Subscribe
Share
Share
Embed
The Fintech Marketing Lab is a podcast where Araminta Robertson, Managing Director at Mint Studios, explores, experiments, and breaks down how fintech marketing actually works in practice.
Speaker: Over the past two years, I've
been interviewing marketing leaders
at top FinTech companies on how they
do content, and these are really
some of the top FinTech companies,
including fintechs, like Adian, Tru
You Unit, and Lio, just to name a few.
At the time, we published those as
separate case studies, but now we've
put it all into one lovely ebook.
The reason I started is because.
At the time, I was looking for tips,
benchmarks, or any case studies on
how FinTech or financial services
companies do content marketing,
and I couldn't really find much.
I think anyone who's in this space
knows that a lot of content marketing
advice is very specific to SaaS.
And it's kind of one of my pet
peeves because in my mind, SaaS is
quite different to FinTech, right?
And so a lot of the advice out
there doesn't address, you know,
the endless compliance reviews, the
complexity of explaining, payments
infrastructure to prospects.
And, what is the role of content
when you're buying cycles are,
you know, years long sometimes So.
In each of these interviews, I ask these
leaders, how is your team structured?
What's working, what isn't?
How do you measure this?
And I'm happy to say that
the ebook is now live.
You can go check it out.
, the URL is tiny url.com/mint
report.
So that's mint report.
Or you can just head to our homepage,
mint copywriting studios.com
and you'll find it right
there, as an announcement.
We also have a virtual event coming
up next week where I'll present some
of the findings and I'll also be
joined by some of the people that I
interviewed as part of this ebook.
Anyway, let's get to today's episode,
which is also very relevant to this topic.
Now, with ai, I think we can all agree,
, creating content is easier than ever, but
proving that it drives revenue, influences
buyers, and kind of builds a brand.
It's.
Getting harder really.
So in this episode, I'm joined by Tom
Ruay, founder and CEO of Demand genius.
He's got tons of experience, working
across multiple SaaS companies, and
he's worked at the intersection of
sales growth and enterprise SaaS.
DemandGen helps B2B marketers build
brands that win in the AI era by turning
content into a measurable growth engine.
And yes, I know I just said that
SaaS and FinTech are different.
However, he still has some very
interesting insights as well as a tool
that can help you understand a little bit,
what the impact the content has on your.
Marketing.
So in this conversation we explore
why most content fails to drive
revenue, and what information gain
really means in ai, the AI era, how
AI is reshaping content discovery, the
difference between influencing buyers.
Early versus capturing demand
at the bottom of the funnel.
We have a nice little debate about
that and how to use content to
support sales conversations and
actually accelerate deal velocity.
If right now you're focused on
pipeline positioning content,
then this episode is for you.
Araminta: Let's hear from Tom
Generic intro: You are listening to
the FinTech Marketing Lab podcast.
I'm Arminta from Mint Studios, a
content marketing agency specialized
in the FinTech space, and this
podcast is where we experiment,
explore, and break down how FinTech
marketing actually works in practice.
Each episode I talk with top FinTech
marketers about what they're testing,
what they're learning, and how
they're pushing the boundaries of
brand strategy and team building.
With that, let's get into today's episode.
Araminta: one of the first questions
I want to ask you is, in your opinion,
why, why do you think content is
often not seen as a revenue driver?
Tom: Yeah, I was thinking
about that a little bit.
So I think marketing as a whole isn't
a revenue in like traditionally in.
B2B SaaS, certainly, and
generally in B2B, right?
It's always like the
sales are the closers.
The rainmakers And marketing, I think
always runs the risk of becoming
a support function for sales.
Which always, inevitably
they're gonna be right.
If you're a sales head motion, that is
kind of marketing's job, but not entirely.
It's very easy for that to
become too kind of subservient.
And content always has always existed
at the more organic, less directly
attributable end of marketing So
marketing solves with that, then
content is bumped in most of all, , but
it's actually, it's an attribution
problem, not an impact problem.
Right?
Because actually content
is the channel that.
Has an impact across
literally every metric.
If you're nailing that and you have great
pieces of brand, kind of pillar content
going out, it supports sales very heavily.
I think it's changing a little bit as
PLG, as buyer behavior changes basically.
So As buyers don't talk to
sales reps every step of the
way and have these kind of look.
Long, very human
intensive sales processes.
I think it's putting more and more focus
on content, and I think that's starting to
filter through to the way that certainly
marketing is prioritized within a B2B
business and as a result, content.
Araminta: no, I totally, I think
I agree with what you're saying.
And it's interesting that you're also
seeing that that's kind of changing.
I also feel like I'm seeing
that more people are keen to
have . Attributable, , content.
So I don't know if this is a change
in the market, but just more and more
people are like not willing so much to
create content that is harder to track.
Are you seeing that as well?
Tom: I think I'm seeing
people go in both directions.
I'm seeing some people really lean into,
and I think it's particularly the, I
think the key difference is where there's
a PLG motion or a freemium motion, I'm
seeing a lot more people lean into brand
spend, which encapsulates all different
forms of content and being quite willing
to get away from every department, having
their own kind of trackable revenue number
that, that or KPI and viewing revenue
as a whole and, and understanding that.
You have to make a decision as to whether
you are comfortable with making those
investments and therefore not having
every little piece be attributable or not.
But , I definitely see some businesses
going in the same route, and I think it's
something that I think a lot of content
and kind of organic focus teams struggle
with and feel quite handcuffed by.
Which it sounds like is, is what you see
as well, it, it feels like it's a, I guess
for you, is it an obstacle that you have
to overcome with clients because they're
like, how can you help us get around this
Araminta: I think I have a selection
bias, obviously, because the people
who reach out to us are clearly.
Wanting to create content that
delivers measurable pipeline.
Right.
Like that's why they, that's
'cause that's what we do.
So they reach out to us.
So, uh, I don't always see the other
side, so it's hard for me to, and maybe
that's why I think I'm seeing more
of it's because, well more people are
reaching out to us, but I think it's
also because there is more pressure.
from leadership to be able
to, to hit those metrics.
You know, just as the tech industry
has changed and there isn't money
flowing around like there used to be,
I remember three or four years ago,
people reach out and be like, look,
we just wanna create great content.
We just want the best content.
Don't hear that so much so anymore.
And I think that's also because of
ai, to be honest, because now ai, a
lot of people are just using AI to
create content and maybe it's not the
best possible content quality wise,
but it kind of meets the standards.
So then they reach out to us and
they're like, okay, well we are creating
content, but it's not bringing in.
Customers, can you help us?
That's kind of what I, I am seeing.
But yeah, it's an
interesting market dynamic.
What would you say is then like the, a big
opportunity that you're seeing in content?
Because so much has happened, right?
You've got AI.
As you're seeing yourself, content
is part of the whole marketing,
especially in B2B the whole marketing
kind of funnel and everything.
So what are you, what are you seeing
people maybe are, are, are ways
that are underutilizing content?
Tom: I think if we think about the content
itself, the biggest thing for me is the.
Information gain is something
I would treat as like a north
star of a content strategy.
Now I think AI is a really, really
huge shift to the way that a content
marketing team needs to operate, right?
So traditional content marketing, the way
I think of it is you find a really common
query that your audience has a question
that they ask a lot, and you synthesize
knowledge against that question.
And if you do the best job of
synthesizing all of existing
knowledge to answer that query.
You are the one who wins the traffic.
And then you have an onsite conversion
funnel, which takes all of this kind
of nebulous, not necessarily related
to you traffic and tries to build a
relationship based on what you actually
want to talk to those people about.
And that's always been a part of the
attribution problem as well, right?
Is that it?
It's, but it has to be
very broad at the top.
'cause we're obsessed with traffic.
I think that role of a content marketer.
Is a complete mindset shift
that people have to make.
I think a lot of people now are
struggling to make, because what does
AI do on a personal bespoke basis?
With full understanding of all
of your context and all of your
requirements and who you are?
It synthesizes knowledge so that
that workflow, that kind of user
job to be done disappears entirely.
So as a content marketer, how
can you add value to humans?
How can you in.
Produce content is gonna be
picked up by machines as well.
You have to produce some kind of
meaningful advancement of knowledge.
So in terms of where the opportunity
exists, we've built this framework
for measuring information
gain that puts it into tears.
There's a first tier and then there's
the second tier, which is, um, empirical
gain, and then there's conceptual
gain, and so you can kind of rank them.
I think getting up most of, most
content exists in Xero, which
is there is no information gain.
It is just rephrasing, reframing
things that already exist.
Tier one is adding a bit of a new
slant on something that exists
and then you can go up from there.
I think I would make my goal being
to have as much in that two tier,
tier two and tier three information
gain level because then you're doing
a job that AI can't do and that
creates a, a value in your content.
Araminta: And, and what do you
think is the best way to do that?
Because another thing that I've seen
is, you know, four or five years ago
people would say, oh, can you not just
do desk research and create the content?
And we don't hear that anymore
because everyone understands
that, Hmm, what's the point?
You're not adding anything
new to the conversation.
AI can do that as well.
We used to get pushback and we had to say,
no, no, no, let's interview the experts.
We don't get pushback anymore.
Now we have no problem interviewing
experts, but like, how would you.
What are the best ways to, to create
that content that is different, as you
say, that's that tier two type content?
Tom: Y Yeah, I think it depends
on the, it depends on the subject
matter that you're talking about.
So one of the things , I'm having
great fun vibe coding at the moment.
And I vibe coded this little tool
that basically takes a content brief
or a piece of content, assesses the
information game score level, and tells
you where the opportunity is to elevate
it to tier one, tier two, tier three.
, which was cool.
It was great fun building it.
I looked to coach.
What it showed me in doing it though
is that actually not everything
can reach tier three, which is
like conceptual information gain.
That's that you've come up with
something genuinely novel, a new
way of thinking, a new framework.
Not everything lends itself to that.
So I think what I find helpful is
when you're looking at this to be
deliberate, okay, for the topic
that we are looking to talk about,
what is attainable and realistic?
Now, obviously empirical information gain.
It requires some resources, but
most topics you can go and do that.
You can capture data relative to
something that is an information gap
in our collective knowledge whether
it's surveys or or something else.
And you can have a high degree of
confidence that based on hypothesis
you've set, you will be able to
produce that empirical information.
Gain conceptual is a
lot more hard to define.
It's a lot more.
Uh, unlikely.
So there's a very good chance that
if you're pursuing that you will
sometimes fall short of it, or, you
know, the data won't quite, it won't
turn out that everyone's wrong in the
way that you hoped, because in most
walks of life, not everyone is wrong.
So I think, yeah, empirical is easy.
I think it's, it's very
difficult to produce that.
Third tier of it.
One thing we've found very
effective is using AI to capture
data and to look into things.
So you can do traditional methods
where you're going and survey.
I mean, we are lucky in that
what we are looking into is ai.
And so AI is naturally very good
at helping us look into that.
Um, but you can just run
analysis at a scale that you've
probably never dreamt before.
So for us, we can run hundreds
of thousands of prompts.
We can analyze hundreds of thousands
of pieces of content across all
of the FinTech industry to produce
a report that looks at trends
that we can extract from that.
If you think creatively about if
I was gonna spend a year reading
something over and over and over
again and just doing a task and,
and what, what would that produce?
Then I'm sure you can find use cases
in your world where AI can produce
really interesting data for your
Araminta: Yeah, I mean, I think
there, there's kind of a few
ways that you can add value.
You can get proprietary data as you said,
and also like interview your experts.
Like, the experts are the people who know
things that an AI will likely not know.
And so kind of gathering the,
those two kind of inputs are a
good way to create higher quality.
And, and maybe let's try and be
more specific because I think.
We're being quite high level.
Like if we take, uh, an accounting
tool, for example and maybe
they do something a bit unique.
I don't know.
They integrate somehow
with the government.
I don't know.
How, what, what, what are some examples
of maybe how you would do that tier one,
that tier two, tier three type content?
Like how how would that different
type of content look like?
Tom: So I think tier one is gonna
be a, a, a reframing of something
that people already know, right?
So we, we are doing this Synthes this
job, but we're just adding our own unique
slant based on probably some really
good work that we've done in the past.
And that I think should be kind of the
base standard for virtually everything.
If you don't have something
meaningful to say on it.
Like if you, like, when you're a
kid, if you're, have really nice
to say, don't say anything at all.
You don't have something interesting
to say, don't write the content.
I think that's a good basic principle,
tier two in that, example, I guess is
gonna be something like, okay, we surveyed
a hundred people working in the government
to find out whether integrating it with
accounting tools is a problem for them.
Right?
At the most basic level, it's
that or, or I'm sure there's a
lot more stuff peripheral to it.
Tier three would be a deep study into why.
Society has changed in such a
way as now government has to
integrate with accounting tools.
So you can see where there's a very good
chance that at the end of that you realize
that hasn't actually really happened.
But that's the kind of thing
that you're looking to.
Get, I suppose.
And if you do, one of the things that
excites me about this is if we think
in traditional terms of distribution,
if you can get that picked up by LLMs
and you can make a new concept that
you have introduced like core to their
understanding of your problem space.
The distribution that a piece of
tier three content can achieve is
basically unlimited because it becomes
literally like a part of our collective
understanding of the category.
The way that problems are framed to
every buyer starts to reflect that new
concept that you've introduced, and then
you, that's how you move beyond kind of
citation chasing in AEO, because then
whether your brand is cited or not.
That's impacted it, and that's
going to kind of push the way that
problems are framed in your direction.
Araminta: and we'll talk
about a o in a second.
'cause I think, you know, the report
that you did was, there was a few
things that were interesting there
that I kind of wanted to ask about,
but then just to bring it back.
Those three examples you shared.
You know, I would describe them all
as kind of top of the funnel content.
So it's interesting how, because
I, I was gonna ask you, you
know, is it still worth it?
Because a lot of people in the SEO o
space say, no, not worth it, uh, because
AI answers those anyway, but what
you're saying is kind of, you can still
do top of the funnel, it just really
has to be unique and different, right?
Is that kind of what you're saying?
Tom: Yeah, I would say I think
the, the goal of top of funnel
is the same as it always has.
You're trying to impact the way that
people frame problems, the challenges.
You're now trying to do it
through an intermediary.
So you need to be able
to work through AI now.
I think the reason that we like
in the industry to say that top of
funnel content isn't worth it anymore.
It's not because it's not having an
impact, but because we can't measure
that impact
one of my critical, kind of like my, my
opinions that, that maybe it's a bit more
controversial on the AEO space is it's all
been defined entirely through an SEO lens.
And that makes sense, right?
You took an interest in it.
First of all, it's only one letter.
A different, the acronym, so
the SEOs took an interest in it.
The SEO platforms built solutions for
it, and we looked at everything in that.
Like, okay, I prompted a keyword,
eh, roughly the same thing.
Let's go and see if we rank for them.
that's not, I don't think
that's very helpful.
I don't think it reflects the
way that models actually work.
And if you are tracking, one thing we
know from our study is that at the top
of the funnel, brands are not cited.
That doesn't mean that
brands aren't influencing it.
Right.
They're influencing the narrative
around the category, the
way the problems are framed.
There's an analogy I like to use
going back to my sales days, right?
Which is.
When I got an RFP request for proposal
through from a company, I could
straightaway read that and I knew which
of our competitors had helped write it.
And when I got that, it didn't say it, it
didn't say that expressly at any point.
And when I got that, I knew we'd lost
the deal because they were asking
really prominently about integration.
Someone else had helped them write it.
I hadn't, I'd just been sent it.
I was the validation and I think
there's a very similar analogy.
In AEO and I think that is where
really the long-term category
defining opportunity is you
can learn how to influence the
way that they frame problems.
I could go on for days about that and how
the models kind of converge on answers,
but maybe we can come back to that
Araminta: it's an interesting point.
I, I would totally agree with you.
And I think it comes
ultimately to positioning.
Uh, and I, I like the phrase ideology
'cause it's a bit more extreme.
But if you have an ideology, a point
of view on something, then it's a
lot easier to influence anything.
Right?
It could be lms, it could be seo, it
could be people, because it's, oh,
suddenly you have something different.
And , our POV has always been
straightforward, which is we
believe content should bring in
conversions in a way that's trackable.
Right.
Which not everyone agrees
with, which is perfect.
That's what you want, right?
You don't want everyone to
agree with your point of view.
If not, it's not a point of view.
Right.
So I, I was gonna ask, what would you
say is demand geniuses, uh, POV and
also later on we can talk about like,
okay, so then how do you track that?
'cause although I totally agree
about, you know, or, or the
fact that brands don't come up.
You still have to talk to A CFO.
Who's gonna.
Ask why invest in this?
, but first question, what was
demand Genius's point of view?
Tom: Yeah, that's a very good question.
I think so I, the awful answer
is I, I'm, I'm a fan of A-D-H-D-I
think we've got like 12.
That's 'cause I can't focus on things.
I would say our point of view on the
AI space is that it is a fundamentally
different problem to SEO and that it is.
The winners of the people who win AI
search will be those who can demonstrate
fit for the right criteria rather
than ranking against specific queries.
And what I mean by that is
probably you sort of go, so one
thing that our study showed is.
So there's very, very little
variability in what brands are cited
at the bottom of the funnel, right?
There's that we developed called a
KAK number, which basically shows
you how many of, if you run the same
prompt over and over time, over and
over again, how many times do we just
see the same brands come up again?
And at the bottom of funnel
conversion focus queries.
, the K number is virtually one,
which means , it's the same brands
that just repeatedly come up.
So what really matters is whether the
option pool is narrowing in your favor.
Right.
Another, one of our kind of core
beliefs in this space is that we
treat prompts as isolated events
and they very much are not.
Right.
A prompt that we track at the bottom
of the funnel doesn't just happen.
There's a series of conversations in a
complex journey that take you to that
point, and during that time, criteria
are applied, which inform how, who
ranks, or who is visible in that end.
State, and we know that it's
largely predetermined in
that bottom of funnel query.
So where the opportunity is, is not small
optimizations at the bottom of the funnel,
but actually, if we can go further up
the funnel and we can make more of these
chains of prompts, more of these chains of
conversations converge in our direction.
That's our point of view, and
that's what we help you do is.
Act on that and do it in a
way which is still measurable.
And I would disagree slightly that,
that things like that aren't measurable.
I think one thing AI is fantastic at
doing is turning probabilistic data into
something quantifiable or taking, doing
qualitative analysis in a way which
produces a quantifiable output so we
can analyze a hundred thousand pages of
content, score them on information gain.
And all of a sudden
information gain is a KPI.
That was something that was, would've
been impossible five years ago, but
now you can treat something like that
as a KPI and we can do a lot of the
same things when it comes to things
like understanding how a narrative is
impacting the overall market narrative,
because we can, AI can understand that
we can do sentiment analysis, we can
pick up semantic kind of links between
different phrases and stuff like that.
Araminta: And how would you pick those?
'cause yes, I think it makes
sense what you're saying.
You need to go, I guess, higher up in
the funnel is kind of what you're saying
and, and influence them earlier on.
But how do you know which prompts
they are putting in at that stage?
What are the topics
that they're searching?
How do you know what Yeah.
What you're targeting there.
Tom: Yeah, another one of my core
beliefs is like, AO it's not a
project, it's not a one and done thing.
It's an ongoing muscle.
Right.
And I think that will be a part of
the muscle that you have to have is,
but it's the same as anything else.
It is the same as how do you find
the keywords at the top of the funnel
that you want to go and try and
hit on what you have to constantly.
Look for them.
Talk to your buyers.
Understand what they're searching.
It, it, it's all of the fundamentals
of getting to know your customers.
You can do that through talking
to them like in the real world.
And you can do that through data and
performance data and by journey data
and understanding, okay, what are they
reading at each stage of their journey?
And from that you can kind of work back
to the questions that brought them there.
And so it, it, there's no perfect
way, but there's lots of signals
that you can look at to, to
Araminta: Yeah.
And it's the same with one on the funnel.
Like people always ask us,
okay, how do you know what
prompts or topics to go after?
Well.
You know, speak to your salespeople.
What are the questions that
keep coming up and all that.
I would also say that although I
agree that it's worth influencing them
as early as possible, that doesn't
mean you shouldn't influence at the
bottom of the funnel because, uh, for
all the, the AO programs that we do
with our clients that is what we do.
We.
Actually mainly target the bottom
of the funnel because as you've
said in your reports that's the
only time that brands even appear.
, and so we have been able to
influence and change those results.
And it has led to an increase in inbounds.
Actually, we've had a couple
of clients that went from.
Zero visibility not turning up
at all in any of those lists, to
turning up regularly and seeing a
substantial increase in, in inbounds
coming through that, that channel.
So it definitely does work.
What I have seen is that it's,
it takes a little bit longer.
It's a little bit harder if it's a
very saturated market where companies
create a lot of content already.
So maybe SaaS, for example.
And it is maybe harder if.
Having said that though, we have a client
where they're competing with Stripe.
They're competing with enormous
companies that publish a lot of
content, and we've still been
able to get them in those lists.
So from our experience, I think
it's worth doing both, basically.
Definitely do the bottom of the funnel,
because that's where you'll see the
biggest impact, and that's where you'll
see the results that you can then show
your leaders and CFO and all that.
But then you.
Like, same with everything else
in marketing, you definitely wanna
go up towards the the hiring of
the funnel because that's what's
gonna influence down the line.
It just might be harder to show that
it's influenced the pipeline just
because you know it takes longer.
Right.
But that's kind of what we've
seen as well on our end.
Tom: Yeah, well, which is
interesting , and maybe I'm being
a little bit too bullish in the
way that I framed this 'cause.
One of the things that we learned
from our study that we did, and
what we did there was we were
trying to simulate complex journeys.
So we were running prompts within
the same category, the same trying
the same journey at awareness,
consideration, conversion stage.
And what we found was
only 16% of those prompts.
Ever produced a citation and they
were all in the conversion stage.
So you are absolutely right in
what you are saying that's kind of
completely born out in the data.
And so citations is a useful metric, but
it's not a very useful North star metric
we find for, for influence because you're,
you are limiting yourself to 16% of your.
Potential influence.
The way that I think of it
is as, as an iceberg, right?
So what you see if you are tracking
traffic to your site and brand
citations mentions you are seeing
the tip of the iceberg, right?
You are seeing the conversion stage.
And we know in the more complex
the journey, the smaller the, the
less critical conversion stage is
to the overall who wins, who loses.
So it's useful to see that,
and you absolutely want to
bevis visible for those.
But if that's all you are focused on,
then everything beneath the surface,
which is the iceberg analogy that was
very familiar, right, is that that's where
the mass is and that's where the meat is.
And the opportunity is is
what you risk overlooking, I
Araminta: I think the , the
mistake that maybe marketers have
made in the past is they only do.
The chunk underwater, the, the stuff that,
as you say is the biggest opportunity.
But the thing is that if you cannot prove
it, you will not be given the budget to
invest in that chunk underwater, right?
And so that's why we focus
on the chunk that is visible.
And yes, there's a smaller
proportion, however, I will say
people always underestimate how.
How big it is.
It might sound small, 16%, but it's
actually a lot bigger, especially
when the intent is a lot higher.
And that's why we always say, you
know, you wanna be doing both.
We'll take care of the part at the
top, the 16%, because that's what
allows you to prove and ensure
that it's working, et cetera.
But you do need to do the rest as well.
We even have a client that
was like, no, no, let's just
do the bottom of the funnel.
It's working super well.
We're getting lots of in embeds.
And we were like.
Please invest in other stuff internally.
Like, this is not what we do,
but you, you need to do that.
Because if not , you're missing
out on the, a much bigger part of
the, of the marketing funnel and,
and of your target, audience.
But it's an interesting kind of dilemma
because yeah, what, what's trackable
is also super important because if not,
you know, leaders nowadays need to see.
See what's working and all that.
But anyway, so I want to, we're
going very deep into uh, into
content frameworks and all that.
I wanted to talk also about like
distribution channels, because I mean,
LLMs, our distribution channel, but
you've said, and I know this is a big
part for what demand Gen use does,
is kind of, you know, salespeople
are a fantastic distribution channel,
and I, I totally agree with that.
Uh, I find that the biggest blocker
there is that, you know, it's hard
to encourage them to, to share it.
Right.
Maybe it's a culture thing or maybe it's
just hard for them to find the content.
What have you found works there?
How do you encourage salespeople
to distribute content?
Tom: Yeah, well maybe this is where I,
I, I have quite a unique background for
someone who works in content and I don't
think a lot of people have gone from
being kind of a sales rep recovering
sales rep into the world of content.
I have to get a sales
person to do anything.
You show them why it
makes them money.
makes them money.
Right?
Speaker 3: true.
Yeah.
Yeah, yeah.
Tom: I, I think there, there's
two things I would say.
One is.
Have a conversation about how you
can remove whatever the barriers
are to them sharing content.
, and to take that seriously.
Like I'll, I'll give you an example.
Going back to one of the roles that
I had, one thing I had said over and
over again is I just really don't
like sending a prospect that I've
just spent a lot of time building a
relationship with to a gated a gated
thing when I can download the PDF.
And that was always a sticking point.
It felt to me like we are prioritizing
marketing's attribution needs over my
relationship with the person who spend
five grand on a piece of software.
No deal.
So that, that, that's one thing where
I think put, put work from customer
experience to your attribution , in
the Right priority order.
And that's where sometimes the, the sales
reps aren't as evil and, self-motivated
as as, as they're often presented.
And often it is stuff like that, that
actually is, is holding them back.
Um, or at least is why you
don't see them sharing it.
, the bigger impact is
gonna come from getting.
I ironically, your attribution
sorted in such a way as you can show,
like, I think I, I think of there,
there's two forms of attribution.
I always think of political attribution
and I don't mean that with a.
Kind of negative, the negative
connotation that it would maybe carry,
but it's about proving the impact
that you are having and that's great.
That's fine.
That's important.
And then there's like practical
attribution, which is understanding,
going back to your question around
what prompts the track, understanding
what are people reading in every
stage of the journey, how does that
engagement impact what we care about?
So it's not difficult analysis,
it's something within the platform.
We do out the box.
But you can do it if you're
really good with look and.
Your, and you have, you
get access to your CM data.
You can see, okay, when there's
two content engagements or two
stakeholders engaging with content
versus three, how does that impact
the speed with the to deal closes?
How does that impact which
stages it gets stuck at?
Where, where are things getting
stuck and are we getting content
engagement if, if we have a, if
we have no, we have a bottleneck.
In technical stage of our process
things are getting stuck there for
three months and we're having no
content engagement during that point.
Well, that's a content gap.
We look at content gaps
exclusively by interest and by
our kind of top of funnel, SEO.
Where are the high intent queries
rather than those kinds of gaps.
But you can go and look at
that data that allows you to.
Make yourself really, really useful to
sales because if that's happening, I
promise you it is probably their biggest
pain point, day to day that they are.
They are under pressure to chase
and to maintain relationships with.
The kind of buyers during that three
month period where it's blocked.
Um, and they really wanna be able to do
that in a way which isn't chasing them and
being annoying, but their boss is telling
them to get an update and giving them
content that they can use in that stage.
So it's organic.
Here's some insight by
the way, what's going on?
They will love it.
And then also proving why doing that
actually closes deals faster at a higher
value and, and makes it more likely.
Araminta: Yeah.
No, that's great.
I think there, there's also,
there's definitely a top down thing.
The head of sales or the sales leader
needs to be the one, I think, rather
than the marketer, uh, showing this,
because I think it, it, you know,
salespeople might be skeptical and
be like, okay, what do you know?
Whereas if there are sales leader
is the one who says, look, this has
proven to, uh, you know, increase the.
I don't know, close rate
by x percent or whatever.
Then it's worth, and then
they're more likely to listen.
So there's also a culture thing, which
is also I think where it can be tricky.
What have you found works best for
how salespeople can find that content?
Do you find that companies, maybe they
have like a notion document with a list.
Do they have like a repository?
What have you seen works best here?
And also later on, let's talk
about how Demand Genius also kind
of helps with that side of things.
Tom: Yeah, I mean, so I think
my general philosophy for stuff
like that is repositories.
It's a good first step.
Ideally, you want to put
that stuff in their workflow.
Rather than have it be either
something that sits in an email
update or, or something like that.
So a custom GPT that allows, like
the, the simple version and everyone
is perfectly technically capable of
doing this, is create a custom GPT
change on all the content you have.
Give it to your sales reps and say, if
you're wondering what you can share.
Pop your question into this, it'll do it.
That, that's a pretty basic thing to
build that will help them a lot more
than a great big notion documentary.
And it's also easier for you to
maintain 'cause you don't have to
worry quite so much about all the
classification, it can do that for you.
So I think that that's
the simplest solution.
We've got some stuff
that we've thought about.
We don't have it at the, at the moment,
but in terms of like, uh, actually
integrating like all of the performance
data into that, so you can be a lot
more prescriptive and that, there's
certainly some cool stuff that someone
could do and we might do there, but I
think the basic level is, put it in their
workflow rather than just giving them a
Araminta: Yeah.
No, I think that's really good.
That's good advice.
And so I know we can't show video really,
'cause this is a listening podcast mostly.
Um, how, how how would you describe
or explain the Demand Genius helps
with, uh, tracking and showing
kind of some of these metrics?
So, for example, I know that you
can show that, uh, I don't know,
the content has helped with.
Sales, um, has helped speed
up certain sales cycles.
So what are some of these
metrics that you can see in the
platform that helps marketers and
salespeople, I guess, as well?
Um, track and, and see
the impact of content?
Tom: Yeah, the best, so the easiest way
I can explain it is always very bad for
podcasts because it's, it's, dude, I,
I like to draw a little hand diagrams.
But the, the way I think there's two
bits of data that you need to connect
in order for that to happen, right?
You have your web engagement data.
And your kind of CRM deal data.
Now, HubSpot, for example, is
doing a much better job now
of, of connecting those things.
If you use HubSpot, CRM plus CMS, you,
you, you might be in a decent spot there.
Most people, the, the CMS and the
CRM are different things entirely and
they don't talk to each other at all.
So that's, they're the two
things that you need to connect.
So demanding is very simply sits as
a layer in between those two things.
We integrate with both.
That allows you to solve a few problems.
It allows you to track which LLMs like
go all the way back and see which LLMs
are actually leading to closed one deals.
It allows you to map everything
that people are reading.
Along the way and give you that
like detailed practical insight that
you can use to understand, okay,
what prompts should we be tracking?
And that's one of the things that like
nice pain points that we just put on
autopilot of we will constantly analyze
your data and surface the prompts
that seem to be making an impact so
that you kind of don't have to have
that headache and then to prove the
impact that you are having as well.
Not just prove it against milestones
that you care about in terms of MQL close
one, which I mean for the most sales led
businesses that might be 12 months apart.
But actually look at how you're impacting
the intervening space as well, because
suddenly you can start looking at
okay, a demo technical proposal, all
of those stages that we pull from the
CRM and understanding what engagement
you're driving in each one of them.
So it allows you to be a lot more
surgical in your content strategy.
And give other people around the
organization information on how that's
Araminta: Yeah, and I think that the
opportunity really here is that the
content that isn't so bottom of the
funnel, which is more like higher
level and will take months before
someone closes, it allows you to take
that content and kind of see the role
it plays in the kind of sales cycle.
Right.
Uh, that PDF, uh, or guide that they
downloaded 12 months ago now you can
see how that was a touch point that 12
months later get to a close deal, right?
Tom: Exactly that.
And, and, and see which stakeholders
it's impacting and stuff like that.
When you talk about sales and marketing
alignment and also just the ability
to take a content roadmap from
something that's very top of funnel.
Topical to something that's actually
looking, I use that word surgical
again, like surgically looking for
gaps and bottlenecks in the buyer
journey and seeing how content, and
to your original question of why is
content not seen as a revenue driver,
that's where it comes full circle.
'cause suddenly you are right.
If you are like, that's the
language that A CRO or A CEO speaks.
If you're like, I can improve your
close rate and improve your deal
velocity, they will listen and they will
Araminta: Yes, exactly.
Well, now that you've done this for a
few companies, it'd be interesting to
hear like what are some top of the funnel
content pieces or types of content that
you've seen that maybe people historically
would be like, yeah, not sure really.
Uh, if this has much fun impact,
but we know it's good, and now
you're able to see, okay, this
is really having an impact.
Is there any.
Anything like that that have maybe
surprised you or that you have seen
have an outsized impact that maybe
people didn't imagine they would?
Tom: Yeah, it's a good question.
I don't know that I've really looked
into the data to understand that enough.
Certainly I think from, from kind of
anecdotally, from looking across different
clients that we've worked with, , it
varies very much company to company.
It's not quite as simple as being
like chi across all clients.
White papers are doing fantastically
well, um, or across all clients, lead
generals are doing fantastic well,
or something, anything like that.
So generally speaking in terms of
formats, the picture looks roughly
as you would expect it to look in
terms of what they engage with, where.
Um, you see a correlation that as
they move through the funnel, it gets
more like to meaty content, I guess,
'cause you get more, more engagement.
But I've, I've not looked into the
data at an aggregate level to give you
really good, a really good answer to
Araminta: Yeah, but I guess it's, it would
be interesting maybe once you have like.
Hundreds of clients.
You can see a little bit like the, any
patterns, because I think this is where
there's no denying the opportunity.
Uh, the content that we'll have
probably the biggest impact is often
the one that's hardest to track.
Right.
Uh, so it'd be really interesting
to see maybe if we can get
closer to tracking that.
Like what is that?
I'd be interested in that.
If you ever do a report
on that, lemme know.
I'll read that.
Tom: For sure.
I mean, one thing that I'm quite excited
about , with what we can eventually
do is like, I, I think what Gong
has done in sales intelligence, so I
think, um, that there's an opportunity
to do something like that in content
intelligence, which would be really cool.
We just need people to , consent to us
using their data for aggregated reports.
Araminta: Yeah.
Yeah, that's true.
You've also in, in your report,
talked about dark ai, which I thought
was an interesting, uh, phrase.
Can you explain a bit
what, what that means?
And I mean, I, it's kind of back to what
we were talking about earlier, but Yeah.
What does that mean and what, uh.
What role does that play?
Uh, in content marketing?
Tom: Yeah.
And sorry, I probably find myself
squeezing it into every conversation
now where I'm far, far earlier than
I should, because it's what I spend
my whole, my whole day thinking about
what we, what we think of as dark AI
is everything beneath the surface in
that, in that iceberg
analogy that I gave you.
So at the moment, the AI impact that
you are seeing is limited to that
16% of the conversion Which is about
half of the conversion oriented prompts,
which are showing up in citations.
And then I don't actually know with the
exact click through rate for a citation.
Because it's hard to measure from a, for
a citation in AI through to your website.
But your traffic is showing a
fraction of Yeah.
it's a fraction of the 16%.
So I think there's two things that
that should give people a lot of
confidence in their A AEO strategy
because if that's the impact you're
seeing and measuring, just think how
much impact it's actually having.
It also should give them a little
bit of pause for thought and think,
okay, we kind of need to get a grip on
what's happening with the rest of it.
So dark AI is the 84% basically, that
sits in awareness and convert and
consideration stages that is impacting
how problems are framed, what, how
requirements are built for each customer.
And ultimately I think is where,
where categories are gonna be won or
lost
Araminta: Yeah, I mean, it's interesting
you say that because I would say, and
I agree with what you said, that I
think, uh, AEO or people are seeing AEO
through a lens of SEO when they are.
So I wouldn't say that it's very important
whether they click on that or not.
Like to me, uh, LLMs are more of
a discoverable, discoverability
platform rather than a search.
I mean, they're both, but I would
say they're mostly discoverable.
To discover new topics
and new, new solutions.
And so that's why with most of our
clients, we try and ask them, we
actually, we track LLM traffic, but
it's more of an interesting metric.
We don't really, it doesn't
really mean anything to us.
Uh, what's more interesting is,
you know, the self attribution.
So when someone submits a form,
we ask them, how did they hear
about us, blah, blah, blah.
And, uh, we have found actually
no correlation between LLM
traffic and number of LLM leads.
So you'll find like, I was gonna
do a LinkedIn post about this.
Clients where LLM traffic has increased.
LLM leads have decreased.
Opposite LLM traffic kind of has gone
up and down, maybe down a little bit.
LLM leads have skyrocketed.
So it's interesting how I and
I, this is like kind of to
support your point on dark ai.
You can't even use like website
really metrics to track dark ai.
You just need to ask the user and it's
back to that dark social whole thing.
You know, Chris Walker and all that.
It's kind of a similar, you just ask your
users is the best way to really to know,
to find out how they find out about you.
Tom: Yeah, I, I agree.
And I think the only difference that I
would say there is between dark social
and dark ai is that you can ask the ai,
um, it, it, whereas dark social, it's
a WhatsApp chat that you can't query
a thousand times and, and do really
deep analysis of the narrative you do
have another, another route that you
Araminta: Yeah, that's true.
And that's why I probably
like dark AI more.
It's more, there's more to do there.
It's more interesting or more,
there's more you can do with it, I
guess, from an analytics standpoint.
So that was, that's
what makes interesting.
. Tom: I, I think it's less of a black box.
I think we haven't worked out and I
think we are doing good a job with
anyone, but we haven't worked out
how to unpick the black box Exactly.
We're, I think we're doing well.
But it's a
journey to go
Araminta: exactly.
It's very fun.
And my last question is, you know,
let, let's talk a bit about the future.
With everything that's changing,
attribution's harder, but also there's
more you can do, ai, all of that.
What do you think content's
gonna look like in five years?
And, and also how do you
see demand genius kind of.
Play a role in that.
Tom: Yeah, there's two
things that come to mind.
I think one thing, not even the
next five years, but like now.
I think the definition of
content can become a lot broader.
Like I said, I spend a lot of time and
I'm having a lot of fun vibe, coding.
I view that as content that I'm producing.
That information gauge, that's content.
You can code content now.
And that opens up a lot in terms of how we
try to take all of this hard to track ai.
Like if the words and the information is
a lot harder to generate conversions and
relationships off of, well, maybe we can
build genuine value, add things on top and
just give it away because it's so cheap
for us to make and easy for us to make.
And that can help solve
some of those problems.
I think the definition of
what is content can expand.
I also think in terms of the website,
we will see much, much lower volume
of much, much more dynamic content.
I think one of the challenges of
the SEO lens where we basically say.
Keyword equal, A prompt and a keyword
are the same thing, and we're gonna go
and we're gonna turn out loads of pieces
of content to try and keep up with the
sheer number of possible prompts that
you could have within a complex journey.
It leads to this massive expansion
of the complexity of your site map.
What we said initially actually impacts.
AI performance is positioning.
I think of it as there's three like points
on a giant positioning content reputation.
Your goal is to keep those three things
as closely aligned as they can possibly
be, and then you create no spaces.
My, my hypothesis, I can't prove this
yet, is that that's why comparison
content works so well, because for
most brands, those three points
are really disconnected because the
brand has evolved over 10 years.
So you've created all of these
contradictions, all of these ambiguity.
Who you were then doesn't line
up with your latest content
and your latest reviews.
And so you're confusing in NLM
as to who you actually are.
'cause it looks at your, at all of the
information, not just the latest stuff
that you've got on your product page.
So your goal is to keep those
three things as close as possible.
At which point, this like content debt
becomes a real problem if you have 2000.
What we started working with a
client with 10,000 pieces of content.
How on earth do you ensure that
you are clear and consistent
across all of that content?
Let alone all of the reviews.
You can't.
So I think in this kind of era, less high
quality, genuine information, gain content
that can also ultimately will dynamically
alter for different user groups and
based on the prompt that sent them there.
And there'll be all sorts
of stuff that happens there.
'cause we can make so much such
advanced decisions in real.
And that's how, that's how you'll
create the effect of the SEO era,
where it's lots of pieces of content
for different user intentions.
We'll have smaller pieces that
then evolve for each specific user.
Create the breadth of coverage
without creating the complexity.
Araminta: Yeah, and it's an interesting
thing where having really tight
positioning, really clear positioning.
It, it will benefit you so much like
in such huge ways that maybe just
producing lots of content, cannot
like it, it'll benefit in ways that
are completely outsized compared
to just creating lots of content.
And I think, and it's interesting 'cause
type positioning, that's a CEO product.
Like every single department
has to be involved in that.
And that's where the hard work really is.,
Tom: I think it still requires humans as
well, which is should give some people.
So good time to be a product
marketer.
I'd suggest everyone goes and gets
a little bit involved in that.
'cause I think it's the part that is
gonna be the hardest for AI to replace.
But I think it's a, it's a good, um.
It's a nice tone to, to end on.
All it is is it's coming back to like
actual traditional brand marketing,
like fundamentals of marketing ai.
Like if we think of it as an extension of
search, it, it is a huge leap forward in
the ability of search to reflect humans.
And so you do the fundamentals
that are great for reaching
and convincing , or influencing
Araminta: Yeah, no, couldn't agree more.
Amazing.
Well, thanks so much, Tom.
This has been really interesting
and yeah, I, I love the work you're
doing at Demand Genius, so keep,
keep doing that and, uh, yeah, look
forward to, to catching up again.
Tom: Thank for having me on.
Speaker 10: Thanks for listening.
You can find show notes and
information about guests@www.mint
copywriting studios.com/podcast.
And finally, huge thanks to orama
TV for producing this podcast.
Thanks for listening, and
see you at the next episode.