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How Real Estate Coaches Turn CRM Data Into a Second Income Stream w/ Maeve Ferguson · Real Estate Investing with RealDealCrew

• 0:00
  With the development of AI, the knowledge economy has completely collapsed.
• 0:05
  Every framework,
• 0:06
  Every course, every ounce of expert IP has already been scraped by AI.
• 0:12
  So charging for knowledge alone doesn't work anymore.
• 0:15
  But there's one asset AI companies and financial institutions are paying fortunes for.
• 0:21
  And most real estate coaches, operators, and investor communities are sitting on it right now without knowing it.
• 0:28
  It's their CRM.
• 0:29
  In this episode, Maeve Ferguson breaks down how she turns a dead lead into a diagnostic engine.
• 0:36
  One that builds a second income stream, creates a data moat competitors can't copy, and hands you the actual behavioral data behind who buys and why.
• 0:49
  If you want to see how this applies to your business, head over to RealDealCrew.com.
• 0:55
  Let's get started.
• 1:01
  Maeve Ferguson joins me here today and you can learn what she can help you with by going to MaeveFergusonConsulting.com.
• 1:09
  I'm going to have that as a clickable link in the show notes.
• 1:12
  Maeve, this is going to be a kind of a unique conversation for my audience, but a really important one.
• 1:17
  So I'm going to kind of do something out of the ordinary and kind of give people kind of a level set here.
• 1:22
  So Maeve helps establish experts, turn their frameworks into diagnostic infrastructure that not only converts clients,
• 1:31
  but also creates proprietary data assets that can outlast the founder.
• 1:36
  Am I correct so far?
• 1:38
  is 100 % yep so DIADA is the real asset.
• 1:42
  So today we're exploring what that means for real estate brands, investor communities, educators and operators who want to build enterprise value instead of just more content.
• 1:52
  And I think that is the key thing there is the content thing because a lot of the people that listen to this show may have, they're almost apprehensive to have to get into some of
• 2:05
  this space.
• 2:07
  So really appreciate your time here today.
• 2:09
  Yeah, it's brilliant.
• 2:10
  Can't wait to dive into it.
• 2:12
  And yeah, it's just a different angle.
• 2:15
  So let's start things off at kind of a level set or high level for people.
• 2:22
  I just read off what sounds fairly complicated.
• 2:25
  Could you simplify what I just rattled off there?
• 2:28
  Yes, absolutely.
• 2:30
  in every single market, whether it's real estate or e-commerce or whatever it may be, we have people selling things and we people buying things.
• 2:38
  When we have that type of environment, we're always going to have to have lead generation systems.
• 2:43
  We always have to have a way to understand our market and what is going on inside of our market so that we can sell.
• 2:49
  And when we think about like normal, what people call funnels, which bring in leads into businesses and qualify leads and segment and all of that kind of good stuff.
• 3:00
  Those worked really well pre-AI.
• 3:03
  And I call it the great IP to P.
• 3:05
  transition where experts and their frameworks that you mentioned those are now completely commoditized they have no value anymore in their current format because every piece of
• 3:18
  publicly available information has already been scraped by AI it's already plugged into all of the models and what ends up happening is that experts and their frameworks now have
• 3:29
  where they used to be able to monetize this they used to be able to charge high-tech
• 3:33
  it just for their knowledge that is no longer the case.
• 3:37
  so what has happened is then everybody kind of ran to AI, so what I call the AI savior trap, they have jumped in and started pouring their IP into whistles and whatnots and then
• 3:48
  kind of flogging that for pennies on the dollar inside of you know custom GPT's or whatever they may be and now once again all of the knowledge industry has been
• 4:00
  commoditized.
• 4:00
  it is the value of that industry has been completely wiped to the floor.
• 4:05
  And then what has happened is that we also have this data demand curve where the AI companies, financial institutions are hungry and insatiable for proprietary first party
• 4:18
  data because they already have all of the publicly available data.
• 4:23
  But what they don't have is that proprietary first party data on the back end, the behaviors.
• 4:28
  and this is where we can kind of really think through the angle from the real estate perspective.
• 4:33
  They don't have the psychographic behavioral data, performance data, what's converting, what's not, who's buying, who's not and all of that kind of thing.
• 4:41
  And when we have this asset or this piece of infrastructure that we'll talk about today that allows you to gather all of that data, it creates a really highly monetizable asset
• 4:54
  inside of your company.
• 4:55
  income stream for sure but it also not only that it is also giving you so much data and insight into what's going on in the market and again with agentic AI and all of these
• 5:06
  things that we build inside of our company we can start to analyze trends and behaviors spot patterns all of those things and actually use the data to make better decisions
• 5:16
  better investment decisions going forward.
• 5:18
  So you kind of hit something kind of close to home on a couple things.
• 5:21
  I know and I've talked to a number of real estate coaches.
• 5:25
  And one of the things I've even seen a couple of them pivot hard because of the situation when it comes to commoditizing what they were teaching to the point where some have even
• 5:37
  stopped doing the in person training, they moved everything to a school community, a fraction of what they were charging before.
• 5:44
  But what I think you're bringing up is, is a bunch of assets that they are likely sitting on, you know, in one case, I know for a fact that they they pretty much abandoned their
• 5:58
  entire database of people and information.
• 6:02
  They had it all in a CRM Because now they kind of pivoted and now they're addressing a different market But what you're saying is that there's there's information to be mined
• 6:13
  out of there that could be potential gold mine
• 6:17
  Yeah, they're 100 % so your CRM is a source of gold, this is like a two tiered conversation, okay?
• 6:24
  So when we think about, let's pretend you have 100,000 leads in your list or 1,000 or whatever somebody's number may be, just have your own number in your head.
• 6:33
  What most experts are doing, what most business owners are doing is they are capturing a name, an email address, and maybe at a push of phone number and pushing some awful PDF
• 6:44
  thing out into the world that nobody reads, nobody understands.
• 6:47
  understands nobody opens or takes action on it.
• 6:49
  Okay.
• 6:50
  And that is basically what most.
• 6:52
  Yeah.
• 6:53
  I'd be just to get leads onto your list.
• 6:54
  have no qualitative data.
• 6:56
  They have no qualifying data in there on each of these prospects.
• 7:00
  And this is where the beauty of diagnostic assessments come in.
• 7:03
  Because if we look at some of our clients where there are thousands and thousands and thousands of leads going through the diagnostics that we build for them, not only do we
• 7:12
  have their, you know, their baseline,
• 7:14
  data like the basic stuff like gender, location, all of that kind of thing, name, email address, phone number.
• 7:21
  We also have hundreds of data points because of how they answered every question in the diagnostic, the behaviors, the patterns of how they answered the diagnostic.
• 7:32
  And also we build these routing engines into these diagnostic assessments that put the right message and the right offer in front of the right person at the right time.
• 7:41
  We also have all of those data points as to
• 7:44
  Who bought what?
• 7:46
  Did they buy your 150k thing or your 10k thing or your 2k thing?
• 7:51
  Did they buy nothing at all?
• 7:52
  How many days did it take them to purchase the first thing?
• 7:54
  How many days did it take them to ascend into the next thing?
• 7:57
  And what ends up happening is we're building these huge profiles against every single lead in the business.
• 8:05
  Now, a couple of years ago, I used to always, I'm writing a book on data.
• 8:09
  I've been well down this rabbit hole for a long time, you know, based on my background and things like that.
• 8:14
  But I was always coming at it from the angle of optimization of marketing and sales.
• 8:19
  So we build the diagnostic assessments.
• 8:21
  We analyze all of the data going through it.
• 8:25
  And then what we do in this advent of AI, we have an agentic AI division of our company where we build these AI agents that analyze all of those patterns of behavior and then
• 8:34
  feed it back up into the marketing department.
• 8:37
  So here's what Facebook ads are working.
• 8:39
  Here's which copywriter against the Facebook ads are having the
• 8:42
  through us.
• 8:42
  Here's the creative that is having the greatest through us, etc, etc.
• 8:45
  Okay, the whole way through from top of funnel, everything is tracked, monitored and reported upon, then analyzed and then fed back to the marketing team to do more and more
• 8:55
  of what's working and less and less of what's not.
• 8:57
  But that was actually this is what we've been doing for years, but it was actually really, really small thinking because it was just focusing on the marketing and the sales aspect
• 9:06
  of this.
• 9:06
  Whereas actually, if you look at what I call the data play from
• 9:10
  much broader scope.
• 9:12
  have hundreds and hundreds and hundreds of behavioral psychographic data on every single lead going through these things.
• 9:21
  and all of that performance data.
• 9:23
  Now, this is not Zillow where we're like flogging names and email addresses.
• 9:27
  OK, this is not that.
• 9:29
  When we package up, when we monetize the data, it's all anonymized.
• 9:33
  We are cross-referencing it with other data sources to enrich it, etc, etc.
• 9:38
  So it is
• 9:40
  you this asset inside of people CRMs they have it has a value for sure now but it is way way less than what it could be if they have a diagnostic assessment in place because
• 9:52
  there's so many data points against each lead it becomes a highly highly valuable asset that these AI companies the financial institutions are paying fortunes of money to get
• 10:02
  their hands on okay and then I often the next thing I always get from people is
• 10:07
  gosh, okay, well it's too late for me.
• 10:09
  I have a hundred thousand people on my list and I didn't have a diagnostic so all I have is names and email addresses.
• 10:15
  That doesn't matter because the way we build this is we actually bring it back to your existing list, back to your existing audience and siphon that entire audience through the
• 10:25
  new diagnostic.
• 10:26
  So it's like a brand new wave of people who have been given an insane amount of value through their customized follow-up report and the insights that they get.
• 10:35
  about themselves as they go through the diagnostic.
• 10:37
  But now this list of 100,000 people or 1,000 people, we actually drive them back through and now we've got that layered data point on every single lead, every single behaviour,
• 10:49
  the breakdown, gender, location, all the different, kind of the normal pieces of data that you really, really want.
• 10:55
  So you mentioned that the commoditize of the knowledge and stuff is just prevalent right now.
• 11:03
  But what I think is really interesting here is that some, and you kind of alluded to this, is that what you're talking about was typically reserved for the really big dogs, the
• 11:15
  really big players.
• 11:16
  This level of detail and assessment and data capturing.
• 11:22
  But with the use of expertise such as yourself and AI, this is really bringing some of these tools that were elusive to most of us down to our level.
• 11:33
  Yeah, exactly.
• 11:34
  And I think this is something I actually wrote about this in Substack last week.
• 11:38
  So something that's really interesting is that we have always built...
• 11:42
  or quiz funnels or assessments or multi-dimensional diagnostics, whatever we want to call them, we've always built them in SAS products.
• 11:49
  Okay, so we use an amazing platform called ScoreApp for many, many, of our diagnostic builds over the years.
• 11:55
  And what has actually happened now with AI, so that is amazing.
• 11:59
  You still get all the same data points, but what we always found was that where a thought leader or an expert had a really sophisticated IP that we, so say for example, one of our
• 12:10
  clients
• 12:10
  is a Harvard professor and number one New York Times bestselling author.
• 12:14
  Okay, so like the absolute creme de la creme of the world.
• 12:17
  The SAS product didn't actually allow easily for that IP to go into their diagnostic.
• 12:25
  So then what we have to do is like in the old days, like the bandages and stickers and workarounds and know, tack like bolt-ons to try to fit square pegs into round holes
• 12:36
  because we were confined
• 12:38
  to use in the SAS products and the custom diagnostics to your point where you have the Sally Hogshead of the world who spent millions and millions of dollars on her fascinating
• 12:48
  assessment because it was completely custom coded.
• 12:51
  Okay.
• 12:52
  But now what we're doing and for every single diagnostic now, we are building them all completely custom because now there is no real bit.
• 13:01
  We don't have to square peg around, you know, hold it.
• 13:04
  We can literally say what is the routing engine?
• 13:07
  we said to people, what do we know, what hidden parameters do we want to capture, what open, overt things do we want to capture.
• 13:13
  Every single piece of this machinery is now limitless.
• 13:18
  Every possibility is there because of the beauty of AI.
• 13:21
  And I think that data capture is obviously something to know how to do all of those things.
• 13:29
  But it is the ability to capture this data at scale.
• 13:34
  living in the most incredible chapter of the history of the world in my opinion.
• 13:39
  Mm hmm.
• 13:40
  Yeah, well, I've been doing some things as of late that are just would have been not even I wouldn't even considered possible.
• 13:49
  Just even a year or two ago.
• 13:52
  I mean, it's it's pretty crazy.
• 13:54
  Yeah.
• 13:56
  for us, I'm a big, big, big numbers person.
• 13:59
  I used to be an accountant, trained in big four consulting and all of that.
• 14:03
  Big, big numbers person.
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  And we are now building these KPI dashboards across companies, analyzing every single piece of performance data and things that would have taken an army of people to pull
• 14:15
  together and Google Sheets in the good old days or Excel before that.
• 14:19
  is literally we're able to build these real time dashboards, these incredibly
• 14:24
  elegant state of the union about every single business that we're working for because we have this at our fingertips.
• 14:30
  there are days where I'm just like, I can't believe we just built that.
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  Like, is this actually like what's available to us right now?
• 14:37
  It is.
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  It's just knowing how to take advantage of it.
• 14:40
  And then from my point of view, it's like we've got to have the infrastructure right so that we have the data that we need at the back end, whether that's just for the marketing
• 14:49
  and sales piece like I talked
• 14:50
  about earlier or if it's for the big data play we have to have the infrastructure there to have that data in the first place.
• 14:59
  Well, we're going to kind of touch on some of this and we're going to maybe get a little nerdy for some people on some of the details.
• 15:04
  But just to remind everybody, it's Maeve Ferguson, you can learn more at Maeve Ferguson consulting.com.
• 15:11
  I'm going to have that as a clickable link in the show notes.
• 15:13
  Maeve, you also have a sub stack you kind of you go deeper into some of these topics, right?
• 15:18
  Yes, exactly.
• 15:19
  So I write a weekly sub stack and then I dive kind of deep into different angles about the knowledge economy collapse, the AI saviour trap, the data demand curve, and then what I
• 15:30
  call data funnels and how the data funnel is the last moat that we have left standing in this age of AI and how every single expert, every single business owner, doesn't matter if
• 15:42
  you're a service provider or an investor or a consultant or a coach or
• 15:47
  ecommerce it doesn't matter it's having this data funnel in place at your top of funnel inside of your company will completely transform the the legacy that we're able to leave
• 15:58
  behind the income that we're bringing into your business
• 16:02
  If you found some value in what we're chatting about so far, do us a favor, share this with one of your friends.
• 16:07
  If you're watching us on YouTube, give us a like and subscribe.
• 16:11
  I was going to go into some other topics on the data side, but I have to address what you just said.
• 16:18
  AI save your trap.
• 16:19
  What did you mean by that?
• 16:20
  Yeah, so I think what has happened with the knowledge economy collapse has already happened.
• 16:24
  Okay, so the floor has fallen out of that market.
• 16:27
  And I say this as somebody who I used to have the 10k group coaching program and the nine digital courses and the low ticket products with the bumps and the OTOs and all of that.
• 16:36
  So I had a really successful business doing that for a number of years.
• 16:39
  But as I mentioned at the top of the episode, the knowledge economy has collapsed and that is now valueless.
• 16:46
  Now, action is
• 16:48
  is the next piece to become valueless.
• 16:51
  We've probably got about 18 months to 24 months left in that space.
• 16:55
  And suddenly action is going to be the next piece that gets gobbled up by AI.
• 17:00
  So we've got to remain agile and have that view.
• 17:04
  think that is also coming.
• 17:06
  But what then happened, most people in the, as the knowledge economy collapsed, they off they skirted to AI.
• 17:14
  They fell into the trap of feeding their IP
• 17:18
  into the machine and then creating little products like you you saw like a load of people starting to sell custom GPTs for this and then skills for that and all of these things
• 17:28
  where they're they're productizing and charging you know pennies on the dollar for their IP for people to kind of self-serve but what has ended up happening is they fell into that
• 17:39
  trap now the machines have all of their IP and what I mean by that is like I go through quite regularly just
• 17:46
  more for fun than anything else.
• 17:48
  There's an amazing Australian guy I respect so much.
• 17:52
  He has been to quite a few of his workshops.
• 17:54
  He is phenomenal.
• 17:55
  His name is Simon Bowen and he teaches the models method.
• 17:58
  I'm big into frameworks and structure and all of that kind of thing.
• 18:01
  So just out of curiosity I was just like right let's go and build every single one of Simon Bowen's models for my company and I did it with Claude.
• 18:10
  And the output was pretty spectacular because it has been trained on all of his IP.
• 18:16
  It has scraped it, scoubled it up.
• 18:17
  that's he's just one example for every single other expert out there.
• 18:20
  If you put in your favorite advisor, your favorite investment strategies, whatever they may be for a real estate, exactly the same thing is going to come back.
• 18:30
  So so many people have fallen into the trap and now they're like, well, what do we do now?
• 18:36
  Yeah, I've done the same thing.
• 18:38
  have I have what I call my board of directors in AI right now.
• 18:41
  And I've trained it on the various people.
• 18:45
  Yeah, regarding their skill set, right.
• 18:47
  So I just like I can ask some of these people what I almost feel directly.
• 18:51
  It's like I'm chatting with with that individual.
• 18:54
  So I the the the trap that I've the trap that I've noticed is is people kind of just
• 19:01
  And we're probably maybe this is a trend or I'm hoping that we see it kind of subside a little bit is the blind adoption of some of these tools without one checking its work.
• 19:12
  I've seen that increasingly more and more.
• 19:15
  But then on the other side, what I call AI slop, you go into LinkedIn, Facebook, wherever and it's just bombarded with nonsense, just junk right now.
• 19:26
  100%.
• 19:27
  So again, it's like to me there is discernment, but I also love this chapter of the world that we're in because it is the survival of the fittest.
• 19:37
  piece I believe and the bottom end of the market will cease to exist.
• 19:40
  People say, nobody's buying right now.
• 19:42
  People are buying like crazy right now.
• 19:44
  So when you are at the right end of your market, when you are really good at what you do, you're going to survive and thrive.
• 19:52
  where you wear, people who wear like middle of the road or just about making it, they're just going to cease to exist in their current form and they'll probably go back and get a
• 20:02
  job or do whatever, do something else.
• 20:03
  Pivot or jump to a different niche or whatever it may be, but it's finding out a lot of people But I do think to your point it is it's harder and harder to stand out when you are
• 20:13
  Elated what you do because of the AI slops So the people who just aren't that good at what they do are able to up level to look decent look smart enough But then the people who are
• 20:25
  actually really good at what they do now look like they are a comparative and again back to this
• 20:30
  proprietary data assets, one of my points of view is that when we have these diagnostic assessments, it's a complete positioning play because your competitors don't have them.
• 20:40
  They have the rubbish PDF lead magnet with no value inside.
• 20:44
  Very, very few people have these really sophisticated diagnostics that position them as elite.
• 20:51
  And then it's not some crummy quiz funnel with like five questions in it.
• 20:55
  It's a real authority play where you're able
• 20:58
  to show, regardless of what's going on in AI, the sophistication of what you do, how it's so different, etc.
• 21:05
  So it's really, really powerful asset.
• 21:07
  Well, let's pivot to the real estate aspect of this.
• 21:10
  probably have worked with some real estate investors.
• 21:12
  Can you give people a practical, lean on your experience?
• 21:16
  What have people implemented as examples as to what we're talking about here?
• 21:21
  Yeah, so if we go into the consulting wing of real estate, example, OK, so that is a perfect example where you bake your framework into the diagnostic and then we're also
• 21:31
  asking those qualitative and quantitative questions so that we can hyper segment that list and know exactly what offer to place in front of the right people at the right time.
• 21:41
  But then what you can also do if you're more in the real estate world itself, the data as it relates
• 21:47
  to your, like let's talk about America, like so let's, as it relates to your particular state, as it relates to different towns within the state, different jurisdictions and so
• 21:57
  on and so forth, when we have people like buyers and sellers of homes going through diagnostics and it matching, you know, here's all the buyers coming through and then
• 22:08
  they're routed to the right property that matches all of their requirements, it just becomes a super sophisticated matching mechanism, but we're also
• 22:16
  gathering all of the data and the behavioral data, the psychographic data of every single person that goes through that diagnostic and also what they want to buy or not buy.
• 22:27
  And that asset in and of itself is highly, highly valuable to anybody that, marketing companies that are also selling to people who are buying homes or whatever.
• 22:36
  So it's like all of these side door industries as it relates to real estate will be interested in the
• 22:43
  data that came from any real estate diagnostic.
• 22:47
  So you're not only talking about taking advantage of it yourself, but possibly selling this as a data source to other companies
• 22:54
  100 % that's what we do inside of so we're very very lucky because we build diagnostics
• 23:01
  and we do the monetization of the data on the backend.
• 23:03
  So I get to geek out, do all that analysis, aggregate the data and anonymize it, all of those things.
• 23:09
  That's actually a product, that's an income stream in its own right.
• 23:14
  And they, I always say that the leads and clients are a given from the diagnostic that we build, and then we monetize the data on the backend.
• 23:21
  The big piece is, is that we have to have enough water flowing through the pipes for there to be data.
• 23:27
  And this is where we then get into marketing and traffic strategies and
• 23:31
  of those things.
• 23:32
  Sure.
• 23:32
  Well, there's a lot of science associated with that building, building out these assessments.
• 23:37
  Could you give people an idea of like, some low hanging fruit?
• 23:42
  You know, we have a tendency as entrepreneurs, especially now with AI, we think we're gonna work, we have this, we can figure this out ourselves.
• 23:51
  So they will just stand a throw spaghetti at the wall.
• 23:54
  What
• 23:55
  Let's give people a little direction like something that they can maybe implement today that could actually move the needle in some regard and maybe at least prepping for this
• 24:05
  type of conversation with your team.
• 24:07
  Yeah, lovely.
• 24:08
  Okay, so yeah, if I had a dollar for every time somebody's like, yeah, I tried a quiz that didn't work and it's used to be some sort of awful type form and now it's some sort of
• 24:16
  awful lovable quiz with like five questions.
• 24:18
  Okay.
• 24:18
  So the first thing you want to do is decide which type of diagnostic is most appropriate for your business.
• 24:24
  There's three main types.
• 24:25
  One end of the spectrum we have what's better known as the quiz funnel.
• 24:28
  So kind of seven to 10 questions.
• 24:30
  It's not an authority play.
• 24:32
  It's not a positioning piece, but it's more lead qualifier, list segment.
• 24:35
  We put people into buckets and we're able to write them to the right message in the right offer to the right person at the right time.
• 24:41
  So they work incredibly well.
• 24:43
  they are for like say as we talked about earlier this golf client they're spending a million dollars a month in ads that thing is printing leads.
• 24:50
  It's crazy.
• 24:51
  Okay.
• 24:51
  Way at the other end of the spectrum we have the multi-dimensional diagnostics.
• 24:55
  So if you've ever been through Myers-Briggs I'm INTJ or Enneagram I'm a three with a four wing.
• 25:01
  become a household name and globally people recognize the profile or the result that you got or the archetype that you were given.
• 25:10
  It just becomes the discs of the world, the enneagrams, the Myers-Briggs, the strength finders, all of that.
• 25:16
  It becomes a globally understood language.
• 25:19
  This is most appropriate for the Harvard professors, the number one New York Times bestselling author where we have statistically validated data.
• 25:27
  We have a thesis, we then prove our thesis and then we build the diagnostic off the back of that.
• 25:33
  OK, because we have our percentiles and all of our proven data points to be able to do that.
• 25:38
  But somewhere in between is where I see most in the expert space fall, where you would have real realtor's themselves, where you would have real estate advisors, coaches,
• 25:49
  consultants, investors, etc.
• 25:51
  is what's called a score based diagnostic.
• 25:53
  And this one more so acts like a
• 25:55
  gap analysis tool.
• 25:56
  So let's pretend you have four steps in your framework.
• 25:59
  We then ask a series of questions as it relates to the steps of your framework to identify over here you're doing really really well but ooh like here this is what needs work and
• 26:10
  then we obviously your offer is in position to solve their greatest area of struggle.
• 26:15
  So the copy that one person sees is completely different to what the next person sees and so on and so forth because of the
• 26:22
  their result.
• 26:23
  So that acts as a really really strong gap analysis and it's like here's where you are, here's where you want to be, to come you know come and work with me and we're going to get
• 26:32
  you get you there.
• 26:33
  Okay so that's that's kind of the three choices so kind of thing that's step number one is think through that.
• 26:38
  The next piece then is most people jump to okay what should my quiz be and they started the quiz hook and it's actually we want to do the complete opposite.
• 26:47
  The hook and the the question of the assessment
• 26:50
  will fall out of the process way down the road.
• 26:53
  What we actually want to do is begin with the end in mind.
• 26:56
  So we start with our offers, where are we sending people?
• 26:59
  What are the price points?
• 27:00
  Why are we sending them there?
• 27:01
  What is our offer portfolio structure?
• 27:03
  What life do we want to live?
• 27:04
  Do we even want to live this life anymore, etc.?
• 27:07
  So we begin with the offers and then we reverse out of those offers to then map the framework that we just talked about to the offers to make sure that there's really, really
• 27:16
  strong funnel congress.
• 27:18
  because we don't want to a framework about synchronised swimming and then offers about gardening.
• 27:22
  That's not going to sell a single thing.
• 27:24
  so it's like that congruence is really important.
• 27:26
  And then what we want to do in the score based example is to talk that through is you want to look at each of the four steps of your framework and then write what are the
• 27:36
  subcategories that go into each of those stages of the framework.
• 27:39
  And so we've got, you know, ABC in inside pillar number one.
• 27:43
  Then from there, I want you to think through what are the questions, this is super, super important.
• 27:48
  So what are the questions that we can ask that when the lead answers them in a certain way, it means that their result is X, Y or Z.
• 27:58
  Okay, it's really, really important.
• 28:00
  And you just simply go through that exercise, subcategory by subcategory by subcategory.
• 28:04
  So that's kind of the main showcasing your expertise, your understanding of your audience and where they are.
• 28:10
  a question build perspective and that's about half the story.
• 28:14
  So that's amazing and you get so many data points, know, just visualize somebody going through this assessment, they're answering questions as they go through, every single
• 28:23
  button they push is a data point that we can then capture.
• 28:26
  But that's about half the information we want from a data play perspective because we also want to know their gender, their age bracket, their all of these different things, their
• 28:39
  job title,
• 28:40
  what industry they're in and so on and so forth.
• 28:42
  So depending on the world that you're in and what those data points are needs to be decided and make sure it's appropriate.
• 28:49
  Now we don't want to end up with a 100 battery of questions assessment, okay just gets too long.
• 28:55
  So there's this dance that we have to do to make sure that we're gathering all the data points we want but it's also be mindful of that this is a top of funnel piece of
• 29:04
  infrastructure that we also want people to go through.
• 29:06
  complete.
• 29:07
  And then so this is again where all of the tools that we now have at our fingertips are so amazing because we can actually scrape invisible data points because we don't actually
• 29:16
  have to ask the lead to tell us we're able to set up all of these systems to scrape various different data points in the background that they don't know we are gathering so
• 29:27
  that we can build a fuller picture of every single lead and every single profile.
• 29:30
  And then as people go through this, then the fun starts.
• 29:33
  So it's like once you go live, it's day zero because then you can start to analyze all that data.
• 29:39
  Mm hmm.
• 29:41
  This is really interesting, Maeve.
• 29:44
  So I just want to kind of paint a picture here now.
• 29:47
  Imagine what Maeve is talking about here.
• 29:49
  And I know that this is really getting into the weeds on some things.
• 29:53
  the way she's painting this hyper local segmentation and and being able to categorize your audience, I think we're all
• 30:01
  you know, when it comes to whether it's face meta ads and YouTube, Google ads and all of this type of stuff.
• 30:08
  And you're just kind of bombarding your your visitors with ads and in hopes to generate some action.
• 30:16
  Imagine imagine the power you have now with this hyper segmentation where you can actually target specific type of ads that specifically answer their pain.
• 30:27
  Like that is what actually gonna drive and move the needle on stuff.
• 30:31
  Am I completely off on that, Maeve?
• 30:34
  No, it's a hundred percent, but this is what I was speaking to earlier when we used to just focus on the analysis of the data.
• 30:39
  from a marketing and sales perspective, but if you think about every single person that goes through your diagnostic, so let's say a thousand people go through it this month, we
• 30:47
  have audiences that are silently building in the background of people who have gone on to buy our, you know, 100K thing or whatever price point your thing is, and exactly how they
• 30:58
  behaved as they went through the diagnostic.
• 31:01
  So the answer question two, C, seven, D, and 11F means that they, at scale,
• 31:07
  of sufficient data we're like this is our perfect profile.
• 31:11
  We're then able to dynamically now, because of AI, we're able to dynamically craft, copy, create the creative that matches their exact profile and show the lookalike audiences and
• 31:23
  then showcase that back to these lookalike audiences that exactly match the profile of the people who have been proven to buy from us before.
• 31:32
  Yeah, so so you're leveraging the power of these networks.
• 31:35
  That's that's their superpower is doing these lookalikes and and and the like it
• 31:41
  Yeah.
• 31:41
  So you can tell them, but what most people are missing is they, they have a list of buyers, name, email, address, and phone number buyers go and find me more people that look
• 31:49
  like this.
• 31:50
  When we start getting a hundred data points at every single person and again, exclusion audiences.
• 31:56
  Okay.
• 31:56
  So here are all the people that we don't want to serve our ads up to build exclusion audiences.
• 32:02
  And it is over time.
• 32:03
  It just becomes like a self-optimizing flywheel that just, it just learns and it gets smarter and smarter with agentic AI now.
• 32:10
  it actually does get smarter.
• 32:12
  So ultimately what's happening, like, and again, in AI, like media buying as an industry is going to be completely floored, completely disrupted because all of these tools, we no
• 32:23
  longer need that particular skill set where they used to manually go through and change stuff.
• 32:27
  Now the agents never have off days.
• 32:30
  They never get it wrong because they're conforming to your rule book.
• 32:33
  And as long as you are, have the discernment to be able to
• 32:36
  put that guidance into the machine in the first place, so we have to say rubbish in rubbish out, get the good instructions into the machine in the first place, it just
• 32:45
  becomes self-optimizing over time.
• 32:47
  And I completely understand it if you're listening to this and are completely overwhelmed with the detail and what goes into this.
• 32:56
  That's why you need to reach out to Maeve and her team.
• 33:00
  Head over to MaeveFergusonConsulting.com.
• 33:03
  Clickable link in the show notes.
• 33:06
  You know, we just scratched the tip of the iceberg on this, Maeve.
• 33:09
  Is there anything else we should have tried to hit on here?
• 33:11
  I think it is just the, like, banging on about the data again.
• 33:15
  think it's my wish for your listeners today is that they have that kind of penny drop moment.
• 33:21
  data, proprietary first party data is the moat.
• 33:24
  And it doesn't have to be with me.
• 33:26
  doesn't have anything like that.
• 33:27
  But it's like, get yourself proprietary first party data.
• 33:31
  Start the, if you wait until tomorrow, you've already lost today's worth of proprietary first party data.
• 33:36
  The build and how I've taken you through that, it might sound overwhelming, but it's actually a very, very methodical step by step, repeatable process.
• 33:47
  We've done this hundreds and hundreds of times.
• 33:49
  Know what to watch out for, all of those things.
• 33:51
  So it's just,
• 33:52
  It's just do it methodically, think through the data points that matter to you from a marketing and sales perspective.
• 34:00
  And then if the data play and building that moat and that extra income stream in your company is important, then yeah, reach out and we'll have a chat.
• 34:08
  Well, I'm going to have that all as clickable links in the show notes.
• 34:12
  I really appreciate your time here.
• 34:13
  We're going to jump into the rapid fire and close out this episode.
• 34:16
  but, I really appreciate it.
• 34:18
  you can learn more again at Maeve Ferguson consulting.com.
• 34:22
  I'm going to have the link links to the, the sub stack.
• 34:26
  But if you're ready, Maeve, we'll jump into the rapid fire and close out this episode.
• 34:30
  Okay, let's see the eye path.
• 34:31
  Let's go.
• 34:32
  What lie do entrepreneurs often tell themselves?
• 34:35
  like my goodness
• 34:36
  They make decisions about what is or is not working on their business based on feeling and emotion, not data.
• 34:44
  I can't agree more.
• 34:45
  In fact, you know, we as entrepreneurs or business owners, we, we think we're just so stoic and we can, we're making infer we're making just logical decisions, but that's
• 34:57
  typically not the case.
• 34:59
  everybody goes and changes their offer and it's never your offer.
• 35:03
  It's never the offer.
• 35:05
  Yeah, that sounds very Russell Brunson.
• 35:07
  to change the offer.
• 35:09
  No, I think I've heard him say something about it's never the offer.
• 35:13
  It's never the offer.
• 35:14
  But anyway.
• 35:15
  right, OK.
• 35:16
  To me, it's like the, I always call it the leaky hole in your bucket.
• 35:20
  The data will tell you where the leaky hole in your bucket is.
• 35:23
  Yeah, and we should take take that advice.
• 35:27
  It's like there's there's certain things we're just convinced that this is the direction I need to go.
• 35:34
  It's it's like I think there might be something about some gurus will even tell you pick your niche, stick to your niche.
• 35:41
  But if the data is telling you something different, maybe you should maybe you should listen to it.
• 35:46
  Dada never lies.
• 35:47
  If you go back in time and give your younger self one piece of advice, what would it be?
• 35:51
  Feel faster and don't worry about...
• 35:57
  so much about what others think in your early chapters I think.
• 36:02
  I've been doing this for seven years now, came from a senior role in corporate, worked in the private equity industry etc and probably if I look back now the first three to four
• 36:12
  years of my business were built and run through the lens of my god what are those people going to think of what I'm doing now and I now I don't give a monkeys because I'm
• 36:22
  absolutely flying and it's
• 36:23
  I wish I could go back and tell myself then to just go get it and who cares what anybody thinks.
• 36:30
  Do you have a book recommendation or what are you reading right now?
• 36:32
  I am really looking forward to reading his book Return to Real.
• 36:42
  I'm just going to flick up my audible to if I've got one more recommendation.
• 36:46
  I have very young children so me and book reading is no longer a suitable thing because they just get ripped.
• 36:52
  I'm actually reading a book called The Inner Matrix by Joey Klein.
• 36:56
  It's worth a
• 36:57
  what single tool or process have you implemented that has had the biggest time-saving impact?
• 37:02
  plot skills.
• 37:03
  Yeah, cloud skills.
• 37:05
  Well.
• 37:06
  single moving part of your business.
• 37:08
  Well, I appreciate it Maeve one last time it is Maeve Ferguson consulting.com clickable link in the show notes.
• 37:15
  Hope you'll consider coming back again real soon.
• 37:17
  This was great.
• 37:19
  This was so much fun.
• 37:20
  Thank you so much for having me.
• 37:21
  Well, thank you.