April 22, 2025 • 37 mins
Sales and marketing should work together—but too often, they don’t.
Instead of collaborating, teams operate in silos and miss opportunities hiding in plain sight.
Victor Adefuye is here to change that. In this episode, we talk about how AI is bridging the gap between sales and marketing—by turning real sales conversations into actionable marketing insights, better customer experiences, and smarter strategies.
If you’ve ever felt like your marketing was disconnected from what your audience actually cares about, this one’s for you.
In this episode of the podcast, we talk about:
- How to use AI to analyze sales calls
- Why transcripts are a goldmine for marketers
- Tools to improve messaging and conversion
- AI for personalization at scale (without losing trust)
- The future of sales prep, follow-up, and content creation
…And More!
This Episode Was Made Possible By:
Riverside All-in-One Podcast & Video Platform
Visit Riverside and use the code DREA to get 15% off any Riverside individual plan. We use it to record all our podcast interviews: https://onlinedrea.com/riverside
About the Guest:
Victor, the founder of Dana Consulting, pioneers the integration of AI with proven B2B
sales methodologies. After founding Dana Consulting in 2015, he led the firm to notable
success—training hundreds of teams and increasing close rates across startups and Fortune 500 companies. Following Dana Consulting’s acquisition by Winning by Design in 2019, Victor has returned to relaunch the company with a revolutionary focus: Superintelligent Sales, a framework that combines AI capabilities with human expertise to transform B2B sales performance.
A sought-after speaker and thought leader, Victor draws on his unique background as a
former attorney and his track record of driving measurable sales improvements to help
organizations thrive in the age of AI.
Website: https://www.dana-consulting.com/
Superintelligent Sales: https://superintelligentsales.ai
LinkedIn: https://www.linkedin.com/in/victoradefuye/
Go to the show notes for all the resources mentioned in this episode: https://onlinedrea.com/354
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to episode number 354 of the Mindful Marketing
podcast. And today, we're talking all about the relationship between
sales and marketing because they go together like peanut butter and jelly. And
today, I'm excited to have Victor Adefuye on the podcast to talk
all about it. But first, a word from our sponsor.
Riverside is the all in one podcast recording and editing tool that
(00:22):
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I love their magic AI clips. Their
little AI robot in the background pulls out the most
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(00:45):
myself, resizes them for social media. So those vertical
videos you see on TikTok and reels, those all come from magic
AI inside of Riverside. It's literally one click. It spits out
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(01:07):
e a, at checkout to get 15% off your membership.
Victor, welcome to the show. Thank you, Andrea.
Nice to see you. I should say welcome back because you are a
returning guest, and I'm excited for the conversation today because you've
been doing some really interesting things with AI
specifically. But before we get into all of that,
(01:30):
tell the listeners, what is the relationship between marketing and
sales? Well, in my experience, it's a
contentious one. You know? You would
think that there would be greater alignment between these two
areas of business that are so dependent on each other.
Right? Sales needs marketing to get them the
(01:52):
leads, to figure out the right strategy, messaging, give
them the assets they need to be successful. Marketing needs sales to
close the leads that they drive. But
all too often, there's a lot of finger pointing and
blaming and misalignment between the two teams. And,
yeah, I mean, I think I think it's, it's always, a
(02:14):
sign of, a a challenge for an organization when there's a lot
of contention between these two sides, and, unfortunately, I see
it all the time. So, yeah, definitely one of,
of friction, if you if you will. Yeah. In my
experience so I used to work for Marriott Hotels, and I was on the marketing
team. Marketing team feels, like, very, like, nerdy. We're in our
(02:36):
offices. Sales team is always, like, suits, five star
restaurants. Like, it always feels like a totally different vibe
too just from the people who work at the different departments too. Has that been
your experience as well? Yes. Definitely. I mean, you know,
there are different types of salespeople. There are different types of marketers, but
I don't think it's a coincidence that marketing as a discipline
(02:58):
is taught at business schools while sales is less
taught. Right? It's that's changing. But historically
speaking, marketing has been a foundational topic
for business. And so what that tells me is that marketing is
thought of as an intellectual enterprise, right, where it's like
strategy and what's the right message and what's the who's the
(03:20):
ICP and all of that, and how do you articulate value,
while sales is seen as execution. Right? Like, go out, meet the
people, shake their hands, you know, articulate that value
and try to get them closed. And so I think, naturally, it attracts
different types of personalities, those that are
analytical versus those that are more of, like, you know, just go out and
(03:43):
do. And, yeah, I think that is also a a root of
the conflict is that, you know, the marketers, I think,
sometimes, you know, as as a sales guy
myself, I could critique both sides, but I think oftentimes
salespeople feel that marketers are are more kind of,
like ivory tower kind of, like, theoretical when they
(04:06):
just need, like, practical how to guides for,
Yeah. A %. And I find that a lot of the people that I work
with, especially the smaller businesses or maybe, like, the
ownership of one businesses, you know, there's just one person wearing all of the
hats, tend to lean more one way or the other. But they kind of
go hand in hand. Like, you you need the marketing message to be able to,
(04:29):
you know, really execute on the sales call, and you need the
sales calls to then fuel the marketing. And one of the
interesting things that you and I were talking about was these sales calls.
So tell us what you're doing with sales calls and how that
benefits marketing. Yeah. So, I mean,
ever since the chat GPT moment of a
(04:51):
few years ago when everyone was like, wow. These large language
models are really working, and they're powerful. You
know, I've been really excited about them because to
me, you know, I I've been describing large
language models as calculators for words. Right? For the
first time, we're able to analyze words
(05:14):
and meaning at scale. And so,
you know, something that used to take, a long
time, I e, you know, even if somebody recorded
a phone call and you wanna listen to that call, you have to put
aside almost as much time as the call itself to review it.
Right? You can speed it up a little bit, but you can't speed it up
(05:35):
too much, right, because you're gonna miss some of the details. Right? And
so it's never actually been realistic
to, analyze, you know, the large
volume of text. But now with AI, it is. Right? And so
one of the first things that I started using AI
for was to analyze sales calls and, you know,
(05:57):
initially started with individual calls, right, to
help reinforce coaching and the methodology. So for
example, if, if a company uses there's a common
methodology called MEDDPIC for enterprise sales. It starts you
know, stands for a lot of different things, but metrics, economic buyer,
decision process, etcetera. And so, what if
(06:19):
you want to, you know, reinforce that methodology,
I can teach an AI chatbot what
metrics mean, economic buyer means, decision process,
etcetera, and then feed it dozens, hundreds of
pages of calls and be like, what patterns are you seeing here?
Right? And so for the individual rep, it's, you know, for this
(06:43):
deal, how well qualified is this deal? Did you get the economic
buyer? Did you talk to them about metrics? But then also
on an aggregate across the entire team, you know, over the
course of a quarter, over the course of you know, you could slice and dice
them. All the win the deals that you won versus the deals that
you lost or the the, certain, segments of your
(07:06):
market and compare them to each other. Now we can analyze those
transcripts and pull insights from them in a way that we couldn't before, and
that just opens up a world of possibilities in both sales and marketing.
Yeah. That like, I'm so obsessed with this idea because I just
naturally record all of my sales calls anyways, and I use them a
lot for my own kind of information just as you said. Going through it
(07:28):
manually, I'll listen to it or I'll pull the transcripts, and I'll be like, oh,
you know, here's something someone said that's a problem. So now I'm gonna put that
on my sales page, or I'm gonna put it in a sales email. But the
fact that you're taking this and then putting it into AI and going,
okay, collectively out of, let's say, these 10 sales calls,
what are the trends? I feel like this is one of the strongest
(07:50):
uses that you can use with all of this information that we already have.
Are you like, what tools are you using for this? I wanna be nosy. How
how are you doing this? Yeah. I mean, look. I think
so the first thing I always recommend to people
is, as much as possible, use what are
called the frontier models. Right? Like, the the ones that are the
(08:12):
cutting edge. Right? And so that's ChatGPT and their
various models. Claw is another one that I use a
lot, and they have a great model or, series of models.
Gemini from Google. You know, if you stay in those categories,
you're you're gonna get the best of modern AI.
And then specifically, though, which tool
(08:36):
depends on the amount of text that you wanna analyze. So, you
know, if I'm doing just one call or just a handful
of calls, then, you know, any of them will do chat
GPT, Gemini, or or Claude. But if you wanna do,
like, large volumes, like hundreds of pages of calls,
I lean more towards Gemini, and that's because Gemini
(08:58):
has a a large context window. So think
of the context window as, like, the bot short term
memory. You know, there's like it's trained on the history of the Internet,
but then you wanted to keep certain ideas in its mind,
and those include the transcripts or whatever else you wanna use as
part of the analysis. And so you need a context window
(09:21):
that's large enough to handle that volume of calls. And,
Gemini has, depending on which one you use, between a million
tokens to 2,000,000 tokens of a context window, which is, I
think, a few thousand pages of words. And
there's a specific tool that is built off of Gemini that's
actually free, and I love using for this use case called
(09:43):
notebook l m. And so just Google notebook l m.
One of the great things about notebook l m is that it allows you to,
I think, upload a few hundred sources, and each one
can be 50 pages or more long. And so
you can really do a lot of, you know, put a lot of,
you know, transcripts in there. And then the great thing about notebook l
(10:06):
m also is that it provides you with citations. So if you're gonna
make big strategic decisions about, oh, these are the pain
points that are coming up in this call, and so therefore, I'm going
to create marketing assets around that. You wanna make sure that,
that, you know, you're basing it off of validated information. And so,
yeah, I think, having those citations in NotebookLM is really
(10:30):
helpful. Okay. I'm glad you mentioned that because one of my next questions was
about this, like, hallucinating that AI does
sometimes where you're like, oh, this sounds like it could be real, but then you
try to go and find the information and it's it just made it up because
it's a people pleaser. And I was trying to just, here, I think this is
what you want. So I love that I literally put notebook l m in another
tab because I'm like, I'm gonna look at this later because, I do
(10:53):
think one of the challenges that we we face as this emerging
technology is being developed is that sometimes,
especially if we're feeding it hundreds of thousands of pages,
we can't verify what it's spitting back out at us. So I like that
you that you did that. Are there any other kind of
downsides to using this strategy, using AI to kind of
(11:15):
filter through and find voice of customer research,
using, largely language models? Downsides?
I think it's hard to think of what the downsides
would be. So, you know, hallucinations, yes, for sure. Right?
But they're getting better and better at this, and I would argue
(11:36):
that you'd never wanna fully substitute your judgment to the
tools. Like, they're, you know, I like to think about them as, like, an
over eager but very inexperienced intern. Right?
Very smart, but, you know, you need to check their work. You
wouldn't take an intern's paper and just hand it to a client. Right? You would
review it. You would give them feedback, right, and iterate on it
(11:58):
until it gets to a good place. And I think it's the same obligation with
AI to double check the work before it goes out, especially if you're gonna make
big strategic decisions based off of it. But
besides hallucinations, you know
yeah, I mean, I I don't know. What is the downside of having more insight
into your customers? Right? What is the downside of understanding
(12:20):
directly from their mouths how they describe your pain points, what objections
they have, what competitors they're seeing, what their buying criteria
is. To me, like, this is less about
something new that is risky and more
about, democratizing something that
already exists in the world, but now can be done at
(12:43):
scale and a lot more cheaply. You know, I'm I I'm thinking of a
client of mine, who was one of the first people that I
did this voice of the customer analysis with. They,
prior to working with me, had engaged the consulting firm that they
paid a few hundred thousand dollars. I wanna say, like,
$300,000 to do a market study for them. And so
(13:04):
they, like, went out there, did a bunch of interviews, you know,
panels, this and that, and they came up with this very
elaborate presentation that my client then shared with me. And
so when I did the voice of the customer research, I was like,
I I just uploaded the, the report from this consulting
firm and was like, what's accurate? What's inaccurate? What did they get
(13:27):
right? What didn't they get right? And there was a good amount of things that
they didn't get right. And I don't think that this is a
bad firm in any way. I think markets
change. Right? And there's a difference between, hey. Let me go and hire
somebody to do a focus group to go back in hindsight and
explain what matters to them, their buying criteria, things like that,
(13:49):
versus directly out of the mouths of this of the
prospects themselves on the sales calls. You know you know,
I I think the the real value here is, you know,
regular marketer, you know, and even in a small
company using a tool like NotebookLM, if they're recording
their calls, can get do a win loss analysis, voice of the
(14:11):
customer analysis on a dime, get the value of that
without having to pay tens of thousands, if not hundreds of thousands
for a consultant to come and do that. You know, it's that's
probably prohibitive for most small companies, but now you can do it
with, you know, notebookLM for free or for some of
these tools, like, $20 a month. You know? Yeah. I mean, I can't even
(14:33):
imagine how long that report took to put together. Like
like, it months, if not a year, to, like, build
out that report and, like, even just the shortened timeline too to be able to
get this information. One of the things you said was interesting was,
how you prompted AI to give you the
results that you want. And I think this is also a skill that
(14:56):
we have to learn as marketers, as salespeople, is, like, we the the
language models are learning us, but we're also learning them.
And so you you said something specific, which was, tell me what they got
wrong, but tell me where they also missed the mark. What are some of
the what are some of the prompts that you use to make sure that
AI language models are giving you the results that you
(15:19):
need? Yeah. I mean, I find that
the more constraints you give these models, the better results you
actually get. So they're getting a lot better at following
instructions. And so
being prescriptive and saying, a, this
is your objective. That's always required.
(15:41):
If it's important to specify the steps in
its reasoning, that is also really
helpful. Giving it the right
context. Right? Meaning, like, here's
my buyer persona document. Here is,
a PDF of my website that describes my products and services.
(16:03):
Here's a one pager. Right? Here's something that describes our
sales process. Whatever it is, that helps it give you better
responses. And then you and so in the prompt telling it,
like, you know, draw on this document for that reason. Draw
on that document for another reason. That level of specificity
helps. And then finally, I I think it's really useful to tell it
(16:26):
the format that you want the output in. You know, I I like to
think of it as, like, something that's writing me a report.
Right? And so if it's for a sales call, right, to specify,
you know, in the start with a 200 word summary of the
call. Then, you know, give me an assessment of the
prospect sentiment at the end of the call and throughout.
(16:48):
Then identify the red flags. Then give me some
coaching on how to improve, this call.
Right? You know, and what questions that I missed that I didn't ask.
And so being very thoughtful about what is the
content of the output is really important. Yeah. And,
you know, there's a lot of stuff out there about prompting and best practices.
(17:10):
I do think that guidance works. And,
yeah, again, the more constraints you put, the
better you are. You know, sometimes when I some of
these prompts, I'm using, like, you know, two, three
page long prompts, right, because it's very
detailed, and that I found gets the best
(17:32):
out of it. Yeah. I find that when I'm talking to
people about AI, especially people who are not
convinced that it's helpful, usually after pulling back the layers, it's like
they asked it two questions and they were like, oh, this is terrible. And I'm
like, woah, woah, woah. Like, we need to get more specific here and I love
that you've done, like, two to three page Yes. Prompts to get
(17:54):
what you need. Okay. So that's that's using the the sales call
itself, creating voice of customer marketing. One of the other things that we've
talked about as well is, like, what to do before the sales call. So
using some of your marketing to help before the sales call. Talk to us about
that. Yeah. To me, this is this is another game changer in the
relationship between marketing and sales. You know, in my career,
(18:16):
one of the most common, contentious points between
marketing and sales is marketing believing that sales is not
using all of the marketing materials that they've created. Right? You
know? You've created case studies. You've created, you know,
certain customer stories or one pagers
or messaging guides. Right? And
(18:39):
too often, that stuff gets in a shelf
somewhere. You know? Nobody is using it. And so
to address that issue, one of the things, like, bots that
I built for my clients are, bots that help them,
sales rep prepare for calls. And so imagine a
sales rep is about to get on a call with a particular prospect. They can
(19:01):
go to LinkedIn, download that person's LinkedIn profile, maybe
use a tool like Perplexity to do some quick research on, you
know, that businesses and, their priority. And
then, you know, upload those into a bot
that I built that helps them identify what's the most relevant
points, to hit on with the person you're about to speak to.
(19:24):
It gives them questions to ask, discovery questions to get them to
open up. And then importantly, it also recommends to
them assets and resources that may be
available that is most relevant to that persona. And
so simple use case, if I'm about to get on the
phone with the CFO, it's, you know, it's a late of late stages of a
(19:46):
sales process where, you know, I know that the CFO just
cares about the bottom line impact. Right? Not how's it gonna help, you
know, Peggy Sue would be 5% better at her job. They care about how does
that impact revenues, etcetera. And so
the talk track, the value statement has to be a little bit different.
And so what if you had a case study of
(20:09):
that was focused on a a CFO as a hero, right, that was
able to articulate the value that that CFO got? Or if
it's some sort of messaging guide that marketing has come up that says, these are
the notes to hit when you're talking to a CFO, I can then,
you know, serve that to the salesperson at the right
time right when they need it. They don't need to go searching through
(20:31):
their materials to go and find this stuff, which they don't do anyway.
Right? And so, you know, being able to give it to them at the right
time makes it much more likely that they're gonna use it, which makes it much
more likely that they'll get the benefit of all that hard work that the marketers
have put in to identify that right messaging. So, yeah, that's
another powerful use case that I that's driving a lot of,
(20:52):
you know, value with clients. Yeah. This, again, feels like
just, like, paying attention at scale because I do find that
so anytime I'm on a call and someone notices something I like,
a social media post that I posted recently or email I shared recently, I'm
always like, oh, okay. They're paying attention. And so I can imagine someone coming
into a call, trying to pitch me on whatever, and they just know
(21:15):
they're, like, hitting all the right notes. They know all the details. And if I
found out that they were using AI to do this, I would be even more
impressed. Mhmm. Because I feel like there's this, it
like you said, it's the calculator effect. I feel like there's this
almost, like, glamorization of,
like, not doing this. Or I feel like some people are like, oh, we
(21:37):
want it to be natural and instinct and, like, this person just cares that
deeply. And I also feel like there's a
power in using the tools that we have available to us to, like, make
the the best impression. I don't know. What do you think about that dichotomy of,
like, is this cheating? No. It's definitely not cheating.
First of all, I remember the for that particular
(21:59):
tool that I built, the first time I did it,
it was, to help, BDRs,
SDRs who are making cold calls to figure out what's the right
message before they reach out to the person. Right? And
so these were folks who just graduated from
college. Right? They were ramping up in their new job.
(22:20):
And in that particular case, they had a pretty complex product to sell,
and they were selling it to, like, electrical engineers. Right? And so
it was the kind of thing where if you aren't at their
level, if you don't hit the right notes with these engineers, and, like, they're
just gonna hang up on you. And so this one of the value
of that tool was to accelerate their ramp time. Right?
(22:43):
Just read the script that the bot gives you, and over time,
you'll be able to connect the dot between this persona and their pain
points and the right value articulation. But until then, this tool
is gonna get you pretty far. So I don't
think that's cheating. I think that's, like, you know, helping to
accelerate productivity and get them, you know, as productive
(23:05):
as possible. And, you know, there is this I have encountered this
idea of, like that some people have of, if they use AI,
they're not gonna learn the right skills or
it's almost feels like people who had, like, a rough childhood or
something, they're like, oh, like, everybody has to suffer because I
suffered. Yeah. But, no, we're not this isn't a game. This is
(23:28):
about revenue and productivity and helping
salespeople, be as effective as possible. And so if
you're not using these tools, your competitors are gonna be using these
tools. And I feel, you know, we're still in the early
stages of this stuff getting out there, but I in the not too distant future,
I see a world where customers are gonna expect you to
(23:50):
have deep knowledge of them, to come into meetings
with a unique point of view based on what you know about them because
it's gonna be table stakes to be able to do that level of research. And
so if you're gonna be like, you know, I'm gonna do this the whole way
and your competitor who they're also talking to is much more
thoughtful, is much more, targeted in their
(24:11):
messaging, in their approach, much more aligned with the needs of the
customer, you're just gonna lose. Right? And so,
yeah, it's to me, we're very closely
approaching a world where it will be a competitive
disadvantage to not use these tools
because your competitors are gonna use it, and they're gonna deliver a better
(24:33):
customer experience. Yeah. Yeah. I I think it's gonna be
interesting to see what shapes the next five to ten years because I think we're
at we're at an inflection point with this. And it's it's here. Like, AI is
here to stay. It's not going anywhere. It's how we all use it as the
tools that we, can to our benefits and and actually
help us grow our business with by leaps and bounds. It really does remind me
(24:55):
of when social media first started too, and people were like, oh, I don't
need this. It's, you know, it's just the kids played around online. Yes. And now
as a business, you can't imagine not having some sort of
marketing present digital marketing footprint. Right? And so,
yeah, the future is here. The future is here. Okay. So we've talked about
using AI, like, using the actual sales calls. We've talked about preparing for
(25:17):
the sales calls. What about after the sales calls? I
know you have a strategy around using AI to build, like, landing
pages and marketing content things like that. Tell us about Yeah.
So AI has a lot of different uses and
means a lot of different things at different contexts. You know, there
are presentation tools. Like, I use one
(25:40):
called gamma that can create
landing pages in an instant.
And they're now these AI coding tools that actually could create much
more sophisticated landing pages in an instant
well designed. And then content creation
(26:00):
is so much easier now, right, to be able to go and
do some research on a company and then, you know,
have, like, a piece of content that you've written before
and upload both to AI and be like, can you rewrite
this in a version that's gonna be most appealing to this particular
customer with this particular research.
(26:22):
The combination of the research, the ability to create unique
content or landing pages on demand, again, tells me
that marketers, salespeople can
build those assets into their, for example, account based lead
generation. Right? If you're going after some targeted enterprise
accounts, you're trying to close six figures, seven figure deals with
(26:43):
them, they're gonna expect you to really understand their business, and
you're gonna have to develop relationships with lots of different
stakeholders. And so if we can create a landing page,
for example, for lead generation that is tailored to
that, particular customer, why JPMorgan Chase
can save $7,000,000 by adopting this new way
(27:06):
of doing things. Right? You know? And it'll be a personalized
one. If you wanna write a a white paper that's just for
them that takes into account their research. Right? Things
that used to take weeks and a team of dedicated
writers and designers, these are things that can be
done instantaneously with AI. And
(27:28):
so, yeah, that's another really powerful use case is
creating that personalized content at scale, that personalized
buying experience at scale, and really
making the customer feel like, you know, you
are crafting something that's unique for them,
whether that's at the top of the funnel or during the sales
(27:50):
process. You know, for example, I one of the uses of
AI, that I with with clients is is
ROI analysis, like coming up with customized tools to
do an ROI analysis that, you know, basically, the
rep just has to ask a few questions, upload it, their
transcript, and then it'll do put together, like, this customized
(28:12):
report that looks beautiful. Right? That used to be a very expensive
thing for businesses to build on their own, you know, with
software, especially. But now with AI, with a lot of this AI
software development tools, you can build those customized ROI
calculators, etcetera, on a dime. And so, again,
it's what can what do these tools make possible
(28:34):
today that we can insert into our existing
processes or do things that we wish we could have done
in the past, but we're prohibited by time, by effort, by
resources. Now we can do those things on demand at
scale in a much more custom way. And sales,
marketing, we are in a world where our
(28:56):
initiatives should produce revenue. Right? We can
directly connect what we do to revenue. And so if
you have a broken process, if you're unsatisfied with your
conversion rates on this or that, I bet you personalization can help
a little bit more. And so we can measure what's the baseline
of, you know, engagement, qualified opportunities, whatever it it
(29:19):
is, then we insert these tools in, and then we measure, are they
moving the needle? And the ones that tend to move the
needles are the ones that are about how do we personalize this, how
do we engage customers in a new way that makes that
educates them. Those are the types of things that I I see really
moving the needle. So yeah. Yeah. Oh my gosh. I think this is so
(29:41):
fascinating because, for a while, especially in my space, in
the marketing spaces, this idea of scaling was
was it. Right? It's like everyone wants to do more. They wanna do bigger. But
the problem with scaling is you do lose the personalization.
Right? Like, there's some of that that gets lost along the way. But then
when we add back in AI, we can scale and we can have
(30:03):
personalization at mass Yeah. When we kind of combine these tools
together, which I find so fascinating and interesting. And
again, I'm curious to see how this plays out in the future
as as more tools get developed, as things happen. Because I
know it can happen even better. Like, I think about companies like
Amazon, for instance. They have so much information on me because I buy so much
(30:25):
stuff on there. But I feel like they could they could really take AI and
start, like, personalizing that whole experience. Like, they already
have some things like reminders to buy, but I feel like there's so much more
they could do. It'd be like, hey, Andrea. I know you're thinking about this, but
have you thought about this? Or here's another option we know you'll like. Like, I
would give them all my money. Yes. Yes. Yes. I I I don't we don't
(30:46):
I don't wanna, like, open up an all other line of, conversation here,
but, I went recently to a an event with a
company in New York that does, video.
They've they've been big in the video space. They compete with, like,
Loom, etcetera. And so, they
just launched an AI avatar solution
(31:09):
that basically a sales manager, you know, asked their
reps to shoot a ninety second video of themselves, and then it
creates this avatar that the sales manager can put
in, like, any script into the mouth of this avatar and
then send it out on triggered plays. And so in their
presentation, the one of the use cases that they use
(31:30):
was, like, confirming an appointment the morning
of. Right? And so the the manager doesn't need
to tell the sales rep, oh, every single time you have an appointment in the
morning, shoot me, like, a thirty second video where you say,
hi, Andrea. Looking forward to meeting you this afternoon.
We're gonna talk about this in the agenda. Let me know if you have any
(31:51):
questions ahead of time, but I'll see you at 04:30. Right? Something like as
simple as that, it's so hard to do at
scale, so hard to do personalized. Maybe you do a generic one that you send
to everyone, but not one that's personalized. But now it's just, like,
submit, like, you know, you substitute the name. Hi,
blank. Right? I'm looking forward to seeing you at blank, and it looks
(32:14):
like it came right from your, you know, SDR
or your salesperson, and they don't even have to think about it. It's just triggered
on meeting on the calendar with a new lead this
afternoon. This automated video goes out to them.
Like, that to me is just another example of personalization
at scale made possible by these powerful
(32:36):
tools. Yeah. The future is gonna look very different from the past.
Yeah. Okay. I do have a lot of thoughts about the AI video, though,
because I know. I know. I don't know. I that's the one where I'm like,
oh. So, like, I use Riverside to record my podcast. They have this built in
now where you because I've done so many on here, they
have all of me saying all of the things. And I can put make
(32:59):
myself say anything. And it's like 90%. I'm like, oh, that does sound kinda
like me. There's some words that are off. I don't know how I feel about
it, though. I feel like there's this trust issue too
with the AI avatar. I feel like we'd have to be very
transparent, and I feel like this is where we're still figuring it out as, like,
the humans behind the machines on how transparent can we be
(33:21):
with this process. Like, hey. This is Andrea's avatar, or this
is this is the the clone. I don't know. I Yeah.
Anyways, that is a that is a whole other question. I I I think it
depends on the use case. Right? So, like, if it's top of the funnel,
you know, prospecting at scale, if it's this kind of meeting
confirmation use case, these are low stakes kind of
(33:42):
things that, you know, even if they're not perfect,
like, you're reaching out to a lot of people, you're gonna have a really low
response rate anyway. So, you know, it's about how do we optimize that
response rate. Yeah. And I I agree with you. Like, there's
definitely more that can be done to make them feel more natural.
Maybe there's, could be more disclosure about
(34:04):
when they're being used. But, again, I come down to the practical
reality. Like, if this thing can,
make it less likely that the meeting cancels,
right, which makes it more likely that you add another
opportunity into your pipeline, right, which then closes
at your typical win rate, then it's really the question is, does this
(34:26):
thing work? Right? Can it Yeah. Actually drive these results?
And if it does, then I think we have to
seriously consider it and overcome some of these resistance.
And also keep in mind, like, these things are only gonna get better
from here on out. Right? Like, they're gonna become more realistic. And
so those those issues about, like, perfection, I think, are
(34:48):
gonna be less and less. Yeah. Well, time will tell.
Okay. So for those people who are listening, they're like, I am so curious
about using AI, especially in sales. I know you
have a blog about this called super intelligent sales. Tell
us all about it. Yeah. You know, I believe
that this AI thing is the most important thing that's ever happened in the go
(35:11):
to market function, marketing, sales, and customer success.
You know, the reality is that all of the good stuff that happens
happens in conversations with customers. And up until now, we
haven't been able to analyze those conversations at scale.
And so once you can, you can do so much with
it, a lot of the things that we've talked about. And so I really see
(35:34):
myself as being on a mission to help marketers,
salespeople, leaders to realize how to take
advantage of these tools and how to adopt them into their sales
process in a way that's effective, right, and not just, like, you know, we're
gonna roll out and go and buy the latest tool. Right? And so so that's
what I write about on my blog. So, I have a blog
(35:56):
called superintelligencesales.ai where I write about
sales. I share use cases. I share implementation
strategies. You know? I wrote a few articles related
to the topics that we share, so I'll I'll put that out there. So folks
can get in touch with me on the block. They can find me on
LinkedIn. I'm Victor Adefuye. That's a d e f
(36:17):
u y e. You know, I have a consulting practice called,
Dana Consulting. So that's
Dana-consulting.com where we help
organizations implement AI into their sales process, you know, with
proper training and coaching. And so, yeah, hit me up on
LinkedIn. Check this out at danaconsulting.com
or on a blog at superintelligencesales.ai. Perfect.
(36:41):
I'm a put all those links in the show notes. You can find them at
onlinedre.com/35four. Victor, thank you so much for being on the
show today. Thank you. This was a fun conversation. Yay.
And thank you, dear listener, for tuning in to another episode of the Mindful Marketing
Podcast. Make sure you leave us a five star rating on Apple Podcasts and
Spotify. Helps keep us in the top 100 marketing podcasts, and that's all
(37:02):
because of your support. And also, if you wanna go even deeper
into the world of marketing and AI, I've got you. Inside of the Mindful
Marketing Lab, one of the biggest benefits of being in the lab is you
get unlimited support. So if you ever have questions about AI, I've
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(37:24):
find that on the website as well. Next week, I have Natalie Bullen
coming on the podcast to talk about having a magnetic personal
brand and using social media to grow your revenue. See you
next Tuesday. That's all for today. Bye for now.
Welcome to episode number 354 of the Mindful Marketing
podcast. And today, we're talking all about the relationship between
sales and marketing because they go together like peanut butter and jelly. And
today, I'm excited to have Victor Adefuye on the podcast to talk
all about it. But first, a word from our sponsor.
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(00:22):
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e a, at checkout to get 15% off your membership.
Victor, welcome to the show. Thank you, Andrea.
Nice to see you. I should say welcome back because you are a
returning guest, and I'm excited for the conversation today because you've
been doing some really interesting things with AI
specifically. But before we get into all of that,
(01:30):
tell the listeners, what is the relationship between marketing and
sales? Well, in my experience, it's a
contentious one. You know? You would
think that there would be greater alignment between these two
areas of business that are so dependent on each other.
Right? Sales needs marketing to get them the
(01:52):
leads, to figure out the right strategy, messaging, give
them the assets they need to be successful. Marketing needs sales to
close the leads that they drive. But
all too often, there's a lot of finger pointing and
blaming and misalignment between the two teams. And,
yeah, I mean, I think I think it's, it's always, a
(02:14):
sign of, a a challenge for an organization when there's a lot
of contention between these two sides, and, unfortunately, I see
it all the time. So, yeah, definitely one of,
of friction, if you if you will. Yeah. In my
experience so I used to work for Marriott Hotels, and I was on the marketing
team. Marketing team feels, like, very, like, nerdy. We're in our
(02:36):
offices. Sales team is always, like, suits, five star
restaurants. Like, it always feels like a totally different vibe
too just from the people who work at the different departments too. Has that been
your experience as well? Yes. Definitely. I mean, you know,
there are different types of salespeople. There are different types of marketers, but
I don't think it's a coincidence that marketing as a discipline
(02:58):
is taught at business schools while sales is less
taught. Right? It's that's changing. But historically
speaking, marketing has been a foundational topic
for business. And so what that tells me is that marketing is
thought of as an intellectual enterprise, right, where it's like
strategy and what's the right message and what's the who's the
(03:20):
ICP and all of that, and how do you articulate value,
while sales is seen as execution. Right? Like, go out, meet the
people, shake their hands, you know, articulate that value
and try to get them closed. And so I think, naturally, it attracts
different types of personalities, those that are
analytical versus those that are more of, like, you know, just go out and
(03:43):
do. And, yeah, I think that is also a a root of
the conflict is that, you know, the marketers, I think,
sometimes, you know, as as a sales guy
myself, I could critique both sides, but I think oftentimes
salespeople feel that marketers are are more kind of,
like ivory tower kind of, like, theoretical when they
(04:06):
just need, like, practical how to guides for,
Yeah. A %. And I find that a lot of the people that I work
with, especially the smaller businesses or maybe, like, the
ownership of one businesses, you know, there's just one person wearing all of the
hats, tend to lean more one way or the other. But they kind of
go hand in hand. Like, you you need the marketing message to be able to,
(04:29):
you know, really execute on the sales call, and you need the
sales calls to then fuel the marketing. And one of the
interesting things that you and I were talking about was these sales calls.
So tell us what you're doing with sales calls and how that
benefits marketing. Yeah. So, I mean,
ever since the chat GPT moment of a
(04:51):
few years ago when everyone was like, wow. These large language
models are really working, and they're powerful. You
know, I've been really excited about them because to
me, you know, I I've been describing large
language models as calculators for words. Right? For the
first time, we're able to analyze words
(05:14):
and meaning at scale. And so,
you know, something that used to take, a long
time, I e, you know, even if somebody recorded
a phone call and you wanna listen to that call, you have to put
aside almost as much time as the call itself to review it.
Right? You can speed it up a little bit, but you can't speed it up
(05:35):
too much, right, because you're gonna miss some of the details. Right? And
so it's never actually been realistic
to, analyze, you know, the large
volume of text. But now with AI, it is. Right? And so
one of the first things that I started using AI
for was to analyze sales calls and, you know,
(05:57):
initially started with individual calls, right, to
help reinforce coaching and the methodology. So for
example, if, if a company uses there's a common
methodology called MEDDPIC for enterprise sales. It starts you
know, stands for a lot of different things, but metrics, economic buyer,
decision process, etcetera. And so, what if
(06:19):
you want to, you know, reinforce that methodology,
I can teach an AI chatbot what
metrics mean, economic buyer means, decision process,
etcetera, and then feed it dozens, hundreds of
pages of calls and be like, what patterns are you seeing here?
Right? And so for the individual rep, it's, you know, for this
(06:43):
deal, how well qualified is this deal? Did you get the economic
buyer? Did you talk to them about metrics? But then also
on an aggregate across the entire team, you know, over the
course of a quarter, over the course of you know, you could slice and dice
them. All the win the deals that you won versus the deals that
you lost or the the, certain, segments of your
(07:06):
market and compare them to each other. Now we can analyze those
transcripts and pull insights from them in a way that we couldn't before, and
that just opens up a world of possibilities in both sales and marketing.
Yeah. That like, I'm so obsessed with this idea because I just
naturally record all of my sales calls anyways, and I use them a
lot for my own kind of information just as you said. Going through it
(07:28):
manually, I'll listen to it or I'll pull the transcripts, and I'll be like, oh,
you know, here's something someone said that's a problem. So now I'm gonna put that
on my sales page, or I'm gonna put it in a sales email. But the
fact that you're taking this and then putting it into AI and going,
okay, collectively out of, let's say, these 10 sales calls,
what are the trends? I feel like this is one of the strongest
(07:50):
uses that you can use with all of this information that we already have.
Are you like, what tools are you using for this? I wanna be nosy. How
how are you doing this? Yeah. I mean, look. I think
so the first thing I always recommend to people
is, as much as possible, use what are
called the frontier models. Right? Like, the the ones that are the
(08:12):
cutting edge. Right? And so that's ChatGPT and their
various models. Claw is another one that I use a
lot, and they have a great model or, series of models.
Gemini from Google. You know, if you stay in those categories,
you're you're gonna get the best of modern AI.
And then specifically, though, which tool
(08:36):
depends on the amount of text that you wanna analyze. So, you
know, if I'm doing just one call or just a handful
of calls, then, you know, any of them will do chat
GPT, Gemini, or or Claude. But if you wanna do,
like, large volumes, like hundreds of pages of calls,
I lean more towards Gemini, and that's because Gemini
(08:58):
has a a large context window. So think
of the context window as, like, the bot short term
memory. You know, there's like it's trained on the history of the Internet,
but then you wanted to keep certain ideas in its mind,
and those include the transcripts or whatever else you wanna use as
part of the analysis. And so you need a context window
(09:21):
that's large enough to handle that volume of calls. And,
Gemini has, depending on which one you use, between a million
tokens to 2,000,000 tokens of a context window, which is, I
think, a few thousand pages of words. And
there's a specific tool that is built off of Gemini that's
actually free, and I love using for this use case called
(09:43):
notebook l m. And so just Google notebook l m.
One of the great things about notebook l m is that it allows you to,
I think, upload a few hundred sources, and each one
can be 50 pages or more long. And so
you can really do a lot of, you know, put a lot of,
you know, transcripts in there. And then the great thing about notebook l
(10:06):
m also is that it provides you with citations. So if you're gonna
make big strategic decisions about, oh, these are the pain
points that are coming up in this call, and so therefore, I'm going
to create marketing assets around that. You wanna make sure that,
that, you know, you're basing it off of validated information. And so,
yeah, I think, having those citations in NotebookLM is really
(10:30):
helpful. Okay. I'm glad you mentioned that because one of my next questions was
about this, like, hallucinating that AI does
sometimes where you're like, oh, this sounds like it could be real, but then you
try to go and find the information and it's it just made it up because
it's a people pleaser. And I was trying to just, here, I think this is
what you want. So I love that I literally put notebook l m in another
tab because I'm like, I'm gonna look at this later because, I do
(10:53):
think one of the challenges that we we face as this emerging
technology is being developed is that sometimes,
especially if we're feeding it hundreds of thousands of pages,
we can't verify what it's spitting back out at us. So I like that
you that you did that. Are there any other kind of
downsides to using this strategy, using AI to kind of
(11:15):
filter through and find voice of customer research,
using, largely language models? Downsides?
I think it's hard to think of what the downsides
would be. So, you know, hallucinations, yes, for sure. Right?
But they're getting better and better at this, and I would argue
(11:36):
that you'd never wanna fully substitute your judgment to the
tools. Like, they're, you know, I like to think about them as, like, an
over eager but very inexperienced intern. Right?
Very smart, but, you know, you need to check their work. You
wouldn't take an intern's paper and just hand it to a client. Right? You would
review it. You would give them feedback, right, and iterate on it
(11:58):
until it gets to a good place. And I think it's the same obligation with
AI to double check the work before it goes out, especially if you're gonna make
big strategic decisions based off of it. But
besides hallucinations, you know
yeah, I mean, I I don't know. What is the downside of having more insight
into your customers? Right? What is the downside of understanding
(12:20):
directly from their mouths how they describe your pain points, what objections
they have, what competitors they're seeing, what their buying criteria
is. To me, like, this is less about
something new that is risky and more
about, democratizing something that
already exists in the world, but now can be done at
(12:43):
scale and a lot more cheaply. You know, I'm I I'm thinking of a
client of mine, who was one of the first people that I
did this voice of the customer analysis with. They,
prior to working with me, had engaged the consulting firm that they
paid a few hundred thousand dollars. I wanna say, like,
$300,000 to do a market study for them. And so
(13:04):
they, like, went out there, did a bunch of interviews, you know,
panels, this and that, and they came up with this very
elaborate presentation that my client then shared with me. And
so when I did the voice of the customer research, I was like,
I I just uploaded the, the report from this consulting
firm and was like, what's accurate? What's inaccurate? What did they get
(13:27):
right? What didn't they get right? And there was a good amount of things that
they didn't get right. And I don't think that this is a
bad firm in any way. I think markets
change. Right? And there's a difference between, hey. Let me go and hire
somebody to do a focus group to go back in hindsight and
explain what matters to them, their buying criteria, things like that,
(13:49):
versus directly out of the mouths of this of the
prospects themselves on the sales calls. You know you know,
I I think the the real value here is, you know,
regular marketer, you know, and even in a small
company using a tool like NotebookLM, if they're recording
their calls, can get do a win loss analysis, voice of the
(14:11):
customer analysis on a dime, get the value of that
without having to pay tens of thousands, if not hundreds of thousands
for a consultant to come and do that. You know, it's that's
probably prohibitive for most small companies, but now you can do it
with, you know, notebookLM for free or for some of
these tools, like, $20 a month. You know? Yeah. I mean, I can't even
(14:33):
imagine how long that report took to put together. Like
like, it months, if not a year, to, like, build
out that report and, like, even just the shortened timeline too to be able to
get this information. One of the things you said was interesting was,
how you prompted AI to give you the
results that you want. And I think this is also a skill that
(14:56):
we have to learn as marketers, as salespeople, is, like, we the the
language models are learning us, but we're also learning them.
And so you you said something specific, which was, tell me what they got
wrong, but tell me where they also missed the mark. What are some of
the what are some of the prompts that you use to make sure that
AI language models are giving you the results that you
(15:19):
need? Yeah. I mean, I find that
the more constraints you give these models, the better results you
actually get. So they're getting a lot better at following
instructions. And so
being prescriptive and saying, a, this
is your objective. That's always required.
(15:41):
If it's important to specify the steps in
its reasoning, that is also really
helpful. Giving it the right
context. Right? Meaning, like, here's
my buyer persona document. Here is,
a PDF of my website that describes my products and services.
(16:03):
Here's a one pager. Right? Here's something that describes our
sales process. Whatever it is, that helps it give you better
responses. And then you and so in the prompt telling it,
like, you know, draw on this document for that reason. Draw
on that document for another reason. That level of specificity
helps. And then finally, I I think it's really useful to tell it
(16:26):
the format that you want the output in. You know, I I like to
think of it as, like, something that's writing me a report.
Right? And so if it's for a sales call, right, to specify,
you know, in the start with a 200 word summary of the
call. Then, you know, give me an assessment of the
prospect sentiment at the end of the call and throughout.
(16:48):
Then identify the red flags. Then give me some
coaching on how to improve, this call.
Right? You know, and what questions that I missed that I didn't ask.
And so being very thoughtful about what is the
content of the output is really important. Yeah. And,
you know, there's a lot of stuff out there about prompting and best practices.
(17:10):
I do think that guidance works. And,
yeah, again, the more constraints you put, the
better you are. You know, sometimes when I some of
these prompts, I'm using, like, you know, two, three
page long prompts, right, because it's very
detailed, and that I found gets the best
(17:32):
out of it. Yeah. I find that when I'm talking to
people about AI, especially people who are not
convinced that it's helpful, usually after pulling back the layers, it's like
they asked it two questions and they were like, oh, this is terrible. And I'm
like, woah, woah, woah. Like, we need to get more specific here and I love
that you've done, like, two to three page Yes. Prompts to get
(17:54):
what you need. Okay. So that's that's using the the sales call
itself, creating voice of customer marketing. One of the other things that we've
talked about as well is, like, what to do before the sales call. So
using some of your marketing to help before the sales call. Talk to us about
that. Yeah. To me, this is this is another game changer in the
relationship between marketing and sales. You know, in my career,
(18:16):
one of the most common, contentious points between
marketing and sales is marketing believing that sales is not
using all of the marketing materials that they've created. Right? You
know? You've created case studies. You've created, you know,
certain customer stories or one pagers
or messaging guides. Right? And
(18:39):
too often, that stuff gets in a shelf
somewhere. You know? Nobody is using it. And so
to address that issue, one of the things, like, bots that
I built for my clients are, bots that help them,
sales rep prepare for calls. And so imagine a
sales rep is about to get on a call with a particular prospect. They can
(19:01):
go to LinkedIn, download that person's LinkedIn profile, maybe
use a tool like Perplexity to do some quick research on, you
know, that businesses and, their priority. And
then, you know, upload those into a bot
that I built that helps them identify what's the most relevant
points, to hit on with the person you're about to speak to.
(19:24):
It gives them questions to ask, discovery questions to get them to
open up. And then importantly, it also recommends to
them assets and resources that may be
available that is most relevant to that persona. And
so simple use case, if I'm about to get on the
phone with the CFO, it's, you know, it's a late of late stages of a
(19:46):
sales process where, you know, I know that the CFO just
cares about the bottom line impact. Right? Not how's it gonna help, you
know, Peggy Sue would be 5% better at her job. They care about how does
that impact revenues, etcetera. And so
the talk track, the value statement has to be a little bit different.
And so what if you had a case study of
(20:09):
that was focused on a a CFO as a hero, right, that was
able to articulate the value that that CFO got? Or if
it's some sort of messaging guide that marketing has come up that says, these are
the notes to hit when you're talking to a CFO, I can then,
you know, serve that to the salesperson at the right
time right when they need it. They don't need to go searching through
(20:31):
their materials to go and find this stuff, which they don't do anyway.
Right? And so, you know, being able to give it to them at the right
time makes it much more likely that they're gonna use it, which makes it much
more likely that they'll get the benefit of all that hard work that the marketers
have put in to identify that right messaging. So, yeah, that's
another powerful use case that I that's driving a lot of,
(20:52):
you know, value with clients. Yeah. This, again, feels like
just, like, paying attention at scale because I do find that
so anytime I'm on a call and someone notices something I like,
a social media post that I posted recently or email I shared recently, I'm
always like, oh, okay. They're paying attention. And so I can imagine someone coming
into a call, trying to pitch me on whatever, and they just know
(21:15):
they're, like, hitting all the right notes. They know all the details. And if I
found out that they were using AI to do this, I would be even more
impressed. Mhmm. Because I feel like there's this, it
like you said, it's the calculator effect. I feel like there's this
almost, like, glamorization of,
like, not doing this. Or I feel like some people are like, oh, we
(21:37):
want it to be natural and instinct and, like, this person just cares that
deeply. And I also feel like there's a
power in using the tools that we have available to us to, like, make
the the best impression. I don't know. What do you think about that dichotomy of,
like, is this cheating? No. It's definitely not cheating.
First of all, I remember the for that particular
(21:59):
tool that I built, the first time I did it,
it was, to help, BDRs,
SDRs who are making cold calls to figure out what's the right
message before they reach out to the person. Right? And
so these were folks who just graduated from
college. Right? They were ramping up in their new job.
(22:20):
And in that particular case, they had a pretty complex product to sell,
and they were selling it to, like, electrical engineers. Right? And so
it was the kind of thing where if you aren't at their
level, if you don't hit the right notes with these engineers, and, like, they're
just gonna hang up on you. And so this one of the value
of that tool was to accelerate their ramp time. Right?
(22:43):
Just read the script that the bot gives you, and over time,
you'll be able to connect the dot between this persona and their pain
points and the right value articulation. But until then, this tool
is gonna get you pretty far. So I don't
think that's cheating. I think that's, like, you know, helping to
accelerate productivity and get them, you know, as productive
(23:05):
as possible. And, you know, there is this I have encountered this
idea of, like that some people have of, if they use AI,
they're not gonna learn the right skills or
it's almost feels like people who had, like, a rough childhood or
something, they're like, oh, like, everybody has to suffer because I
suffered. Yeah. But, no, we're not this isn't a game. This is
(23:28):
about revenue and productivity and helping
salespeople, be as effective as possible. And so if
you're not using these tools, your competitors are gonna be using these
tools. And I feel, you know, we're still in the early
stages of this stuff getting out there, but I in the not too distant future,
I see a world where customers are gonna expect you to
(23:50):
have deep knowledge of them, to come into meetings
with a unique point of view based on what you know about them because
it's gonna be table stakes to be able to do that level of research. And
so if you're gonna be like, you know, I'm gonna do this the whole way
and your competitor who they're also talking to is much more
thoughtful, is much more, targeted in their
(24:11):
messaging, in their approach, much more aligned with the needs of the
customer, you're just gonna lose. Right? And so,
yeah, it's to me, we're very closely
approaching a world where it will be a competitive
disadvantage to not use these tools
because your competitors are gonna use it, and they're gonna deliver a better
(24:33):
customer experience. Yeah. Yeah. I I think it's gonna be
interesting to see what shapes the next five to ten years because I think we're
at we're at an inflection point with this. And it's it's here. Like, AI is
here to stay. It's not going anywhere. It's how we all use it as the
tools that we, can to our benefits and and actually
help us grow our business with by leaps and bounds. It really does remind me
(24:55):
of when social media first started too, and people were like, oh, I don't
need this. It's, you know, it's just the kids played around online. Yes. And now
as a business, you can't imagine not having some sort of
marketing present digital marketing footprint. Right? And so,
yeah, the future is here. The future is here. Okay. So we've talked about
using AI, like, using the actual sales calls. We've talked about preparing for
(25:17):
the sales calls. What about after the sales calls? I
know you have a strategy around using AI to build, like, landing
pages and marketing content things like that. Tell us about Yeah.
So AI has a lot of different uses and
means a lot of different things at different contexts. You know, there
are presentation tools. Like, I use one
(25:40):
called gamma that can create
landing pages in an instant.
And they're now these AI coding tools that actually could create much
more sophisticated landing pages in an instant
well designed. And then content creation
(26:00):
is so much easier now, right, to be able to go and
do some research on a company and then, you know,
have, like, a piece of content that you've written before
and upload both to AI and be like, can you rewrite
this in a version that's gonna be most appealing to this particular
customer with this particular research.
(26:22):
The combination of the research, the ability to create unique
content or landing pages on demand, again, tells me
that marketers, salespeople can
build those assets into their, for example, account based lead
generation. Right? If you're going after some targeted enterprise
accounts, you're trying to close six figures, seven figure deals with
(26:43):
them, they're gonna expect you to really understand their business, and
you're gonna have to develop relationships with lots of different
stakeholders. And so if we can create a landing page,
for example, for lead generation that is tailored to
that, particular customer, why JPMorgan Chase
can save $7,000,000 by adopting this new way
(27:06):
of doing things. Right? You know? And it'll be a personalized
one. If you wanna write a a white paper that's just for
them that takes into account their research. Right? Things
that used to take weeks and a team of dedicated
writers and designers, these are things that can be
done instantaneously with AI. And
(27:28):
so, yeah, that's another really powerful use case is
creating that personalized content at scale, that personalized
buying experience at scale, and really
making the customer feel like, you know, you
are crafting something that's unique for them,
whether that's at the top of the funnel or during the sales
(27:50):
process. You know, for example, I one of the uses of
AI, that I with with clients is is
ROI analysis, like coming up with customized tools to
do an ROI analysis that, you know, basically, the
rep just has to ask a few questions, upload it, their
transcript, and then it'll do put together, like, this customized
(28:12):
report that looks beautiful. Right? That used to be a very expensive
thing for businesses to build on their own, you know, with
software, especially. But now with AI, with a lot of this AI
software development tools, you can build those customized ROI
calculators, etcetera, on a dime. And so, again,
it's what can what do these tools make possible
(28:34):
today that we can insert into our existing
processes or do things that we wish we could have done
in the past, but we're prohibited by time, by effort, by
resources. Now we can do those things on demand at
scale in a much more custom way. And sales,
marketing, we are in a world where our
(28:56):
initiatives should produce revenue. Right? We can
directly connect what we do to revenue. And so if
you have a broken process, if you're unsatisfied with your
conversion rates on this or that, I bet you personalization can help
a little bit more. And so we can measure what's the baseline
of, you know, engagement, qualified opportunities, whatever it it
(29:19):
is, then we insert these tools in, and then we measure, are they
moving the needle? And the ones that tend to move the
needles are the ones that are about how do we personalize this, how
do we engage customers in a new way that makes that
educates them. Those are the types of things that I I see really
moving the needle. So yeah. Yeah. Oh my gosh. I think this is so
(29:41):
fascinating because, for a while, especially in my space, in
the marketing spaces, this idea of scaling was
was it. Right? It's like everyone wants to do more. They wanna do bigger. But
the problem with scaling is you do lose the personalization.
Right? Like, there's some of that that gets lost along the way. But then
when we add back in AI, we can scale and we can have
(30:03):
personalization at mass Yeah. When we kind of combine these tools
together, which I find so fascinating and interesting. And
again, I'm curious to see how this plays out in the future
as as more tools get developed, as things happen. Because I
know it can happen even better. Like, I think about companies like
Amazon, for instance. They have so much information on me because I buy so much
(30:25):
stuff on there. But I feel like they could they could really take AI and
start, like, personalizing that whole experience. Like, they already
have some things like reminders to buy, but I feel like there's so much more
they could do. It'd be like, hey, Andrea. I know you're thinking about this, but
have you thought about this? Or here's another option we know you'll like. Like, I
would give them all my money. Yes. Yes. Yes. I I I don't we don't
(30:46):
I don't wanna, like, open up an all other line of, conversation here,
but, I went recently to a an event with a
company in New York that does, video.
They've they've been big in the video space. They compete with, like,
Loom, etcetera. And so, they
just launched an AI avatar solution
(31:09):
that basically a sales manager, you know, asked their
reps to shoot a ninety second video of themselves, and then it
creates this avatar that the sales manager can put
in, like, any script into the mouth of this avatar and
then send it out on triggered plays. And so in their
presentation, the one of the use cases that they use
(31:30):
was, like, confirming an appointment the morning
of. Right? And so the the manager doesn't need
to tell the sales rep, oh, every single time you have an appointment in the
morning, shoot me, like, a thirty second video where you say,
hi, Andrea. Looking forward to meeting you this afternoon.
We're gonna talk about this in the agenda. Let me know if you have any
(31:51):
questions ahead of time, but I'll see you at 04:30. Right? Something like as
simple as that, it's so hard to do at
scale, so hard to do personalized. Maybe you do a generic one that you send
to everyone, but not one that's personalized. But now it's just, like,
submit, like, you know, you substitute the name. Hi,
blank. Right? I'm looking forward to seeing you at blank, and it looks
(32:14):
like it came right from your, you know, SDR
or your salesperson, and they don't even have to think about it. It's just triggered
on meeting on the calendar with a new lead this
afternoon. This automated video goes out to them.
Like, that to me is just another example of personalization
at scale made possible by these powerful
(32:36):
tools. Yeah. The future is gonna look very different from the past.
Yeah. Okay. I do have a lot of thoughts about the AI video, though,
because I know. I know. I don't know. I that's the one where I'm like,
oh. So, like, I use Riverside to record my podcast. They have this built in
now where you because I've done so many on here, they
have all of me saying all of the things. And I can put make
(32:59):
myself say anything. And it's like 90%. I'm like, oh, that does sound kinda
like me. There's some words that are off. I don't know how I feel about
it, though. I feel like there's this trust issue too
with the AI avatar. I feel like we'd have to be very
transparent, and I feel like this is where we're still figuring it out as, like,
the humans behind the machines on how transparent can we be
(33:21):
with this process. Like, hey. This is Andrea's avatar, or this
is this is the the clone. I don't know. I Yeah.
Anyways, that is a that is a whole other question. I I I think it
depends on the use case. Right? So, like, if it's top of the funnel,
you know, prospecting at scale, if it's this kind of meeting
confirmation use case, these are low stakes kind of
(33:42):
things that, you know, even if they're not perfect,
like, you're reaching out to a lot of people, you're gonna have a really low
response rate anyway. So, you know, it's about how do we optimize that
response rate. Yeah. And I I agree with you. Like, there's
definitely more that can be done to make them feel more natural.
Maybe there's, could be more disclosure about
(34:04):
when they're being used. But, again, I come down to the practical
reality. Like, if this thing can,
make it less likely that the meeting cancels,
right, which makes it more likely that you add another
opportunity into your pipeline, right, which then closes
at your typical win rate, then it's really the question is, does this
(34:26):
thing work? Right? Can it Yeah. Actually drive these results?
And if it does, then I think we have to
seriously consider it and overcome some of these resistance.
And also keep in mind, like, these things are only gonna get better
from here on out. Right? Like, they're gonna become more realistic. And
so those those issues about, like, perfection, I think, are
(34:48):
gonna be less and less. Yeah. Well, time will tell.
Okay. So for those people who are listening, they're like, I am so curious
about using AI, especially in sales. I know you
have a blog about this called super intelligent sales. Tell
us all about it. Yeah. You know, I believe
that this AI thing is the most important thing that's ever happened in the go
(35:11):
to market function, marketing, sales, and customer success.
You know, the reality is that all of the good stuff that happens
happens in conversations with customers. And up until now, we
haven't been able to analyze those conversations at scale.
And so once you can, you can do so much with
it, a lot of the things that we've talked about. And so I really see
(35:34):
myself as being on a mission to help marketers,
salespeople, leaders to realize how to take
advantage of these tools and how to adopt them into their sales
process in a way that's effective, right, and not just, like, you know, we're
gonna roll out and go and buy the latest tool. Right? And so so that's
what I write about on my blog. So, I have a blog
(35:56):
called superintelligencesales.ai where I write about
sales. I share use cases. I share implementation
strategies. You know? I wrote a few articles related
to the topics that we share, so I'll I'll put that out there. So folks
can get in touch with me on the block. They can find me on
LinkedIn. I'm Victor Adefuye. That's a d e f
(36:17):
u y e. You know, I have a consulting practice called,
Dana Consulting. So that's
Dana-consulting.com where we help
organizations implement AI into their sales process, you know, with
proper training and coaching. And so, yeah, hit me up on
LinkedIn. Check this out at danaconsulting.com
or on a blog at superintelligencesales.ai. Perfect.
(36:41):
I'm a put all those links in the show notes. You can find them at
onlinedre.com/35four. Victor, thank you so much for being on the
show today. Thank you. This was a fun conversation. Yay.
And thank you, dear listener, for tuning in to another episode of the Mindful Marketing
Podcast. Make sure you leave us a five star rating on Apple Podcasts and
Spotify. Helps keep us in the top 100 marketing podcasts, and that's all
(37:02):
because of your support. And also, if you wanna go even deeper
into the world of marketing and AI, I've got you. Inside of the Mindful
Marketing Lab, one of the biggest benefits of being in the lab is you
get unlimited support. So if you ever have questions about AI, I've
got a whole course on it. But also, if you wanna ask, there's no shame
in asking. I'm here to support you. So come on into the lab. You can
(37:24):
find that on the website as well. Next week, I have Natalie Bullen
coming on the podcast to talk about having a magnetic personal
brand and using social media to grow your revenue. See you
next Tuesday. That's all for today. Bye for now.
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