Inside Marketing with MarketSurge

Welcome to Inside Marketing
With Market Surge.

Your front row seat to the
boldest ideas and smartest

strategies in the marketing game.

Your host is Reed Hansen, chief
Growth Officer at Market Surge.

Reed: Hello and welcome back to The Inside
Marketing with Market Search Podcast.

Today I'm joined by Matt and Andrew,
who are the co-founders and voices

behind Digital After Dark, a flagship
podcast born from their late night

conversations about digital analytics,
data strategy, and emerging tech trends.

What began is two friends sharing
war stories in an ever evolving

digital landscape has blossomed into
a vibrant community of practitioners.

Analysts and storytellers where
guests and listeners alike come to

debate concepts, swap best practices,
and stay ahead of the curve.

Matt and Andrew, welcome to the podcast.

Matt: Thank you.

Reed: Yeah, my pleasure.

And it's been nice to get to
know you over recent weeks

Andrew: because it's feeling like

Reed: I had a great time on your podcast.

Andrew: other one,

Reed: the banter's.

Fantastic.

And, um,

Andrew: same things again.

Reed: I understand that
you have a sponsor.

Andrew: eight, because

Reed: give you a chance to

Andrew: And I

Reed: chime in if you'd like.

Matt: it's a running joke.

'cause I normally, uh, because it's
digital after dark, we are based in,

Andrew: Bye.

Matt: in the uk.

Um, so it's, it's 10:00
PM uh, our, our time.

And that's generally
when we, when we do it.

So I'm normally having a beer, uh,
by, by that point Andrew doesn't

drink, so he's never having a beer.

but today, today I'm on
the non-alcoholic beers.

So Beck's Zero is our
unofficial sponsor for today.

Reed: I love that tradition.

to start, I, uh, earlier
I was sponsored by Dr.

Pepper, strawberries and cream
zero, which was disgusting.

Matt: like, um, I like the, uh,
the Pepsi Max, uh, cream soda

and cherry cream soda ones that
they've, just got them in the uk.

I don't know whether they have,

Reed: I'll have to look for 'em.

I haven't seen it yet.

Andrew: Yeah.

Reed: as zero?

Matt: Yes, the, it's the zero zero
sugar, but they're, they're nice.

I think they're nicer than the, um,
just the straight Pepsi Mark Zero.

I like, the cream soda flavor.

It's nice.

Andrew: Yeah, I've been going
on more of a health trend,

so I've been doing more
vitamin tablets in my water.

Reed: Uh ah.

Okay.

Well.

Andrew: to keep

Reed: Yeah, we've got
one Healthy guy here.

Um, how did the After Dark podcast
come to be, you know, digital After

Dark is the title, how did you make
these discussions turn into a podcast?

What was kind of the inception of all?

Andrew: for me, I've always
wanted to do a podcast.

I've been wanting to do it for
quite some time, but just needing

to find the right co host.

about, I think it was just
last year, I got invited to

go to the Analog Rockstar in
Las Vegas for the Adobe Summit.

And unfortunately, I was unable
to go, I asked Matt if he

wanted to go in my place.

And part of the gifts that the
presenters got was an entire

podcast setup to be able to
keep the good work going.

After hearing that, I was
like, well, Matt, do you

want to start a podcast?

Matt: We kinda had to do it by that point.

Um, I think for me as well, it
comes from a few different places.

the most obvious place was Andrew
and I, at the start of 2024.

So quite a while ago now, or
maybe even, the start of 2023.

made a New Year's resolution to
try to put more content out on

LinkedIn and to generate a bit of
interest and just to kinda share.

Expertise and things that we've learned.

we work with a lot of different
clients and come across a lot of

different setups and interesting, work
with lots of different vendor tools.

we come up with lots of different
interesting things within.

Given parameters of interest given
the, given the field that we work in.

interesting to us, and our listener.

that was one thing we were starting
to put more content out and then

the Adobe thing happened and we were
like, why don't we do a podcast?

for me as well, I've got a young family, I
spend most of my time looking after them.

and don't really get to do a lot of,
self-expression, I didn't manage to

keep up really putting the content
on LinkedIn 'cause I'm putting my

kids to bed and things like that.

Um, and so this was one opportunity
to just still be able to kind

of keep something semi-regular.

where I do something that is of
interest and is a bit of a hobby to me.

Um, whereas we don't really get
to do that most of the time.

Reed: Well, that's great.

Andrew: think I kept that New Year's

Reed: Go ahead.

Andrew: going for a while.

So, I think I kept it for
four months doing daily

content out on LinkedIn.

Matt: Better.

Andrew: did really work for a while.

Matt: You did a lot better than me.

Andrew: I just...

Yeah, I couldn't
keep it going either.

After a while, you just sit down
at the computer like, you know what,

I'm sitting down at the computer all
day, do I really want to sit down

at the computer to type some more?

Matt: This is why I'm standing
up at a computer right now.

Reed: No, that's, that's smart.

and.

You know, for my audience that
hasn't maybe heard your podcast yet,

I would definitely recommend they,
uh, tune in digital after dark.

And, uh, Matt and Andrew actually do a
great job making this fun and interesting.

They're funny guys themselves and
just, you know, I, I, I really

enjoy their, uh, their banter.

now tell me a little bit about,
maybe your work, you know, outside of

podcasting, you know, what are your
specific, um, fields of expertise.

And then I'd like to dive into that
and how small and medium sized business

owners and, and marketers, uh, can do
more with, with data, more with analytics.

and, you know, I'll, I'll take you
there, but I'd love to hear more

about, what you do in your day jobs.

Matt: Do you wanna go first, Andrew?

Andrew: could go first.

So, I'm actually part of
Matt's team at Loop Horizon,

where we are focusing on the
implementation and usage of digital

analytics and how to get the
most out of your investment.

One of the things that we always
talk about was it's not just about

collecting the data, but it's about
how do you use it and leverage it

even in an automated way to be able
to turn yourself from a call center

to a revenue generating center.

So my field is more around
the implementation and the

collection of digital data that
may be using Adobe Analytics.

It could be using Google Analytics.

Um, decibel, content square.

if it's a tool that can go on
and understand how people are

using websites from collecting data
to marketing pixels, then I'll be

getting involved in it and digging
into and understanding how it works.

Reed: See yeah, Matt.

Matt: Very similar.

Um, I mean, so yeah, I, I mean I've,
I've been really keen for, um, and

this, this is my thinking face where
I'm looking up away from the camera.

Um, I've been really keen for,
uh, probably the last 10 years,

I think it's safe to say in
exactly what Andrew mentioned

around turning digital analytics.

There's, there's a perception
in the market that.

Digital data collection is just reporting
and, and, you know, some analysis and

it may inform business decisions, but
fundamentally, those business decisions

are things that will take place in
the next quarter or the next year.

And I've always been very keen.

I, I've never really thought
that that was the case and

I've always been very keen to.

Showcase that digital
analytics isn't a cost center.

Uh, it's not a secondary or tertiary
revenue generation function.

It's it, it's a direct
revenue generation function.

And the way that you do that is by
taking data that you collect and

activating against that data and not
activating against that data by looking

at a report and then taking a decision
that gets activated five months later.

In milliseconds, taking a piece of
data that feeds into an automated

system that you've built, that the
automated system might have taken

you months to build, but the actual
cogs, when you pump the fuel into it,

spits an output within milliseconds,
within half an hour, within a day that.

Activates that data so that that data
point and the collection of that data

point in the analysis that goes on, that
data point has a revenue value that you

can then report back to the business.

Um, and then since joining Loop
Horizon five years ago, five and

a half years ago, um, it's been
taking that attitude and trying To

give that to our clients basically.

'cause I've come from client side
into agency side, so Loop Horizon's

my first time working for an agency.

Um, and so it was to take those things
that we've been trying to do for

our company and actually, you know,
give them to other clients and help

them turn their digital analytics
into a revenue generating function.

And then in terms of the
technical side of it.

I mean, Andrew mentioned around data
collection, but also data layers, data

architecture, and making sure that data is
generated in a sensible and efficient way.

So it's not just collecting and using
the data, but the way that the data is

generated and piped in in the first place.

It's done in an automated and consistent.

fashion.

So, you know, like a data layer would
collect data from multiple backend.

So let's say you've got a CRM, you've
got a product management system, an

order management system, and you need
APIs into your content management

system, to all of those backend systems.

Bring that data together in an automated
way, and then have logic that pulls

that together into a format that then.

Renders that out to the web or website
or the app or the iot device that

you are running the platform on.

So that data is consistent and repeatable.

Um, 'cause if it isn't, you're
not gonna be able to use it to

generate revenue, which is what
you wanna do further down the line.

So yeah, that's kind
of, that's where I sit.

Reed: You know.

And, um, something I maybe didn't
mention, uh, early on, you, I know you

work with the Adobe Analytics Suite.

do you work with the OMNISURE tools
like the site, site, catalyst, and

Andrew: Ooh, I want
to handle this one.

So, um, At Sky, I
absolutely loved it.

There was a developer who came
up to me and go, So, Andrew,

what's the difference between
Armature, and Adobe Analytics?

And, I mentioned to them, Well,
actually, they're all the same

Reed: Right,

Andrew: Armature was the company
that had a tool called Site

Reed: Uhhuh.

Andrew: which Adobe then
bought out and transformed

it into Adobe Analytics.

Reed: Got it.

Andrew: it's absolutely one of the
things that I believe Adobe themselves

are putting themselves in this box
because whenever you look at their

links They still sometimes refer to
as armature and sc for site catalyst

Reed: Yeah,

Andrew: not doing themselves
any favor by keeping some

of the old architecture

Matt: Well there.

Go on.

Reed: Yeah, well, the reason I asked
is my first job in college was with

Omniture and, um, uh, you know, I
was an intern and so I was mostly

like running the copy machine.

But, um, it was, uh, it was a
really cool environment and I, I

moved on before it became Adobe.

But yeah, that's, um,
that's my, uh, pedigree.

Andrew: well to keep it a
little light I have to ask a

Reed: Sure.

Andrew: is going to date
you a little When it was

Reed: Yeah.

Andrew: do you know
what h code it was on?

Reed: No, I don't.

Andrew: Nope.

Reed: Unfortunately I don't.

But

Andrew: All right, so at those
times, everything was H code.

So if you think about like iOS,

Reed: uh.

Andrew: iOS 16, iOS 17, iOS 18,
and they did the same thing.

It was H12, H13, H14, H15,
and H15 was the cutoff

Reed: Um,

Andrew: moving it from
Omniture to Adobe

Reed: I see.

Okay.

Well, let's see if I think really
hard, I maybe by the end of our

conversation I can remember.

'cause they, they would always
make a big announcement whenever

they, uh, they moved up.

Um, so yeah, we'll come,
let me come back to that.

so now in, uh, you work with
large enterprises, but um.

so maybe some of this is a little bit
speculative and, um, a lot of my clients

and a lot of the audience for this podcast
are small and medium sized businesses.

Um.

But, I think are very, uh, young or, uh,
less mature in their use of analytics.

Uh, for, for the web, you were
starting your own small business.

Um, what are the first three metrics
that you'd recommend that, uh, business

start tracking, uh, for, you know, web
activity, web traffic, revenue generation,

and, uh, you know, what would those be?

Matt: I think it depends
on the type of business.

Um, Are we talking about e-commerce
businesses or are we talking about

businesses that may be, um, just generate,
uh, like visibility and brand awareness

online and actually conversion takes
place maybe in the shop or so like what

kind of businesses are we talking here?

Reed: I'm thinking, yeah,
say like a service business.

So, like either a building
contractor for example, or,

they deliver design, services.

So it's, mainly awareness.

the site primarily drives people to reach
out to get a consult and do pricing, for

instance, rather than, pure eCommerce
or product sales on the website.

Matt: So I would think that the
key, key dimensions and metrics

that you would want would be, um.

Volume of visitors on the side,
which you're gonna get just from

deploying an analytics tool with
basically no additional config.

So that's nice and easy to achieve.

Um, dimension wise, I'd be looking at
your inbound traffic so that you are

understanding where it's coming from.

'cause if you're a small to medium
sized business, you probably don't

have a massive marketing budget, so
you'll be relying a lot on organic

reach, um, and understanding.

Where those users are coming in from and
trying to understand, I guess nowadays

as well, understanding what's AI traffic
versus what's actual genuine user traffic.

Um, so what, you know, what's crawling
to spit a result out in the ai,

response to the search rather than
actually putting a user on the side.

Uh, so trying to get a feel for that.

And then if you've got an
online form through, um.

You know, what are the relatively
cheap, integrations, with A CRM, for

lead gen and, the ability to tie.

The lead to the landing on the site
and to the data source so that you're

getting an understanding of whatever
marketing activity and word of

mouth, traffic you are, generating.

How successful is that being?

Um.

And then, you know, if you do have
a form on site, you're understanding

which of those traffic sources beyond
driving volume, you might drive a load

of volume, but it might not convert.

So it might be the wrong
audience, for example.

So that's gonna help you understand
if those data sources are well, if

your activity is driving volume, and
if the volume that is being driven is

the correct audience for your product.

Um, by collecting the lead.

And that's relatively easy to do.

For free or relatively cheap.

Reed: So using the Google Suite
for instance, probably get

them everything they needed.

Andrew: Yeah,

Matt: Yeah.

Reed: So, um, to what extent do
you think, so somebody that doesn't

have a background either in data
statistics or, um, like, uh, techno,

you know, like develop, so computer
science, to what degree do you think

these skills around analytics can be.

and, um, you know, is there
a cutoff to where they should

hire an expert, a consultant to
do the heavy lifting for them?

Um, you know, how would you
counsel, a small business

entrepreneur to think through that?

Matt: I would definitely say start with
the free suite and try and do it yourself.

the barrier to entry for getting
Google Tag Manager and GA four onto

a WordPress site is very minimal.

Like watch a couple of YouTube
videos and you'll figure it out.

and if you've built your own WordPress
site, I should say, then you've already

got the skill sets to go and do.

And if you've got somebody else to build
your WordPress site for you then lean

into them and say, well, how would I get.

an analytics tool on, um, because
in terms of what we are doing,

Probably to begin with for the kind of
basic metrics, you don't really need

to pay somebody like us to do it for
you or, you know, your web developer

might be able to do it for you.

It might be worth just getting like a
small consult from somebody because,

you know, web developers aren't
analytics implementation specialist

and it is possible to get it wrong.

And you know, if you've got like
a Shopify integration, then that's

where things start to become
a little bit more complicated.

And maybe You do need some sort of
support or just a consultation to check

if you've done it right, but certainly
for like really basics, just landing

people on your site, getting volume,
understanding if they've clicked on

a particular button to send a form
submission, should be relatively

easy to achieve depending how you've
integrated the form in your website.

Of course, like if it's in an iframe, then
that might cause you some problems, but,

Reed: Sure.

Matt: um.

So I think that, yeah, I mean, I
would certainly have a go at it

first, and when I've been setting up
my own website, it's obviously, I,

Andrew: of my life.

Matt: I work in this space, but
I've always just done it myself,

as you would, where it would be
worth putting in some time to learn.

Beyond, watching videos
about implementation is how

you do marketing tracking.

Andrew: Um,

Matt: businesses get that wrong.

Um, large businesses get that wrong
and it's really, there's no excuse.

There's so much documentation about
how you do, like, if you've got GA

four, how you do marketing tracking
set up for the basic marketing

channel implementation for GA four is.

All there and available.

Um, and that'll get you, you know,
that'll get you quite a long way.

And then you can decide
if you need more data.

but get yourself to that first position
where data's coming in and you can

start to do some reports and you feel
like you're understanding them, um,

before spending a lot of money on it.

Reed: Yeah.

Andrew: I was going to say, definitely
around the marketing channel.

That's where most people will get
wrong, especially considering that's

one of the first times you're
really going to have more control

over what the values are going in.

So you want to make
sure that it's consistent.

You're going to want to have that
strategy of like, how do you want

to set up each of the different
parameters to ensure that you

have that consistency and you're
not having email with a lowercase

e and email with a capital E.

And that's just going
to throw off your data.

Reed: Yeah.

No, those are, that's very helpful.

so jumping into what you're
doing, what are some of the

more complex things or, um.

You know, as an organization evolves,
what are some of the more complex kinds

of analytics that you're dealing with?

You know, you're starting to use
some of these enterprise systems

and, you know, multiple systems to,
uh, combine and synthesize data.

What kinds of like, high level
metrics or, uh, some of these

larger enterprises really targeting?

And I know that's a very broad question
'cause you're all over the place, but, um.

You know what, what's like something,
organization can aspire to?

Matt: I think it's, I mean, and again,
we're in the implementation space, so

I don't want to pretend that I'm an
absolute expert with analysis, although

I have done analysis, over the years and
I know you have to, Andrew, of course.

it tends to reflect the complexity
of the business and in some cases,

I would argue that businesses.

Well, I definitely argue, strongly argue
actually, that businesses overcomplicate

things unnecessarily a lot of the time.

A lot of what we are doing is
actually trying to simplify what

somebody else has implemented.

'cause it doesn't make any sense.

And you end up getting to the point
where your core metrics, there's so

much, like there's all this assumption
of collect everything and actually,

you know, if you collect everything,
you lose sight of the important things

because you haven't defined them.

so actually a lot of what we
do with larger businesses.

Is you might come into, an implementation
that has 200 separate dimensions and

a hundred variables and, you know,
a hundred, metrics, I should say.

And a lot of what we might do is
come and talk to that business, speak

to the people at the top and say,
well, what are your primary KPIs?

What is it that actually
drives value for your business?

because those are the things you wanna
monitor, and you wanna make sure that

they're being collected and aren't being
muddied or impacted by other things.

Then at a lower level, you might,
interview people who are using the

data as it stands today and say, well.

Which of these bits of data drives value?

So let's try and put a cash value on these
data points, and then we'll prioritize

them and decide which ones to keep.

Um, now I know that doesn't really
answer your question, but, that's

the sort of thing we're looking at.

It's 'cause it's very
easy to complicate things.

Um.

The complexity should follow
the complexity of your business.

So if you're working with like an
online retailer, for example, you

would go beyond, Just views and
marketing and lead generation.

And you start looking
at product information.

What products have been shown to a user?

What products have been added?

What products have been removed?

How many products were added to a basket?

Were they then in the checkout?

And then you would say, okay, well how
much revenue was assigned to that product?

and if I dropped outta the
basket, how much was the basket

worth that got abandoned?

And then once you know that a basket's
been abandoned, then how might I recontact

that person who's abandoned the basket?

And then you start to get
into user identifiers.

So now we've got cookie based usage,
we've got product information that's

coming from a product, backend
system serving to the website.

We've got revenue.

and now we've got user identifiers
that we might want to use for

a basket abandonment program.

And so you can see it quickly.

Reed: Mm-hmm.

Matt: but it should grow with
the complexity of the business

rather than just let's collect
everything, um, from day one.

'cause that tends to muddy
the water and you lose sight

of what's actually important.

Reed: Mm-hmm.

Okay.

Yeah.

And um.

Sorry, I saw your,
Andrew, I saw your hand.

I thought you were like raising your hand.

Um, and feel free to chime in.

Andrew: no, I was muting and I'm

Reed: Yeah, no worries.

Andrew: I was just going to give
one quick metaphor, and I know it's

going to sound really bad just from
a environmentalist point of view,

but if you think about if you were
trying to see the horizon through a

forest, your different variables and
all of your different metrics are

just adding more trees, so the more
that you have on the harder it is

to see the horizon and see what
you're actually trying to aim for.

Reed: Oh, interesting.

Andrew: Mm -hmm.

No,

Reed: simplification, that sounds,
uh, like a common theme and, you know,

getting and tying it to revenue and,
and, uh, the return on investment and

of course, um, uh, you know, and that,
I think that's a good principle that

applies, to just about any business.

Um, now let me ask you a little
bit about the current environment

and what you're looking forward to.

Um, are there certain processes
or approaches in web analytics

that are exciting to you?

Like whether it's, opportunities
that AI presents, or do you

have access to more real time
analytics that allow businesses to.

react more quickly than in the past.

What, what's exciting that's
ahead in data analytics?

Matt: Andrew, do you wanna, 'cause
I feel like I've been talking a lot.

Reed: I.

Andrew: I was gonna say this one is
actually quite interesting because the

two main things i've been looking
at the new features that adobe's

bringing they just did a adobe summit
here in london where everything

was talking around ai So how can
you use AI from an analyst point

of view to be able to get better
understanding out of the reports

by using natural search language?

Or how can you use AI to be
able to connect more with your

audiences using, I think it's
LLM that they, described it as.

the other one that I think I'm
more interested in will be around.

Over in Europe we have the GDPR
and as we know we had Brexit

now they're looking at how do
we take the GDPR and make it

a little bit more focused and
a lot more business friendly.

that finally got passed through
quite recently There should be

more of a guidance come winter
time to understand what this

actually mean to businesses.

it's going to be focusing on
that and how can we take these

new regulations and help companies
to ensure that they're meeting

their governance requirements.

Reed: Yeah.

Matt: I mean, I've got
a whole bunch of things.

I don't know how long we wanna spend them.

Um, really big things for me.

I mean, and, and I probably will touch
on AI at some point, but, um, there's

a whole rollout to server side, which
has been going on for a few years now.

So that's, um, trying
to remove script from.

User devices from the browser,
for example, and, to take that

orchestration server side.

So instead of, having a Facebook pixel
and a GA four pixel, and a Google ads

pixel and floodlight et cetera, you
would have one collection script that

would then hit the server side end
point and distribute to all of those

vendors from a server that you own.

the barrier to entry for that is
becoming, Less and less, and it's

getting much easier to get into.

that's been going on for a
while, but it's still exciting

and it's still picking up speed.

it hasn't slowed down.

Um, and then the benefits that
that brings, sort of feeds into

the GDPR, and e privacy, in Europe,
the California, legislation.

and I dunno that that's.

Getting adopted more widely, but
actually safari and Apple, in

particular in their privacy features.

So there's been a lot of stuff going
on with, safari Intelligent Tracking

Prevention, which basically takes
all of your first party cookies and

cuts off how long they last for.

So I'm mentioning earlier about,
you know, you deploy GA four, you

can tie your marketing to a lead.

Well, not if that lead
takes place next day.

'cause then the cookies disappeared and
you can't tie the market into the lead

anymore because the mechanism of joining
those two things together has been deleted

if the user was on Safari and 50% of
users are basically, um, so server side,

um, offers some mitigations for that.

insofar as you can set cookies in a
different way, to allow, and this is

the kind of stuff it feeds back into
your previous question about the kind

of things talking to clients about SMEs.

you know, small to medium enterprises
don't necessarily to look at server

side, although as I say, the barrier
to entry is becoming less and less.

So they might want to look at something
like a sta io or an adding well, or you

know, one of those vendors that will.

Do the service side implementation
for you at a relatively small cost,

volume based cost, usage cost.

and then you start to get
cookie persistence back and

you get some of that back.

So that's all very exciting at the moment.

obviously identity resolution
and collecting user identifiers,

you know, with consent.

Very important in Europe and becoming,
very important in the us but becoming even

more important with legislative changes.

so identity resolution and
collecting hashed user identifiers

for things like meta capi.

Um, so that's the conversion API
and sending user identifiers to, um,

allow better conversion attribution.

Uh, you've got user provided data
in GA four, which is basically the

same thing, but will also allow
you to connect to, um, Google's.

Database and bring in
demographics and interest data.

Probably very relevant to, um.

Some of your, some of your clients,
because you can then create audiences

off that, that have visited your site
and, and access Google's database to,

to understand, um, more about them.

So, you know, are they
interested in sports?

Do they like, uh, are they male or female?

Basic age ranges, things like that.

So that's, that's all available.

You can also do that through, um.

I can't, the names slipped my mind, but
there's another way of doing it through

third party cookies, but that's becoming
less and less reliable because third party

cookies are, are basically deprecated now.

Um, so using user provided data in
GA four, and then the equivalent for

Google Ads is enhanced conversions.

And again, it's just sending
in these user identifiers.

So identity resolution, um, is
becoming more and more accessible.

For free or very cheap server side
tagging is becoming more and more

accessible, free or very cheap.

Um, which get, you know, gets
you cookie persistence, backup.

And then the other, um, big thing
that I found very interesting

lately is, um, these, these tagless
solutions, um, so essentially

they, I mentioned about trying to.

Audit, um, analytics
implementations, and apply a value

to all of the data collected.

And part of the reason why you do that
is because data collection has a cost.

You've got the people who set it
up and maintain it, but you've got

your development team for making the
data available in a consistent way.

So, you know, every time you add more
data, um, there's a business cost

to creating it and maintaining it.

Um.

you can slow the website down if
you don't do it in the right way.

You can even break the website.

So there's potentially a user experience
cost and an ultimate revenue cost.

So there's an efficiency and
the revenue cost rallying data.

So that's why you try to add a value
to each data point, because each

data point has an impact as well.

Um, tagless solutions, on the
other hand, purport, to be.

to not, you don't have to
worry about that anymore.

And so what they do is you put the Tagless
solution in and it scrapes the whole

site and pulls all of the information in.

And so then instead of you having to
set up a complex data layer with your

development team and have all the
overheads of having that implemented,

you just collect everything and then
your analysts can go in and define.

You know, pull out the
bits that they want.

Um, and the bits that have meaning
for them do the orchestration

after the data is being collected.

Um, which also means it
can be retrospective.

'cause you can change that data
orchestration and apply it backwards.

Um, so that's really interesting.

That's quite new.

That's, uh, it takes the whole model
of data collection and who owns it.

'cause I always say like a data layer and
data collection is a division of labor.

somebody has to do these
data transformations.

You've got the data coming from the
backend product management system and the

CRM and the headless content repository
and the content management system.

And somebody has to manage the 50,000
data transformations that need to

take place To make that intelligible.

Um, so who's gonna do it?

And historically it's always been
your development team would do it.

'cause there's lots of them.

Reed: Right.

Matt: they're not data experts and
they're not benchmarked on data quality.

They're benchmarked on speed of delivery.

And so, actually, are you going
to get the best quality of data

by using that traditional model to
collate all of your data up front

and make sure it's consistent.

Or does it make more sense to scrape
absolutely everything and then let

your analysts who are data experts and
who are benchmarked on data quality

and reporting quality, figure it
all out after it's being collected.

So I'm really interested in
seeing how that plays out.

And I promised I'd mention ai,

Reed: Yeah.

Actually, I have a follow up.

Matt: because, um, in that scenario
where you've pulled everything

in large language models.

Large language are very good at
receiving vast amounts of information

and trying to make sense of it.

And so I think where this is
gonna be really interesting is.

If the industry does go in the direction
of collect everything and figure it out

later, what role AI plays in that, and
then who has oversight of it because it

still needs some sort of oversight from
somebody who knows what they're doing

to understand if the AI is talking crap.

Reed: Sure.

Right,

Matt: Um, those are the things
that are kind of interesting and

exciting for me at the moment.

Reed: No, that's a lot.

And, um, I mean, I, you know, it
gives me a lot to think about.

I, um, curious if in the circles you
run in you've heard any on the horizon,

if there's going to be any access to.

around the way people are using LLMs.

Like, um, you know, I know that a lot
of web search has been siphoned off

because people are, answering their
questions on, chat GPT or others that are.

functioning as the intermediary
where Google Search used to fill.

So, um, you know, right now, I don't
believe that's accessible at all, but

have you heard of any, I mean, can we
try to exert pressure to get that data?

Or is that, on the

Matt: It would be nice.

No, I haven't heard about that
being opened up unfortunately.

I don't know if you have Andrew.

Andrew: that was one of the questions
that several analysts were asking

Adobe as well at the Adobe Summit.

So, trying to understand, is there any
way of being able to capture this?

Because it's really hard
whenever it's a bot going

on and scraping off.

Because their sites have always
been designed to ignore the bots.

Especially because the very
first bot that was very

successful became Google

Reed: Right, Yeah.

No, excellent point.

I find this really fascinating
and obviously it's a big.

time for change in the technology
space and, you know, just interesting

to see how things are playing out.

I could probably talk to you for
hours and, I'm impressed with you

both as podcasters and as, data guys.

So why don't we put a pin in it for today?

now if people would like to hear more
about you, tune into your podcast,

network, where can they reach you?

And maybe we can start
with Andrew and then Matt.

Andrew: Well, be able to listen to
our podcast, we're on Spotify, we're

on Apple Podcasts, we're on YouTube.

You just have to look
up Digital After Dark.

On there, there are
two different podcasts.

So there's the actual Digital
After Dark, which was the

thing that started it all.

off and that was between matt and
i so anytime matt is on a podcast

with me it automatically becomes
a digital after dark the second

one is andrew talks and this is
one where it's just me or me and

someone else and that is one where
i'm trying to really get off the

ground because as you hear matt's
very busy he can't dedicate as

much time and i want to become a
better podcaster and the only way

to become a better podcaster is
by Going out there and doing it.

So that's why I decided
to start a second one but I

already had the integration set
up for digital off the dark.

I was like, no i'm not
going to do that again

But reaching out I tried to keep
things a little bit more privacy, so

Reed: Fair enough.

Welcome.

Andrew: very easy to reach
out besides just the

Reed: These are laughter dark.

Matt: you can get in
touch with me on LinkedIn.

so my LinkedIn handle is just,
Matt does data all one word.

Uh, so you can find me there.

Reed: Awesome.

Well, Andrew, Matt, thank you
so much for joining us today,

and I think we learned a lot.

sure for a lot of the solopreneurs
and entrepreneurs in the audience,

they are going to be thinking about
this and trying to implement, aspiring

to have better data and turn their
marketing and web efforts into dollars.

So thank you so much.

Matt: Oh, no worries.

And, um, yeah, I mean, if any of them want
to reach out 'cause there's so much stuff.

I mean, we kind of touched on some of
the free tools, but I haven't even talked

about BigQuery yet and getting the data
outta GA four and all of that stuff.

So, um, if anyone wants to reach
out on, on LinkedIn, I'm, I'm more

than happy to, uh, to have a chat.

Reed: Perfect.

Andrew: Thank you so much, Reed.

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