June 4, 2025 • 33 mins
In this episode of Digital Coffee Marketing Brew, host Brett Deister welcomes guest Tim, a software engineer who has created influential social media bots for growth and revenue generation. They delve into the nuances of black hat marketing, its crossover with cybersecurity, and its effect on social media platforms. Tim shares insights on his career, including the high profit margins from using bots and the ethics of such practices. The conversation covers the challenges of achieving organic reach in the current social media landscape, how algorithms and platform strategies affect content visibility, and the controversial topic of shadow banning. Tim also provides practical tips for marketers on balancing automation and manual tasks, emphasizing the irreplaceable value of critical thinking and genuine content creation. Tune in to explore the ever-evolving dynamics of social media marketing and the role of AI and automation in shaping its future.
Guest Bio:
Tim O'Hearn is a software engineer whose career took him through a wide range of businesses and industries during his twenties. In 2017, he found himself drawn into the shadowy world of Instagram and social media automation, a notorious space where violating platform terms of service was commonplace and highly lucrative. While not an original inventor in the field, Tim became a power user and skilled developer, building and deploying some of the more advanced botting platforms of the era. Throughout the late 2010s, he leveraged this expertise to establish a successful business, navigating the complex and often controversial landscape of social media underworld.
3 Fun Facts:
- Tim Ohearn is into sparkling teas, especially those found in Korean dining spots in New York City—he even describes them as similar to de-alcoholized champagne.
- Tim created some of the most pesky and effective social media bots, helping his agency rack up millions of followers and over $500,000 in revenue for clients.
- In his book, Tim shares that he was once a video game cheater who outgrew gaming but maintained a knack for breaking the rules—eventually channeling that into social media strategy.
Key Themes:
- Black Hat Marketing and Social Media Tactics
- The Rise and Regulation of Bots
- Algorithm Changes and Decline of Organic Reach
- Viral Content and Time Decay Effects
- Role of Email Marketing and Mailing Lists
- Shadow Banning Controversies and Platform Power
- Proper Use and Limits of Automation and AI
Tim's Book: https://amzn.to/43KCVqS
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
We see this crossover between cybersecurity, black
(00:03):
hat and white hat, and then marketing and search engine
optimization, black hat and white hat. The idea
behind black hat marketing, which then lends itself itself
to black hat social media growth, really
approaches it from the angle of what you're doing might not be explicitly
illegal, but you likely are affecting other
(00:26):
users on the platform.
That's good. And welcome to a new episode of
digital coffee marketing brew with I'm your host, Brett
(00:48):
Deister. If you could please subscribe to this podcast and all your favorite podcasting apps,
you have a five star review, really does help with the rankings and let me
know how I am doing. But
this week, my guest is Tim and he is a software engineer who has
created some of the most pesky and effective bots to ever be
unleashed on social media. Between 2017
(01:09):
and 2022, his agency gained millions of
followers for its clients with generating hundreds of thousands of
dollars in revenue. In February 2025,
he debuted framed a villain's perspective on social media with a
number one release in social aspects on the internet
on Amazon. Framed is Tim's
(01:31):
confrontation confrontation with the Internet age delivered
by a video game cheater who outgrew gaming, but never stopped
breaking the rules. So welcome to the show, Tim.
Hey, Brett. Thanks for having me. And my first question is all my guests is,
are you a coffee or tea drinker? I'm more of a tea drinker. Tea
drinker. Do you have, any, like, specifics you like? Green, black, or you
(01:53):
just, like, whatever? I don't really care. Generally
speaking, I've really gotten into, sparkling teas recently.
So especially on the Korean dining scene here in New York
City, I found that there's some local producers or
bottlers, and I've enjoyed those a lot as an alternative
to, like, alcohol forward, menus. So, like, is, like,
(02:16):
green sparkling tea, like, sparkling water with tea, is that how it is?
I would say it's more like a de alcoholized,
champagne. It really had like, it still has many of the
notes that you would find in a glass of champagne except, no
bite. But then, of course, there is, like, caffeine content as well.
(02:36):
Got you. And so I gave a brief summary of your expertise. Could you give
our listeners a little bit more about what you do? I'm a software engineer.
I spent most of my twenties, writing code at a variety of
different businesses and different industries. A huge
portion of it was spent in the Instagram and social media
underworld, where beginning in 2017, I was pulled into this
(02:57):
space where misbehavior was rife, and people were
making large sums of money by violating the terms of service
of social media platforms. I was not an
inventor, of anything in this space, but I was certainly
a power user and someone who developed, some of the better botting
platforms, that I used and built a business on, throughout the late twenty
(03:19):
tens. Got you. And so what is Black
Hat Marketing? I know what Black Hat is because it is like the nefarious
hackers, but what is specifically pertaining to marketing?
We see this crossover between cybersecurity, black
hat and white hat, and then marketing and search engine
optimization, black hat and white hat. The idea
(03:42):
behind black hat marketing, which then lends itself to
black hat social media growth, really
approaches it from the angle of what you're doing might not be explicitly
illegal, but you likely are affecting,
other users on the platform. So you're likely violating social contracts,
and at worst, you're probably also violating terms
(04:05):
of use, which are not laws, but they are
provided by, private businesses as a condition of using a
platform. So black hat marketing really is doing these things that
are likely breaking the rules while not being the,
computer hacker type destructive behavior that maybe we'd commonly associate.
So just breaking their TOS, but not actually, like, breaching any
(04:28):
of the user data. Yeah. That's fair. And you
managed to generate over 500,000 through social media
growth strategies. Can you walk us through your most effective tactics to
actually move the needle? This number, is one that I
have proof of, but it's something that while I was doing it, we
didn't know what the number was because we were so often looking
(04:50):
at the Stripe dashboard of monthly recurring revenue. It's
only in retrospect when I was writing the book that I actually checked
Stripe one last time and saw we were we were over 500 k.
For us, the main learning or the main, I would say,
takeaway was that when you're running a social
media automation business or something vaguely related
(05:14):
to scraping, the profit margins are
exceptionally high. At Shark Social, which is the company
that I, you know, code named in my book, we're probably talking
about an 80% or higher profit margin. This is not,
totally new, for anyone in the software as a service space,
but what was useful for us was that we were running a software as a
(05:37):
service business, but our customers thought that
humans might have been the ones growing their accounts. So there is
definitely a little bit of deception there, which I have admitted to. And
when it comes to profit, you really are locking people in
to a month over month subscription, during which
our average customer value was
(05:58):
as high as a hundred $80. I think during the time period, like, there's
obviously fat tail, but during the time period, it was definitely over a hundred
dollars, which is pretty good. And so, I mean, even in your book, you
mentioned bot automa automa automaization.
So and with that, you're saying that you use bots to
get monthly things. So what how was it successful to use those bots? What were
(06:21):
the key metrics that you found to be targeted to be successful in
gaining all that revenue? Even as far back as 2016 or
2017, Instagram had some threshold
of how many actions any user could take per day. It
doesn't matter if it's you sitting there tapping. It doesn't matter if it's me,
with my bot, you know, just continually doing something, just in
(06:44):
cyberspace. There were these bounds of how many actions you could
take per day before you might face a block or a ban or other
types of restrictive action. What made
the programs I created and manipulated so
successful was this abuse of the human
tendency to reciprocate. And on
(07:06):
Instagram, it was very, very easy to find or to
target certain content or certain creators in a niche and
say, hey, I can send maybe 300,
two hundred 50 actions per day to this account and
related accounts, and I can expect that I'll receive
actions back at a rate of roughly 10%.
(07:29):
So even on a per per day basis, that could be as many as 20
or 30 actions back. Over the course of a month,
many smaller accounts and even what you would say micro influencers
would be more than happy to get hundreds and hundreds of
real organic ish follows back per month. So that was
really the core, the core value in this system, which is
(07:51):
broadly, termed follow unfollow. Yeah. And
so, I mean, how how do you what do you have the insider
tips online on, like, performing well organically? Because everybody knows
now with Metta, they don't like organic
stuff anymore. They really want you to pay to play now. And it's kind of
like, if you don't pay to play, you don't get the eyeballs or the
(08:13):
actions as you say. So are there any tips to actually still
do that? Because I know it's getting harder and harder because the
algorithm just ruins everything, my personal belief, because it's just
it's just for them to make money. One of the
concerns that was brought up, when we first started facing
actions, you know, anti botting measures, was that Meta
(08:36):
cared less about the user experience, and they cared more that
we had found this shortcut to not having to purchase ad space.
And what you say is right on, Brett. Like, the problem
is that now everybody who remembers how good coverage
was, how good exposure was five or ten years ago
is now trying to pursue the same content strategies and
(08:59):
effectively getting forced to run ads or at least to experiment with
boosting a post. One, there's less space. And
two, as you say, the algorithms have kind of been designed
now to trick us into doing this. I would say that to some extent,
this organic interaction still holds weight. And
I can say this even now as someone in the second life as an
(09:22):
author promoting his book. It is meaningful to reach out to
journalists or to other authors or to people who I think would like to read
my book and say, hey. I know a little bit about you. I've read your
research paper. I've read read your past work. Here's a free copy of my
book. That type of outreach, even if it's cold, still
works to some extent, but it's so so time consuming.
(09:43):
You know, in the time that I could do a thousand with bot programs
I've created, I could maybe only do 20 or
30 personalized bits of outreach. And that's where, like,
there's this this awkward it's it's like, what has software really
allowed us to do if we're basically just having to take out the phone book,
you know, look up the directory and, you know, figure out someone's life story before
(10:06):
we contact them anyway. Right? It's kind of forced us into a more traditional
way of, building relationships. And so how do you how do you capitalize that?
Because, I mean, we talked about how the algorithm has changed. Should your
content strategy drastically change? Because, like, the
new thing was reels, now it's not as
popular or it's too popular where even if you
(10:28):
post a reel, it doesn't really mean you're going to really going to gain, gain
traction. Should you use some, some pictures again? Should you use
some regular videos stories? Like, is it just a mix
of everything, or do you have to, quote, unquote, go viral,
which, I mean, always changes every day. And I know every business is like, we
wanna go viral. And I'm like, okay. Yeah. And I've even seen this
(10:49):
with past guests on your podcast. This comes up a lot
where people are talking about how to beat the algorithm.
Fundamentally, there is a way because understanding
exactly how it works, provides some value. But
also, it's nearly impossible and it's extremely
costly to even hypothetically understand what the algorithm is
(11:12):
doing. As you say, Brett, it changes day over day, and it also
changes in ways that aren't easily explainable in English.
So there's no way we can really go and know for sure, that a
campaign that was successful seven years ago will be successful in
2025 into 2026. My recommendation
is that there's definitely some benefit in trying to be platform
(11:34):
agnostic. So creating content, distributing it on
several different platforms, and kind of seeing what works. And then I
think the ultimate, agnostic approach would be to centering
things around a mailing list. If you have more written content, if you
have richer content that is not based around pictures and
videos, we definitely have seen this flight to
(11:56):
Substack and Beehive and other similar platforms now
where, people are saying it's been the easiest,
new medium to monetize, especially in the last couple years.
So basically go back to old school email marketing because that thing
has been told to ad nauseam that it's going to die
and it still never dies. I mean, I think I've seen
(12:19):
that for the past ten years. It's finally dead. Social media is taking over.
TikTok is taking over. And then it's like, well, it's not really dead. It's
actually thriving. It's a very difficult conversation because
each person who has built a business and perhaps an agency in
social media, they don't want to admit how little they understand.
My perspective is unique because I broke the rules, which means getting very,
(12:42):
very close to truth. And then later, I was employed by a
software startup where I actually built persuasive technology systems. So
I never worked at Meta, but I mean, we came pretty damn close to getting
an understanding of how this stuff really works. The truth is that nobody knows how
it works and that chasing viral, exposure
is still valid and prospecting for leads
(13:04):
by way of fans, on some of these distribution
platforms, social media platforms, is still valid. But I wonder
how many people it's really useful for and, really
with the saturation we see today, how many people are getting meaningful,
you know, meaningful stats out of it considering how much time it takes up. I
only say, like, I criticize going viral only because it feels
(13:26):
like everybody's chasing the past trend of going viral. And I feel like
a lot of times people need to understand that going viral means you need to
be unique and a little bit different from what has already happened.
Yeah. That's true. And I've explored it in a few places in
my book where I really pay, you know, I pay a tribute to the
early Internet and what it really meant. And one of the most
(13:49):
interesting, discoveries or hypotheses that I proposed
was that on early YouTube, it was very rare that
content went viral from the jump. If I
can think about the 10/20, '30 most significant
videos from founding through twenty eleven, twenty
ten, we'd find that almost all of them
(14:11):
were uncovered much later. And they were men maybe
promoted by a an aggregation channel like Ray William Johnson back
in the day, or they were even hand selected by
YouTube's editors. People forget that originally, some of the top
videos were manually selected as
YouTube was actually in this era during the dying days of what we
(14:33):
remember as directory sites, where you would have a webmaster telling you
what the top content was. So what you're saying is is very much
true in that these are older patterns. And now
that we're trying to, have the same
success when the algorithms have extremely aggressive
time decay functions, you must go viral
(14:57):
immediately because otherwise you'll get completely buried.
And I think we see a lot less discovered viral
content and, you know, we see this, this almost standardization,
this formulaic approach of what people think they have to do.
In a lot of cases, that involves compromising, either their values
or really what their content should be about. So could we say that's the TikTok
(15:20):
effect of the time decay of virality? Because I
feel like TikTok kind of, like, catapulted that where YouTube wasn't
as bad at it at it, but now they are since they have shorts.
LinkedIn has shorts now. I mean, all basically, almost all of them have
a short function now. I would say that shorts are
what completed this this this transitional
(15:43):
period. As far as time decay functions, they've
always existed to some extent, and there is some,
like, academic exploration of how
Reddit's top posts work. But on Reddit, you get a
little bit more of a reprieve. If you actually look at how their
time decay function of each upvote relative to
(16:05):
downvotes works, you get many days potentially.
And that's why in some subreddits, you might look at you look at something and
you're so used to seeing the newest thing on TikTok or the
newest thing on Instagram. I'm often surprised to find,
I'm getting posts at the top of my feed that were posted three to five
days ago. And so there are different aspects of time decay. I
(16:27):
think Reddit does a decent job of holding this middle ground. But as you said,
in short form, a lot of the times, it's prioritizing
the absolute newest content. And so working with these influential
accounts, I mean, what have you noticed that drives the actual consistent
engagement? Because that's what we all want. We don't want the consistent engagement,
not the one hit wonder, and you're like, well, what happened? How did that work?
(16:51):
If somebody's on a platform for entertainment purposes, and
I think broadly a lot of people are. I I kind of explore this
from, you know, this this idea of Pletchik's wheel of emotions,
and we're trying to experience this whole entire spectrum of
different emotions, but every emotion pretty much has, you
know, an opposite emotion that is quite negative. So it encourages
(17:14):
creators to maybe post things that make people feel on both
sides of it. I mean, just broadly saying they want some drama. They want
some controversy. And when you have people on a platform who are
looking more for this short form entertainment, that tends to
perform much better compared to, like, a twenty minute video
on some niche thing that happened during World War two.
(17:36):
Right? So, like, we have these these broad broad,
splits of, of different users, these partitioning, these
partitioning of user groups. What I saw that was most successful
during my Instagram phase was overwhelmingly
those cheap fast food content
(17:57):
type pages. So we're talking about, models. So we're
talking about things that are, perhaps, sexualized.
We're talking about people who are effectively doing stunts
or just, like, very, very in your face, attention grabbing
type entertainment content and, things that are just, generally speaking, very
aesthetically pleasing. So, like, hey. We're gonna post nice pictures
(18:19):
of of the beach. Not to say there's anything wrong with
this, but I think anyone putting more nuance, behind
their content on these platforms is probably suffering and finding they have to
go to YouTube and they have to build a very niche audience compared to,
what they're competing against. Does this also rely on,
like, the different genders, male or female? Does it mean
(18:42):
that maybe females like more drama than males? Or
is it just kinda apolitical and it doesn't matter? People just want the drama. Do
people just want, I guess, spilling the tea? In
my very, very blue collar research, I
found big differences between how this plays out on
each platform. Specifically on Facebook,
(19:04):
I think we do see this much more,
demographic based, filtering where, if you
find yourself in, you know, what's been called a filter bubble, those most
commonly exist on Facebook for whatever reason, where
we find, oh, there's a group, there's a piece of content, and now you're in
another group. And the idea behind filter bubbles or why it's become a
(19:26):
dirty word is that it eventually becomes an echo chamber
that, you know, tends to be more and more extreme. And that
facts go to more like a facts laced with opinion and the
facts aren't really provable and it's just conspiracy theories, which as we
know, there's some basis in political and, like, propaganda type
things. On other platforms, I haven't found as
(19:48):
strong of a relationship between what one gender is
doing, versus another. I'm
positive that the base feed that one would
get on Instagram versus on TikTok, like, when you create a
new account, of course it's taking into account your gender because that's
one of the only, bits of demographic information it has.
(20:10):
But how that actually plays out, I'm not sure. Like we
doing research there would require so
such resource it's so like the
resources required are just crazy. And that's why we can only get these little tiny
anecdotes of people saying, hey, I created 10 accounts and here's what happened 10 times.
Rather than saying, hey, we ran 10,000 simulations and it cost us a million
(20:33):
dollars. Could that be the next frontier of AI figuring out, like,
if this actually happens? Because I feel like AI could do this a lot quicker
than us doing, like, 50 to a hundred different counts and trying to
see which one happens. In understanding social media,
if we really want true algorithmic, you know, transparency,
and that's something I address in a couple different chapters of my book, starting
(20:56):
in chapter four, which is called algorithms and truth. We start
saying, what's the platform's responsibility
to fact check? Do they have to fact check every piece
of the millions of pieces of original content they get per day?
Do they have to say this image was manipulated? This text
doesn't represent facts? What is the responsibility of the
(21:18):
platform? Very controversial. But what we don't realize is
that if we live in a world where the platform does have the
responsibility, for the platform to actually
be providing this information in a way that is explainable
in plain English, so not only this is what the content
is, but then also this is why Brett was
(21:41):
shown this content. I estimate we're probably talking
two orders of magnitude of compute data storage
throughput costs to be able to provide that at all levels in
a way that was auditable, for example, by a central authority.
So, yes, as resources maybe become
more collected and you get these, let's say we have
(22:04):
billionaires who really, really care about, uncovering this stuff.
Yes. You could throw a ton of resources behind it and better understand
these things, but, even what we're talking about now is
above, way beyond the understanding of of many people. It would be hard
to, make an impact there. And I think we did see
Meta try to do some fact
(22:26):
checking, but apparently that didn't even Zuckerberg
admitted that it really wasn't fact checking. It was opinion based,
like, feeling more. So I'm
on the, I'm on the end of a political platforms just
because people need to figure it out for themselves. I know they use
AI to actually do a lot of different types of decisions, but my
(22:48):
appealing is do your fact checking. You have AI now. If
you really need to use that to fact check, then do it that way. But
I think social platforms need to stay out of that. I agree with you on
this. The point I make in the book is that we already had
two generations grow up with the Internet, and nobody was
looking out for us. It was up to us to do fact checking in
(23:10):
ways that in 2006 or 02/2007, when you
received, like, chain email about Lil Wayne being dead or some
celebrity being dead, you had to actually dig pretty deep to find
out if it was true or not. And I think that was
a separate like, this major separation of generations of where
we had to do the work and form our own opinions, where now
(23:33):
later generations have shown up, including older generations in The United States
who are newly, like, tech literate, are now coming with totally different
expectations. So I'm with you there. There's no way you're gonna keep everyone happy,
and there's no way you can establish, you know, universal truth
for every piece of content. And then moving on to, like, shadow banning
because you also mentioned that. And plus, for those that don't know,
(23:55):
shadow banning is kind of like you aren't really banned, but you're banned
because you don't know that you're actually banned. So it's kind of in the shadows
and you just don't know. So how can markers avoid
getting that reach limit from being shadow banned? Because I feel
like sometimes markers are like, why is this getting no reach now?
Shadow bans are very controversial, because
(24:17):
as a public figure, you can also,
harness this idea of a shadowban to explain why you're not
more popular. So if you look on Urban Dictionary, which is a
source that was extremely useful for my book, you
can see how the definition of shadowbanning evolved
from 02/2007 to 2010
(24:40):
to 02/2012, and it evolved from web forums. So,
like, these pre Reddit type forums, to then people talking
about Twitter, to then people just talking about this general, like,
tech kleptocracy, right, where you just have way, way,
way, too much, influence from the tech from the
platforms that nobody really understands, how to
(25:02):
stay on their good side or even how to determine if they are themselves shadow
banned. So that's the unique thing that you say. It's like a ban, but it's
not really a ban. Because if it was a ban, the phones would be
ringing off the hook, so to speak. The support tickets that would be getting
filed would be crazy. But for a shadow ban, you actually
have to think a lot more critically and maybe do your own tests. Ask
(25:25):
your friend, hey can you see my content? Or you know start thinking
statistically why can only one one hundredth of the audience
see my content now? It's an effective tool but
it's also very, very controversial for that reason. So, yeah, shadow
bans aren't going anywhere. Meta has come out with a blog
post talking about shadow bans, in which I cover in my
(25:46):
book, they don't give many satisfactory answers. So, yeah, it
continues to be this fringe topic that a lot of people proclaim,
knowledge of when, as we said, with with algorithms and other
things, you cannot be a true expert as an
outsider. And to be fair, one side if you're in politics,
one side says it's more often on their side than the other side. So there
(26:09):
is that at play too. And since from what I've
seen just looking at it, it seems like one side was heavily targeted
more because they were willing to, I guess, talk about the
controversial topics that maybe these platforms didn't want them to talk
about. And so that's why it became more prevalent on one side than
the other. This is true. And I think now, hopefully, we're
(26:31):
getting to the stage where we can have normal discourse. Again, we can kind
of discuss these things and say, That that wasn't right. Like,
that should never have happened. I wade into this,
very, like, gingerly in my book where I'm like, hey. We'll
keep it apolitical, but some of these people have really good points
that it's unpopular, but it still should be covered under
(26:54):
free speech. And whenever a platform can
create these, I would say, systems for algorithmic
interference, that's very, very dangerous. Because not just
for political you know, the highest level political stuff, but what about
even if there's like a local corruption case and you can't find
information on it, you can't discuss it because somebody paid
(27:15):
50,000. You know, it's it's really, really dangerous and it's a
really slippery slope. The one example I give in my book
is that many many years ago when Donald Trump was elected,
I did like a Facebook live video because I lived in Chicago and there
was actually like a major protest. And I did a Facebook live, where
I was basically trying to be a comedian. And what I
(27:37):
found so funny was that when I searched for this video, which is now like
whatever, like seven or eight years later, I couldn't find it on
Facebook. So and I titled it Trump
Riot. And so I searched for Trump Riot, it didn't come up.
When I removed the term Trump and just typed riot, I could
find it. And I could type Trump or any iteration of
(28:01):
of Trump riot whatever. I can only find it when I remove the term Trump.
So it kind of suggests that this was way beyond a conspiracy theory. I'm
just a random guy who was then writing a book because I thought I was
funny when I was 22 years old, and then much later realized
that there's still algorithmic interference on me
searching my own content that contains the word Trump.
(28:23):
And so, I mean, based on automation, what tasks should
marketers automate versus handle manually for best results? Because I
think that's what we're all thinking about is, like, there's so many things to do,
especially for social media. How do we automate effectively?
This is really tough, and I I realized that you just had a guest
who said, hey. You have to use AI or you're going to fall behind as
(28:46):
a marketer. I do not subscribe to that,
philosophy at all. For me, as a writer and
someone who spent years focusing on the craft, there's
currently no substitute for being a good
writer or having a critical thinking ability that,
enables you to kind of handle, you know, handle things as
(29:07):
they as they come up. Right? To have a little bit more, dynamism in
your approach to problem solving and to stimuli. Whether
that's, yeah, you you know, cold emails or whether it's outreach or whether
it's just things that happen to you on a daily basis. AI is a
tool and automation is a tool. But for me, I
can look at my book marketing efforts now and say, anytime I've tried
(29:30):
to use any type of automation, it's gone
pretty poorly. The only part that I
think, we have some success with or I've had some success with
is just generally some things for lead generation.
I would struggle to say that AI, generative AI, has
improved lead generation. People claim that it's improved
(29:53):
outreach. I think any person who claims that it improves
outreach is just a really shitty writer because that's not true. And
every time I get AI outreach, I throw it away. It looks
terrible and it's never actually personalized. It's just using big words
and hyphens. Like, for me, like, lead generation is
pretty is pretty useful, and I think some automation there. Okay. If you could scrape
(30:15):
the if you could scrape in and get a little bit more information from the
person, if you could actually get their LinkedIn, If I could have maybe some
summaries of research, if somebody's an academic, that's nice.
But I'm still very much in this pure state where, we're
going over and directing way too much on,
AI. And the automation plays that I use at the core of my
(30:36):
business, specifically for follower growth, are largely
forbidden now. It's almost impossible to do them at
scale. If somebody wants to try to do them, homegrown on their
laptop, there are services specifically on LinkedIn
for whatever reason, where you can do it.
But I want people to know that people like me are out there
(30:58):
looking for you. And I know these comments and you've probably seen them already
where you can tell somebody is running a bot that does a little bit of
context and analysis, and then it leaves an AI generated comment. And it's
like, what's the point? I mean, I use it for, like, doing
show notes and finding the best stuff for my stuff because it's a good tool,
and I don't have to spend hours trying to figure all that stuff out. But
(31:20):
I do agree with you. I mean, one of my other shows, I actually read
the article, but I have AI give me the bullet points. But I still read
it, so I understand what I'm talking about and not having AI
just do everything for me. So I'm more in a balanced state,
but I do agree with you that you need to understand how to write and
you need to understand how to critically think. Because if you give everything to AI,
(31:42):
then you aren't gonna be critically thinking ever. Right. People are listening
to this podcast, they're wondering where can they find you online to learn more about
what you do and your book. Yeah, Brett. The main place, that people
could find more about me is probably on Amazon where I'm
selling framed both in the paperback and Kindle
versions. We're also currently working on the audiobook, which I'm
(32:04):
hoping to release later this summer. Those who do read the
book and want to read even more, will be happy to know that
I do have a Beehive mailing list. So it's tim ohearn dot
beehive dot com. And for much more long form stuff,
going back almost a decade now, I have a variety blog at
tjohearn.com. My main social media platform,
(32:27):
is actually LinkedIn. And there I'm Tim Ohearn. And any final
thoughts for listeners? Brett, it's been a pleasure to be on this podcast. I
know we've been, anticipating it for a couple months now. So I just wanna say
thank you for having me on. Yes. And thank you, Tim, for joining Digital Coffee
Marketing Brewing, sharing your knowledge on social media AI and
bots. Thank you. And thank you for listening. As always, please
(32:48):
subscribe to this podcast and all your favorite podcasting apps with a five star review.
It really does help with the ranking. So let me know how I'm doing it.
And join me next week as I talk about what's going on in
the PR and marketing industry. Alright, guys. Stay safe. Get to understanding how you can
use automation to the best ability, and don't get shadow banned. And see you
next week. Later.
We see this crossover between cybersecurity, black
(00:03):
hat and white hat, and then marketing and search engine
optimization, black hat and white hat. The idea
behind black hat marketing, which then lends itself itself
to black hat social media growth, really
approaches it from the angle of what you're doing might not be explicitly
illegal, but you likely are affecting other
(00:26):
users on the platform.
That's good. And welcome to a new episode of
digital coffee marketing brew with I'm your host, Brett
(00:48):
Deister. If you could please subscribe to this podcast and all your favorite podcasting apps,
you have a five star review, really does help with the rankings and let me
know how I am doing. But
this week, my guest is Tim and he is a software engineer who has
created some of the most pesky and effective bots to ever be
unleashed on social media. Between 2017
(01:09):
and 2022, his agency gained millions of
followers for its clients with generating hundreds of thousands of
dollars in revenue. In February 2025,
he debuted framed a villain's perspective on social media with a
number one release in social aspects on the internet
on Amazon. Framed is Tim's
(01:31):
confrontation confrontation with the Internet age delivered
by a video game cheater who outgrew gaming, but never stopped
breaking the rules. So welcome to the show, Tim.
Hey, Brett. Thanks for having me. And my first question is all my guests is,
are you a coffee or tea drinker? I'm more of a tea drinker. Tea
drinker. Do you have, any, like, specifics you like? Green, black, or you
(01:53):
just, like, whatever? I don't really care. Generally
speaking, I've really gotten into, sparkling teas recently.
So especially on the Korean dining scene here in New York
City, I found that there's some local producers or
bottlers, and I've enjoyed those a lot as an alternative
to, like, alcohol forward, menus. So, like, is, like,
(02:16):
green sparkling tea, like, sparkling water with tea, is that how it is?
I would say it's more like a de alcoholized,
champagne. It really had like, it still has many of the
notes that you would find in a glass of champagne except, no
bite. But then, of course, there is, like, caffeine content as well.
(02:36):
Got you. And so I gave a brief summary of your expertise. Could you give
our listeners a little bit more about what you do? I'm a software engineer.
I spent most of my twenties, writing code at a variety of
different businesses and different industries. A huge
portion of it was spent in the Instagram and social media
underworld, where beginning in 2017, I was pulled into this
(02:57):
space where misbehavior was rife, and people were
making large sums of money by violating the terms of service
of social media platforms. I was not an
inventor, of anything in this space, but I was certainly
a power user and someone who developed, some of the better botting
platforms, that I used and built a business on, throughout the late twenty
(03:19):
tens. Got you. And so what is Black
Hat Marketing? I know what Black Hat is because it is like the nefarious
hackers, but what is specifically pertaining to marketing?
We see this crossover between cybersecurity, black
hat and white hat, and then marketing and search engine
optimization, black hat and white hat. The idea
(03:42):
behind black hat marketing, which then lends itself to
black hat social media growth, really
approaches it from the angle of what you're doing might not be explicitly
illegal, but you likely are affecting,
other users on the platform. So you're likely violating social contracts,
and at worst, you're probably also violating terms
(04:05):
of use, which are not laws, but they are
provided by, private businesses as a condition of using a
platform. So black hat marketing really is doing these things that
are likely breaking the rules while not being the,
computer hacker type destructive behavior that maybe we'd commonly associate.
So just breaking their TOS, but not actually, like, breaching any
(04:28):
of the user data. Yeah. That's fair. And you
managed to generate over 500,000 through social media
growth strategies. Can you walk us through your most effective tactics to
actually move the needle? This number, is one that I
have proof of, but it's something that while I was doing it, we
didn't know what the number was because we were so often looking
(04:50):
at the Stripe dashboard of monthly recurring revenue. It's
only in retrospect when I was writing the book that I actually checked
Stripe one last time and saw we were we were over 500 k.
For us, the main learning or the main, I would say,
takeaway was that when you're running a social
media automation business or something vaguely related
(05:14):
to scraping, the profit margins are
exceptionally high. At Shark Social, which is the company
that I, you know, code named in my book, we're probably talking
about an 80% or higher profit margin. This is not,
totally new, for anyone in the software as a service space,
but what was useful for us was that we were running a software as a
(05:37):
service business, but our customers thought that
humans might have been the ones growing their accounts. So there is
definitely a little bit of deception there, which I have admitted to. And
when it comes to profit, you really are locking people in
to a month over month subscription, during which
our average customer value was
(05:58):
as high as a hundred $80. I think during the time period, like, there's
obviously fat tail, but during the time period, it was definitely over a hundred
dollars, which is pretty good. And so, I mean, even in your book, you
mentioned bot automa automa automaization.
So and with that, you're saying that you use bots to
get monthly things. So what how was it successful to use those bots? What were
(06:21):
the key metrics that you found to be targeted to be successful in
gaining all that revenue? Even as far back as 2016 or
2017, Instagram had some threshold
of how many actions any user could take per day. It
doesn't matter if it's you sitting there tapping. It doesn't matter if it's me,
with my bot, you know, just continually doing something, just in
(06:44):
cyberspace. There were these bounds of how many actions you could
take per day before you might face a block or a ban or other
types of restrictive action. What made
the programs I created and manipulated so
successful was this abuse of the human
tendency to reciprocate. And on
(07:06):
Instagram, it was very, very easy to find or to
target certain content or certain creators in a niche and
say, hey, I can send maybe 300,
two hundred 50 actions per day to this account and
related accounts, and I can expect that I'll receive
actions back at a rate of roughly 10%.
(07:29):
So even on a per per day basis, that could be as many as 20
or 30 actions back. Over the course of a month,
many smaller accounts and even what you would say micro influencers
would be more than happy to get hundreds and hundreds of
real organic ish follows back per month. So that was
really the core, the core value in this system, which is
(07:51):
broadly, termed follow unfollow. Yeah. And
so, I mean, how how do you what do you have the insider
tips online on, like, performing well organically? Because everybody knows
now with Metta, they don't like organic
stuff anymore. They really want you to pay to play now. And it's kind of
like, if you don't pay to play, you don't get the eyeballs or the
(08:13):
actions as you say. So are there any tips to actually still
do that? Because I know it's getting harder and harder because the
algorithm just ruins everything, my personal belief, because it's just
it's just for them to make money. One of the
concerns that was brought up, when we first started facing
actions, you know, anti botting measures, was that Meta
(08:36):
cared less about the user experience, and they cared more that
we had found this shortcut to not having to purchase ad space.
And what you say is right on, Brett. Like, the problem
is that now everybody who remembers how good coverage
was, how good exposure was five or ten years ago
is now trying to pursue the same content strategies and
(08:59):
effectively getting forced to run ads or at least to experiment with
boosting a post. One, there's less space. And
two, as you say, the algorithms have kind of been designed
now to trick us into doing this. I would say that to some extent,
this organic interaction still holds weight. And
I can say this even now as someone in the second life as an
(09:22):
author promoting his book. It is meaningful to reach out to
journalists or to other authors or to people who I think would like to read
my book and say, hey. I know a little bit about you. I've read your
research paper. I've read read your past work. Here's a free copy of my
book. That type of outreach, even if it's cold, still
works to some extent, but it's so so time consuming.
(09:43):
You know, in the time that I could do a thousand with bot programs
I've created, I could maybe only do 20 or
30 personalized bits of outreach. And that's where, like,
there's this this awkward it's it's like, what has software really
allowed us to do if we're basically just having to take out the phone book,
you know, look up the directory and, you know, figure out someone's life story before
(10:06):
we contact them anyway. Right? It's kind of forced us into a more traditional
way of, building relationships. And so how do you how do you capitalize that?
Because, I mean, we talked about how the algorithm has changed. Should your
content strategy drastically change? Because, like, the
new thing was reels, now it's not as
popular or it's too popular where even if you
(10:28):
post a reel, it doesn't really mean you're going to really going to gain, gain
traction. Should you use some, some pictures again? Should you use
some regular videos stories? Like, is it just a mix
of everything, or do you have to, quote, unquote, go viral,
which, I mean, always changes every day. And I know every business is like, we
wanna go viral. And I'm like, okay. Yeah. And I've even seen this
(10:49):
with past guests on your podcast. This comes up a lot
where people are talking about how to beat the algorithm.
Fundamentally, there is a way because understanding
exactly how it works, provides some value. But
also, it's nearly impossible and it's extremely
costly to even hypothetically understand what the algorithm is
(11:12):
doing. As you say, Brett, it changes day over day, and it also
changes in ways that aren't easily explainable in English.
So there's no way we can really go and know for sure, that a
campaign that was successful seven years ago will be successful in
2025 into 2026. My recommendation
is that there's definitely some benefit in trying to be platform
(11:34):
agnostic. So creating content, distributing it on
several different platforms, and kind of seeing what works. And then I
think the ultimate, agnostic approach would be to centering
things around a mailing list. If you have more written content, if you
have richer content that is not based around pictures and
videos, we definitely have seen this flight to
(11:56):
Substack and Beehive and other similar platforms now
where, people are saying it's been the easiest,
new medium to monetize, especially in the last couple years.
So basically go back to old school email marketing because that thing
has been told to ad nauseam that it's going to die
and it still never dies. I mean, I think I've seen
(12:19):
that for the past ten years. It's finally dead. Social media is taking over.
TikTok is taking over. And then it's like, well, it's not really dead. It's
actually thriving. It's a very difficult conversation because
each person who has built a business and perhaps an agency in
social media, they don't want to admit how little they understand.
My perspective is unique because I broke the rules, which means getting very,
(12:42):
very close to truth. And then later, I was employed by a
software startup where I actually built persuasive technology systems. So
I never worked at Meta, but I mean, we came pretty damn close to getting
an understanding of how this stuff really works. The truth is that nobody knows how
it works and that chasing viral, exposure
is still valid and prospecting for leads
(13:04):
by way of fans, on some of these distribution
platforms, social media platforms, is still valid. But I wonder
how many people it's really useful for and, really
with the saturation we see today, how many people are getting meaningful,
you know, meaningful stats out of it considering how much time it takes up. I
only say, like, I criticize going viral only because it feels
(13:26):
like everybody's chasing the past trend of going viral. And I feel like
a lot of times people need to understand that going viral means you need to
be unique and a little bit different from what has already happened.
Yeah. That's true. And I've explored it in a few places in
my book where I really pay, you know, I pay a tribute to the
early Internet and what it really meant. And one of the most
(13:49):
interesting, discoveries or hypotheses that I proposed
was that on early YouTube, it was very rare that
content went viral from the jump. If I
can think about the 10/20, '30 most significant
videos from founding through twenty eleven, twenty
ten, we'd find that almost all of them
(14:11):
were uncovered much later. And they were men maybe
promoted by a an aggregation channel like Ray William Johnson back
in the day, or they were even hand selected by
YouTube's editors. People forget that originally, some of the top
videos were manually selected as
YouTube was actually in this era during the dying days of what we
(14:33):
remember as directory sites, where you would have a webmaster telling you
what the top content was. So what you're saying is is very much
true in that these are older patterns. And now
that we're trying to, have the same
success when the algorithms have extremely aggressive
time decay functions, you must go viral
(14:57):
immediately because otherwise you'll get completely buried.
And I think we see a lot less discovered viral
content and, you know, we see this, this almost standardization,
this formulaic approach of what people think they have to do.
In a lot of cases, that involves compromising, either their values
or really what their content should be about. So could we say that's the TikTok
(15:20):
effect of the time decay of virality? Because I
feel like TikTok kind of, like, catapulted that where YouTube wasn't
as bad at it at it, but now they are since they have shorts.
LinkedIn has shorts now. I mean, all basically, almost all of them have
a short function now. I would say that shorts are
what completed this this this transitional
(15:43):
period. As far as time decay functions, they've
always existed to some extent, and there is some,
like, academic exploration of how
Reddit's top posts work. But on Reddit, you get a
little bit more of a reprieve. If you actually look at how their
time decay function of each upvote relative to
(16:05):
downvotes works, you get many days potentially.
And that's why in some subreddits, you might look at you look at something and
you're so used to seeing the newest thing on TikTok or the
newest thing on Instagram. I'm often surprised to find,
I'm getting posts at the top of my feed that were posted three to five
days ago. And so there are different aspects of time decay. I
(16:27):
think Reddit does a decent job of holding this middle ground. But as you said,
in short form, a lot of the times, it's prioritizing
the absolute newest content. And so working with these influential
accounts, I mean, what have you noticed that drives the actual consistent
engagement? Because that's what we all want. We don't want the consistent engagement,
not the one hit wonder, and you're like, well, what happened? How did that work?
(16:51):
If somebody's on a platform for entertainment purposes, and
I think broadly a lot of people are. I I kind of explore this
from, you know, this this idea of Pletchik's wheel of emotions,
and we're trying to experience this whole entire spectrum of
different emotions, but every emotion pretty much has, you
know, an opposite emotion that is quite negative. So it encourages
(17:14):
creators to maybe post things that make people feel on both
sides of it. I mean, just broadly saying they want some drama. They want
some controversy. And when you have people on a platform who are
looking more for this short form entertainment, that tends to
perform much better compared to, like, a twenty minute video
on some niche thing that happened during World War two.
(17:36):
Right? So, like, we have these these broad broad,
splits of, of different users, these partitioning, these
partitioning of user groups. What I saw that was most successful
during my Instagram phase was overwhelmingly
those cheap fast food content
(17:57):
type pages. So we're talking about, models. So we're
talking about things that are, perhaps, sexualized.
We're talking about people who are effectively doing stunts
or just, like, very, very in your face, attention grabbing
type entertainment content and, things that are just, generally speaking, very
aesthetically pleasing. So, like, hey. We're gonna post nice pictures
(18:19):
of of the beach. Not to say there's anything wrong with
this, but I think anyone putting more nuance, behind
their content on these platforms is probably suffering and finding they have to
go to YouTube and they have to build a very niche audience compared to,
what they're competing against. Does this also rely on,
like, the different genders, male or female? Does it mean
(18:42):
that maybe females like more drama than males? Or
is it just kinda apolitical and it doesn't matter? People just want the drama. Do
people just want, I guess, spilling the tea? In
my very, very blue collar research, I
found big differences between how this plays out on
each platform. Specifically on Facebook,
(19:04):
I think we do see this much more,
demographic based, filtering where, if you
find yourself in, you know, what's been called a filter bubble, those most
commonly exist on Facebook for whatever reason, where
we find, oh, there's a group, there's a piece of content, and now you're in
another group. And the idea behind filter bubbles or why it's become a
(19:26):
dirty word is that it eventually becomes an echo chamber
that, you know, tends to be more and more extreme. And that
facts go to more like a facts laced with opinion and the
facts aren't really provable and it's just conspiracy theories, which as we
know, there's some basis in political and, like, propaganda type
things. On other platforms, I haven't found as
(19:48):
strong of a relationship between what one gender is
doing, versus another. I'm
positive that the base feed that one would
get on Instagram versus on TikTok, like, when you create a
new account, of course it's taking into account your gender because that's
one of the only, bits of demographic information it has.
(20:10):
But how that actually plays out, I'm not sure. Like we
doing research there would require so
such resource it's so like the
resources required are just crazy. And that's why we can only get these little tiny
anecdotes of people saying, hey, I created 10 accounts and here's what happened 10 times.
Rather than saying, hey, we ran 10,000 simulations and it cost us a million
(20:33):
dollars. Could that be the next frontier of AI figuring out, like,
if this actually happens? Because I feel like AI could do this a lot quicker
than us doing, like, 50 to a hundred different counts and trying to
see which one happens. In understanding social media,
if we really want true algorithmic, you know, transparency,
and that's something I address in a couple different chapters of my book, starting
(20:56):
in chapter four, which is called algorithms and truth. We start
saying, what's the platform's responsibility
to fact check? Do they have to fact check every piece
of the millions of pieces of original content they get per day?
Do they have to say this image was manipulated? This text
doesn't represent facts? What is the responsibility of the
(21:18):
platform? Very controversial. But what we don't realize is
that if we live in a world where the platform does have the
responsibility, for the platform to actually
be providing this information in a way that is explainable
in plain English, so not only this is what the content
is, but then also this is why Brett was
(21:41):
shown this content. I estimate we're probably talking
two orders of magnitude of compute data storage
throughput costs to be able to provide that at all levels in
a way that was auditable, for example, by a central authority.
So, yes, as resources maybe become
more collected and you get these, let's say we have
(22:04):
billionaires who really, really care about, uncovering this stuff.
Yes. You could throw a ton of resources behind it and better understand
these things, but, even what we're talking about now is
above, way beyond the understanding of of many people. It would be hard
to, make an impact there. And I think we did see
Meta try to do some fact
(22:26):
checking, but apparently that didn't even Zuckerberg
admitted that it really wasn't fact checking. It was opinion based,
like, feeling more. So I'm
on the, I'm on the end of a political platforms just
because people need to figure it out for themselves. I know they use
AI to actually do a lot of different types of decisions, but my
(22:48):
appealing is do your fact checking. You have AI now. If
you really need to use that to fact check, then do it that way. But
I think social platforms need to stay out of that. I agree with you on
this. The point I make in the book is that we already had
two generations grow up with the Internet, and nobody was
looking out for us. It was up to us to do fact checking in
(23:10):
ways that in 2006 or 02/2007, when you
received, like, chain email about Lil Wayne being dead or some
celebrity being dead, you had to actually dig pretty deep to find
out if it was true or not. And I think that was
a separate like, this major separation of generations of where
we had to do the work and form our own opinions, where now
(23:33):
later generations have shown up, including older generations in The United States
who are newly, like, tech literate, are now coming with totally different
expectations. So I'm with you there. There's no way you're gonna keep everyone happy,
and there's no way you can establish, you know, universal truth
for every piece of content. And then moving on to, like, shadow banning
because you also mentioned that. And plus, for those that don't know,
(23:55):
shadow banning is kind of like you aren't really banned, but you're banned
because you don't know that you're actually banned. So it's kind of in the shadows
and you just don't know. So how can markers avoid
getting that reach limit from being shadow banned? Because I feel
like sometimes markers are like, why is this getting no reach now?
Shadow bans are very controversial, because
(24:17):
as a public figure, you can also,
harness this idea of a shadowban to explain why you're not
more popular. So if you look on Urban Dictionary, which is a
source that was extremely useful for my book, you
can see how the definition of shadowbanning evolved
from 02/2007 to 2010
(24:40):
to 02/2012, and it evolved from web forums. So,
like, these pre Reddit type forums, to then people talking
about Twitter, to then people just talking about this general, like,
tech kleptocracy, right, where you just have way, way,
way, too much, influence from the tech from the
platforms that nobody really understands, how to
(25:02):
stay on their good side or even how to determine if they are themselves shadow
banned. So that's the unique thing that you say. It's like a ban, but it's
not really a ban. Because if it was a ban, the phones would be
ringing off the hook, so to speak. The support tickets that would be getting
filed would be crazy. But for a shadow ban, you actually
have to think a lot more critically and maybe do your own tests. Ask
(25:25):
your friend, hey can you see my content? Or you know start thinking
statistically why can only one one hundredth of the audience
see my content now? It's an effective tool but
it's also very, very controversial for that reason. So, yeah, shadow
bans aren't going anywhere. Meta has come out with a blog
post talking about shadow bans, in which I cover in my
(25:46):
book, they don't give many satisfactory answers. So, yeah, it
continues to be this fringe topic that a lot of people proclaim,
knowledge of when, as we said, with with algorithms and other
things, you cannot be a true expert as an
outsider. And to be fair, one side if you're in politics,
one side says it's more often on their side than the other side. So there
(26:09):
is that at play too. And since from what I've
seen just looking at it, it seems like one side was heavily targeted
more because they were willing to, I guess, talk about the
controversial topics that maybe these platforms didn't want them to talk
about. And so that's why it became more prevalent on one side than
the other. This is true. And I think now, hopefully, we're
(26:31):
getting to the stage where we can have normal discourse. Again, we can kind
of discuss these things and say, That that wasn't right. Like,
that should never have happened. I wade into this,
very, like, gingerly in my book where I'm like, hey. We'll
keep it apolitical, but some of these people have really good points
that it's unpopular, but it still should be covered under
(26:54):
free speech. And whenever a platform can
create these, I would say, systems for algorithmic
interference, that's very, very dangerous. Because not just
for political you know, the highest level political stuff, but what about
even if there's like a local corruption case and you can't find
information on it, you can't discuss it because somebody paid
(27:15):
50,000. You know, it's it's really, really dangerous and it's a
really slippery slope. The one example I give in my book
is that many many years ago when Donald Trump was elected,
I did like a Facebook live video because I lived in Chicago and there
was actually like a major protest. And I did a Facebook live, where
I was basically trying to be a comedian. And what I
(27:37):
found so funny was that when I searched for this video, which is now like
whatever, like seven or eight years later, I couldn't find it on
Facebook. So and I titled it Trump
Riot. And so I searched for Trump Riot, it didn't come up.
When I removed the term Trump and just typed riot, I could
find it. And I could type Trump or any iteration of
(28:01):
of Trump riot whatever. I can only find it when I remove the term Trump.
So it kind of suggests that this was way beyond a conspiracy theory. I'm
just a random guy who was then writing a book because I thought I was
funny when I was 22 years old, and then much later realized
that there's still algorithmic interference on me
searching my own content that contains the word Trump.
(28:23):
And so, I mean, based on automation, what tasks should
marketers automate versus handle manually for best results? Because I
think that's what we're all thinking about is, like, there's so many things to do,
especially for social media. How do we automate effectively?
This is really tough, and I I realized that you just had a guest
who said, hey. You have to use AI or you're going to fall behind as
(28:46):
a marketer. I do not subscribe to that,
philosophy at all. For me, as a writer and
someone who spent years focusing on the craft, there's
currently no substitute for being a good
writer or having a critical thinking ability that,
enables you to kind of handle, you know, handle things as
(29:07):
they as they come up. Right? To have a little bit more, dynamism in
your approach to problem solving and to stimuli. Whether
that's, yeah, you you know, cold emails or whether it's outreach or whether
it's just things that happen to you on a daily basis. AI is a
tool and automation is a tool. But for me, I
can look at my book marketing efforts now and say, anytime I've tried
(29:30):
to use any type of automation, it's gone
pretty poorly. The only part that I
think, we have some success with or I've had some success with
is just generally some things for lead generation.
I would struggle to say that AI, generative AI, has
improved lead generation. People claim that it's improved
(29:53):
outreach. I think any person who claims that it improves
outreach is just a really shitty writer because that's not true. And
every time I get AI outreach, I throw it away. It looks
terrible and it's never actually personalized. It's just using big words
and hyphens. Like, for me, like, lead generation is
pretty is pretty useful, and I think some automation there. Okay. If you could scrape
(30:15):
the if you could scrape in and get a little bit more information from the
person, if you could actually get their LinkedIn, If I could have maybe some
summaries of research, if somebody's an academic, that's nice.
But I'm still very much in this pure state where, we're
going over and directing way too much on,
AI. And the automation plays that I use at the core of my
(30:36):
business, specifically for follower growth, are largely
forbidden now. It's almost impossible to do them at
scale. If somebody wants to try to do them, homegrown on their
laptop, there are services specifically on LinkedIn
for whatever reason, where you can do it.
But I want people to know that people like me are out there
(30:58):
looking for you. And I know these comments and you've probably seen them already
where you can tell somebody is running a bot that does a little bit of
context and analysis, and then it leaves an AI generated comment. And it's
like, what's the point? I mean, I use it for, like, doing
show notes and finding the best stuff for my stuff because it's a good tool,
and I don't have to spend hours trying to figure all that stuff out. But
(31:20):
I do agree with you. I mean, one of my other shows, I actually read
the article, but I have AI give me the bullet points. But I still read
it, so I understand what I'm talking about and not having AI
just do everything for me. So I'm more in a balanced state,
but I do agree with you that you need to understand how to write and
you need to understand how to critically think. Because if you give everything to AI,
(31:42):
then you aren't gonna be critically thinking ever. Right. People are listening
to this podcast, they're wondering where can they find you online to learn more about
what you do and your book. Yeah, Brett. The main place, that people
could find more about me is probably on Amazon where I'm
selling framed both in the paperback and Kindle
versions. We're also currently working on the audiobook, which I'm
(32:04):
hoping to release later this summer. Those who do read the
book and want to read even more, will be happy to know that
I do have a Beehive mailing list. So it's tim ohearn dot
beehive dot com. And for much more long form stuff,
going back almost a decade now, I have a variety blog at
tjohearn.com. My main social media platform,
(32:27):
is actually LinkedIn. And there I'm Tim Ohearn. And any final
thoughts for listeners? Brett, it's been a pleasure to be on this podcast. I
know we've been, anticipating it for a couple months now. So I just wanna say
thank you for having me on. Yes. And thank you, Tim, for joining Digital Coffee
Marketing Brewing, sharing your knowledge on social media AI and
bots. Thank you. And thank you for listening. As always, please
(32:48):
subscribe to this podcast and all your favorite podcasting apps with a five star review.
It really does help with the ranking. So let me know how I'm doing it.
And join me next week as I talk about what's going on in
the PR and marketing industry. Alright, guys. Stay safe. Get to understanding how you can
use automation to the best ability, and don't get shadow banned. And see you
next week. Later.
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