Subscribe
Share
Share
Embed
Uncover hidden gems and insights from the world's greatest marketers.
Today. We're going to talk customer pain. We're going to talk
AI, we're going to talk b to b messaging sales. There's a
lot that's going to go on here today. Thankfully, we have Jordan Crawford here
to navigate it. Jordan, thanks for joining. And before we really dive
deeper, we'd love to just know kind of what you care about in
marketing right now. What what are the things that are keeping you up at night
or or that are exciting? You like, what what are those things that you really
deeply care about in marketing? Oh, boy. This is a
great question. And I would say that that answer to me is the
speed at which you need to be innovating now.
And specifically, AI is going to really change
how you should be thinking about marketing and sales.
And so I think it's absolutely important for you to be experimenting
with these tools, because AI is coming for my
job. Coming for your job, and we need to figure out ways to work
with it to drastically expand our capabilities.
And basically both the cost and time has
gone to near zero to do a lot of tasks.
And the challenge people have now is they're
asking AI questions that don't include
nuance and that they can't operationalize. And so
really, you need to be able to find ways to break down your work into
smaller chunks that AI can do exceptionally well.
So that's kind of my big focus right now, is how can
I take specifically GPT Four into a lot of my
process and do it in such a way that I don't have
to worry about its hallucination problem? And that's by
basically constraining the questions that I ask
of AI and the expected output.
Yeah, I think we're still at a point a place where even, like, early days
of search engines, it was really basic prompts or basic searches
weren't really harnessing the full power of this, but this is, like,
ten times more important, prompting an AI prompt versus a search.
Even so, I'd love to dive into that. You did talk about kind of
the risks that we might be heading into with replacement, things like that.
Where do you view right now in terms of marketers and AI,
that relationship? Who's at risk and what should we
be doing? Boy great question. Well, I think when
you talk about who's at risk here,
I really believe that you will be replaced by someone that uses AI.
Not an AI will replace you, certainly not in the next six months to
a year. And I think the people that are at risk are
not trying to reinvent themselves.
And this, unlike any time in the last ten years or at least five years,
is the time to reinvent yourself. Andy Grove, the previous CEO
of intel, had a really great framework with this, which is, if the
board fired me today, what would my replacement
come in and do? And that type of thinking
is the thinking that you need to be able to figure
out how should I be using AI,
what am I doing today that is inefficient and
how can AI help me? And to give you a sense of the
framework with which I use here is AI is
good with creative constraint,
with context. So you have to have those three things to
make AI really work for you. So it is amazingly good
at being creative as long as you constrain it and you provide
it the right inputs and training set to be able to do that.
Now, operationalizing, it is a different thing, different problem.
You can do all of this just inside of Chat GPT.
You can paste in the context, you can paste
in the sort of constraints. But to
do this well, you need to work backwards. And so the first
thing this weekend on Sunday, I'm giving a talk about how to use
AI for a company called Signals. And I
asked the question of AI, what questions would I ask if
I had AI replace me in the creative process?
And so my company does programmatic outbound,
so we'll help folks with large data sets, send programmatic messages,
and we've started to use AI for a lot of our internal campaigns.
And so my hypothesis is that really great targeting
data is the key differentiator between a good outbound and a
bad outbound campaign. And a lot of people have bad data. I'm not talking about
Apollo or zoom info. It's not good enough, it's not useful enough. So to
give you a concrete example here,
one of my customers is a company called Bonfire Women. They help women get
promoted at an organization. So I fed it the
company's web page and I've already done a lot of work for them, strategy work.
What should we target? Who should we target? When should we target them? So I
pasted in all of Bonfire's website and I
didn't ask GBT to write an email for me. I said,
here is the context of a website. If I had to score a company
from one to ten to determine if a company would be a good fit for
Bonfire services, what are the top ten data points I would use to
define who a perfect fit customer is? Pretend you had
perfect information on every company. So this is the lens that I
use when a client comes to me. And it came up
with ideas that I originally pitched. So I didn't provide any other context,
I didn't tell it who I was or other types of ideas.
I gave it context and that's all I said. And here are some answers to
give you some ideas. Gender diversity ratio. A lower ratio
of women to men in leadership positions would indicate a greater need for Bonfire services.
We actually ran this play. Employee turnover rate, especially for women.
High turnover rates, particularly among female employees. Which suggests the company could benefit from Bonfire's
talent and development retention services. There was a couple of bad ones in here
that were like, fine. They were just like a little too generic.
Public commitment to sorry. Presence of employee research group.
ERGs companies with existing or planned women focused ERGs
might be more interested in supporting. We ran this play, we look at historical job
descriptions for the keywords women at so we were able to determine
who are the companies that actively have an ERG employee research group?
So it was very creative. I constrained it and I gave
it context. Right. I did not say AI do my job for me.
So that was like one piece of the process that I pulled apart
so that I could have AI do different
pieces. And as I keep thinking about my workflows over
and over again, I am trying to dissect each piece and
inject AI with creative constraint,
with context. Is that helpful? Definitely, yeah. So if
we were to simplify that whole process just based on principle because I know that
every use case is so different in marketing totally just based on your
example, if you were to kind of dumb it down to a few core principles
of how to make a great prompt for that. How would
you simplify that in very clear, bullet point terms?
Boy, I'm going to answer the question I
wish you asked me, which is a politician's response.
But really the question I wish you asked me is like, what is the process
to start defining the prompts that
you should give? And I think that you need to invert
your thinking to get here, which is take what
you're doing today and write it out in as many
discrete steps as possible. So in my world,
it's like, understand who the company is, then once I understand who
the company is, I want to know who they target. Once I know who they
target, then I can think about my data sources.
Once I think about my data sources, then I can think about creative ideas
to come up with. Once we have creative ideas, then I can help with messaging.
And so I have those steps in my head and they
have never been sort of spoken out loud. And now that they are spoken
out loud and I have a process for them, I can zoom
into one particular part, which is take context on the company and
figure out what I would do. And now I have a small unit
of value that I can get GBT to help me with.
Right? And the more of those small units of
value I can string together, it helps me evaluate
what the AI is doing. So I know I look at these things and because
I know this customer really well, I'm like, bad idea, bad idea, good idea,
good idea, good idea. And there are enough good ideas because I have constrained
the problem well enough. So you need to dissect your
process. Just write it out on a whiteboard, just write down exactly what you're doing
and that should be enough. Yeah, I want to
get to the.
Operationalization I have the same problem. That's so hard.
It's so hard. Yeah, that's a big one. I want to get to that in
just a second. But really quickly, I would love to just kind of ask based
on everything that you have put together, process wise,
prompt wise, using AI for all your use cases you just mentioned, for those discrete
uses, do you feel like you're doing much
more work but much more efficiently? Or do you feel like you're doing
the same amount of work, but just ten times faster? So are you increasing the
amount of work you're doing, but you're still kind of like working the same amount
now and just doing more or working the same amount with far less
required of you to do that? I think actually
this is not a productivity hack,
which is weird because that's how a lot of people think about it.
They think about this like, oh well, I can take what I used to do
in 10 hours and do it in two. Actually, the huge
opportunity is what would you have done
with 100 hours that now you can do in one?
So something that you would have never done, you just would never have done.
Like, for example, one of the campaigns that we're running,
it takes in a company description and nothing else. It identifies
who their buyers are. And then in my case, it provides
basically a Google search for how you would find the exact
moments that those buyers would need you, which is like what my product does.
My product can sort entire markets worth of jobs data to find
the perfect moment for you for the companies that you target.
And so I basically created Google Searches
programmatically to thousands of companies
that I could have done probably 5
hours per company, right? But now I can send that because
I have creative constraint. And to give you an example, there's a good
friend of mine, David, that runs marketing at Kentech, which is a network observability
company. I know them pretty well. I have some understanding
about what they do. I did not write this sentence. I'm going to read you
a sentence that I did not write that AI wrote. But this is what
I would do if I had a limited time to write a sales email.
And this is an example of one of those search queries. So they do network
observability. So they tell you if your network is down and what pieces
are down and why it's down, et cetera. So show me
job descriptions for Network Operations Center NOC
managers that mention challenges in network performance monitoring,
maintaining network health, improving visibility across cloud and on
premise infrastructure, and ensuring fast troubleshooting for networks.
So the AI put together that search without
like it invented the title, which is like, right,
it invented the problems that exist in the title. And then it basically wrote
a Google search query for how you
would search inside of my system for the problems that they solve.
So amazingly great email that an account executive could
send one a day, I don't know, two or three a day.
So I think the greatest opportunity in AI is how do you apply
that creativity, constrain it, give it context,
but then do that at scale. And that's how you stay.
You just have a gigantic leap among the people that don't have
sales teams of 100.
So let's get into the operations side of things. You had mentioned you've
strung together some of these processes. Do you feel like you're pretty
far along there or still early days of building all the processes
you would still want to do? Oh boy. Every time I
log in to this tool, I think I'm
the problem. And I don't really feel that way about much software. I log into
much software. I'm like, damn, this dumpy thing doesn't do this, doesn't do this.
But this chat box is a particularly frustrating
thing because I think I'm
just not creative enough to be able to unlock its full potential.
And so I think that if I think about where my journey
has to go, it's way further.
But I do think I'm running far ahead of the pack.
But that is not because I have any particular insight.
I just spend so much time tinkering
with it to come up with these use cases, to test
it, to figure out what it does wrong,
what it does wrong at scale. And so I think
that really the best advice here is play with this stuff.
And you can play just with context inside of Chetty BT and
then figure out you should ask the inverse question, which is not how I should
use AI. It's like if I had unlimited time to do
the perfect thing, what perfect thing that involves language?
What perfect thing would I do? And then how can AI
help me get there? Yeah,
for sure. I love the concept of allowing it to help you
go much deeper than you ever possibly would because of the amount of effort
and constraint you would have normally. But now you can go so much
deeper. So it's not necessarily you're working 2 hours a
week, you're just going much deeper, putting much higher output
out. And I'm sure you're finding that across the board. You'd already given
one example of kind of a big process that you've kind of built now where
you've got this really impactful task you're able to accomplish. Are there other examples of
that in your process now where it's basically taken
over something that you would have been doing manually forever, and now you
just have this full system for doing it. Through AI not
the full system yet. I think I have just started a
piece apart. I just have plucked pieces of
the process and operationalized AI, because I
think that the bar for this thing
to successfully do something that I would hit send on
is high, which is that the second it starts hallucinating.
And let me give you an example. I took the three
most recent sales and marketing jobs in my database,
and I wanted to build SEO pages for every
company's ICP. So I wanted to say, well, marketer hire
sells to VPs of marketing at companies between
these sizes and that are trying to scale their paid ads or SEO
efforts, et cetera. It's not a crazy hard
thing for a person to do, but really hard at large scale.
So a perfect example of where AI would be good here,
but because I didn't give it creative constraint, and I let that
thing rip on about 10,000 companies, it just started making
shit up. To be fair,
if you gave a really smart person just the information I
give, they might like without I mean,
basically what you're trying to do is you have a fifth grader,
maybe a fourth grader, and then you give them the
Xanos glove or whatever, right? And you're like, use it responsibly,
and he's like and it's like, no, you're snapping too
much, way too much. And so you have to be like, okay,
no, do this very one thing, and test
it, and test it and test it, and then sort of scale it. And so
that's kind of how I'm approaching this process. And when I let it run amok
and I find two or three good examples, then I have to sort of pare
it back. At the end of the day, I have
to ship something that I'm proud of, and if I'm not proud of it,
I kill it. And so I'm pretty aggressive about killing stuff, but I
dip my toe, I scale it. If I review a
lot of these things, and it looks silly, the problem was that I gave it
too much creativity, and I didn't constrain it enough,
and I didn't break it down into smaller processes. So if
I had to do this again, for example, I would say, look at this job
description, and is there an ICP here? Do they talk about
who they target? Yes or no? If they do, where do
they talk about it? Great, now extract that information. Now with that information,
go do this. So really, you're talking with a fifth grader,
and you need to be explicit. And if you can break down something
that you think is one step into five steps, the AI will do much,
much better. Yeah, I think that's
a big downfall of a lot of results you see out there is just trying
to do too much with too little context. When you're looking at the scope of
if you're trying to actually build a process for this, trying to build something that's
going to be repeated many times for your business. How do you think about the
scope for a prompt or the scope for a specific query?
How do you know if it's too big or if it's too little?
How do you kind of land on that so that you kind of have some
level of certainty that you'll actually get what you wanted from
the results? I think that the
best thing to do might even be to have it impersonate
someone that knows nothing about you, your business or your context, and start
there and ask it a complex question and have it break down the
steps for you and then use those steps back in
this process. So it's like, what you might even and this is why this tool
messes me up. It's so meta. It's like you can ask it to help you
break down the process so that you can use it better. It's like, where does
it end? How far does this thing go? So I
think that the best approach is like, I'm trying to accomplish this goal.
Tell me the smallest possible discrete steps that
you would take to accomplish this goal. So that if I was explaining
this to someone that had no context on my business, my problem,
that even they could do it. Put that question into Chat
GBT, and then it will give you the discrete steps.
And then follow those I mean, audit those steps,
but follow those steps because then what you'll be able to do
is at every point you can check it.
Great. Is there an ICP? Yes or no? Okay, great. If yes, extract the ICP,
extract the audio customer profile, and print out a paragraph.
And then you can look at that paragraph and be like, that's wrong,
shoot. Let me go back and give it more like, let's break that down to
smaller steps, which is like and another way you can do is give it examples.
Here's an example. Here's an example. Here's an example. Now it's your turn. Now you
do it. And so every time, the more steps
that you have, every time along the way, you can
be clearer with it. And the possibility,
again, is not reducing time, right? This is something you would never do
with a human, right? The possibility is,
what are the gigantic possibilities if
you had a person to work near unlimited amounts of
time on a creative task? That's the possibility.
It's not saving. I mean, the low hanging fruit is saving time,
but the real opportunity is like,
what if you had unlimited dollars to spend on someone that's like,
okay, creative, and they had unlimited energy and they didn't get distracted?
That's the opportunity, I think. Do you have
any true automations going on for this yet? Because a lot of
it sounds like you're still kind of putting things in manually
to make sure you get really good outputs. But do you have plans to automate
or to have things just happen naturally? As you
have a process that's triggered in certain software, you got to start writing things.
Do you have any of that set up yet or is that in your plans?
I do. I think about this is I have campaigns that are going out right
now with AI, which is this like search campaign, for example.
So I have a handful of campaigns that I have used
that in very targeted ways where I can trust the output,
where I'm not saying asking it like truth questions.
And I think that the challenge here is that to automate
this, you need to make sure that a wrong result
won't kill you. And what I mean by that is that
the other day, sales reps like to use this for Icebreakers. And this
is an email. This is a really email someone sent. Hey, did you know that
Fiona also means white? That must be why you so pale.
Ha, just kidding. And so it's like, what? What are
you doing? That's a terrible idea. And so
that's the kind of and just the pain is
so high if it gets it wrong or it's like if
I start talking about case studies that marketer hire doesn't have,
or if it lies one times out of 100,
it's too many. And so most of my
automations are not discreet.
They're like campaigns, they're not push
things through. But I will get there. But I need to
think more about how to creatively constrain it so that if
it gets it wrong and it'll get it wrong, like, it's not going to get
all these titles right, for example. But if it gets it wrong,
it's like someone will see it and be like, well, that's not exactly right,
but pretty close. As opposed to like I
see. I asked it, I was playing around. I said write
a sentence as if my wife went
shopping at this company's Brand,
and I was just like casually encountering them. And it's like invented
children and stuff. It's like I was buying some diapers for my kid. And it's
like that's where the message is probably pretty
compelling. People respond to it. It seems like a human wrote it,
but it's like weaponization in the worst possible way
because then how far do you follow that lie down the path, right?
And so that's what you need to make sure that it's
not doing is that if it's lying or if
it's not getting it perfectly right, that it's a harmless mistake.
Last one for you here. And then we'll call it quits here for today.
But appreciate your time and would love to chat again for sure.
There's a lot to dive in here. This is just one quick little foray into
AI, but my last question would be around the knots of
AI, because you have talked about a lot of things that you're trying to build,
keeping it really positive with, like, this is cool, this is cool. Here's how
to fix certain things. What are the things that you just absolutely will not
trust AI with right now, with your business?
Most things. So I think that I don't trust
it to write a complete email. I don't
trust it to act on my behalf. Like,
I would never send messages as me that
are fully written by AI. I don't believe that it can write a
great email. Maybe the only way
that I think we could write a great email is if you basically trained it
on how to write five discrete sentences with like,
six to 15 steps per sentence, and then you took
another step to summarize that email. But if anything
involves requiring of truth,
I don't trust it. And so,
yeah, there's a lot of things I don't trust with AI,
but I do think that the problem is us.
We don't know enough about how to use it, about how best to deploy it.
And so there's a question problem first, which is how do you get
the right questions? And then there's a process problem. And the
best possible tool that I've found for the process problem is clay.com.
And you basically can have conversations with Chat
GBT on a per row basis, which means that for every row
of data, you can have four 5610 chats
with chat GPT to further refine, further refine,
further refine. And that has been really helpful
to hone the results to be exactly what I want.
Awesome. Well, this has been fantastic. There's so much more
to cover here, but any parting words or last little thoughts before
we hit the stop record button? Totally play
around with it. Use it. Use AI. It doesn't matter what you use it for.
Ask you questions about distances, about just the more time
that you spend with the tool, the more you
think, I should try this with chat GBT first, you're going
to get better and more creative ideas about how to start replacing
pieces of what you do today. And think about firing yourself.
If I had to fire me today and I replaced myself
today, what would new Jordan come in to do with
AI and how would he rebuild this from the ground up?
Amazing. Jordan, thanks for coming on.