

a tool to be able to auto-populate

25:09

an RFP for me right

25:11

, based on all the RFPs we've done

25:13

in the past , right ? So now you've got

25:15

a tool like Project Mark , which

25:17

is a fantastic group that helps

25:20

do a lot of that auto population

25:22

and make sure that it's very easy for you to , you

25:24

know , generate your proposals

25:27

as well as track them in a CRM environment

25:29

and make recommendations on how

25:32

you can , you know , be more effective or more efficient

25:34

From . I mean , you've

25:36

got your Procores and your Autodesk . They're buying AI

25:39

like it's going out of style . They've

25:43

got so many tools and

25:45

so much data running through their

25:48

platforms that they're able to start cross-comparing

25:50

different companies and making recommendations

25:53

accordingly to improve

25:56

their operations

25:58

or point out opportunities or point

26:01

out risks in a project that they may have

26:03

overseen or that

26:05

may have gone overseen . So I really think

26:07

AI and construction is about , first

26:10

, how do we build efficiency and then how

26:12

do we start identifying things that could be human

26:15

error ? Right , and we can start

26:17

to bring that in as an extra layer of oversight

26:19

into what we're doing , and then from

26:21

there it really comes down to where

26:24

do we want to go as people here ? You

26:26

know , do we want to be the robots or do we

26:28

want , you know , do we want to be , you

26:30

know , wearing our Google vision or Apple

26:33

vision pros and you

26:35

know , being told what to do in the field ? Are

26:38

we looking at robotics to solve a lot of our

26:40

problems because we're dealing with labor shortages

26:42

? How do us , as

26:45

people , evolve in this process

26:47

, knowing that we have , you

26:49

know , automation at our fingertips now ?

26:52

Right . Well , I

26:54

mean , aren't we at the point where I mean we

26:56

can sort of remember back ? Well , I can't , at least is

26:58

like we're processors , for instance ? I mean , aren't we

27:00

at the point where I mean we can sort of remember back ? Well , I can't , at least is like word

27:02

processors , for instance ? I mean that was a huge thing for to be able to be , you know , typing

27:05

going from a typewriter , which

27:07

is you know you make a mistake and you get the whiteout

27:09

. I mean it's ridiculous To a word processor

27:11

that is , you know , checking your spelling

27:13

. It's doing all this kind of stuff that you couldn't do before

27:16

punctuation . And now we're at a

27:18

point where we have predictive

27:20

. You can see on your iphone , even when you're

27:22

sending a text , it gives you the suggestion

27:24

of what it thinks you're going to say and then you just press

27:26

the space bar and keep going . I

27:28

mean these kind of things are just a natural

27:30

progression of helping

27:32

us out . So I think that you

27:36

know , I think that the ai

27:38

is getting

27:40

a bad rap in terms of its

27:45

connection to taking

27:47

over humans versus tools

27:50

that can really help us . So

27:52

even when you talk about the , just

27:55

from , I can tell from the psychology

27:57

of the customers that we have , that

28:00

a lot of the entrepreneurs

28:02

in

28:05

construction started

28:07

their own company because of having

28:10

autonomy . They wanted freedom , they didn't

28:13

want to work for somebody , etc . A lot of the

28:15

people listening to this are those folks

28:17

and when they hear

28:19

, oh well , pro

28:21

core autodesk , they're taking a whole bunch of information

28:24

and then , you know , comparing

28:26

it , they're like , well , hang on a second , this is all my stuff

28:28

, this is my stuff and

28:31

I want to know that you're not actually doing

28:33

that to my stuff , because

28:37

I pay you to house

28:39

my stuff , not to use my stuff , even

28:42

if it creates value for you

28:44

as a company . So there there's

28:46

. I think that that's . Even though in

28:49

the long run , the long game , the

28:51

benefit would be for them , the

28:54

short-term risk is like , hang

28:56

on a second , I didn't approve that . Blah , blah

28:59

, blah , all that kind of stuff . So

29:02

I think we're in an interesting spot in terms of where AI is in construction , because

29:06

I've said this multiple times on the podcast

29:08

with multiple interviews is

29:11

when you see the dovetailing of robotics

29:13

and AI together , we're

29:17

going to see , because

29:20

the terrain continuously evolves . It's not like

29:22

manufacturing where you have a , you know you want

29:25

to make one car and then you switch to the

29:27

next tooling to make the next car . Well

29:29

, the tooling changes every day on

29:31

a construction site because the elevation changes

29:34

. You know all the environment changes . You

29:36

know different stages of the project . So you

29:38

know once everything is bim and

29:41

which I don't know how long that's going

29:43

to take for everything to be bim

29:45

modeling . I mean luke forrest we had on at

29:48

from autodesk at the um at

29:50

buildax and he's like I can't believe

29:52

how many people are not using 3d

29:55

models .

29:56

It's like well , not

30:03

using 3d models .

30:03

It's like well James 2021 was the year that most construction companies

30:05

got a CRM .

30:06

I know from the world that we come from that

30:08

was like that was 2008

30:10

. Right In our industry

30:13

, yeah .

30:13

Yeah , for sure .

30:14

So I mean we are . I

30:17

think . I think it comes down to a couple

30:19

of things right , we've

30:22

got and

30:24

this is one of the reasons why we went into construction

30:26

is because it's one of

30:28

the last industries that had haven't

30:31

become tech companies

30:33

right , if you look at all

30:35

of these other industries , they've had to

30:37

hire their own analysts and their own data

30:39

scientists and started to build their own developers

30:42

and and and create their own

30:44

products . And we and we

30:46

haven't and I think I think there's

30:48

challenges in that there's a lot of small

30:51

players and the accessibility

30:53

of technology , just the understanding

30:55

of it . I mean , canadian government right now

30:57

is doing a digital

30:59

adoption program where they're literally paying

31:02

people to go out and help small

31:04

businesses become more digitized . Because

31:07

that's what's ? It's not the

31:09

first 20% that accounts

31:12

for 80% of the GDP

31:16

, it's the tail end , it's everybody

31:18

else who's not on it yet . And when

31:21

you get somebody like that onto one of your projects

31:23

, now you're dealing with archaic

31:25

systems together with your you know existing

31:27

systems . So now you've got , you know , 20

31:29

odd different companies all coming together with

31:32

different , different tools . We

31:34

were at Built Worlds back in 2022

31:36

. And one of the common sayings was we are

31:38

the best industry at collaborating , but we

31:40

actually suck at collaboration . You

31:44

know our tools aren't the same

31:46

. We're not supporting each other that way , and so

31:48

I struggle

31:50

with this concept that you know we are

31:53

. If only we could

31:55

all get onto the same systems . If

32:00

only we could all get onto the same systems . But it's because it's it's it's a foreign

32:02

concept to most people who've started companies out there in this industry

32:04

. You do not need a prerequisite to

32:07

understand tech in order to start

32:09

a construction company , and that's okay

32:11

. And so that's where I I

32:13

always say come back to your vendors and you

32:16

know . These conversations are important because

32:18

if you're scared of what your vendor vendors doing with your data

32:20

, you need to , you need to ask questions and know

32:22

what , what your rights are . Right

32:25

. There's too many companies out there taking advantage

32:27

of the fact that you know smaller

32:30

or you know folks

32:32

that aren't as educated in data and what

32:34

can be done with that data , are

32:37

basically consuming

32:39

that information or taking that data , storing

32:41

it themselves , processing it in a way that's

32:43

, frankly , you

32:45

know , not respectful of the person giving that

32:47

data in the first place , because they don't understand

32:49

it . So I think it's on the vendor side , but

32:51

I also think conversations like this help

32:54

educate the industry of you

32:56

know what can be done with that data

32:58

so that you can ask better questions , and smarter

33:00

questions , to your vendors .

33:02

Yeah , that's um . Can we ? Can we

33:04

um chat about your platform a little bit and just

33:06

and just look at the the opportunities

33:09

for um , for

33:13

sub trades to be looking

33:16

at ? You know potential work and sort

33:18

of where things are going . So

33:22

do you have information about what

33:26

? I'll give you an example . So

33:29

if you know that a company

33:31

is going to be using frameless glass

33:34

with you know a

33:36

lot of metal hardware and

33:38

that's a specific of type of specific type of glass

33:40

company that's going to do that kind of cladding , are you , are you

33:42

going ? Does it say that ? And do you

33:45

have detail like submittal

33:47

plans that have all of the

33:49

details of the project

33:51

as it evolves ?

33:54

we're still early days in that , and so that's

33:56

why we've kind of focused very

33:58

upstream in the

34:01

conception stage , the pre-con stage or

34:03

somewhere else . We want to be able to bring it

34:05

in and process it so we can stitch

34:23

that information together . So we are just

34:25

kind of at the cusp of starting

34:27

that work right now . But in the

34:29

future the idea would be that you know

34:32

, a building product manufacturer , sub-trade

34:34

could come in and say , hey , who's

34:36

recently won this project or

34:38

who might be doing work of

34:40

this type , or leading work of this type

34:43

? Or can I even search some specs

34:45

to see what's getting specified right

34:47

now ? And so , moving

34:50

into that realm , I think it's going to be really critical

34:52

for us to tell the whole story , not just a

34:54

portion of it , not just the pre-con portion

34:56

or the conception portion , but the whole story

34:58

of a project and

35:00

of all projects in a market .

35:02

Interesting ? Yeah , because currently

35:04

, right now , you're using public information

35:07

.

35:10

No , so which part of ?

35:11

it is private or not . Should say private

35:13

, but which do you have to gain access to ? Which do you

35:15

have to gain access to ?

35:24

Yeah , so for some instances we actually

35:26

have to be a licensed realtor in order to get

35:28

certain information . So that might be when

35:30

we get into things like land transactions or deed

35:32

transactions , for example

35:35

. Sometimes we actually

35:38

purchase data from aggregators where

35:40

they have custom relationships , where they've

35:43

created a certain type of data

35:45

set , so in those

35:48

cases those

35:52

are paid but would allow

35:54

us to then process , say , things

35:56

like PDFs , to

35:58

extract additional data that we would need

36:00

in order to paint the picture of

36:03

the project .

36:04

Cool . So right now , when

36:06

you go

36:08

and pitch a customer , I saw a book

36:10

, a demo button on your website . So

36:13

what is the ? You're

36:15

calling GCs , typically Certain

36:18

size GCs .

36:20

Yeah , so we work really well for

36:22

general contractors that are over 100

36:24

million in revenue , so that mid-range

36:27

or that mid-market , so

36:29

100 million to 500 million size . We can

36:31

go higher than that . We certainly have some

36:35

large enterprise customers on our platform

36:37

today . I would say the challenge is when

36:39

we go smaller than that at least for right

36:41

now we get a lot of interest

36:44

. However , those companies

36:46

don't have dedicated business

36:48

development team members .

36:49

Right for retail yeah .

36:51

So they end up becoming project

36:54

managers who are doing BD work and then , as a

36:56

result , will either churn

36:58

or become more seasonal

37:01

users , and that's difficult

37:03

as a startup trying to build up

37:06

consistency and revenue

37:08

and things like that .

37:09

So what is the pricing model ? How does

37:11

that work ?

37:12

We do fixed rate . We do fixed rate because

37:15

right now we love to learn

37:17

from our customers .

37:17

Like fixed rate . What per ?

37:18

month , no annual

37:20

. We do an annual fixed rate contract . It

37:24

usually I mean it'll include

37:26

typically unlimited features

37:28

that we launch . We typically give

37:30

unlimited seats . That's super

37:32

important . We're learning , actually , that right

37:35

now , if you can put Mercator in the hands

37:37

of your discipline leads , you can actually Mercator in the hands of your discipline

37:39

leads . You can actually start decentralizing your deal

37:42

flow so your business development people are focused

37:44

on projects that they can or like

37:46

pursuits that they can go and win , instead of doing

37:48

a lot of the research , because you've got the whole organization

37:50

tapping into Mercator on a regular basis . So

37:53

that's really useful . And then we're

37:55

also starting to open up geographies . So

37:57

right now we're in Vancouver , Edmonton

37:59

, Calgary , Toronto and the Canadian

38:02

markets and we're pushing pretty heavily

38:04

in Austin and the States . But we'll start opening

38:06

up Dallas and Houston and really focusing

38:08

in on the Texas market first and

38:11

then starting to grow across the United

38:13

States , probably later this year .

38:16

So without naming any other names , because

38:18

we don't like to talk about competitor , or maybe you do

38:20

, but is there anyone doing this kind of like

38:22

you are right now ?

38:26

No , and I think that that's what has

38:29

always really shocked me . Frankly and

38:31

granted , you know , going into this and being

38:33

almost four years into it , it is

38:35

not an easy task

38:38

. It is incredibly difficult , requires a very large team . It is not an easy task . It is incredibly difficult , requires

38:40

a very large team , requires a lot

38:42

of upfront investment for us to

38:44

do what we're doing , because we're

38:46

really digitizing an industry , like we're digitizing

38:48

word of mouth in construction , with

38:51

data sets that have never been created before , and

38:54

so we have to go out and create those data sets . So

38:56

, really , I mean , you've got your downstream

38:58

bid boards , who we hope

39:00

to partner with someday as

39:02

well and are already starting to partner

39:05

with . We've got you've

39:07

got your Zoom Infos or your Dun

39:11

Bradstreet , which are more kind of your contact

39:14

information but lack the construction side of

39:16

things . And then you've got a lot of locally

39:19

. You've got a lot of development

39:21

boards or like permitting

39:23

boards , which are helpful but

39:25

don't share the like , don't give you

39:27

the rest of the context that you can get just

39:29

a piece of the story . So it's

39:31

happening in fractions but

39:33

not as a whole like we're doing it .

39:36

Interesting . Okay , yeah , I can think

39:38

of a number

39:40

of customers that we have that would use your platform

39:42

. You probably already have them as

39:45

customers .

39:46

We'd love to meet them .

39:48

Yeah , no , it sounds . Yeah . I mean the biz dev

39:50

side is yeah , it's

39:53

kind of interesting . So actually

39:56

, christian , who used to be on the you know the

39:58

host on the podcast he used to be with SightMax we

40:01

should reach out to him for sure .

40:04

Yeah , definitely .

40:04

Yeah , I'll definitely do an intro there . So

40:08

, yeah , it seems like so

40:13

. On

40:15

the biz dev side , I guess

40:17

it really is so . To get to the sub dev side , I guess that's really it really

40:19

is so to get to the , the sub

40:21

trade side , you kind of need more detail

40:23

, right For them to even know what the project's going to

40:25

be . And then and

40:28

I guess it also depends on on what the

40:30

the market is like , too , right , if it's

40:32

a the trend of

40:35

I mean , right now , you

40:37

, you can't get sub like

40:41

we can't get them on the platform no , no

40:43

, no , no , no . Not that , no , it's . It's difficult

40:46

to oh , like you can't get sub trades in the market

40:48

no , because there's just there's too much

40:50

work and there's not enough of a particular you

40:52

know division of construction or typical type and

40:55

you know they're just saying no to projects all day long because

40:57

they just can't take all the volume . So

41:00

you know when . But

41:02

when that flips is when

41:04

they're like God . You know we need

41:06

business . It used to be . We had

41:09

to keep turning down business because we couldn't handle it

41:11

.

41:12

When that changes and it becomes sort of a certain

41:14

you know the typical paradigm of buyer-sellers

41:16

market , that

41:19

ebb and flow is actually really important , and that's

41:21

why it is especially for your business flow

41:26

is actually really important , and that's why it is especially for your business

41:28

and um , you know , for for us , I think the way that we address that is um , when

41:30

, when you're up and you've got more work than

41:33

you know what to do with , then you're picking the

41:35

right work right , you're picking

41:37

the right partners to work with , the folks that don't

41:39

have a bunch of leans out on them or

41:41

you know that actually pay their people , for example

41:44

, or don't have a lot of site safety incidents

41:46

. When the market is down

41:49

and you're trying to hunt for work , then

41:51

you're able to find a lot of that new information

41:53

in Mercator , even though it is like few

41:55

and far between . And so that's really

41:57

why I see , you know , the progression of

41:59

where we're headed isn't necessarily sticking

42:01

in lead generation , but rather in

42:03

market intelligence and kind of growing and

42:06

giving more of an understanding of who's doing

42:08

good work . And we do a lot of that with the cities

42:10

, actually helping them understand who does who

42:12

, who builds great buildings , who

42:16

could use a little more education , and

42:18

how do we structure policy to better support

42:20

that ?

42:21

Interesting . So what kind of information from

42:25

a developer point of view . So

42:28

let me ask you this , so the

42:30

information you have for

42:33

a developer and then you have the

42:35

information for , do you collect

42:37

who actually won

42:40

the job after won the

42:42

job after Yep ? Okay , so you basically

42:44

have both pieces of information there

42:46

. So , on the developer , do you have a rating scale

42:48

of how good to poor

42:50

they are ?

42:52

That'll come with time . So what we're working on

42:54

right now is improving the quality of our company

42:56

profiles and getting them to be more

42:59

specific per kind of stakeholder

43:01

type throughout the construction

43:04

lifecycle , and so starting

43:07

to then beef them up and say , okay , you

43:09

know , are we seeing , say , for example

43:11

, liens that are going out , or what

43:13

are their financial records looking like ? How

43:16

many job postings do they have out ? Really

43:18

starting to understand them as an entity outside

43:21

of just the project-based information . And

43:23

so that's kind of the next step that we're

43:25

taking this year is how do

43:27

we open up those profiles to become

43:29

more useful from a qualifying

43:32

perspective , to determine , you

43:35

know , are we working with the right partners

43:37

or are they bringing risk to

43:39

a project that might be one or two degrees

43:41

away from us that we wouldn't have known

43:44

about ?

43:58

had we not had a tool like Mercator

44:01

in a way , because the

44:04

the , the

44:06

content that your platform

44:09

is curating , is not opt-in

44:11

and that's , and

44:13

that's similar to the way

44:15

that G2 Crowd is . They

44:17

basically , and you know SourceForge

44:19

and Capture , they all do the same thing . You

44:22

know GetApp , they're basically

44:24

all they scour the internet . They basically

44:26

get the SEO nailed and

44:28

you find their results before you find anything else . I'm

44:30

not saying you do that , but essentially

44:32

there is then a rating system

44:35

based on something that , like Sitemax

44:37

for instance , I didn't even ask to be on this thing

44:39

and I'm on it , right

44:41

, and then now I have which is useful right

44:43

well , sort of , but I have to pay to control

44:45

it because I gotta pay

44:47

to now enhance my profile to make it not a

44:50

crappy , all that stuff , you know . Now

44:52

they're like hey , do you want badges ? I'm like I guess

44:54

I want badges . I mean , they're not

44:56

hard to get . You know winter , you know 2023

44:59

winter ? I'm like okay , well , sweet

45:03

, great . I guess when the customers use it they're like

45:05

well I guess that looks like other websites

45:07

. I guess we trust it . I mean

45:09

, I guess that's there . But from

45:11

your side , going back to that developer

45:14

profile , for instance , that you see on

45:16

a pin on a map that here's an upcoming project

45:19

, because it was a permit , pulled the

45:23

rating system of whether or not . So

45:25

what would you were saying some of the vectors ? One

45:27

would be past liens . What

45:30

other vectors would provide a model

45:32

for a rating ? Do you think ? I mean , have you thought

45:34

of that stuff ? Or is it you don't want to give away your

45:36

secret sauce yet ?

45:39

No , actually we're actually in development

45:41

of this exact thing with

45:43

one of our

45:45

partners in industry , one

45:48

of our GCs . We've been chatting about creating

45:50

these kind of company directories and

45:53

so we're looking at what would be

45:55

the makeup of that so

45:58

that we could create some really strong ratings

46:00

. This is also again

46:02

feeding that back to the municipalities also

46:05

really helpful there too . Right now we have

46:08

a risk score actually that we feed

46:10

back to the city on

46:13

residential developers

46:15

who are building secondary suites and

46:17

we let them know which ones have high

46:19

risk factors and which ones don't , based off

46:21

of a wide variety . I think there's about 14

46:24

or 15 different values that

46:26

make up that score and

46:29

that helps them to determine you know who to talk

46:31

to first or who to you know build

46:33

policy around or reeducate

46:37

. I'll

46:40

caution , or I won't dive

46:42

into exactly what we'd be looking at there

46:44

, but mainly because

46:46

that's mostly in discovery and we'd have to be doing

46:49

the analysis to determine what fields actually make

46:51

sense . But yes

46:53

, absolutely I think having a profile

46:56

score , also

46:58

, things like accreditations and

47:01

certificates , understanding who can build

47:03

what , is also super important

47:05

. I

47:10

think when we get into , you know , the GCs or even the sub-trades , like I know on public projects . That's really important , so for

47:12

the cities to even be able to pull up a profile

47:15

and very quickly see the work that they've done before

47:17

. What kind of certificates

47:19

do they have ? I mean , all this gets submitted , but

47:21

as a first pass especially

47:23

when you're inviting people out to bid

47:26

on private projects super

47:29

valuable to pick the right partners . Or

47:31

even entering into a new market when you don't know

47:33

who those partners could be and you want to understand

47:35

who it looks like you in that market

47:37

and who do they work with Right

47:39

.

47:41

Yeah , yeah , that's

47:43

pretty's pretty cool

47:47

. So

47:49

do you get an estimated so

47:53

you know when they get the building permit

47:55

approved and then they have a start date

47:57

? Do you get that start date ?

47:59

Sometimes we do , sometimes we can infer it

48:01

. It depends .

48:03

Inference my favorite word inference

48:05

. Okay

48:07

, so if you do that , then

48:09

, and then do you get the occupancy

48:12

permit date .

48:14

Exactly , yeah . So what

48:16

we try to do is triangulate all of our

48:18

data sets so we should have at

48:20

minimum two to three different data

48:22

sets that describe the same thing .

48:23

Okay .

48:24

Because different sources will have

48:26

different dates . For example

48:29

, like on your drawing

48:31

packages , you'll have your DP date sometimes

48:33

, but then the city will have a different date

48:35

and so which one's the right date ? Right

48:37

, a lot of that in

48:40

terms of like dates and , you

48:43

know , permit information . When we're talking about

48:45

permit information , permit numbers and things like that

48:47

, all of that is really critical for us to get

48:49

right . So we try to look at it from

48:52

different angles to be able

48:54

to say , okay , how confident are

48:56

we that this is the right piece of data ? Because

48:58

that data is critical to feedback into

49:00

our models , and so we always want to make

49:02

sure that reported data can sometimes

49:04

be misreported .

49:05

So how do we find , you know , multiple angles

49:08

to look at that data so that when we feed it into our

49:10

model , we're not outputting the wrong

49:12

outcome for you Interesting , because

49:14

I would imagine if I was a

49:17

GC who had worked on a project

49:19

and there was the

49:21

estimate that , well , the start time , and then

49:23

the estimated completion , and

49:26

then there is the actual occupancy

49:28

permit that's

49:31

issued , and

49:33

then there's like , whoa , okay , well , what

49:36

were the reason for the delays ? So

49:39

then you get into your G2 situation where

49:41

you reach out to the GC and say , hey , would you like to add

49:43

some color to this ?

49:45

Well , so take it one step further Now . Start

49:47

to analyze all the different projects in that

49:50

market . Say , for example

49:52

, we're looking at restaurant fit-outs right , and

49:54

we now know all these different GCs

49:56

that do restaurant fit-outs . Well , why

49:58

do your restaurant fit-outs take you know

50:00

about , you know 90 days longer

50:02

than somebody else's restaurant fit outs . What do you

50:04

do differently ? What do they do differently to

50:06

speed up that process ?

50:08

Yeah , exactly . So this is where you're . Yeah

50:12

, some of the data that you're creating

50:14

is goes

50:16

way beyond just a developer trying to find business . I

50:18

mean a GC just trying to find business .

50:21

Totally . But I mean like , like you know , you

50:23

got to sell what's on the back of the truck today , even

50:26

though you've got quite the vision in your back pocket

50:28

.

50:28

Yeah , that's true . That's true . Yeah , that's pretty

50:30

cool . So so

50:33

, in terms of your

50:36

, do you have business development , people that are calling

50:38

companies and all that ? Hey use our platform

50:40

, all that kind of stuff right now .

50:51

Like BDRs . You know what's amazing when you get to use your own platform to do your own business development

50:53

. Oh yeah , nice , it is so fun . You get to learn how to use your tool in a totally different way . No , we actually

50:55

just hired our first salesperson

50:58

. We had a really interesting . Our

51:00

journey's been really quite interesting in

51:02

that when we did our seed round

51:05

we actually stopped selling for six months

51:07

. We pulled together a beta program really

51:09

targeted a very specific group of customers

51:12

that ended up becoming our ICP and

51:15

we honed in on doing stakeholder

51:17

interviews . We

51:21

did product roadmap reviews with them . We

51:23

did language studies

51:26

, pricing studies , usability

51:28

studies , value

51:30

studies with them Basically any

51:32

new thing that we were thinking

51:34

of we put in front of them to get their perspective

51:37

hitting

51:46

product market fit with that group in three months . It was very quick to very consistent

51:48

delivered value . And that's where we started to kind of build out okay , well , what's

51:50

the ROI behind that and how

51:52

do we build case studies around that ? And then we went back

51:55

into market like late

51:57

September , early October and in six

51:59

weeks we closed four

52:02

net new customers on 30-day trials

52:04

, 100% conversion

52:07

rate on those trials , and so we went . We've

52:09

had quite a discovery of

52:12

a journey in terms of coming

52:14

from . Okay , we think we have value

52:16

. Let's really face it head

52:18

on and make sure that this value is truly worth

52:20

building . You know

52:22

we have two years of runway not considering

52:25

revenue . Let's really dig in . And

52:27

then now we're starting to really open up or go

52:29

to market . And so what we're learning is how

52:32

do we take this thing to market ? How

52:34

do people find us ? We've constantly

52:36

had people coming to our website requesting

52:39

demos and requesting trials , but if we

52:41

want to amp that up and start building real

52:43

revenue around this and moving towards

52:46

kind of our series A , how

52:49

do we get out there ? And so what we've

52:51

noticed is it's

52:55

not the typical go to site

52:57

and knock on the trailer .

53:00

No , that's not the way .

53:02

You know it's about these

53:06

types of interactions hearing us on a podcast

53:08

, watching us speak , seeing

53:10

an article that's been written about us participating

53:14

and adding more value back into the industry

53:16

than taking from it and that's always been

53:18

an ethos that I thoroughly

53:20

, thoroughly bank on is , if

53:22

we give more value than we take

53:24

, then we will build

53:26

fantastic partnerships that

53:29

um will help us to grow

53:31

a really solid customer

53:33

value for the industry well , I mean for

53:35

a gc to get a job , I mean you

53:38

know it's not not hard to return

53:40

value there .

53:42

I'm sure your fees aren't that expensive , they're not

53:44

excruciating , I can imagine . So , like

53:49

I'm just thinking , you know , before

53:51

I did SiteMax , I was doing , I did

53:53

a rebrand of a construction company

53:55

that's your ICP , like right there doing

53:58

$100 and $500 million . And

54:01

you

54:03

know the VP of development , business development , you know the VP of development , business

54:06

development , you know worked with him very closely

54:08

. And I was just thinking

54:10

of you know what they would , how

54:14

often they would go into the platform and look

54:16

at the map . It's mostly they're going to react to an

54:18

email right Alert and then they're going to go

54:20

back in and just take a look .

54:22

Yeah , if you , we talk about like no known

54:24

searching and unknown searching

54:27

, so it's . If I'm , if I'm trying to find

54:29

something that I don't know about already , then it's

54:31

my email . If I'm driving past

54:34

something and I want to look it up in the platform and

54:36

see everything that's going on , then I'm

54:38

in the platform digging into that map .

54:41

Ah , so you can have guerrilla marketing . Way to look , you are going

54:43

next to the development application here

54:46

check this think , oh , there's information

54:50

on mercator . There you go , mercator

54:52

, right , it's mercator .

54:53

It's like I have to keep saying it's like alligator

54:55

mercator yeah , well , and

54:57

that's funny because we so many people screw

55:00

up our name . They often , uh , say

55:02

mercator , mercator . That sounds like a dungeons and dragons

55:04

character , mercator , right , yeah , so we've called up our name . They often say Mercator , mercator .

55:05

That sounds like a Dungeons and Dragons character . Mercator

55:08

Right .

55:08

Yeah , so we've called ourselves Murgators

55:10

. So everything we do is green , and

55:13

so the team calls themselves Murgators

55:16

.

55:16

Murgators so close there with alligator

55:18

. Yeah , alligator , I like it . Yeah

55:34

, so I get the sense that this is a really clever way

55:37

for I mean , it's essentially like product discovery and what is going on and what

55:39

the pulse is open API on

55:41

your end for companies to

55:43

be able to do what they want with their data Not

55:46

their data , but your data so that they can sort of

55:48

pull it into . Can you

55:50

download spreadsheets from your system

55:52

? Can you download ?

55:53

Okay , yes , okay yeah .

55:55

Integrated with Google Docs or Google Spread

55:57

, Google or Smartsheet or something like that .

55:59

Right now it's a CSV download , but you'll be able

56:01

to , in the future , here connect directly

56:04

into your CRM . So we give you the option

56:06

to be able to hide projects

56:08

, watch projects or star projects

56:11

right now , and so starred projects are projects

56:13

you want to pursue and those in the future

56:15

will get pushed directly into your CRM

56:17

.

56:17

Right , interesting , yeah

56:20

, and I would think that the Are you also pulling

56:24

anything from LinkedIn as well ? For

56:27

project contacts .

56:29

We will be but we actually

56:31

have our own contact vendor

56:33

that we work with , and so we look at

56:35

that data . It updates every single month

56:37

for us to get the freshest contact

56:40

data . Like I said , we use

56:42

it as well to reach out to folks , and

56:44

so we have to make sure that

56:46

it's very reliable . But

56:49

it also helps us to map out who the organization

56:51

like . How does the organization look in

56:54

terms of structure and org chart , which is helpful

56:56

to understand . You know how large

56:58

is the organization and

57:00

you know how successful are they . And

57:06

how successful , are they ? I like it

57:08

. I can see your gears turning , james

57:10

.

57:10

Yeah , they do . Yeah , yeah , I

57:13

mean , I

57:15

often stutter

57:18

and start and stop because my wheels

57:20

are . You know , I'm a dude too , so I

57:22

can't do like 10 things at once . But I'm basically

57:24

thinking spatial

57:27

reasoning like way out here , and then I'm

57:29

also listening to the detail right here . So I'm kind

57:31

of doing this and that at

57:33

the same time and , yeah

57:36

, I can see some huge knock-on macro

57:38

effects here that are pretty exciting . Okay

57:41

, so what

57:44

else ? What's next on the menu for

57:46

Mercator ? But okay , so what else ?

57:53

What's next on the menu for Mercator now ? Yeah , I mean , the biggest thing

57:55

that we hear from our customers is just being able to centralize a lot of their research efforts

57:58

. So that's a big goal for us this year is

58:00

to really bring in your news , your project

58:02

releases , all of our Mercator

58:04

data all into one space to

58:07

really make it like the central hub

58:09

. The second thing that we

58:11

typically hear is obviously that

58:13

we're not in enough geographies and that

58:15

if we could get into more geographies

58:18

that would be great . So

58:20

we've already done all of the scouting and

58:22

prep work for 400 markets

58:24

that we'll look to launch here over

58:27

the next probably two years and

58:29

that'll give us coverage over the entire

58:32

US and Canada and

58:34

that'll be really interesting because now we can

58:36

start digging into cross-market comparisons

58:38

and the future of that macro intelligence that we hope to provide kind of the

58:40

future of that macro intelligence that we hope to provide .

58:43

So what would a piece of intel be

58:45

? Cross-market comparison of what . What

58:48

would be the vector that somebody would be like , wow , that's valuable

58:50

information . What is that ?

58:51

Oh my gosh . I mean even

58:53

just timing of . You

58:55

know , if the larger markets are getting hit by , say , a

58:59

recession or a boom

59:01

, how long does it take for

59:03

smaller markets to then react ? If

59:06

we're seeing an upward trend towards

59:09

more senior care being developed in certain

59:11

industries or certain markets , geographies

59:13

, how long does it take for other

59:16

markets to catch up ? Where's the kind of relational

59:18

, kind of ebb and flow

59:20

that occurs market to market

59:22

? Another way to look

59:24

at this is actually a huge

59:26

value prop back to our

59:29

customers as well , who are the municipalities

59:32

to understand . You know , where are those ? Where are

59:34

there opportunities for them to become better

59:36

partners to industry based off

59:38

of , say , other markets that they're actually competing with

59:40

, because everyone's vying for

59:42

development to happen in their , in their

59:45

local city ?

59:46

I see , yeah , that makes sense . So you have municipalities

59:50

as customers right now .

59:52

Yeah , absolutely . We

59:54

work very well with them in

59:56

terms of being the middle person between industry

59:59

and municipalities .

1:00:00

Cool , all right , so

1:00:04

I think we've we've talked

1:00:06

exhaustively on your platform now

1:00:08

, so let's , I want to do these rapid

1:00:10

fire questions . So what

1:00:12

do you think about that ? You ready for this ? Did you look

1:00:15

at ?

1:00:15

that .

1:00:15

Sure , let's do it . Well , you don't have to look at them

1:00:17

because they're rapid fire anyway . So what

1:00:20

is something that you do that other

1:00:22

people would think is insane ?

1:00:26

What is something that you do that other people would think

1:00:29

is insane ? Starting

1:00:33

a company comes to mind , because I think you need to be a little insane to start one of these things

1:00:35

, but I'm an adrenaline junkie and maybe

1:00:38

that's because I have a real high risk tolerance , but I'm

1:00:40

a rock climber , mountain biker

1:00:42

, skier , surfer

1:00:45

. I do it all , so

1:00:48

probably hanging off of a cliff is

1:00:51

probably the scariest thing that I do .

1:00:53

Do you free climb or do you like full on ?

1:00:57

So I sport climb , yeah , so bolts

1:01:00

in the rock , but leading

1:01:02

my own ropes , bringing my own ropes up

1:01:04

, bringing my own protection up .

1:01:05

A lot of trust there , a lot of trust . Okay

1:01:07

, what

1:01:10

would you be doing if you weren't doing what you're doing

1:01:12

now ?

1:01:16

I mean , I've only been in this , for I've

1:01:19

had a much longer career than I have been

1:01:21

a founder , so but

1:01:24

I think what I've learned as a founder is that

1:01:26

I would

1:01:28

love to make my next step into

1:01:30

mentorship and

1:01:33

volunteering

1:01:35

and working for

1:01:37

, for organizations that don't get

1:01:40

what you know private

1:01:42

entities get in terms of talent

1:01:45

and skill and

1:01:47

guidance , and so I think I would love to spend

1:01:49

a little more time giving back to the world versus

1:01:54

maybe taking from it

1:01:56

. In a sense , I feel like the capitalistic

1:01:58

nature of being

1:02:00

a for-profit founder feels a little like

1:02:04

you're taking a lot sometimes .

1:02:06

Really , I think you're providing a lot .

1:02:09

I think you're providing a lot as well , but you're also

1:02:11

, I

1:02:14

would love to give back

1:02:16

to the folks that don't get the capital

1:02:18

to raise to do all the amazing

1:02:21

things that they're doing from a human standpoint

1:02:23

.

1:02:23

All right , that makes sense . That's very nice of you . It's

1:02:26

very nice . Okay

1:02:29

, Do you have a memorable story from

1:02:31

dealing with a customer or something

1:02:33

, maybe perhaps

1:02:36

going to a job site and trying to talk about

1:02:38

this stuff ? I saw you at BuildX . You know you're pounding

1:02:40

the pavement . Do you have a funny story

1:02:43

or something memorable you want to share that you

1:02:45

would think would be reasonably entertaining ?

1:02:48

So maybe not , maybe

1:02:50

wholehearted and wholesome . I

1:02:55

mean , I grew up , you know , my

1:02:57

dad's been in industry for almost 40

1:02:59

years and I

1:03:01

grew up , you know , listening to his passion

1:03:04

about this industry and

1:03:06

I always just thought that was him . I

1:03:09

never really thought that that was something that was

1:03:11

so pervasive in industry . I've had like

1:03:13

full blown , you know , men

1:03:16

in their 50s and 60s like

1:03:19

cry in front of me about how

1:03:21

much they care about this industry and

1:03:23

it's incredibly

1:03:26

heartwarming and I honestly have never

1:03:28

seen it in any other industry other than agriculture

1:03:31

and it absolutely

1:03:33

endears me to this industry and

1:03:35

makes me want to work that much harder for every

1:03:37

single person we serve . And I know that

1:03:39

seems probably a little , you know , probably

1:03:48

a little , you know , self-serving in terms of a story , but I yeah it's , it's actually just really

1:03:50

shocked me at how much every single person in this industry

1:03:52

cares so much

1:03:55

about what they do .

1:03:58

All right . Well , that sounds pretty good . Another

1:04:02

very , you're a very nice entrepreneur . Geez

1:04:04

, you make me look like the devil , that's

1:04:08

okay . That's okay

1:04:10

. Maybe I should put some horns on the

1:04:12

on top of my baseball hat , okay

1:04:15

. Or it's a trucker cap , right ? Trucker , I

1:04:17

guess , with the mesh on the back . Yeah , I guess it's trucker

1:04:19

.

1:04:19

Yeah , what do you have ? Is that a ? Is that a bighorn

1:04:21

sheep or something ?

1:04:22

Yeah , what do you have ? Is that a ? Is that a bighorn

1:04:24

, sheep , or ?

1:04:25

something .

1:04:25

Yeah , this one says black sheep Okay , yeah , these are , these Is that how you identify

1:04:28

. No , it's not how

1:04:30

I identify , it's just the hat that I wear . But yeah , like

1:04:33

I don't know , it was just cool . I

1:04:35

liked the cause . There's actually a black

1:04:38

sheep embroidered thing . So

1:04:40

before we go , let's just your

1:04:43

website is Mercatorai

1:04:45

.

1:04:46

You got it Very easy .

1:04:49

And Chloe Smith on LinkedIn Correct , okay

1:04:51

. And then

1:04:54

if

1:04:56

someone does book a demo , you're going to be nice to

1:04:58

them . You're not going to hassle them . It's going to be a very

1:05:00

great experience . You're going to walk

1:05:02

them through the platform . They

1:05:05

don't have to buy anything . It's all good , even

1:05:07

if they don't go forward

1:05:09

with your platform , they'll be smarter after

1:05:11

that . That would be the pitch .

1:05:14

Actually , we're

1:05:17

quite rigorous when we do demos , and

1:05:20

for good reason . We

1:05:23

will do a discovery call first with you , to

1:05:25

make sure that you know it's worth us

1:05:27

spending the time with you and it's worth your

1:05:29

time spending it with us , um

1:05:31

, and make sure that you know you're the right kind

1:05:34

of profile to get success out of the tool . And

1:05:36

then we'll go into a demo and in that demo

1:05:38

, that's really where we are at risk of pass

1:05:41

, fail , right , um , in terms of

1:05:43

making sure that it's it is there

1:05:45

to solve , you know , the

1:05:51

problems that you you have and and that you know it's doing so in the same vision that you

1:05:54

had anticipated . And then , from there , we'll go into whether or not you're ready

1:05:56

to do a trial , and so we do 30 day trials

1:05:58

today . It may not always be the

1:06:00

case , but we do them today and

1:06:02

we make sure that our customers are

1:06:04

ready to subscribe

1:06:07

during those 30 days . And if they're not

1:06:09

, then we you know kindly say

1:06:11

thank you . And let's talk about a trial

1:06:13

when you're ready to be able to

1:06:15

commit to a budgetary spend

1:06:17

. And so we want to make sure that we're a small

1:06:19

team , right , we need to make sure that we're spending

1:06:21

time with customers that have a vested

1:06:24

interest in what we're building and want to become partners

1:06:26

, and so , yeah

1:06:28

, it's a little more rigorous , I would

1:06:30

say , than your typical vendor

1:06:33

demo .

1:06:34

Cool . Well , it sounds like a time well spent for

1:06:37

somebody to do that . Yes absolutely All right

1:06:39

. Well , that's good then . So yeah , everybody who is

1:06:42

interested in this , head over

1:06:44

to Mercator and take

1:06:46

a look at this thing .

1:06:48

Well done , you said it right .

1:06:57

Well , that does it for another episode of the Site

1:06:59

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1:07:02

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1:07:31

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