Artificial Intelligence (AI) is changing the way we approach marketing, and the direct mail industry is no exception. With the ability to analyze data, segment audiences, and personalize content at scale, AI is revolutionizing the way businesses communicate with their customers through direct mail.
This webinar explores the various ways AI is transforming the direct mail industry, including:
Predictive Analytics: By using AI-powered predictive models, businesses can identify which customers are likely to respond to direct mail campaigns. This allows for more targeted and effective marketing efforts, resulting in higher conversion rates and ROI.
Personalization: With AI, businesses can create highly personalized direct mail campaigns tailored to individual customer preferences and behaviors. This leads to a more engaging and relevant experience for customers, increasing the chances of a positive response.
Automation: AI-powered automation streamlines the direct mail process, reducing costs and saving time. From list segmentation to content creation and distribution, AI can handle many of the repetitive and time-consuming tasks involved in direct mail campaigns.
Learn how to leverage these new technologies to improve your marketing efforts. Our expert panel will share their insights and experiences, and provide practical tips for implementing AI in your business. Featuring:
Brad Kugler, CEO/Co-Founder of DirectMail2.0
Thomas Cross, Managing Editor of ChannelPartner.TV
Ken Vermeille, CEO of Vermillion Sky
Shivam Ramphal, Co-Founder of Maya AI
Don’t miss out on this opportunity to stay ahead of the curve and revolutionize your marketing strategy!
Transcript:
0:00
I want to start with introducing myself I’m Brad Kugler the CEO and co-founder
0:05
of direct mail 2.0 we are a direct mail technology company we don’t print or
0:12
mail anything we use digital marketing and layer it on top of direct mail to
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get about a 50 lift in response rate so we currently have about 13 different
0:23
digital technologies that we layer on to direct mail I’ll give you an example
0:29
things such as call tracking pearls uh personalized QR codes uh what do you
0:36
call it retargeting geofenced ads uh pixel tracking so that we can attribute
0:43
enhance lift and report on the effectiveness of direct mail I’ve been doing this about six years I am a
0:50
marketing technology geek at heart before this I spent 26 years in
0:55
wholesale distribution retail and e-commerce so I went from being
1:01
disrupted oh here’s Ken he’s coming in thanks Ken glad to see you there I’m just making introductions so uh
1:08
I will not put you on the spot and make you go next I’ll let you get in here you
1:13
still are on mute though um anyways I was disrupted in the uh DVD
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CD selling space and I had to reinvent myself at the age of 50 and become a
1:24
technology guy and that’s what I’ve been doing I’m gonna let uh Thomas introduce
1:29
himself and give us a little bio and why he’s here and uh over to you Tom
1:36
thank you Brad and good afternoon welcome to the audience my name is Tom cross I’m from Boulder Colorado I’m the
1:43
managing editor of Channel partner TV the world’s largest Channel video news network on cyber security and channel
1:49
news with over 1100 videos I wrote the first book on teleconferencing I do a
1:55
conference and you’ll see more about what we’re doing here on the AI user Forum I’ve written three books on AI and
2:02
I’m pretty much a proponent of the concept but I’m not you know necessarily
2:07
excited about the execution of it and I’ll explain more during my presentation so without further Ado I’ll get back to
2:12
you Brad thank you all right Siobhan will let you go next give us a quick intro on what
2:17
you’re all about hey everyone I’m so glad that you guys can make it here today uh my name is Shivam I’m one of
2:23
the co-founders of Maya AI uh what Maya really is as an AI data platform that
2:30
helps to find actionable insights and opportunities from historical and changing data so today we are in couple
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of Industries Healthcare Pharmaceuticals mostly but we are also in retail Banking
2:43
and Technology as well so um thank you Brad and back to you excellent all right
2:49
thank you for being here as well Ken let me hear your Spiel tell me what you do
2:54
hey everyone I’m Ken Vermeil uh the founder and CEO of Ronaldo inside we
2:59
help entrepreneurs and startups build mobile and web applications we are
3:05
heavily invested in also integrating AI into existing and new applications and
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so um personally for me I understand and we’ve been actually tweaking and using
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AI tools for a a good amount of time and it’s interesting to see that uh you know
3:22
the world is using um some of the tools that we’ve been using uh and it’s I mean
3:28
I’m excited to be here excellent well thank you guys thanks to our panel thanks to our attendees so you know we
3:34
put this together because all we hear now is a AI this and machine learning that and chat GPT and Bard and
3:42
everybody’s in this world and this is uh for me I’ve been around a little
3:47
while this is very similar to the explosion of the internet itself back in the late mid to late 90s everybody is
3:54
jumping in everything as fast as they can it’s like gold was just discovered in California and it’s 1849 all over
4:01
again and this is what I’m calling a a formative I
4:08
think change in the human experience that we’re gonna sort of evolve to over
4:14
the next 20 or 30 years we are just touching the surface in my opinion on what’s Happening Here so
4:20
um it’s going to touch everybody’s lives and in in it’s one of those things where
4:26
if you aren’t educating yourself and bring yourself up to speed you will get
4:31
left behind now uh there are many sides to this there is no
4:38
get rich quick scheme there is no simple way to learn it all it’s such a massive subject so I’ve decided I’m going to put
4:45
together a little 10 minute intro to kind of orientate people kind of bring it back to how does this affect
4:51
marketing or direct mail is what I’m all about and these guys are here as
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industry experts and having more experience than I do to help kind of tie
5:01
it all together and answer questions that I can’t so let me jump right into it
5:06
you know from from what I’ve discovered AI has actually been around for a while
5:12
it’s it started uh Thomas corrected me it’s first I guess inklings of it were
5:19
in the 30s and 40s and in the 50s and 60s there were really big uh
5:25
changes in the computer sort of space IBM formed and and this was sort of the
5:30
start of it all it accelerated a little bit in the 60s and 70s with the with the things I have here and I don’t want to
5:36
get into these and spend a lot of time but it it Advanced even in an order of
5:42
magnitude in the 80s and 90s with neural networks in the beginning of machine learning up until about 2010 till now
5:48
where we’ve seen the explosion of deep learning and application started as chat
5:54
GPT and sort of the other things so it’s in the news everybody hears it
6:00
everywhere uh nobody can go five minutes without hearing about chat GPT now it’s
6:06
one of the quickest applications ever to hit a hundred million users I think it was 60 days and if you’ve used Dolly
6:14
which is a computer AI generated Graphics tool it’s really interesting
6:21
you’ve got the wars heating up between Google and Microsoft and
6:28
this is kind of where all of the money is going in terms of uh what do you want
6:35
to say invest your money we’ve heard about crypto and blockchain the last few years whether you think it was a big fad
6:42
or or it just I’ll tell you something and this is my own opinion those are difficult to understand and they’re
6:48
difficult to use almost anybody can open a chat GPT and ask a question and get an
6:54
answer that is much easier and that’s why this thing in my opinion is growing so quick
7:01
um a lot of people say well anything that blows up like this is going to be a bubble right most likely there’s going
7:06
to be some very early expansion of this technology that’s going to roll out too quick with high valuations that are not
7:13
justifying those valuations and I wouldn’t be shocked if we can see
7:19
something very similar to what happened in 1999 with the.com bubble all right one of the interesting things here is
7:28
um there’s a lot of ethical considerations which I’m saving and we’re going to discuss that in depth
7:34
here because it’s it’s it’s different and deeper than the.com explosion of the
7:39
late 90s um the investment in this sector is 154
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billion dollars estimated this year that is huge last year there were 960 M A
7:51
deals alone and what’s really going to fuel this fire is there’s six trillion
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dollars of cap little sitting in vcpe firms and the public markets ready to
8:05
deploy that’s being held back because of this economic uncertainty and everybody wants to jump into AI so you know you
8:12
raise a sign and you’ve got an AI product people are going to throw money at you all right
8:19
this is a this is a slide that shows one person’s Viewpoint that the big Tech
8:25
Giants are going to dominate this industry which is very possible and I’m putting this out here because I know
8:32
there’s a lot of anti-giant government giant tech company sediment growing out
8:38
there but these are the companies that are really best suited to jump into this market and they’re all going into it
8:44
hard so keep your eye on all the big boys what makes a good AI obviously AI is
8:52
completely relate is completely reliant on the data that it’s founded on if that
8:58
data is not owned or if that data is not accurate and there’s not a continuous
9:03
flow of new data being fed into those learning models well then that AI is
9:09
only as good as its snapshot of that data at that point in time all right so
9:14
it’s very important when you when you look at an AI product platform company
9:20
whatever check out their data sources do they own it is it proprietary is the data being
9:27
fed into it accurate you know there’s already lots of talk about chat GPT giving out bad data and wrong answers
9:35
well any AI is only as good as the data that goes into it all right and and that
9:41
being said and this is one of the first Segways into it is marketing is really a great place to use AI because of the
9:48
constant new data because of the proprietary data sets that marketers are compiling and have ownership to
9:56
um so great place to use AI what are the overall sectors of AI this
10:02
is this is from an article of some of the research I’ve done and uh generative
10:08
AI where it generates answers based on natural language processing like chat
10:13
GPT you ask a question the the AI goes out to a data set based on all sorts of
10:19
language rules and and again the availability of the data at hand and it produces a plain language answer this is
10:26
what most of us are familiar with internet of things iot every device
10:32
coming out these days either has some Internet available uh application even our refrigerators
10:40
our ovens of course are going way beyond our phones my sprinkler system my pools
10:46
uh meters will all communicate with the internet and thus are available to be
10:53
upgraded with AI technology uh robotic automation this is if you
10:59
follow um Arc Investments a big New York Wall Street firm that moved down to Saint
11:04
Pete Florida they are going deep into robotic automation you’ve got all of these robots now being perfected that
11:11
then connected with AI whoops here you go cyberdyne systems and Terminator 2 all over again and I’m sure we’ll
11:18
discuss that the metaverse uh to me I feel this is a specific generational
11:26
Target I don’t know that this applies to everyone I’ve tried it it hasn’t bitten
11:31
me the way it’s bitten some I I think it it could develop but it hasn’t for most
11:37
yet uh computer vision computer vision is the AI or machine learning reading of images
11:45
or the creating of images and using the data in pixelated images to propose a
11:53
solution a change or some sort of other event based on images fed into it so
11:59
these are all major sectors of AI how is AI transforming marketing and
12:05
digital mail well very easily personalizations customer segmentation
12:10
Predictive Analytics chat Bots and conversational Ai and sediment analysis
12:16
how are people reacting to the marketing I I’m not going to go deeply into each
12:21
of these because we can discuss them but personalization the more that you can
12:27
speed up and automate personalization marketing recipients respond to
12:33
personalization AI makes this much better and much quicker
12:39
targeting analyzing past engagement past purchases past past
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active data from from potential receivers of marketing data and using
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that data to Target more effectively this is a great task that uses hardcore
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giant big data to improve marketing optimization tracking these responses in
13:05
real time adjusting the response out or the new marketing algorithms based on
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immediate response data you can now Target digitally almost instantly and
13:16
improve results on a minute by minute hour to hour basis and obviously you’re
13:22
going to reduce cost and you’re going to increase lift with the result of AI
13:27
automation obviously the key thing of of AI it’s not an actual sentence being yet
13:34
but it can make decisions in mass and faster than we do so by using this data
13:41
you can make business decisions marketing decisions any decisions much much quicker
13:47
uh here are some marketing tools that AI is specifically already operating in I
13:55
add our new dm2o.ai which we’re putting together and I may have time to tell you more about
14:01
that later but anyone doing any type of print marketing we are in this business to stay and and I’m spending a good
14:09
amount of my time educating myself so I don’t become a dinosaur or irrelevant
14:14
about this so at that point I hope I’ve kept to my time limit I am going to turn it over to
14:22
Thomas for a quick presentation on some of his things I’ll admit he’s a little
14:28
bit of a protagonist I’m sorry an antagonist to the general thing and I
14:33
respect his his Viewpoint and it may come across as a little bit different
14:38
than most of you will will come on hey what do we learn if we all think the
14:43
same way go ahead Thomas you got you got 10 minutes
14:52
you there yeah all right here he is you see my screen you see this your screen
14:59
let me make sure that everyone else can you’re says I’m viewing your screen can
15:04
anybody confirm that everybody sees Thomas’s screen all right okay you got
15:09
the floor man have at it thank you and good afternoon thank you Brad uh these
15:14
are some highlights from an executive seminar that I do on building an Intel artificial intelligence marketing and
15:19
business due diligence and validation strategy I think it’s really important before we get started and getting all
15:26
enthusiastic about it but we need to look back on what why AI has failed and failed badly for the for forever really
15:34
and it will still continue to fail because there’s just trying to solve too many issues at the same time and here’s seven reasons why it fails I think it’s
15:41
really important that we kind of look at you know the legal intellectual property copyright ethics issues too I’m not a
15:47
fan of the signatory thing that they did today you know I think Elon should fix Twitter in the meantime but also I
15:52
really think it’s important that we kind of understand what’s fake what’s real out there those are the real real issues
15:58
on making sure if somebody uses AI the actual information has some reality to
16:04
it and people rely upon it for good decision making because if you know bad bad data is Brad points out equals bad
16:11
decisions so you can’t you got to figure that to begin with I think there’s also the other thing is unrealistic AI
16:17
results people think that it’s going to solve all these problems it’s like the shiny new toy thing it’s not I mean chat
16:25
gbt may be able to solve or read you know write a grammar statement but it’s not going to help you figure out the
16:31
weather or help you drive a car or anything else like that so failure to understand where we’re going with this is really important as well number three
16:38
uh Venture and investors you know that’s the part of this thing there’s been so much money thrown at this and I think
16:45
that there’s a lot of people got to fess up to the fact that this for the most part has failed has failed miserably for
16:51
the last 20 years I wrote my first book on AI in 1989 so I’ve been around for
16:56
this industry for quite a long time and I’ve seen so much failure going on out there so I think those are really
17:02
important you know the other thing is that AI companies don’t want to hear anything bad and don’t want to tell their customers that you know stuff’s
17:08
going to happen out there that they’re they’re really not going to solve all their problems so there’s kind of I think needs to be kind of a ownership
17:15
you know a reality check to you know what is the problem they’re really trying to solve out there and how realistic can they do that because
17:22
otherwise it’s they’re gonna people are going to try AI or try the solution and it’s going to fail and Brad pointed out
17:28
he showed what 20 different marketing things there was just another list of another 50 different AI copy companies AI is not one thing so you got to really
17:36
understand you know what is going on out there and I think the same thing at the Enterprise sea level I’ve interviewed a
17:42
lot of sea levels and they’ve spent millions millions of dollars on this technology and they have not seen any
17:48
results and I’ll explain why and what is in my opinion Ai and how to recover
17:53
solve these problems but real realistically understand that this is going to fail and you’ve got to start
17:59
from that perspective and don’t assume that it’s going to be some shiny new toy that’s going to solve everybody’s
18:04
problems out there the next thing is cyber security this is
18:10
if you’ve read the White House the cyber security thing if you follow the nacd
18:15
National Association of corporate directors put out 104 page security
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handbook for boards level people on cyber security and I think we need to
18:26
understand how that’s going to impact AI because if your AI system gets attacked or you get attacked and I think that’s
18:33
the someone wrote an article a critical Insight did a really good article on how chat gbt is going to be used to program
18:39
or write uh ransomware so we can’t you know I agree a little bit on the idea
18:45
that we should be looking at you know what where’s AI is but you know it’s got
18:50
to be it’s not going to stop that you know cats out of the horses left the barn so there’s no stopping that that
18:55
letter is just nonsense about how we’re going to stop AI oh we’re going to take a pause who’s going to take a pause the
19:02
the Chinese the Russians whoever who’s ever the Bad actors are in this process out there I think we got to really take
19:08
a look at that the other thing is that there’s just so many things that society as a society we cannot work Saul you
19:17
know sadly Tennessee gun violence is causing Lives why do we
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work on that 23 people in Mississippi died this week
19:28
weather related accidents how about better forecasts that save lives that way traffic accidents it goes on and on
19:35
and on so we need to work on that kind of part all right so you cannot predict competitive hack attacks either in m a
19:41
advances in Tech or anything else nor react to them you can only direct your customers to your content and Leadership
19:48
thought leadership and that’s really the key Point here is that you’ve gotta whatever your business is you’ve got to
19:54
be working on who are you and what can you bring to the bait the table for your customers out there and if you use AI
20:00
That’s fine but you gotta understand what a you got to explain to them what it’s going to really solve out there and
20:05
it’s not some sort of Panacea out there all right so I’m going to go through I consider Core Concepts to AI the first
20:12
one and you know this goes way back you know and you’ve got to look at different problems we’re trying to solve out there
20:18
and I call it vertical intelligence and this is like for example soup people you know people in restaurants people who
20:24
make things like that you know um one soup manufacturer try using Ai
20:29
and they it worked for vegetable soup but it didn’t work for mushroom soup so realize that even within a small context
20:36
of trying to solve people’s problems that AI is not a panaceus and it’s not going to solve people’s problems because
20:43
whether you’re when you deal with humans we’re all different and we all like different things at different times and
20:49
we’re actually frankly devious and sometimes diabolical at the same time as
20:54
we’ve seen was causing the war lateral is kind of even more fun in the sense is that there’s vertical intelligence
21:01
there’s lateral intelligence you know as a human’s we can get off our bikes drive a car without even thinking about it we
21:06
can get in an airplane we can even fly an airplane and go to different places and so is the what is the AI trying to
21:12
tell us or help us solve is it can help the pilots do better things could it interact with the weather system to do
21:19
better forecast to fly a better plane if Hazard plane Etc I think that the questions become so complex that there’s
21:25
not going to be any one AI or a multitude of AI systems that need to be solved on that especially even apply
21:31
that to marketing marketing is not one thing you know is it blimpse Billboards you know Stadium ads what is it that
21:38
really works out there what resonates on that you’ve got to try a lot of different things and the other thing I like to talk about oblique intelligence
21:44
oblique intelligence is the kind of Randomness that humans really adore we like random things in our lives you know
21:51
and you kind of try to bring these together you know when you think about humor you know you know humorous and
21:57
comedy and things like that’s a very complex subject out there and I don’t know that we’ll ever automate that or
22:02
even have an AI system to do that but we have to understand whatever technology we’re using it’s going to be the person
22:09
is going to be using that as a person and that person has different needs at different times they’re going to change and so one needs to kind of build these
22:16
things as kind of I like to think is kind of a complex I think Network together because the human mind isn’t a
22:22
computer it doesn’t compute things it’s a connection device it connects ideas you know when I say red you that can be
22:29
10 different things to another person if I say car to you if I say pizza oh I
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don’t think we have enough time to talk about that so I think we need to take a build a long-term view of what we’re
22:40
going to do with that technology and see how we kind of build work toward towards that you know it’s a very Dynamic and
22:46
changing industry and even the academics underestimate the rate of change so oddly enough in the last few months has
22:52
changed a lot and now we’ve got a hundred thousand or 100 million people trying to use chat gbt for what reason I
22:58
don’t understand I still question the copyright on that plagiarism things like that focus on the compelling business
23:04
issues I mean every business has problems and pain points they want to
23:09
gain from so whether it be delivery complex order processing EDI ESG and
23:15
those kinds of things you know how can AI solve those problems and maybe compartmentalize aha we have an AI
23:21
system for ESG we have another AI system for Dei and they’re very different systems and then realize that’s not
23:27
going to be one great big you know monolithic AI system out there the other thing is build an AI business model what
23:34
is the goal how does it fit in how does AI fit in and Approach at an intermediate and long-term business
23:40
model as well as this an internal or external business be sold to others so I think we
23:45
need to see how that fits in I think I think it’s all possible but what I have seen out there time and time again for
23:51
decades is that no one is really working on that part now one way you can do this I think heat
23:57
Maps were a good start humans like heat Maps you know we like we like weather reports uh whether you know weather
24:03
report’s a heat map of of sorts you look across the United States you know heat maps of knowledge and how can this be
24:10
automated I think if you’re going to look at heat Maps you could look at your competitors look at your Solutions you
24:16
know what selling what’s not selling out there things like that Global issues how do Global issues how does the weather impact oil prices how do oil prices
24:23
impact people’s buying habits you know the Silicon Valley Bank to me is a bigger issue than chat gbt because
24:29
that’s going to have a dramatic impact that’s had a dramatic impact on most all business and customers out there you
24:37
know what is a good bank to use out there so you have to understand where you kind of fit into these heat maps and
24:42
how they work together you know we’ve built one we call it cross net points but the idea is that you kind of come to
24:47
bring to get a lot of different factors together and you bring them together to solve the problems because you’re not taking a kind of a silo approach and
24:55
that is what’s happened out there there’s they see you know AI I’m going to use for my Trucking I mean there’s a
25:01
different AI system for my shipping ah each one’s very different well we’re solving different problems out there we need to solve them differently
25:08
so how am I doing I got five more minutes so anyway I also think that again I’ve mentioned this before
25:14
terrorism is going to gonna get us you know that scares me more than anything else because we’re just we’re so I think
25:22
so complacent about it you know it’s going to happen to someone else and you
25:27
know it’s it’s not it’s going to happen to you and I think that we need to step up the AI effort into cyber security to
25:35
protect people because I’ve done over 800 videos on cyber security companies and they all tell the same thing stuff’s
25:41
gonna happen you may detect the stuff we may not stuff’s gonna happen but we may not be able to solve it stuff’s going to
25:47
happen and the and if you get screwed you know hit too bad more positive level
25:54
rethink the CEO the CEO is really an awesome person in the company whether it be Iger Disney or they brought back the
26:01
new HSBC guy et cetera for those the banking or whatever Jamie Diamond you
26:07
know these people really understand their businesses and they’re really great leaders out there and I think we
26:12
need to take AI out of the basement so to speak and out of the coding area and we need to move that expertise up the
26:19
food chain and I think if you want to start with hey I start with a CEO how does a c you know CEO think
26:25
you know what is the CEO thinking about where are their plans now they may not
26:31
tell you all their plans but it’s a great place to start and I think we need rethink those kind of processes other
26:37
way to do it is look at your customers you know each customer is a bit unique and you need to start out where they are
26:42
where they are in that process and how to help build them through the process if you’re going to offer an AI solution
26:48
you need to be talking to them okay what is it you’re trying to solve here what do you need out here what can we do this
26:55
maybe we can’t do that you know maybe they’re willing to do that help help you do it anyway I put together kind of like
27:01
I call a future roadmap put together roadmap where things are going where do you think things are going not just with
27:07
your product not just with your industry but where things are going in general as far as intelligence and technology and
27:13
put it them all together whether it be a heat map or a road map or Etc and kind of take a look at where things are going
27:18
how you’re going to fit in where is your plan from five years from now how does these all things fit together you know
27:24
Brad brought up iot big big thing all right here’s a few trends for you and then I’ll stop all right if you haven’t
27:30
watched the movie the greatest movie of all science fiction movie all time is The Day the Earth Stood Still and I
27:36
still think it’s my favorite and this is a picture of Gort and uh Gort was a robot he destroyed
27:42
things and he would destroyed the Earth had we messed up but I do think that chat DBT is not real AI I think it you
27:50
know it’s like an advanced grammar system and I think you need to think about you know what is it really going to happen out there I am really
27:56
fascinated by Quantum I think Quantum is a really Game Changer both on the criminal side as well as on the positive
28:03
side and when you think about it it’s going to be 50 50 or even 60 40 crime beats you know goodness you know so but
28:10
you know when you look at the technology out there Etc also I think that the privacy issues the reputation issues are
28:16
very important for our business to consider you know that Federal Reserve Zoom form bomb was pretty bad you know I
28:22
think you know people’s got to take a look at how your technology if you’re making technology or using technology if
28:28
you use it and it causes harm to your customers where will you be then I also think that you know uh you know Brad
28:35
didn’t want me to use that f word so I won’t say f-bombs Etc but I can use f UPS uh this is a picture from the Gulf
28:42
at the bottom of the gulf and this is why I love this picture because it was a place the humans could not go to
28:48
you know solving a problem of the gulf oil spill and while we haven’t had one
28:53
recently you know good good grief it could happen anytime soon and so that’s what’s going
28:59
to happen the pandemic is one of those things and Silicon Valley Bank was a small one but has will have a big impact
29:05
out there I also think we’re just kind of like sidestepping oh yeah pandemicovit’s gone have a nice day we
29:12
don’t have to wear a mask anymore no it’s gonna there’s gonna be a next one and it’s just gonna be prepared is for
29:17
the next one and the next one the next one because it’s going to get us and that’s how we’re all going to die I’m skipping conclusions because I’m running
29:23
out of time you just come to my get my seminar and I can do that for you and you know I’ve got one few a few last
29:30
slides here the competition has not have has this time prevented us from knowing
29:35
enough about them but we have not prevented them from Annoying far too much about us so keep in mind that the
29:41
competitions out there is always going to come after you they’re going to come out to you from different ways Etc uh
29:47
we’re doing a call for papers at the AI user Forum you’re welcome you know submit a paper love come to a conference
29:52
it’s going to be hybrid online and here in Boulder Colorado and this is a little bit more about that here’s my in my book
29:58
called smine mail stuff like that and there’s just a final thought this is a from a great book you’ve got to be I
30:05
think really realizing how devious people are and I think that you know Chamberlain who has been noticed for his
30:11
appeasement out there he was a very devious person too it wasn’t just like he was the passive thing trying to avoid
30:18
the war that he saw World War one he was he was very very devious person he hired he hired people to go after his you know
30:26
his competitors out there and I think that that’s really important to realize thank you for Brad I hope I didn’t take too long too long no problem Thomas
30:32
thank you let’s dive into questions that was great I hope that people feel a little bit educated and you see
30:38
different sides of this so the first thing I want to ask Ken since uh you’ve been the most quiet so far uh what do
30:46
you personally think I’m assuming you heard of Elan and Steve wozniak’s open letter today to pause AI I’m I’d like to
30:54
I think we got Thomas’s opinion on that I’d love to hear from both
31:00
what do you guys think of that so the interesting thing is I’m in the middle on this so I I’m very optimistic
31:08
about AI but I’m also very worried about AI um me working with me being a programmer
31:15
I understand that you can build something one way and you can watch the
31:21
users use it in a way that is unintended and from there you can see that yes
31:27
people are going to use it in the various ways um today and well the the open letter was
31:37
they do need to put a pause on artificial intelligence and my gut says
31:43
that they are correct the reason being is that there is no oversight
31:48
um you can even though these algorithms well I call them algorithms but these are these AI
31:54
agents are becoming very sophisticated very quickly the problem is it is moving
32:00
too fast for us to understand the second order consequences that may happen by
32:05
releasing these uh AIS into the into the world right there does need to be some
32:11
type of legislation that says hey you know what your AI cannot um go on the internet and do nefarious
32:17
things there does need to be something there in order to there needs to be a
32:23
stop Gap right now there is no stop Gap and usually we
32:28
run into a stop Gap when something terrible happens but by that time it’s too late so
32:35
we don’t necessarily want an a nefarious Act of decree and AI that
32:41
does something terrible we don’t want the AI to become autonomous which I
32:48
think that we’re some ways like we’re we’re some time away from there but we
32:54
also want to be careful that we don’t stifle Innovation because if we don’t do it
33:00
um we meeting the United States somebody else I agree I agree great and and uh let me
33:08
hear your thoughts Siobhan what do you think on this yeah so this this topic is definitely very interesting as Thomas and Ken had
33:14
mentioned some really good points I think I would also agree that you know we need to take a look at where it’s
33:21
headed because it’s going way too fast and us as people we love to move fast we
33:26
love to go on to the next things really relatively fast as well so I think collectively as Ai and other technicians
33:34
developers we need to really see what the capabilities of this AI can do just
33:40
because I’ve even myself I’ve heard many stories and as Ken just mention right like we can build the AI to do one thing
33:47
we can create it to do this type of process but whoever’s using it because you can use it 180 degrees and
33:54
it’s way different than we intended and therefore it can be either you know it can be very dangerous right and I
34:01
also think that with AI there’s a access question there as well because as the
34:08
models is trained to do certain things go fetch this go fetch that what is
34:13
stopping the AI from going to a public access points getting some of that information and thinking about it right
34:20
another part of that is like some of the way these AI thinks and bias information
34:25
right like you know is the AI going to scan over Wikipedia to deliver medical insights I don’t think that should be
34:32
there but does the AI know that um yes or no so I think that from an
34:37
ethical value we need to say like these are the boundaries of what AI can do this is what we programmed it to do and
34:44
these are the rules behind it right because it can go it can go it can go either or right it can be very very good
34:50
or very very bad in that sense so great and I’m going to interject my own
34:56
opinion on on this same question a I think the proverbial toothpaste is out
35:02
of the bottle at this point there’s no entrepreneur or BC group that’s going to
35:08
tell their developers take it down a notch actually don’t go there there go you know stay out of that that that’s
35:15
too complicated and too good of an AI not going to happen uh what we probably
35:21
need I think we’ve all heard of Isaac Asimov in the um three rules or robots
35:26
that they can do no harm we need a set of laws like that that are uh created
35:32
and required for all machine learning and AI algorithms that they must comply
35:40
to that there’s a certain boundary that they cannot exceed all right I don’t know what that is I’m not a ml engineer
35:47
but I think that at some point these these agents becoming sentient or
35:52
conscious at some point could be a problem as we’ve all heard the Doomsday
35:58
scenarios they decide that humans are just shouldn’t be around they can’t be trusted let’s get rid of them you know
36:04
but uh that’s that’s my point on that
36:09
did someone want to say something oh yeah I like that you bring on you brought up Asimov because
36:15
later on in in some of his books there are you know he created the concept of the robot and
36:23
in in the later books these three laws of robotics are imprinted into their you
36:30
know cybernetic brains and because of that it’s not something that can be removed it is something that’s part of
36:36
the personality and you know I’m not thinking where we are now when it comes
36:41
to yeah I’m thinking you know this is something that’s gonna happen like 10 years from now and by that time would
36:47
have those laws in place you’re right the toothpaste is out of
36:52
the bottle and now we need to figure out what makes sense and what we can do to
36:57
preventions needs to be created I I don’t disagree so
37:02
I I wanted to ask a question is you know what what has chat GPT done to
37:10
the market and the acceptance of AI in each of your eyes you know
37:17
um and let’s try to keep it brief what do you think is the biggest effect of the release and explosion of a product
37:23
like that in the last 90 days uh Thomas you’ve been quiet for a few
37:29
minutes count your breath tell us your thoughts you’re you’re muted though you’re muted
37:36
all right keep reading that uh going back to robot thing for a second uh if you watch the movie The Day there’s
37:41
still uh Gort was the robot that was given the power by the society to
37:48
destroy other planets if they did not comply so I think it’s a really good movie to watch it’s 1953 and
37:55
understand how Society treats and feels about how robots how they should treat
38:01
other people basically they build a robotic police force so number two is that this chat TBT
38:08
thing again it’s a shiny new toy we’ve seen that before whatever it is we seem to kind of Glop onto that and then it’s
38:15
just going to fade you know as fast as you know a lot of these different things out there because people don’t you know
38:20
hey you know if you’ve if you follow that great editorial cartoonist Tom Fishbourne on LinkedIn he has this you
38:27
know two two things going like here’s the one person standing in the chat gbt email and the other person responding
38:32
using chat gbt email and you go back and forth using chat GB as we’re going to spend too much time wasting our time
38:39
trying to figure out how to use it’s just another thing that big companies try to sell us to oh you have to use
38:47
this application to to write a letter nonsense you know call people up write
38:53
your personal note out there you know it’s not going to help you solve a problem you’re going to spend all your time trying to figure out how to respond
38:59
via chat gbt sorry okay I I respect that
39:05
tell me your thoughts what is the biggest impact of the chat GPT explosion of the last 90 days yeah so
39:13
based on what Thomas was referencing before like the AI and these type of Technologies been around right I think
39:19
what has blown up was the access of that right so as more people start to get access to chat qpt they’re like wow this
39:27
thing can help me create a letter create an article but what I think
39:32
from an innovational side it made us more adaptable that says AI is here now
39:38
the next step to that is like how do I leverage it or how do I use it right that’s on the Innovative side but I
39:44
think what it did to the market was it shooked it up a lot and saying hey like this is the new advancement of
39:50
technology and this is where is going to lead to eventually just based on how the Market’s moving what
39:57
these other companies are creating Tesla Microsoft Etc so I think open AI
40:03
strategically produce chat GPT to say hey this is the new emergence of tech it
40:09
may not be so valuable from a business side or a personal side but it
40:14
definitely broaden our eyes in terms of like what we can what we’re able to build today and what we can do with that
40:21
right so I think that’s my perspective and um it leveraged a lot of us to say
40:27
hey well if this type of tech is here today what the heck can I do right what
40:33
am I able to do today as well right if this thing gets smarter in five to ten years is it going to be smarter than me
40:39
at creating letters is it smarter than me at creating content so I think there’s also a battle of skills there as
40:45
well hey Brad one of the things that this Craig green mentioned that Chad DBT is ubiquitous and college campuses and
40:52
high school students these companies will be users of generative AI for life and that may be true but the question I
40:57
would mind is at what point does you know does the creative mind circumvent or be used by a machine and
41:05
the idea is you know how do you know this is plagiarism and I worry about copyright as a book author right and I
41:11
think the idea is that yeah we’ve got tools out there and I use you know diction grammar things like that but
41:16
again I I value the the creative opinion that is written that people take and not
41:22
just have a machine come up with some I’ve seen these gen these articles written by chat gbt and I go you know
41:28
that’s not helping me educate people about things that’s just a regurgitation of a better search uh listen nothing I
41:36
agree we are in some some new ground here Ken would you like to comment on any type of content generation from chat
41:43
gbt and how you what your feeling is on it yeah I think
41:48
when it comes to the market chat GPT has allowed people to create things that
41:55
they have probably always wanted to read but never had the time um it gives the advantage of hey I want
42:02
to write I want to write a chapter of a book okay you know kind of help me along and outline the chapter of the book you know
42:09
fill in some some of the speeches here and there right I think that moving forward everybody’s going to
42:14
everybody’s going to be doing some type of prompt Engineering in where
42:20
the you’re having AI fill in the blanks for you the thing is the thing that people
42:27
um are mistaken about is that they think that it’s going to replace the the what
42:33
right so if I want to create a blog post I can say hey I want to create a blog
42:39
post about X and then I can go in and chat DPT and it’s going to pull into the data and it’s going to give you some stuff and
42:45
um honestly you shouldn’t you should be copy and paste the blog post is right out of check you can see because it’s
42:50
going to be a little bit inaccurate you know they’re going to be some uh seven figure hands in there
42:56
and then and then what what what essentially will will happen is the person who figures
43:03
out what the what is the the most valuable what is going to be the person that’s going to be Innovative it’s gonna
43:09
right now you’re seeing content flood the market and a lot of this generation a lot of it is not necessarily creating
43:15
value but what will happen is just like how it’s important to know HTML today uh it’s
43:23
going to be important to learn how to do uh prompting for a variety of fields
43:28
um but it’s going to be more important to know what what it is that you need to do rather than just the prompting itself
43:34
right right that makes sense I I’ve got some commenters here with Alex Elliot
43:41
says when are we getting to uh direct mail and AI uh we’ll get to that in a
43:48
second I’ll segue to that um we’re trying to do is understand the
43:54
implementations of using AI in any kind of marketing and and I wanted to make a
44:00
point on and this is this is relevant to any sort of content or digital marketing
44:06
using an AI tool is the validity of the data the the veracity or the
44:12
non-plagiaristic content being created there’s actually AI tools that once you
44:18
take the content generated by chat GPT you can dump it into a another service
44:24
and I should have written it down I saw a video about it today from a Content writer there is another tool that scans
44:32
the AI generated content and actually points out words or comments that look a
44:37
little too similar to where it got the original data and suggests changes to it so it’s not quite as I don’t want to say
44:45
plagiaristic it takes a phrase here and a phrase there it it it moves things around to make it a little better
44:52
so a huge problem with creating articles and I’ll give you my quick little story
44:58
as I I wanted to create the entire slide deck uh from chat GPT I said make me a a
45:06
presentation about uh Ai and its use in marketing and IT spit out something I’m
45:12
like yeah I don’t really like that and it spit out something again and I I didn’t really like that and then it spit out something was a little better and I
45:19
still took it and edited it myself so in the end did I really save any time I
45:24
mean I had fun playing with it but in the end it was close it was it
45:30
definitely sparked the creative juices to come up with ideas and and buy lines
45:35
and headlines and bullet points I still had to research those bullet points or re-feed them into the prompt to get more
45:42
dissertation or discourse on those bullet points but I don’t know did it really save me anything and and to sum
45:50
it up my point is is the prompting of an AI is where the new skill set is going
45:57
to have to come from the Next Generation as we learn how to speak to an AI there
46:02
will be positions created in companies that do nothing but give the right prompts to elicit the correct most
46:10
idealistic efficient response so that’s my point I want to go on to try to focus
46:16
in on marketing and and I’ll start with um
46:21
Siobhan why don’t you tell me how would you use AI marketing let’s let’s move past the uh content writing option into
46:31
more of a digital campaign a print campaign where where do you see AI used
46:36
in marketing yeah so just based on our product and we’ll be developing so far uh I see AI in marketing on more of the
46:44
analysis side of things so for example us as marketers we’re trying to influence you know new customers you
46:50
know create a new ad you know create content but beside the creation part I think AI is going to help us deliver
46:56
ideas in terms of this is what the market looks like this is what the patterns look like of people’s buying
47:02
Behavior so I think AI is is able to generate like insights more of these key
47:08
information of what’s going on rather than Hey Thomas you need to write about this this is what it looks like in da da
47:15
da more of a Content style because what chat apt fails to do is provide a
47:20
perspective right saying hey like um Brad you were asking Chad jpt to create
47:26
you the slide deck but who the heck was the slide deck for who’s it speaking to what kind of a market who who what where
47:33
one why right all of these mini phrases I think AI can help us understand that
47:39
before we come to the generative part side of it so I think it’s helping us find these key indicators of you know
47:46
what does the economics look like what you know what did FDA just provide in terms of policy changes right all of
47:53
these manual research I think AI can help in that aspect even more than the
47:59
generative side of things I completely agree the analysis side and others all
48:04
right Ken what what is your uh advice on AI and marketing so a really cool thing that I’ve been
48:12
doing is I’ve been creating customer personas based off of reviews
48:17
and well based off of internal customer data
48:23
um reviews buying patterns and just any other data that we can get to
48:30
essentially create a fake person that you can ask questions to
48:36
um I think that’s going to be super valuable creating like a fake persona of of your customer that you could talk to
48:43
that you could ask questions to obviously it’s not going to be exact but the more data that you can put into this
48:51
model of a Persona the better results you can get the other thing is the the
48:58
cool and interesting thing is that you can get it to spit out some things that you aren’t able to see from from the
49:04
series for instance if um let’s say if you have a gifting platform and every uh people between you
49:14
know 20 and 30 always get there always purchase their a gift for their mom a
49:21
week before uh their mom’s birthday you might not be able to see that pattern but you could build a Persona to be able
49:28
to identify that pattern to figure that out so you can test ideas with that model you can even write a blog post and
49:36
say hey do you find any value from this blog post but a lot of cool and interesting things that you can do just
49:42
from just from that and again the the better solution is talking to an actual
49:48
person and getting their real feedback but if you treat both
49:54
if you treat both lanes differently in one sense of hey this is my this is our AI Persona they kind of get all of our
50:01
historical data and we’re gonna pull out some analysis from this and hey this is
50:06
a real person they have real needs and problems and we’re going to help them solve their problems then that works the
50:11
other thing that you have to keep in mind is that when it comes to when it comes to getting data and
50:16
pulling data from the machine a machine is going to take the most logical um
50:22
it’s going to take the most logical path and that’s not necessarily how humans work uh a lot of my incidents are made
50:30
uh via emotion and right now there’s no
50:35
real way to simulate emotion in a digital environment so as long as you
50:41
keep that in mind when you know you should be fine good good and Thomas tell me what your
50:47
ideas of using Ai and marketing to help businesses Market themselves
50:53
well I think that Ken and Siobhan bring up some really interesting points about you know it’s it’s given maybe you can
51:00
think of as a tool to surround your ideas you know I’m I’m not I’m not opposed to
51:06
using a power drill you can drill faster have a machine do
51:12
that but realize the difference between what you’re doing and what’s it’s doing and what the customer needs out there
51:18
and I am a big fan I’m not a big fan of focus groups or surveys or whatever you go out and you simply talk to the
51:25
customer you know I did interviews with the university you know ATT a long time ago you don’t go into the chancellor of
51:32
the University of Alabama and you give them a survey you ask them tell me tell me what you think about educational
51:37
technology oh and you keep tell me more tell me more you want to peel back that
51:43
onion you know to what people are really thinking and then you can really help them because otherwise they’re going to
51:48
keep their Shields up they say you know and you’re gonna kind of lose so that’s
51:54
just the way I think it’s really powerful as a tool to surround us but keep keep the differences in mind keep
52:01
the lanes in mind thank you and just just to add on to that real quick Ben um so what Thomas had just said right in
52:07
terms of like Forefront engagements with users like even for me when I go to a doctor I lie to them right if and if you
52:13
tell them AI what you lie to the AI is going to think this is hard truth right so on that side
52:19
how is the AI going to remove bias or lies from the user if that’s if it’s going to because
52:24
yeah well I’m gonna I’m gonna take a second I
52:30
want to explain how we’re using AI in a in a marketing or direct mail related
52:36
world and you tell me if I’m right or wrong and I love the
52:43
audience in this as well I’m almost doing a little product research here by the way so I apologize for taking this
52:51
soapbox opportunity to sort of get feedback so as you know we do digital
52:57
campaigns in conjunction with Direct Mail we’ve been doing this for five years we’ve uh tracked over a quarter
53:06
billion pieces of direct mail in all 50 states um in about a hundred different
53:11
verticals as a result of the direct mail campaigns we’ve collected digital response and
53:18
engagement when I say response and engagement on every piece of mail there’s either a phone number there’s a
53:24
website there’s a QR code there is some way to interact with that piece of mail all right
53:31
so what we’re doing is we’re using computer vision we’re taking all 50 000 pieces of direct mail these
53:39
are not piece you know 50 000 different campaigns okay uh one direct mail
53:45
campaign will send out thousands or hundreds of thousands of the same piece so we’ve done 50 000 campaigns to over a
53:52
hundred verticals over five years to a hundred and thirty million households so
53:58
I have a massive amount of of nail data creative pieces of Engagement data and
54:07
what we’re trying to do is take all of those mail pieces and using computer vision and annotation
54:15
every Everything has a phone number some have a QR code they all have websites they all have uh an image they have a
54:22
headline they have different things that can be digitized from that piece of mail
54:28
whether it’s the size of the phone number the percentage of image to text
54:33
the size of the image the the time of year it’s delivered the ZIP code it was
54:40
delivered the type of message is this a real estate advertisement financial
54:45
institution educational non-profit you know Landscaping Company a pizza company you
54:52
know so we feed this all into computer vision and we correlate that piece of creative
55:00
to the results of the campaigns and we put them back together and saying wow
55:06
we’ve noticed over years for this type of clientele or this type
55:11
of vertical we see a three percent lift in website visits or phone calls or QR code scans
55:18
when you have a picture of an elephant on the thing I don’t know well now I can
55:23
have a practical usage from big data collection that says hey if you’re doing a financial campaign and you put an
55:30
elephant in your picture you will get a two percent lift in phone calls if you
55:36
make your headline 72 Point type in red you’re going to get a one percent lift
55:43
in phone calls for education so I have access to all of this data and we’re
55:50
building dm2o.ai that will for lack of a better word monetize this
55:57
so if someone’s going to spend a hundred thousand dollars on a print mail campaign and they’re sending it to
56:04
homeowners that have homes over a certain amount and if they put a certain image or a certain phone number or a
56:10
certain thing on their postcard they can get a five percent lift and response from doing that that’s valuable
56:17
information this is information that only Big Data machine learning and AI can can
56:23
regurgitate because that data is changing as we’re doing these campaigns all the time and obviously if there’s
56:30
bad data I have to strip out the outliers on the top the outliers on the bottom and so that I’m providing good
56:37
data but to me this is a valid use of machine learning or Ai and marketing
56:43
what say you guys tell tell me where I’m wrong you know I you you’re not wrong
56:50
that’s the that’s the thing that that is most likely where everybody’s going to go with marketing they’re going to take
56:57
the same approach of analyzing everything that we’ve done in the past which everybody should be doing anyway
57:04
um but analyzing everything that they’ve done in the past looking for the hidden patterns that they were not able to see
57:09
and then applying that and using AI to generate content around that a b testing
57:16
and just iterating towards success yes yes Greg talk Tom you you’re itching to say
57:23
something about this turn off make sure you turn on your mind yes sir I’m okay great if you’re going to take a
57:30
historical approach to data analysis data driven all that far out but I guess the question becomes is how do you use
57:37
going forward with a changing demographic Society you know how do you
57:43
respond to crisis issues Silicon Valley Bank you know shootings all kinds of things like that how to use it going
57:48
forward so that we’re not we’re not we’re not just keep looking in the rear view mirror
57:53
well to me this is this is purely a marketing thing I’m not trying to solve societal issues with this I’m trying to
58:00
help my clients get a leg up on their uh advertising Roi due to the fact that I
58:09
have five years worth of proprietary Direct Mail digital marketing data you know if
58:14
a bank is going to go bad and I’m doing an advertising for a bank right I don’t
58:20
know that I’m able to be socially responsible for checking
58:25
that client’s financials and making sure they’re still in good standings with the FDIC and the SEC I’m not saying that I’m
58:33
just saying you know as an as a creative person what you’ve done in building this your company is how would you recommend
58:40
to a client that that your new tool can be used in a creative process of going forward you know because as for example
58:48
down landscapers Boulder is going to pass a law against gas powered you know leaf blowers good for society good for
58:55
noise everything else so you know how do you get a you know advise landscapers
59:00
get ahead of that curve you know get go all electric promote promote yourself as all green sure that you know as as a
59:08
marketing automation platform any problem can be solved with enough data and enough resources to bring those in
59:15
but obviously those those type of regional issues could be fed in to any
59:20
sort of marketing plan if if a guy I can’t advertise uh gas in the state of
59:28
Colorado after a certain date well you know shame on me for not knowing but
59:33
more shame on the client for getting me to pitch his campaign without knowing you know we have to draw a
59:39
responsibility Circle somewhere you know that’s right uh Siobhan did you want to
59:45
comment on anything about my use of marketing and AI we’re down to the last minute here and I want to be respectful
59:52
for everybody’s time today uh we’ll always say spot on you’re using it very well and ethically um I would say all of
59:59
this is to deliver a more personalized approach right because as Thomas was saying like if you have an AI to speak
1:00:05
to a human that’s going to be possibly the worst thing right I don’t know about anybody else but a support chatbot for
1:00:11
me not too well right so um with that being said I think if AI is able to help you aggregate some of these
1:00:17
findings with historical data and then pinpoint saying hey based on this it
1:00:22
could better lead to this because of that’ll be the perfect thing from a marketing side because one I know what
1:00:28
is being changed and two what could be impacted and then three
1:00:34
um what does that look like for the customer right so I think it is definitely the right area and the end
1:00:39
gold obviously from a marketing side is to be more personalized good hey Brad one last thing uh if uh Robert Hackett
1:00:47
asked a question we can answer it now or he can email it to me uh I saw that if
1:00:53
you want to give a quick answer and then we’re going to wrap up and and let you guys all get back to your lives but we
1:00:59
will be sending out a copy of this so go ahead make it as quick of an answer as you can oh you can okay 10 words or less
1:01:05
uh he asked a question will companies need to develop their own cyber security or for AI or these applications and
1:01:11
programs continue to enhance Security on the their own businesses so they won’t need to my view is that you know what
1:01:19
I’ve seen out there if you ask me in general is that the cyber security company Solutions I’ve seen out there are not a Panacea and you’re really on
1:01:26
your own they’re going to give you the car to drive in and if you drive it off the cliff you bad so uh we can discuss
1:01:32
it further but I hope that answers the question Robert well all right thank you very much uh
1:01:39
that was good I do want to end I want to I got put up on the screen everybody’s contact information so that you can
1:01:46
reach out to them directly I will send a copy of this webinar to everybody who
1:01:51
registered so that they can follow up on any of the data here or anything else but I want to call it quits at this
1:01:57
point thank you to my esteem panelists much appreciated I think was great discourse and some great ideas here so
1:02:05
thank you very much everyone good afternoon and uh let’s keep moving forward bye-bye definitely thank you
1:02:12
thanks Brad
