Shownotes
In this episode, we unravel how advanced AI workflows can scale a truly effective outbound strategy (and not just create more spam).
Jordan Crawford shares his expertise on how to use AI to automate deep research, identify the most targeted accounts, and develop unique and relevant messaging—all without falling into the trap of reductive "AI SDR" approaches.
We also explore how to leverage AI as a thought partner, the future structure of BizDev teams, and why Clay is all the rage right now.
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About Today's Guest
Jordan Crawford has been in growth for over 10 years, and for the past three and a half has been the founder of Blueprint, an agency that specializes in structuring any data from the public web about your ideal prospects. He's also been an advisor to Clay since 2021.
https://www.linkedin.com/in/jordancrawford/
Key Topics
- [00:00] - Introduction
- [01:59] - Changes in the outbound landscape
- [06:41] - How to use AI as a thought-partner
- [11:28] - Why AI SDRs are not the future
- [14:28] - AI in the writing process
- [20:42] - What WILL replace the SDR function
- [28:59] - The difference with enterprise buyers
- [30:34] - Signals
- [38:48] - Making AI plays resilient
- [43:04] - Clay
Thanks to Our Sponsor
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This is the only truly community-led tech-agnostic MOPS conference out there. It's got the best speakers, the best networking, the best social events, and maybe even a trip to Disneyland. This isn't your 50,000 person tech company conference. It's an intimate gathering of folks who are in the trenches every day.
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Transcripts
When we look at how AI has affected go to market over the past year
Speaker:and a half or so, it seems clear to me that outbound sales has seen
Speaker:the biggest impact by a long shot.
Speaker:Let's look at the things that outbound sellers can easily do today
Speaker:that would have been difficult or even unthinkable a few years ago.
Speaker:They can scrape websites.
Speaker:They can perform these complex analyses of unstructured data using generative AI.
Speaker:They can daisy chain automations together.
Speaker:And the list goes on and on.
Speaker:So we have all these new powerful capabilities, but the question I keep
Speaker:coming back to is what is the best way to use them because technology
Speaker:doesn't change the fundamentals of human behavior and what we respond
Speaker:to, at least not right away.
Speaker:So is this about fully automating the SDR function?
Speaker:Is it about using AI to enable SDRs?
Speaker:Is it about finding better signals?
Speaker:Is it something else?
Speaker:And today's guest has been in growth for over 10 years.
Speaker:And for the past three and a half has been the founder of blueprint, an
Speaker:agency that specializes in structuring any data from the public web.
Speaker:About your ideal prospects.
Speaker:He's also been an advisor to clay since 2021.
Speaker:So well before it became a household name in the SAS world, and he's thinking
Speaker:deeply all the time about the questions I mentioned above dropping a ton of
Speaker:knowledge on LinkedIn in the process.
Speaker:If you don't follow him, go and do that right after this episode.
Speaker:Jordan Crawford, welcome to the show.
Speaker:Thanks for having me and I appreciate that you said thinking deeply.
Speaker:You, the, let the listener be the judge of that statement.
Speaker:Giving it an appearance of thinking deeply about About these about these
Speaker:topics So and and and has a lot having a lot of fun in your videos as I
Speaker:mentioned to you a moment ago One of the reasons why I enjoy your content a lot
Speaker:I would like maybe just to zoom out like you've been doing this for a long time How
Speaker:has the landscape changed aside from like the tidal wave that chat GPT has caused?
Speaker:what's been going on in the outbound world from your perspective?
Speaker:So to your point earlier about the intro is that at the end of the day
Speaker:we are dealing with people and people are a dynamic system just like AI is.
Speaker:there used to be a time where the play, Hey Jordan, I saw you raise money.
Speaker:I like money.
Speaker:Can I have your money?
Speaker:Uh, or that worked.
Speaker:Or it'd be like, Oh my gosh.
Speaker:Because you know, when you raise money, you do have a standard set of challenges.
Speaker:But.
Speaker:Basically, we've come from a world where, the frontier used to be it was hard
Speaker:to find someone's contact information.
Speaker:And then when that frontier was breached and it was easy to get
Speaker:emails, like the first people to jump on that bandwagon won.
Speaker:Same thing with the sequencing tools.
Speaker:So you used to have to type emails by sequencing tools came out and the first
Speaker:person to jump on that bandwagon won.
Speaker:And in those days there wasn't as much competition.
Speaker:You were doing pretty advanced things if you were using sequencing tools.
Speaker:And, we are now moving into this territory of diminishing
Speaker:returns with the same approach.
Speaker:And so what people are doing is they're holding onto their point, you know,
Speaker:it used to be a 1% positive reply.
Speaker:Right now it's a point.
Speaker:Oh, one, you know, for 0.
Speaker:1%.
Speaker:And so, they're holding onto the system and they're trying to get
Speaker:every last bit of juice out of it.
Speaker:And it's really challenging for a couple of reasons.
Speaker:A The deliverability systems have changed dramatically.
Speaker:You can't be sending on your main domain.
Speaker:There's, I saw Tito had a post recently, there's an AI that just
Speaker:looks if the domain is registered less than a year old and it just puts
Speaker:all that to automatically to spam.
Speaker:Wow.
Speaker:You have to create these multi domain systems where there are a bunch of
Speaker:inboxes and you need to fluctuate the amount of emails that you're sending and
Speaker:the way in which you set up the inboxes.
Speaker:And if you use the same credit card on all the inboxes, Google
Speaker:and Microsoft will get you.
Speaker:And so, a much deeper technical setup that's required.
Speaker:All right, well, that's fine.
Speaker:but so deliverability is actually a weirdly big and much
Speaker:more important piece of this.
Speaker:But let's talk about the elephant in the room, which is the idea of a sequence.
Speaker:One of the reasons that you ran a sequence in the past is because You
Speaker:had some insight about your persona.
Speaker:you needed to find their email.
Speaker:You knew the titles, you knew the kind of the companies, and that was sort
Speaker:of the best that you had available.
Speaker:But the shift that's coming and it's not quite here yet is that you don't have to
Speaker:rely on, the same message to everyone.
Speaker:Um, you also don't have to rely on the same targeting as everyone.
Speaker:So perfect example of this is I had a customer, they target K through
Speaker:12 schools they sell into that market and they're targeting the
Speaker:person responsible for like teacher
Speaker:And it turns out that that's At the school district level, that could be anyone.
Speaker:Like, sometimes it's the head of DE& I, sometimes it's human resources,
Speaker:sometimes it's the assistant principal.
Speaker:Well, in a sequence world, you're like, Hmm, what's the
Speaker:80, 70, 60 percent use case?
Speaker:Well, you target this title and you send, right?
Speaker:So, suddenly now with AI, you can send an agent out in the
Speaker:world for one tenth of that.
Speaker:One tenth of one penny.
Speaker:Let me repeat that.
Speaker:One tenth of one penny, GPT 4 0 mini.
Speaker:It is very, very, very inexpensive.
Speaker:And you can say, go find the person responsible for this initiative.
Speaker:And you can also say something like, tell me how they're thinking about it.
Speaker:Is this school district even thinking about this problem?
Speaker:So when we did this on a sample set, we limited 75 percent of the companies.
Speaker:Now, the way in which you would do that in the post AI world is you would say,
Speaker:well, they have between 000 students and they're in Georgia they're part
Speaker:of this program or whatever, right?
Speaker:You wouldn't, you wouldn't have this ability to essentially.
Speaker:do an unlimited amount of research to first qualify the prospect,
Speaker:know how they're thinking about the problem, and then know who
Speaker:is responsible for that problem.
Speaker:so all of those things mean that you can start to break
Speaker:out of this sequence thinking.
Speaker:to double click on one thing that you said, my understanding of these
Speaker:AI systems, is that you need to kind of break down that problem.
Speaker:Like, let's say, School districts in Georgia, like these criteria,
Speaker:are you supplying that criteria?
Speaker:Like this is what it looks like when a potential school board
Speaker:is considering this problem.
Speaker:Uh, now, you know, Claygent go out and find them and, and check these things.
Speaker:Or are you just giving that problem and allowing Claygent to interpret
Speaker:what might be an indicator of that
Speaker:existing?
Speaker:That's a good question.
Speaker:The problem that people have with this, with AI generally, is they want
Speaker:to outsource their thinking to it.
Speaker:You can have it as a thought partner, but to outsource your thinking to it,
Speaker:it will for sure be like, hold my beer.
Speaker:I got this.
Speaker:And the way in which that data comes back is it's like, this is celery juice.
Speaker:This is not beer.
Speaker:And it's like, it's a liquid.
Speaker:I mean, you got to give me that.
Speaker:It's like, Okay, it is a liquid, but if you said, I'm into double IPAs,
Speaker:which is a disgusting opinion to have, but if you happen to be of that wrong
Speaker:opinion that double IPAs are delicious, um, you can say, this is a double IPA.
Speaker:This is what I want.
Speaker:I want this amount of ABV.
Speaker:I want to make sure that it is from Portland, Maine, because Portland,
Speaker:Maine, of course, as everyone knows, has the best beer in the country.
Speaker:And so, and Oregon, too.
Speaker:All of Oregon and Portland, Maine, those are the two best places to get beer.
Speaker:and if you do that, you suddenly have a capability that you never
Speaker:had before, which is to answer the question if you could spend
Speaker:unlimited amount of time researching a prospect, what would you look for?
Speaker:And so the problem is you got to get your elbows dirty and you
Speaker:can start with chat to be team.
Speaker:And so when you ask it to, like what I'll do now is I'll say, I'll send an agent
Speaker:out to the world and I'll say, provide me in this case, I said, provide me
Speaker:four paragraphs about these four topics.
Speaker:This is one collegiate prompt.
Speaker:And then I split them with semicolons.
Speaker:And, It's like, Oh, well, this school got a main schools grant for education.
Speaker:I'm like, What the hell is that?
Speaker:It turns out that I have a whole new line of interesting things to go research.
Speaker:Okay, great.
Speaker:Main schools.
Speaker:There's some grant there.
Speaker:And then it said, Well, this is how I found out that the titles were different.
Speaker:I said, Who's?
Speaker:for the person responsible and it's like, this is Jody.
Speaker:She's the head of basket weaving at the school and she
Speaker:deals with teacher retention.
Speaker:I'm like, I didn't know that basket weaving was a title.
Speaker:And so you can have the agents help consolidate that information, but you
Speaker:have to then deploy your own thinking against that and go elbows deep
Speaker:and go read the main school grant.
Speaker:Right.
Speaker:And say, is there something really interesting here?
Speaker:Because then you can start to see how the data shows up in the real world.
Speaker:There's something comforting about that.
Speaker:I like the show Star Trek and I always have been in my
Speaker:mind, at least likening it to like how people in that show interact with
Speaker:the computer because they have to keep prompting it to like zoom in on this.
Speaker:And what about that?
Speaker:They're, they're partnering
Speaker:with it.
Speaker:Enhance.
Speaker:Enhance.
Speaker:Exactly.
Speaker:I love that.
Speaker:And so it, it's giving me that vibe versus like, Hey, I just do
Speaker:my job and I'm going to go play ping pong in the other room kind
Speaker:of scenario.
Speaker:And, and actually to further this, to go really deep in Star Trek
Speaker:here, there's, Commander Riker would always, leave his balls on
Speaker:the table when he would do anything.
Speaker:And there was a great scene where like data is like, look,
Speaker:it's either you or the computer.
Speaker:It's 50, 50.
Speaker:Like if we let the computer automate it, 50 percent of the
Speaker:time, it's just going to kill us.
Speaker:If the human does it, you know, So pick one and or actually Captain Picard I
Speaker:think is is actually navigating and at the last minute he uses the gravity
Speaker:of an asteroid and slingshots out of this like deadly trap and you know data
Speaker:is even like you've used a thing as a gravity brilliant, you know, and so
Speaker:this is kind
Speaker:what you're talking about.
Speaker:the trap one where they get into like a very old, um, uh, booby trap.
Speaker:And so this is totally the way to think about it with AI.
Speaker:like another perfect example of this is I was feeding it 10Ks PDFs.
Speaker:These are like 300 page documents And I'm like, quote the point in this document
Speaker:for NVIDIA's 10K that talks about why.
Speaker:It's like, Jordan, hold my motherfucking beer.
Speaker:And it came back and it just totally, it just made up people.
Speaker:It made up a quote.
Speaker:Just, you know.
Speaker:And, you know, you're already seeing implications of this when it's like lawyer
Speaker:uses case that doesn't exist at all from chat GBT to like argue that it's okay
Speaker:for us to each own a personal nuclear weapon, you know, like, so there's a lot
Speaker:of that ridiculousness that AI and so you kind of have to follow the old Reagan
Speaker:euphemism, which is trust but verify.
Speaker:So this maybe feeds nicely into, another question.
Speaker:I think you, you posted about this recently that the future
Speaker:of SDRs is not an AI SDR team.
Speaker:And, um, You know, some of your answers seems to suggest why, but for the, cause
Speaker:there are people that it's like, you know, meet your AI SDR, like these are
Speaker:products that are commercially available.
Speaker:Um, why is this a bad idea?
Speaker:Why will people not get good outcomes from doing this in your point of view?
Speaker:well, what you should notice is that none of these AISDRs are like for whom.
Speaker:And so any product that is like unless you're selling water, which is like,
Speaker:it's like, what additional value do you have for me and my industry?
Speaker:And they're making the claim that AI can just miraculously bring
Speaker:you leads from any industry.
Speaker:Um, and what that means is that they have no insight about your customer.
Speaker:They do not know the market.
Speaker:They do not know why you bought.
Speaker:What they are mainly doing is sending outbound emails that
Speaker:are about personalization.
Speaker:Jordan, you wear a hoodie.
Speaker:I wear a hoodie.
Speaker:We're basically the same thing.
Speaker:I would love it if you could buy my B2B SaaS software.
Speaker:and so what you need to ask those AISDRs is like, let me see the last 10 emails
Speaker:that you sent on behalf of a client.
Speaker:The message is where you can tell if there is, uh, hogwash in that product.
Speaker:And I can tell you, almost all of those things are showing up and throwing up.
Speaker:Which is, we personalize the first line because God wants it.
Speaker:God willing, if people read a message that talks about how they were on a
Speaker:podcast, they will buy my electric truck.
Speaker:I'm like, I live in San Francisco, I don't need a truck.
Speaker:There's nothing you could tell me about me that would make me interested in a truck.
Speaker:Now, let's envision another variant of this AISDR.
Speaker:which said something like,
Speaker:we help chemical manufacturing companies find and message.
Speaker:chemical makers that can support high temperature ingredients like water.
Speaker:that is a believable sentence because it's like, you know, me well enough
Speaker:to talk about my industry, talk about like a specific transaction I had.
Speaker:And if there's automation, I also believe that your automation
Speaker:will improve over time.
Speaker:And the one boner thing about the ASTR as like a general concept is that
Speaker:it gets worse the more it is used.
Speaker:A lot of good growth is about creativity.
Speaker:But AISDRs, because they are watered down, they're doing the same play for everyone.
Speaker:And so that will be fine for two months, three months, and they're
Speaker:going to change the system for everyone, and then people adapt.
Speaker:And so because they're not focused on a niche, they don't get better at anything.
Speaker:They actually get worse the more people adopt it.
Speaker:So any product that gets worse, the more it is used is a, uh,
Speaker:it's just a, it's a bad business.
Speaker:So I contrast that with your example, the, uh, the school board, school district
Speaker:example, um, AI is doing this research based on this very carefully constructed.
Speaker:process that you've modeled out.
Speaker:So that makes perfect sense to me.
Speaker:And you're getting back your list.
Speaker:Is the SDR or the person still writing each email by hand in
Speaker:that case, or is it still doing a first draft with a human review?
Speaker:How do we solve that last mile problem that you just described?
Speaker:Yeah.
Speaker:Well, let me answer this in two ways.
Speaker:The first is we are obsessed with personalization.
Speaker:It's ridiculous.
Speaker:we don't have a personalization problem.
Speaker:We have a prioritization problem.
Speaker:Because, You don't know why that company is on that list.
Speaker:So, if you can't tell me why, then you have no reason to
Speaker:personalize any message, right?
Speaker:Now, when I did a sample for this prospect that we're selling into,
Speaker:and I looked at 121 districts.
Speaker:35 of them had any markers that they were at all relevant.
Speaker:And you know what?
Speaker:When I did the research, the relevance determine the message.
Speaker:And so we get obsessed with all of this personalization when really what
Speaker:I say here is what's a cold email that someone would pay to receive.
Speaker:So let me give you an example of that.
Speaker:And here's how I think I'm, like a big fan of the idea of complex workflows
Speaker:because AI is getting so cheap.
Speaker:You can have AI do something that people never would and this is a lot
Speaker:of like AI agent chaining So here's an email that I closed a 6, 000 deal
Speaker:in two days because of this cold email
Speaker:Jordan it seems like you solve X Y or Z problem for your And then this
Speaker:one I'm gonna stick with the school districts for your school districts
Speaker:Uh, I searched the web and I found a district that seems to have this problem.
Speaker:Here is the contact information of that person and here's why I
Speaker:believe they have that problem.
Speaker:Um, you could even take that a step further and I could do
Speaker:permissionless outbound for that company before I ever contacted them.
Speaker:So I can chain these AI agents to actually do permissionless
Speaker:prospecting for my target.
Speaker:And I can say, Hey, look, I've got no beef in this, but.
Speaker:let's say I'm messaging the principal at the school that my customer would target.
Speaker:have you seen, No Red Ink?
Speaker:They're a great, software that will help you do writing assessments, which
Speaker:it seems like you're struggling with.
Speaker:No, I haven't.
Speaker:So now I can automate that response.
Speaker:If I get one positive reply, I can send that off to my ideal lead.
Speaker:It's like, Hey Kim, I don't know if you've heard of Broward County Schools, but I
Speaker:just got a message from the principal that said they were interested in no red ink.
Speaker:do you want me to introduce you?
Speaker:Right, that's an email you would pay to receive.
Speaker:I'm giving you a lead.
Speaker:And I can automate 100 percent of that with AI agents.
Speaker:And so, Suddenly now the message is not about what jacket I'm wearing
Speaker:or what school I went to or how there's a mascot or something, right?
Speaker:It's like actually I'm understanding my customer.
Speaker:I'm deploying AI agents on the permission list on their behalf.
Speaker:I'm waiting until I actually have value to prove and then I can
Speaker:actually send them that value.
Speaker:I saw you post about this the other day and.
Speaker:I probably like many people who watch it.
Speaker:I was like, wow, that's so cool.
Speaker:That's so interesting.
Speaker:And then there's like a skeptical part of your brain that kicks in and you're like,
Speaker:but could that actually work in practice?
Speaker:Like, it just seems like so many things have to go right.
Speaker:how are you addressing that in the market?
Speaker:so devil is in the details here.
Speaker:And a perfect example of this is, we're building a 10 K finder for a customer
Speaker:where we're taking 10 Ks, structuring that information, asking structured data.
Speaker:The first, and Clay released a, clay template to do this, but
Speaker:they would find 10 Ks that are two years old and everything
Speaker:looks good until you look into it.
Speaker:And so you have to spend a lot of time with these models to do it.
Speaker:because at any given step, you can have fuck ups.
Speaker:But the interesting thing is the models are getting so cheap, you can have another
Speaker:model, basically an agent, validate if the information is good before you send it.
Speaker:And, the way I think about this is that the best way to deploy these models is,
Speaker:The first thing is that every column of data, you need to
Speaker:look into 10, 20, 30 examples.
Speaker:And if it's making a mistake, you need to improve the prompt, you need
Speaker:to improve the inputs, um, and you need to limit the scope of that column
Speaker:so that you get reliable results.
Speaker:Um, and the way in which you think about limiting that scope is something
Speaker:I call creative constraint with context.
Speaker:And the models are great if you use this framework.
Speaker:So let's talk about those three things.
Speaker:Um, uh, let's talk about, uh, context.
Speaker:So you have to provide relevant context, which is their website is context, right?
Speaker:The key snippets.
Speaker:So you can have a column that just pulls out snippets from Google
Speaker:search results, which we've done.
Speaker:So Google, you know, if you use Google, you don't have
Speaker:to have that little preview.
Speaker:So if you type something in Google, that little preview, and if you can
Speaker:actually point Google at an individual website and say, give, give something
Speaker:in quotes and all of those little snippets become context, right?
Speaker:So we have context, um, website, Google snippets, um, constraint.
Speaker:So constraint looks like something.
Speaker:Um, I was on your website and I saw, and then curly, you know, those
Speaker:two, two or three curly brackets, five to 10 words about how they are
Speaker:managing their hall passes, period.
Speaker:And then you tell the model, fill up this sentence with this context.
Speaker:And that's constrained.
Speaker:So now it's ultra creative, right?
Speaker:Like it's inventing things from these snippets that are actual context, right?
Speaker:So it has, it's creative, it has context and it's been constrained.
Speaker:So that means that the models can reliably now produce at very, very,
Speaker:very low cost the exact thing that you want and you don't have to worry
Speaker:about them getting these things wrong.
Speaker:So that would be like a specific example of how you can narrow this thing to
Speaker:make sure it doesn't make mistakes.
Speaker:So in this process though, I'm still not.
Speaker:Seeing any SDR, like, it seems that it's not AI that's killing the SDR, it's like a
Speaker:growth hacker with AI that's replacing the
Speaker:SDR or
Speaker:am I missing that?
Speaker:in, this kind of analogy, I think about the SDR as a horse and that we
Speaker:are basically the AISDR is like, Oh, I will, where it's a faster horse.
Speaker:we will whip the horse when you're in the morning, the horse will run,
Speaker:we're, putting some, 91 octane horse, uh, you know, he put it on us on
Speaker:the saddlebag so it can go faster.
Speaker:You know, we got these great oats.
Speaker:And the problem is that if you look at the distribution of regular
Speaker:SDRs, let's put AI for a second.
Speaker:What happens is that the top 10% hate the job and get promoted to AEs,
Speaker:but, and everyone else is just fired.
Speaker:and so what kind of a role is designed for people to get fired in?
Speaker:And like most of the output is like, you're just, you're
Speaker:not, producing results for us.
Speaker:And so the problem with the SDR, I developed another framework
Speaker:called the story development representative, which is that.
Speaker:The best way to think about the evolution of this role is someone that can invent
Speaker:a test, deploy it operationally, and then take the leads that come back from it.
Speaker:And, Instead of, Trying to take this role that has elements of
Speaker:education that we're not doing well.
Speaker:We're not educating them than buyers we're not giving them any messaging, right?
Speaker:Just like I don't know you're talking with this CFO of a fortune 500 company I don't
Speaker:know figure it out like what 23 year old I couldn't do that I don't know what they
Speaker:I don't know what CFOs care about like that's an unreasonable thing to ask So I
Speaker:think the problem is the role needs to be destroyed You Uh, new roles need to, arise
Speaker:from, the ashes, which are a growth person that can operationalize low scale testing
Speaker:place, a systems person that can maintain inboxes if you're talking about cold
Speaker:email or do LinkedIn automation, right?
Speaker:and then someone to talk to the customer and that's, the, heart of a good SDR, it's
Speaker:the discovery, it's the understanding, it's the building use cases.
Speaker:Someone might call that an AE, but all of the work before
Speaker:that is really creative work.
Speaker:And the problem is that if the SDR is to survive, the only thing I think they
Speaker:should be doing on an outbound side is low scale experimentation, which is like
Speaker:spend unlimited amount of time Transcribed sending 10 messages, sending 20 messages.
Speaker:Don't your goal is not to, we don't have a contact number.
Speaker:You have to contact a hundred people.
Speaker:It's like, no, what's the very, very, very best thing that you can do.
Speaker:And if you could get it to work at low scale, you send that off to some machine
Speaker:here to, to a Jordan to be like, great.
Speaker:Let me like connect up the data sources.
Speaker:How would I do this?
Speaker:but those people should be experimentation engines if they are
Speaker:to do any outbound things at all.
Speaker:that vision has a ring of truth to me on some level.
Speaker:I don't know how long until we, we see it actually materialize within
Speaker:companies, but it makes sense to me that.
Speaker:This STR role has been, stitching together various capabilities and
Speaker:activities that don't actually have a totally natural home, you know,
Speaker:like being really savvy and curious and researching and all of that.
Speaker:And then at the same time doing a million repetitive tasks, like
Speaker:what, what super curious person wants to do the second
Speaker:No, no.
Speaker:Yeah,
Speaker:it's like what we want you to do.
Speaker:I had a friend that's he's a designer at a.
Speaker:Series a startup and he said my job Jordan is to be creative on demand.
Speaker:And those two things aren't compatible.
Speaker:Like so that's why I get my ideas in the shower I go take walks or whatever right.
Speaker:And I think that we just have this weird expectation.
Speaker:Um, yeah.
Speaker:I don't know if you've seen like the product marketing triangle, which
Speaker:is like speed, quality and price.
Speaker:Pick two.
Speaker:and so I feel like we're doing that with the SDR.
Speaker:It's like you have to hit activities, every message should be personalized,
Speaker:you're measured on output, not the quality of the test, and I won't give
Speaker:you any help on messaging or who you should target, and if you fail, we will
Speaker:take no responsibility for that failure.
Speaker:And basically the reason that you have to hire a 22 year old to do this
Speaker:is they don't have the wherewithal to be like, this feels like a setup.
Speaker:I wouldn't take that job.
Speaker:I'm excellent at selling and I would not take an SDR job at any price
Speaker:because I'm like, you're gonna ask me to do activities, you're gonna
Speaker:measure me on things that are really silly, you so I feel like that line of
Speaker:thinking is the same line of thinking that is like, Wells Fargo, like,
Speaker:fired a bunch of people because they were using, like, mouse jigglers to,
Speaker:like, keep their computers active or
Speaker:something, they're working.
Speaker:Is that an actual category
Speaker:it's a, that's a thing you can buy from Amazon.
Speaker:And so what I told, I've got some of the Philippines that works for me.
Speaker:And I was like, just so you know, if you want to expense your mouse
Speaker:jiggler, like, of course, happy to do, you know, we lost the thread, right?
Speaker:The thread is not, am I going to measure this person on the, either
Speaker:the thinking of the input or in some cases where you can the output.
Speaker:No, I'm going to measure them sitting at a computer, which is like totally absurd.
Speaker:there's a reason that there's such thing as a 10 X engineer and in a
Speaker:knowledge economy, some people can do things much faster than other people.
Speaker:And it's like, that's the same thinking as this SDR.
Speaker:It's like, be creative, I won't give you any training, you're gonna be measured
Speaker:on output, not the quality of the test.
Speaker:whereas I think a much better heuristic is how many high quality tests can the
Speaker:organization launch in any given week.
Speaker:because that testing mechanism is really what will save us
Speaker:because most tests suck and fail.
Speaker:But you only need a couple to work.
Speaker:So the team of the future, I'm just sketching this out,
Speaker:make sure I got it right.
Speaker:We have like a Jordan type person, like someone who's
Speaker:clever.
Speaker:I have to be
Speaker:He has, he, center him in, in the, but
Speaker:someone who
Speaker:can like come up with the ideas and do the like, what if we did like,
Speaker:you know, who has that curiosity to traverse those byways and, And figure
Speaker:out a potential play.
Speaker:potentially a technical person, if that growth person is not
Speaker:already technical, who can help.
Speaker:out that vision and, and execute it at a certain level of scale.
Speaker:And then we have people that are like, for lack of a better word, nice people that
Speaker:someone would like to talk to that when a lead is like, I'd like to speak with
Speaker:someone, they can hold that discovery.
Speaker:They can be congenial.
Speaker:They can be a bit charismatic and, enter them into that one to one human process.
Speaker:Is that what it might look like?
Speaker:we probably also, and maybe this exists, so you got it very close.
Speaker:there needs to be someone that understand why the customer bought and we need to
Speaker:have more of those type of conversations because these insights, these things
Speaker:that you're emailing, they come from the customer, they don't come from an
Speaker:SDR, the way that I talk about this is that your buyer has spent their entire
Speaker:life getting to the point that they want to build to buy your product.
Speaker:And so it's like, well, how am I supposed to distill 40 years of information?
Speaker:It's like, well, you don't.
Speaker:You talk to them and you let, you let your customer do that.
Speaker:And they'll generally tell you, it's like, well, why did you buy?
Speaker:Well, we're using HubSpot, but the problem is that it turns out that it
Speaker:does integrate with gong, but not like this one feature in gong that we need.
Speaker:And it was so important to us because if we don't get sentiment
Speaker:analysis in our CRM, we can't do it.
Speaker:Like they're going to tell you some weird things, things that you're
Speaker:like, we've never marketed that.
Speaker:We never knew that was a thing.
Speaker:you discovered it.
Speaker:So you need to basically extract those stories and then take those stories to
Speaker:market in a structured and repeatable way if you want to do growth of the future.
Speaker:It feels to me that every, Conversation I haven't on some level, whether it's
Speaker:outbound or marketing or whatever, always comes back to like understanding those
Speaker:essential truths of the customer and their needs or pains or desires or, what have
Speaker:you.
Speaker:I mean, they made the transaction.
Speaker:This is probably more true for mid market companies.
Speaker:This becomes harder if you're, you know, Talking with enterprise companies,
Speaker:like really, really, really large enterprises, because like I have a
Speaker:friend, he's like 50 percent of my engagements with large enterprises.
Speaker:No one ever does anything with what I do.
Speaker:And they buy for totally different reasons.
Speaker:Like there are people at organizations that purchase because I was chatting
Speaker:with a friend this morning and a very large food manufacturer, bought him.
Speaker:And they're like using him, but they're not like, like more, we want more.
Speaker:And I said, look, there's probably someone at this company that is
Speaker:responsible for innovation and they need to report that they are innovating.
Speaker:And it's like, did you buy some innovation this quarter?
Speaker:I spent the hell out of my innovation budget.
Speaker:We are innovating.
Speaker:And it's like, what is the problem you're trying to solve?
Speaker:Well, the innovation is here.
Speaker:And so like you can get these like weird things where it's like, Oh, in that case,
Speaker:the innovation person's not going to be like, look, man, I'm just, I'm just
Speaker:trying to get in my innovation budget.
Speaker:And you know, like they'll never say that to you.
Speaker:They'll be like, we want to believe in things for the future of blah, blah, blah.
Speaker:And so in that case, you have to take that.
Speaker:Um, it with a grain of salt and you can't go and target people that way.
Speaker:but usually mid market companies, you can, the customer understands the value
Speaker:here,
Speaker:to spend your innovation budget, spend it
Speaker:with
Speaker:yeah, yeah, Yeah, I mean seriously, like, Hey, you know, here's how
Speaker:young and dynamic and from Stanford and from YC we are are you looking
Speaker:to like associate with that
Speaker:oh yes I
Speaker:am.
Speaker:So there
Speaker:are
Speaker:a play.
Speaker:I mean,
Speaker:yeah,
Speaker:Let's talk about signals for a second, because
Speaker:signals are all the rage right now in the, trendy Outbound LinkedIn
Speaker:sphere and and you took a swing at signals the other day Which I thought
Speaker:was I was a nice contrarian position to take What's wrong with signals?
Speaker:We all love signals.
Speaker:Why aren't they a silver bullet in your point of view?
Speaker:have a feeling here that
Speaker:people are looking for the next laziest thing to do.
Speaker:don't get me wrong.
Speaker:I am a big fan.
Speaker:What I generally do when I'm running any growth experiment is I do two things.
Speaker:I'm like, what is the lowest calorie thing I can do?
Speaker:can I enjoy eating one wheat thin?
Speaker:Like, will that produce the energy that I need to go, take a 10 mile hike?
Speaker:And sometimes, rarely, but sometimes that works.
Speaker:And I'm like, well, thank God I didn't make a nine course meal.
Speaker:But if the wheat thin doesn't work, I make a nine course meal.
Speaker:I'm like, okay, well.
Speaker:If the laziest, easiest thing didn't work, and we kind of knew
Speaker:it didn't, it only took me a week.
Speaker:But let's actually spend two weeks, doing the best we can.
Speaker:Now, if that doesn't work, we have a big problem.
Speaker:so let's talk about signals.
Speaker:The way that people, I think, think about signals is when X
Speaker:happens in the world, reach out.
Speaker:And that is utterly ridiculous.
Speaker:that is not the future of outbound because it has the same
Speaker:problem with you raised money.
Speaker:I like money.
Speaker:Can I have your money?
Speaker:Right.
Speaker:It's like when X in that world happens, do Y thing.
Speaker:And this is why my response to this idea of signals is more like complex workflows.
Speaker:Um, which is like the school example.
Speaker:We can go back to that and say, okay, well, only 25 percent
Speaker:of the TAM was qualified.
Speaker:So it doesn't matter what those other 75 percent do if they post a job or
Speaker:whatever, like it's not relevant because they are not the cream of the crop.
Speaker:It's not what's happening at the account.
Speaker:and There is a world where if you think of a signal as after you have
Speaker:done all of your research, structured and at scale to know which companies
Speaker:you care about and you know that your customer will purchase if you find
Speaker:that they're doing this very specific thing inside of the job description.
Speaker:then send a message about it.
Speaker:I'm on board with that version of reality, but the version which I think
Speaker:a lot of these tools are selling, it's the same bag of goods as the AISDR.
Speaker:It's like when X happens in the world, send a message, but that
Speaker:is not really how people buy.
Speaker:It's not why people buy.
Speaker:and it, usually is completely disconnected from the customer.
Speaker:And so that's my, take on sort of this idea of like, if you just
Speaker:give companies enough signals and when Y happens, send an email.
Speaker:That's ridiculous.
Speaker:what I'm hearing is it's, not the idea of signals themselves.
Speaker:Like if I look at your example with the school district, the fact that somebody
Speaker:had a grant could be a very meaningful, you know, call it lowercase signal that
Speaker:is important is relevant, but it's the sort of reductive and simplistic and
Speaker:unsophisticated, use of those signals.
Speaker:We ruin everything.
Speaker:I mean, like, like all other
Speaker:emotions since the beginning of time, we've
Speaker:ruined everything and we will
Speaker:continue
Speaker:to do that.
Speaker:there's a reason that clay is doing so well and they are
Speaker:growing at such a great clip.
Speaker:Because.
Speaker:Clay allows you to capture the nuance in the world and structure it.
Speaker:and none of these signals tools, I mean so far that I've seen, allow you to do that.
Speaker:Which is like a perfect example.
Speaker:I built a tool that monitors anytime a keyword is posted on LinkedIn.
Speaker:And it's like instant.
Speaker:So it's like within less than a minute when someone posts.
Speaker:Now, the problem is that the person that post might not be your buyer
Speaker:and the topic of the post might not be completely relevant and the
Speaker:company might not be a good fit.
Speaker:and so the signal here is someone posts on LinkedIn.
Speaker:Now the unsophisticated growth person will be like, if they mentioned this
Speaker:keyword, send them a message and you have for sure received these messages too.
Speaker:That's like, Hey,
Speaker:I've got multiple this week.
Speaker:Like I saw you posted, like commented on XYZ want to buy this?
Speaker:Like,
Speaker:Yeah, yeah, yeah, yeah, and that's
Speaker:and that's the problem is that these are how all these tools are designed
Speaker:because they don't allow you to capture the nuance in that, in what happened.
Speaker:and what they're trying to do is they're trying to personalize themselves out of
Speaker:a torture machine, which is like, if I only could write more fake compliments
Speaker:about you, then you'll buy my thing.
Speaker:Whereas it would be a different thing if I said, And let's talk
Speaker:about a complex workflow example.
Speaker:So let's say I, and let's talk about a totally automatic.
Speaker:I parse your recent podcast.
Speaker:Actually, we do this with Airtable.
Speaker:But I parse your recent podcast and I say, Okay, great.
Speaker:Who has this person interviewed?
Speaker:What are the general criteria of the people?
Speaker:Well, it's probably things like the amount of followers so that you can
Speaker:get more distribution in your podcast.
Speaker:It's probably something like do they post on LinkedIn often because you
Speaker:know that they have something to share.
Speaker:it might even be how controversial are their takes or something, right?
Speaker:Well, I can distill some of that.
Speaker:Publicly and programmatically, and then I can go find you
Speaker:another person to interview.
Speaker:And let's say I selfishly wanted to be interviewed, I could build this workflow.
Speaker:And I said, Hey, Justin, like, I was listening to this
Speaker:podcast, which would be a lie.
Speaker:I was listening to this podcast and, you were targeting this growth expert.
Speaker:Have you seen Jerry?
Speaker:Jerry has about 20, 000 followers and he posts about once a week on LinkedIn.
Speaker:And specifically he talks about this same topic.
Speaker:I looked through all of your past posts.
Speaker:I couldn't find that you've had him on.
Speaker:Um, he's a good friend of mine.
Speaker:Do you want me to make an intro?
Speaker:that's like a much different message.
Speaker:And in that case, the only thing that I'm not actually trying to
Speaker:attempt to close a deal or something.
Speaker:I just want to provide you value.
Speaker:And presumably if I can provide you value, it is the first step
Speaker:towards a relationship where you might then invite me on the podcast.
Speaker:And that is way better than the, you know, I also get, multiple emails a week about
Speaker:like potential guests for the podcast and stuff, because there's these podcast
Speaker:booking agents that that's their job.
Speaker:And quite often the, the guests are not very relevant and, you know, they
Speaker:haven't necessarily done any research on the show and, or any of that.
Speaker:And that's a
Speaker:human being probably doing it manually, I think.
Speaker:you can have AI agents do, I did this for air table.
Speaker:I looked at the partnerships page, I had the AI agent summarize
Speaker:everything that makes a good partner.
Speaker:And then I had the AI agent search the web for people that have a
Speaker:lot of LinkedIn followers that are like all in on air table.
Speaker:And then I can go contact them and be like, Hey, Justin, like I saw that you're
Speaker:like really into air table, but I couldn't find you on the partnerships page.
Speaker:Is there a reason why you didn't join?
Speaker:So now I have information back.
Speaker:You're like, well, yeah, you know, so I can take that information.
Speaker:And then when I get three replies that are interesting and valuable,
Speaker:I can then go send a message to the head of partnerships at Airtable.
Speaker:And it's like, Hey, Justin, I know you probably been running partnerships for
Speaker:a while, but I'd actually just source some people that seem to be great fits
Speaker:for Airtable's partnership program.
Speaker:And here's some feedback about why they never joined, which I
Speaker:thought would be useful to you.
Speaker:Um, there's no call to action.
Speaker:I'm not trying to sell you anything.
Speaker:Like I'm establishing that I am a legitimate professional that
Speaker:cares about you and your job.
Speaker:And the second that you respond and you're like, Oh, this is great, Jordan, thanks.
Speaker:By the way, what do you do?
Speaker:That is essentially an inbound lead.
Speaker:That is someone that is open minded to have an honest conversation
Speaker:with you because they recognize that they are having a conversation
Speaker:among peers, not a cash hungry SDR.
Speaker:If we think about the future and we've already alluded to this about, Something
Speaker:works for a little while, we ruin it, like we, we spoil the environment,
Speaker:and we like, you know, move to another section of the beach that isn't covered
Speaker:with litter, and then we mess that section of the beach up, and we move on.
Speaker:What's to stop us from continuing to do that?
Speaker:Like, on the one hand, we have these
Speaker:tools that in the hands of someone who's capable can, Clearly do some really cool
Speaker:things and scale out a thoughtful process.
Speaker:And then we're going to have everyone that just comes in guns blazing.
Speaker:It's like, you know, AI, AI, and it's going to be a mess out there.
Speaker:I think actually this is the promise of the models.
Speaker:So let's talk about a resilient signal, if you will, which
Speaker:is the job changers, right?
Speaker:Like Justin, you bought, my cottage cheese when you're at your last B2B company.
Speaker:I imagine that you might want to buy the cottage cheese that I make because you
Speaker:knew when you're like, well, I don't know.
Speaker:Jordan, I love your cottage cheese.
Speaker:I would love to bring it into my office so that everyone here can eat it.
Speaker:and so that works because my cottage cheese competitor, even though it's
Speaker:the same shit, can't copy me because they don't know my customers and they
Speaker:also haven't built the deliciousness, loyalty that, that we have established.
Speaker:Right.
Speaker:And so it, that cannot be.
Speaker:Uh, stolen from you essentially.
Speaker:And so I think that the idea behind it, I think that there is a product to come and
Speaker:it might be a derivative product of Clay.
Speaker:These complex workflows, Um, in the perfect example is the post
Speaker:workflows, the LinkedIn post workflow.
Speaker:If I can take in the context of your website, this all programmatically,
Speaker:identify the keywords that you would care about, turn on the monitoring,
Speaker:and then use that same generative AI to identify if they are good fits for you.
Speaker:And what I can do is I can deliver that as a slack notification.
Speaker:I'm not messaging the customer in this case, but I am
Speaker:filtering the world for you.
Speaker:I am delivering you something that the large language model has taken in
Speaker:enough context to be able to deliver you something that is unique to you.
Speaker:so I think that that if we are to build like these systems that can
Speaker:deploy to different companies, that that is what will have to happen.
Speaker:And I think what will be true today also be true tomorrow,
Speaker:which is there's a bunch of money.
Speaker:There's a bunch of dumb companies with dumb amounts of money that are
Speaker:trying to serve absolutely everyone.
Speaker:And And their go to market will fail totally independently of
Speaker:how good your growth systems are.
Speaker:And those people run up against fundamental realities in the market that
Speaker:no amount of great workflows can solve.
Speaker:And so, and I think that generally the problem with these horizontal
Speaker:go to market tools is that They are often selling to people that
Speaker:have no clue what they are doing.
Speaker:And so you get two groups together, the AISDR, which is like an SDR for everyone.
Speaker:You know, it's like, we can make sure that we can target anyone, anywhere,
Speaker:anytime with the best message.
Speaker:it's ridiculous on the face.
Speaker:And then these companies that want to use those AISDRs that have the same asinine
Speaker:idea, which is like, Who's, who's your ICP anyone under the sun that breeze and says
Speaker:the word marketing in that title and it's like, well, what can you do with them?
Speaker:Absolutely anything in marketing.
Speaker:Right?
Speaker:So get those two yokels together and it's like, Oh wow, growth isn't coming out
Speaker:the other side and we have no idea why.
Speaker:Well, I could tell you why,
Speaker:is survival of the businesses that are producing 10 X outcomes for
Speaker:their customers where the competitive environment for their customers.
Speaker:Is like light relative to their solution, which is to say that if I'm selling you
Speaker:a guitar, there are lots of guitars.
Speaker:Um, but if you've never heard music before and I'm selling you a recorder, right?
Speaker:That is a much gigantic, that's a huge gap.
Speaker:Even though the recorder is not nearly as complex of an instrument
Speaker:as the guitar, the recorder gives you music where none existed before.
Speaker:And the problem we have today is people are selling thousands of replica
Speaker:guitars to basically music experts.
Speaker:They're like, oh, mine has more strings.
Speaker:It's like, I don't need more, but you could.
Speaker:Like, you could use more string.
Speaker:Their strings are slightly better.
Speaker:And you're just like, yeah, I mean, I guess so.
Speaker:Um, and so there's just a lot of products that shouldn't exist in the world.
Speaker:And the explosion of VC money and SaaS, like, has meant that a lot of
Speaker:people are trying to grow products that fundamentally the company shouldn't exist.
Speaker:I think it's true and that reality will hit a lot of people and they'll, they'll
Speaker:be like a thinning of the, the herd and that'll just be market forces at work.
Speaker:I want to close just for the time we have left, just for your, just for your time.
Speaker:Your thoughts about Clay, not that I want to make it all about Clay because
Speaker:I'm almost tired of seeing that word everywhere because everyone's so, so
Speaker:into Clay since they raised some money, but it has seemed like there's this
Speaker:explosion and I have, I have a lot of thoughts about like what they've
Speaker:done well and are enjoying like really well earned success in terms of their
Speaker:product and their community and the people building businesses around
Speaker:their platform as a someone who was like early onto that train, what's
Speaker:your perspective on what they've done right and what they are doing right?
Speaker:Clay is the exception that proves the rule.
Speaker:And it gets people excited to build bad businesses.
Speaker:You have to know that Clay had struggled for the longest period of
Speaker:time, and they raised enough money in an era where that was relatively easy.
Speaker:And Kareem is a founder like Ivan and Notion is a founder where they're just
Speaker:these like thoughtful future dudes, you know, they like exist in the future.
Speaker:And they're like, what if you didn't have to drink water from a cup?
Speaker:Like, how would you do it?
Speaker:It's like, I don't know yet.
Speaker:Um, it's like, Oh my God, amazing.
Speaker:And so, um, what clay did well is that they found, like, I talk about
Speaker:this like curve, which is if your product is It's really, really
Speaker:simple for a really niche audience.
Speaker:It's amazing.
Speaker:That's what you should always do.
Speaker:And then as your product gets more complex, it becomes worse.
Speaker:But then your product gets so complex that there are people
Speaker:like me that like, love it.
Speaker:Which is like, there's enough bells and whistles there, like, and this is
Speaker:true for like engineers or whatever.
Speaker:It's like, Oh my God, 50, 000 columns where I can put 20, 000 prompts and I
Speaker:can connect 100, 000 API's like, yes.
Speaker:And so what clay did well is that they just built and built and built and built.
Speaker:Um, and AI helped a lot of that complexity that it only took develop only
Speaker:developers could have done until clay came around and they made that easier.
Speaker:And they stumbled.
Speaker:Ass backwards into that.
Speaker:Um, because they just built a lot of things.
Speaker:They had a couple of early amazing engineers that are still there.
Speaker:it is a great culture and they happen to find users like me that
Speaker:just were absolutely insane about building the things that we wanted.
Speaker:So don't replicate what they did.
Speaker:It is like ridiculously hard and people now want to recreate what they did.
Speaker:And I would never start a business like that.
Speaker:but Clay's great.
Speaker:I love Clay.
Speaker:I just, I just think that it's
Speaker:like the exception that proves the rule.
Speaker:I think those are once in a sort of generation in terms of sass company
Speaker:generations and the vibe that it
Speaker:gives me most is, you know, early days of Marketo, which is how I started my
Speaker:career because Marketo was workflows.
Speaker:It was relatively unstructured just like clay and that like you you can get smart
Speaker:people and put tools into their hands and give them A feeling of empowerment like I
Speaker:can do anything and that is the vibe I get when I talk to clay Experts like yourself
Speaker:or other folks like one other guy spoke with these like first time I use clay I
Speaker:just went home and I didn't sleep that night I was just up all night like just
Speaker:playing if you can do that for somebody the right type of person Then you have
Speaker:found like a tribe and not everyone can do that.
Speaker:But when you can it is magical
Speaker:that's exactly right.
Speaker:And the thing is that when clay breaks and it breaks plenty amounts
Speaker:of time, they have other features that you can use to get around that.
Speaker:And so they just literally built so much software that I'm like, what if I
Speaker:used AI here and I could like, so it's like you can kind of do a little bit
Speaker:of anything in a no code interface.
Speaker:And that's really rare to have.
Speaker:Basically something that can talk to any API and like, does this field go here?
Speaker:And you're like, paste that in a chat.
Speaker:She's like, what should I do?
Speaker:And it's like, Oh, escape your quotes.
Speaker:And I'm like, I don't know what that means, but I'm, I'll do it.
Speaker:Tell me where I do it.
Speaker:And so the combination of product plus AI has really kind of made
Speaker:it a tool for all seasons, which is not a good way to go to market.
Speaker:And they will see other challenges in crossing the chasm here, sort of Jeffrey
Speaker:Moore, but that's why it's doing well.
Speaker:Super interesting and yeah everything that we've talked about very fascinating.
Speaker:I really appreciate you coming on keep doing what you're doing Out on linkedin
Speaker:sharing your knowledge with the world.
Speaker:Thank you for that.
Speaker:And yeah, just thanks for spending time with me today
Speaker:Thanks, Justin.
Speaker:You can find me if you go to jordancrawford.com that will
Speaker:direct to my LinkedIn profile.
Speaker:So would love to have any of your listeners here follow
Speaker:me and ask me questions.
Speaker:Thanks.
Speaker:Awesome see you again
