Known as “The Chief Rainmaker”, Gil Ortega has been a go-to Customer Acquisition Specialist for over 24 years and today works exclusively with agencies to transform their client’s customer acquisition cost.  Currently head of IDENTYO and Profit Worldwide, Inc., Ortega has also served as CEO of Leads to Wealth, Inc., Vice President of Sales for Pixels3d, CEO of Beyond Profit, Director of Entertainment Client Recruitment for ProSports Management International and Owner of Chili Productions -- a company he started as a sophomore in high school.  He is a graduate of UCLA where he earned a Certificate in Music Business Extension, and Grossmont Community College where he earned an AA in Video and Film.

TAKEAWAYS

Why ridiculously expensive Customer Data Platforms are obsolete -- and how to get even better results at a fraction of the cost.

How to create an outcome-based ideal offer in 30 days or less.

Why static data is history and what you should be using instead.

How ramping up too fast can kill your algorithm’s targeting -- and what percentage increase on ad spend per day will keep it alive. 

Who’s 1000X better (and cheaper)  than Axiom and Oracles at finding your best customers.

RESOURCES/CONTACT:

SHOW NOTES:

TRANSCRIPT

Speaker 1 (00:01):

On this episode of the rich dad, poor dad podcast, we have a very special guest, mr. Gill, Ortega, we dive into real-time data and how to use it properly across multiple channels. Ultimately lowering your cost per acquisition. We also kind of dive into some tips that Mark Cuban gave them towards the end of last year. That completely changed the way their businesses ran this year on the poor ad side of things we dive into, you know, not understanding more real-time data and static data and the importance of using, you know, the data you do have with consumer behavior, um, to really kind of move that needle and lower your CPAs. Make sure to tune in this one's all about data and it is solid

Speaker 2 (00:39):

Created an outcome result-based offer that literally within 30 days, all we're doing is pushing in audiences that we're identifying segmenting and delivering into the various ad platforms, Google and facial being the primaries, but it can go everywhere. Every, every major ad platform, including DSP is

Speaker 3 (01:12):

You're listening to the rich add poor ed podcast, where we break down the financial principles that rich advertisers are deploying today to turn advertising into profit and get tons of traffic to their websites without killing their cash. These advertisers agencies, affiliates brands are responsible for managing over a billion dollars a year in ad spend. You'll hear about what's working for them today. They're rich ads and we'll roast their Epic failures and crappy ads on the internet with core ads. Let's get into it.

Speaker 1 (01:40):

All right. All right. On Friday, everybody, we are back in action with another episode of the rich dad, poor ad podcasts. We've got your host, Dylan Carpenter and the house. You know, we're going to talk about what's working, what doesn't work and then some bad-ass financial principle tips. So today we have a very special guest, mr. Gill Ortega.  Back in the day, he was doing a ton of lead gen, you know, managing she probably 4 million a month, but that was in the past. Now he's the co-founder and chief Rainmaker of identity, which is kind of more of an audience creation biz, but without further ado, but the hype is real guilt. What's that, man. Thanks for hopping on

Speaker 2 (02:12):

You doing thanks for having me

Speaker 1 (02:14):

Not a problem at all. So kind of give everybody some context of, you know, who you are, what you're doing these days. I didn't see. Oh, sounds super awesome. I'm super into it. I'm excited to learn more, but kind of give everybody some context of kind of what you're getting into.

Speaker 2 (02:27):

Sure. So Zach and I met in 2015 and right when he was starting funnel dash and, uh, it was big data that I was making a really big pivot into from lead gen to, to audience creation and data-driven campaign. So, you know, all, all the privacy can per all the privacy concerns that we're hearing nowadays, you know, from like the Cambridge Analytica fiasco a few years ago, to current concerns, GDPR, all of that, wasn't going on when we started in 2015, creating what is known as identity resolution or identity graphs. And I, and just to give you some background, I'm going to, I'm not going to get into the weeds of data because it always makes people's heads spin and it, and, um, it just, you know, it's not the sexiest thing. And when it comes to marketing, you know, it's like the data and the analytics and how, you know, how you target somebody.

Speaker 2 (03:30):

But basically we started, uh, creating identity graphs and, you know, the old cliche of the right message at the right time, you know, pretty much every company either says they do that or wants to do that. It's, it's basically the, the levers in terms of data leverage to be able to do that. So you identify somebody that is visiting your website, right? So that's the identity part, and this is all top of funnel. So people that have not filled out a form, you know, opted in to your, to your list, we're identifying somebody and then you you're able to track that person across devices. You know, how many devices do you got now? Like you just look around your desk, right? Like a lot, right? Yeah. Probably eight or nine. It seems like. Right? So the more devices that people start piling onto their daily usage, the harder it becomes to attract somebody.

Speaker 2 (04:29):

So that's the, that's the goal when you, when you're doing a data-driven type of campaign, um, or from a, from a brand's perspective, the goal of building an identity graph is to just identify your potential audience, your entire total universe of potential audience. So whether you're B2B or B to C, you know, you have this avatar of potential, like if you just sell the women of a certain age, et cetera, like, or if you just sell to, uh, you know, whatever type of audience you want to identify, everybody that you could potentially sell to, and then you want to key in to their behavior when they're looking to buy a product that you have, right? So you want, you want to be able to sense through all the various sensors of the internet, you know, when somebody shows up to a page or somebody else's page, and then you want to be able to send them the message, the right message at the right time, that's the cliche.

Speaker 2 (05:38):

So people do this with, uh, CDPs, right customer data platforms, like in the past three, four years, a massive amount of CDPs have been getting funded, like tens of millions of dollars because it's bringing together the functionality of building the identity graph. The, and it's, it's not cheap. You know, this is, these are normally six figure seven figure endeavors for a brand to be able to do this kind of stuff. So, um, what, you know, I'm telling you this, because that's where we start it. And what we've done now is we've simplified it to the point where you don't even have to do that. It's like the, the end result is what we're focused on now, just the outcome of being able to do all that cool tracking. And, and, um, and now we just want to give you a lower cost per acquisition on media that you're already spending on your budget span right now. That's it

Speaker 1 (06:36):

Now with most of the brands you mentioned, you know, high six or seven figures, they're pretty established businesses. So before you even dive in, is it possible for you to look at past data or do you all have to incorporate new systems and then look at the new data to be able to kind of find these more data points more or less?

Speaker 2 (06:53):

So historical data has been a big part of building a graph, but we, the things that we've learned, um, so like if somebody is, um, historically been purchasing some kind of product or, uh, has visited a certain website, uh, what would you call like affinity groups or, or, um, you know, just transactional type data that, you know, Oracle and, and, uh, Axiom and all these big data companies experience, et cetera. All of these data companies are building these audiences in a manner that what, what a marketing agency or brand will basically do is take those audiences and put them into a platform or into Facebook and Google directly as a custom audience and create the targeting that way. We used to do that. That's what we start, that's where we start it. And we saw the flaws. There's so many flaws in that approach, that what we realize is that historical data, even data that's days or a week old is, is secondary to real time data. So real-time behavior. Like, I mean, when, I mean real time, I mean, by the second, by the minute behavior and the data associated with it. And so a visitor to a website, all traffic and all, all clicks and all interactions, all engagement is data and visitors to your website that you own is first party data. So that data is the most crucial data that we have found that we've started to leverage to create better audiences.

Speaker 1 (08:33):

Oh man, I'm fired up. I'm big data guys. I'm fired up over here, but man, heck yeah. I mean, that, that helps a ton of context there without a doubt. Now we love to kind of dive into what's working for you. I know in this scenario, we're going for more of a strategy, go ahead and open up the kimono. You know, let the world know what's worked well for you on this kind of strategies forefront. So,

Speaker 2 (08:56):

You know, I always referenced back in the day because so many marketers are still using what I called static data, disconnected data disconnected in the sense that it's not real time. So if you, if it's your customer or your CRM data, everybody believes that that is the, you know, the Holy grail of creating a custom audience like your customer data, but it's not, um, believe it or not. It's like, um, you know, pre-packaged audiences data that comes from even like the biggest data companies in the world like Axiom or, you know, my, one of my business partners used to work for Axiom creating data products for them 15 years ago, um, or for 15 years. And so like Axiom started this company called library, live ramp is probably the biggest, uh, 800 pound gorilla in our space. They, you know, they make, uh, they have 500 clients of, uh, of their identity link product, which doesn't seem like a lot, but they do hundreds of millions of dollars quarterly.

Speaker 2 (10:01):

That's another huge, you know, they're big, big company and, um, and now they own bigram now owns Axiom. So the reason I tell you that is because everybody's taking data, the, the, the standard approaches is taking data, whether it be customer CRM or third party data, and putting it into a custom audience or their platform, their DSP, or, or what have you, and doing the targeting in that manner. And what I'm, what I'm telling you is that is sub par or lesser to creating the audience in, in real time. So the, the downside to, uh, say like bringing your customer data, but just say you're selling mattresses, right? Like somebody owns a mattress, there's a lot of mattress companies out there. So you take your customer data that people have bought say like last week or last month, whatever, you're you're, you got these customers, right.

Speaker 2 (11:00):

And now you upload them into Facebook, Google's custom audience, and to create, you know, to, to create a lookalike. Right. That seems, that seems logical. Yeah. Have you ever done something similar to that with audiences every day, every day, it's a manual process for one, right? It's, it's very labor involved, you know, and, uh, so that it'll, it'll produce what I call a streak of brilliance. A streak of brilliance is going to be a lift that you're going to see. It may last a few days, maybe as long as a week, and then it'll start going down and you just keep doing this. You're like, Hey, that worked. I mean, do it against some other, you know, next month, next week, whatever the problem is that that data set the behavior of those, those individuals, your customers, if you're looking at it from like an avatar, you know, or like finding co cohorts, like it is, it's great.

Speaker 2 (11:57):

But their behavior there, that list of people are no longer looking for a mattress, right? So their behavior right now in real time is no longer behaving like a customer. And so, and, and if, if you're a B2B marketer, let's just say, you're, you're, you're people that buy some kind of SAS product, right? Some kind of B2B SAS product, and you're doing this. Um, the same thing applies because everybody wants to find somebody that's in the market, right. Google term, uh, created the term in the market. So it's like, it's like this behavior that is deeming this group of people they're searching for insurance or whatever. Right. So the problem is that those people, maybe a month ago, or a week ago, whenever they became a customer are no longer in real-time behaving like the person that you wanting Google and Facebook's algorithm to find,

Speaker 1 (13:05):

I actively searching for fresh mattresses versus, Hey, they did that two weeks ago. Now they're looking for sleeping pills. So it's kind of those different behaviors is that kind of,

Speaker 2 (13:13):

That's exactly it. So Google, so there's a lot of, uh, uh, businesses and specifically B2B too, that are looking elsewhere. Third-party data to, to find the segment of people that are going to be right for their product or service. And what I tell everybody is Google and Facebook are the best at finding the people that you're looking for. There's no other, no data company, Oracle Axiom experience. Nobody can find the people that are behaving in real time, as good as Google and Facebook. And the reason is because they have such a large footprint of retargeting pixels globally. Think about how, how wide, how many websites, B2B, and B to C have the retargeting pixel of Google and Facebook on their website, massive comparison. So that network of retargeting pixels functions as a sensor, real times, behavioral sensor of people on a website. And if you go back to identity, Google and Facebook knows who you are, right?

Speaker 2 (14:27):

So when you're basically asking for a lookalike, the algorithm, Google and Facebook's algorithm is all about behavior, more so than it is about the demographics of this person meets this specific profile. And if you're uploading data that is static non real time, you know that like your CRM data or, or worse, you know, some, some audience that some company produced for you and you're uploading Matt saying, Hey, find me more people like this. It's it's called data decay. So the algorithm is going to basically be lesser because you have unqualified people in that audience as your seed data, right? So that seed data is essentially, you know, saying, Hey, there's some people in here that really aren't looking right now for whatever product or service that you're looking, you know, to build the audience. So Google and their algorithm and their Facebook is going to basically give you more of those people, right? So you have unqualified people in there and they're going to give you more of those unqualified people. And, and you'll see sometimes a lift, but it's just not sustainable. It's not your pain. You're basically paying for clicks, leads and customers at a higher rate.

Speaker 1 (15:54):

You're saying we're having this conversation now. Um, especially with everything kind of going on, I'm over here, amping up for Q4 with black Friday and cyber Monday. But what we've noticed even on the Facebook forefront is, you know, back in the day, you would be able to get, you know, custom audiences of 180 days. Everybody who's purchased when these days is that they're, aren't working so well. But in the past week, I've been doing a lot more seven day 30 day audiences, which are kind of a bit more recent. Um, it's where it's not as real time, but it's as close as we can kind of probably get. So where does it performing way better? So, I mean, it kind of goes hand in hand on how Facebook and Google, they know what you're looking at, what products, what kind of websites to have that real-time data and have those specific behaviors are going into, I think it's kind of cool how I I'm over here noticing kind of trends that I'm seeing it's correlating with you're.

Speaker 2 (16:39):

So it's the old computer adage of garbage in garbage out. So it's an algorithm, you know, their, their local like algorithm is, is behavior-based more so than data, uh, profile based the demographic base. And if you're putting into the seed, the custom audience and that seed audience, if it, if there's unqualified people in there even a little bit, it's going to skew the lookalikes to have a little bit, or sometimes a little bit too much unqualified lookalike audience. And so in essence, what we've been doing is we've created a real time, include an exclude audience creation system, and it automates this, this entirety of, of, uh, of one identifying people, right? So we get rid of bots bot, you know, that's, that's not hard, but there's, you know, it matters if you're, you're getting rid of, um, you know, the bot traffic. And then once you identified somebody, that means that you can take that person to a variety, different ad platforms all in real time.

Speaker 2 (17:52):

So if you're, you know, like, you know, your audiences and Google and Facebook with their pixel, even though, I mean, you should be using their pixel adjust. You should be capping your, your daily spend and your frequency caps with their pixels, Google and Facebook's pixels because becoming a premium, I mean, it's, they, they work, you know, amazingly, but you're gonna pay more for, for their, you know, for their traffic. You're retarded and they're going to expire that on you and it's just not portable. Right? So what in essence we're doing is we're making that audience identifiable it's. It goes back to what I was saying earlier. It's identity resolution, is that the key and doing it in a privacy compliant manner where we don't use any PII, personally identifiable information and we're cookie plus. So you combine those two were GDPR compliant for Europe, CCPA compliant for California.

Speaker 2 (18:51):

And at the same time, we, when we started doing this, this is, this is what, this is kind of why it's against, against the grain of the norms in terms of what all the data companies, all these really big companies are doing, uh, the PII route or they're they're buying and creating their own identity graphs, which is not, not cheap, like I was saying. And, and ultimately you're paying way more than you need to, it's going into your cost right. Of acquisition. And I think no matter what kind of marketing you're doing, whether it be online, offline, the end goal, the end goal is to just lower your acquisition costs, improve, improve the quality of customers. You're getting the targeting and then lower the cost constantly to be able to do that. And I should probably tell you about, uh, the, the, the changing with, uh, the meeting that we had in December with the shark, because it really changed the game for us.

Speaker 2 (19:53):

Um, so we see that for the financial side or dive into the now you think, well, yeah, I mean, I tell you, I'll tell you now. All right. So in December of 19, at the end of the year, we basically were, we were trying to be a, a quasi CDP customer data platform. Everybody was getting funding for, you know, uh, being a CT CDP. And so first click, last click, and every click in between is what we track. We still track that, but it's like, we, because you can track that, you know, go back to the identification of a person and then you can track everything and you can do that. Cross-platform right. So whether it's TV, radio, mobile, post postcards, physical postal, uh, you name it right. Google, Facebook, native, native email, you name it. So tracking all of that was what we were building. And it's like a behemoths that's like this huge monster,

Speaker 4 (21:00):

Have a platform and activity to be able to do

Speaker 2 (21:03):

That. And so, um, in December we were, uh, talking with some groups about bringing on investors and partners and such. So we had these new partners that we, uh, were on the verge of, of, uh, working with in December. And they set up a meeting. Um,

Speaker 4 (21:24):

One of their clients, one of their clients, one of my partners owns an agency.

Speaker 2 (21:27):

You set up a meeting with Mark Cuban, the sharp, right? Like the guy that claps right on, on the chart. So, um, would its axis. And we got this meeting with, with Mark Cuban, from what was supposed to be a 30 minute lunch meeting, turned into two hours. We showed him our, our, uh, like our full plan

Speaker 4 (21:52):

Form that was basically tracking everything and been able to do all this stuff. We know he's invested in a lot of data. Yeah.

Speaker 2 (21:58):

Companies. So he, he was like the perfect, uh, we want it sharp juice. Right? So we, he was the perfect target for us to bring on, to get that shark juice or that, you know, somebody that knew data and could influence, uh, what our direction, big time. So the long and the short of it is, um, we didn't get investment from him. He did say, uh, you know, come back in six months, but what he, this, what he wanted us to do was he, he looked

Speaker 4 (22:27):

At everything and he goes, this is awesome. He gave us three claps

Speaker 2 (22:30):

During, like, he gave us, you know, that was cool. But you know, at the end of the, at the end of the day, this is like a lemonade out of lemons, because what you mean we didn't, we didn't get shot, uh, you know, shark juice. But what he said was like the game changer for us, because in December, from December to February of 2020, this year, at the end of February, we had basically re transformed, just pivoted and created a hyper-focused on what we were doing all because of what Mark Cuban said. And this is what he said. He basically said, look, all this tracking and stuff, all it is, you know, amazing data and the attribution of, you know, ads. And it's awesome, but it's not actionable. You got to package this up and is perfectly honest. I don't care about all that data that you guys are collecting

Speaker 4 (23:26):

And tracking and all that stuff. And he's a, really,

Speaker 2 (23:28):

What I want is I want one dashboard, one screen that shows the outcome, the results of all this cool stuff like you guys can do this, just do it, just do like, show these all, then show me in real time, the, the, the results of the stats. And we're like, and he's like, you guys are good at lowering acquisition cost for customer acquisition. That's what you guys do. Right. That's the end. That's your, that's the end destination, the journey. And I go, yeah, that's yeah, basically. That's, that's it. So, um, he goes, just do that. And so that's basically what we did. We, we threw out all the complexities of data and building a graph and doing all this stuff. And we said, let's just build the platform to be as simple as getting a result within weeks under a month, under 30 days, we'll basically lower your acquisition costs by half or even more.

Speaker 2 (24:34):

And just show that, yeah, you know, whatever reporting platform they are, somebody already is using already uses, or they can use Google data studio. They're just, you know, we have a template that shows the results for, for clients in our, in our clients or agencies. So we work with agencies and the agencies have a lot of different clients. Some, you know, some pretty big brands that are getting millions of visitors spend millions of dollars on, on ads. And the simple thing that we've done because of Cuban is we've created an outcome result-based offer that literally within 30 days, all we're doing is pushing in audiences that we're identifying segmenting and delivering into the various ad platforms, Google and facial being the primaries, but they can go everywhere every, every major ad platform, including DSPs. And we just say, run our audience to a converting campaign that you already know benchmark is doing well, run those same ads for our audience and just watch it, just compare it.

Speaker 2 (25:48):

And then in 30 days or less, probably within a few weeks, if somebody has a lot of traffic, it's a lot easier. It happens really fast. That's it? You just, you, you see a kill and it boils down. So the simplicity of that is where we've, we've come from this complex, uh, you know, data-driven platform and building, and, and there's so many companies that are doing that right now. Like that is huge activity right now. And what we're saying is that's cool, but you don't have to do that. If the end goal is to lower your acquisition cost for customer clicks, leads and customers, there's a, we've got a really simple, like no brainer solution. It's super cheap and it'll dress. Like I got a mortgage client, you know, through our, one of our agencies spending 50 grand, I think 60 now, and within weeks, they've taken that same budget and we're getting 44% more conversion to application on, on refi applications, 44% more on the same exact budget. And I got, you know, countless other examples of that. So companies that are spending a lot of money, I haven't gotten to the really big budgets yet that like, uh, I saw, uh, you and Zach talking about people spending a hundred thousand a day or something like that. We haven't gotten the budgets, but, um, you know, maybe this, uh, this, uh, this, this, uh, holiday season, but yeah, so people that are spending millions of dollars, you know, a year, it just that's the idea is that we're lowering that position costs.

Speaker 3 (27:38):

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Speaker 1 (28:57):

Now, I think this is the perfect segue into the next segment of the poor ad side of things. So, I mean, on the rich dad, I mean, definitely dove in to kind of, you know, how to reduce the CPA, very data oriented approaches more real time.

Speaker 2 (29:10):

But I mean, for this

Speaker 1 (29:13):

Poor ad side of things is, you know, if this is an executed correctly, what kind of turn into more or less, or have you had these scenarios where you kind of went all in on a specific feature of this, where it just did not work at all?

Speaker 2 (29:28):

So, um, you know, so since 2015 we've been testing, I can't tell you how many variations of custom audiences to lookalikes. And everybody thinks that it's the custom audience that you're going to be retargeting. Um, that's that that's the money. It's not the money. The money is in the, in the local like similarities. Yeah. And so the, uh, like for instance, if your, if your, if you have a custom audience and you're updating that custom audience, right? So every week, every day, whatever, and you know, this is, if you're not doing it automated, you're you hate doing so people get new data from wherever their CRM customer and what they've, what we've have found is that when you update an existing, um, audience, that you've already created a custom audience, it will produce less than if you're creating a brand new custom audience and taking, getting that new data that you got and loading that into versus loading it into the existing custom audience now.

Speaker 2 (30:40):

So we would see a massive difference in conversion. Now this is the brain twister we were doing that manually for years, right? This is, we call it a protocol. Like you have to create a brand new custom audience to get, uh, to get, uh, the most, the biggest lift. Yeah. Don't update an existing one to create, you know, your local likes. So what we realized was that when we started, when we, we always had this theory, it was a theory. If we could become real-time right, it goes back to the data decay and not uploading, you know, static data. If we could become real time, real-time includes an excellence. Meaning by the second, every second minute, I'm taking somebody in and out based off of some score on their behavior, into an audience. So what we found is when you update an audience, the same exact customize, like that, it's golden being an audience by uploading a data file, right? Like manually, it doesn't work as well as creating a brand new custom audience. And, and the difference is like staggering. Like this is, these are the things that, that will, you know, triple cut your costs. Like you'll get three times lower costs for clicks, leads, and customers doing, doing these tasks. The, the, the thing was that once we figured out doing this real time, it's consistent. Like if you have seasoned retargeting data, like warmed up audiences that are the best with the best optimized campaign, we'll beat that data.

Speaker 5 (32:34):

Ooh. Ooh, . So

Speaker 1 (32:40):

Just to kind of reiterate, so hypothetically speaking, say I group, you know, we'll look at September for example. So if I were to group everybody from the first of the seventh, that would be one bucket just for that week. Now, if I wanted to kind of, you know, have a dynamic list and a, of the next week, I would go through the eighth to the 14th and not go from the one the first before though, I would kind of have it segments. So that way the older list isn't polluting the more recent, real time, real time data.

Speaker 2 (33:06):

And this could be your, this could even be your CRM data. So this is like a map. Like if you're, if you're not going to be real time, just, I mean, this is a test that people can go do on their own to prove this, you know, this is like, they're getting a lift from just creating a brand new custom audience. Now, is that strategy the best strategy? No, but I mean, really you can't beat real time is as good as it gets. This is that. So when you identify, for instance, like an e-com situation, um, you know, there's all, all of this on, on page identification from like number of times to site time spent on site, certain types of products that somebody looking at, you want to be specific in your segmenting, but things like off, off page transaction history, have they made transactions so offline data events more or less, right?

Speaker 2 (34:05):

So we'd basically be, uh, API APIs and, and using non, non PII, personally identifiable information I can grade or score somebody based off of transactions. I don't even need to know what they bought. I just need to know that they're, they're actually transacting. Like they you're selling t-shirts or whatever, you know, something expensive. You want to know that this person has a transaction history. Yup. And how recent, so that kind of data will make all the difference in our score because now that I'm building segments based off of behavior, right. And transaction history is a heavily weighted behavior to say, these people are not only behaving, like they're in the market, they're able to buy. And if you create a custom audience of those people, the garbage in garbage out, right. There's no garbage in that custom audience and it's in real time. So it's the timeliest audience.

Speaker 2 (35:07):

You create a look like that, that it's going to kill. It'll, that's why it'll beat any CRM or co I mean, if you have enough customers and you're doing the, like every day, you're building a custom audience, that's, that's pretty darn good. I mean, that, that would be pretty hard to beat, but most people don't have enough customers to meet the threshold minimums in the custom audiences to be able to do that and then do it in real time. Right, man, I'm about to go into all my accounts and like make some more recent lookalikes and custom audiences off of this man. But I think I can officially say you've coined, you know, the real-time data and audience creation King man, like this is, this has been super juicy. So I mean, it kind of wrap it all up, go ahead and give everybody, you know, some insights of what's next for you, how to get in touch with you and kind of, you know, how to test y'all out. Um, you can go to [inaudible], um, it's ID ENT y.com identi.com. But I wanna, I wanna, uh, leave something else to like, or before we wrap, but like there's, so my, my, uh, my, what I would call the poor ad, like the strategy that is like the kiss of death.

Speaker 2 (36:29):

So we, you know, we have these winners and our whole goal as a company with agencies and their clients is to basically win as fast as possible within 30 days or less. What I, what I call proof in the pudding. And it's like, you know, if you have a winning campaign, the worst thing that you can do is wreck it. Right? So things that we've seen that have the biggest impact on wrecking a winning campaign. And this is the knee jerk reaction that we basically tell our clients, our agencies, the basically don't do, don't go from spending X number amount, whether it's a hundred or a thousand a day, whatever amount to quadrupling doubling, like you basically will kill the algorithms targeting if you ramp up too fast. So the success for ramping up, especially using our strategies, our techniques of creating these real time audiences and taking, you know, scaling it, it's 10 to 20% per day, maximum increase on your budget.

Speaker 2 (37:37):

If you are staying within those parameters, you're allowing for the machine learning on the platform side to keep pace with you, because, so, do you understand what I mean? So like, if you, if you're spending a hundred bucks a day, don't go to 200. So 15 between 10 to 20% increase per day maximum because to go to 115 hundred 20, as you're aligning that machine learning to graduate up with you, instead of taking it from, you know, this, you know, winning campaign that you're spending, and then, you know, putting 500 bucks a day from a hundred, it's just going to be the kiss of death. And is that more of just because they're going to try and spin your budget. So the quality's going to be a lot lower there in that scenario, doesn't have time to kind of pick, there are kind of a lot of variables, but it sounds like that's kind of, you're basically the platform to just take your money. Yeah. That's basically it like they, and they do as they will. So like, if you want to, to take something that is hyper data centric, like our, our audience strategies and our technology and, you know, incrementally grow it successfully, keep it consistent, ongoing, just don't blow it like that. And, and that is that's, that's my, my, uh, poor ad, uh, avoidance recommendation.

Speaker 1 (39:07):

That's killer. I I've, I've fallen to the kiss of death numerous the way too many times that scenario.

Speaker 2 (39:15):

Yeah. Hell yeah.

Speaker 1 (39:19):

Sweet. So we got, I didn't see. Oh, um, you know, how can people kind of find you Facebook, LinkedIn? What's the best bet there. Yeah.

Speaker 2 (39:26):

Uh, LinkedIn, you know, Gil or Tayga and, um, yeah, identi.com. We're we're, uh, you know, I'm, I'm, we're virtual, so I'm out of San Diego. You live in San Diego, but you can meet up. And, uh, I know Zach. And were you ever living here in San Diego? Was Zach or?

Speaker 1 (39:47):

Well, I've been in Austin for shoot probably eight years now because he had one of my clients like, Hey, one of my buddies is actually moving to town now should link up and we hit it off. So it's kinda, it's kind of a weird story, but yeah, I've been up there a couple of times or conferences, but never lived there.

Speaker 2 (40:00):

Yeah. I just came back in February from the Bay area. I was living up in the Bay area and it's so much nicer weather wise down here. I'm just so glad we moved back to San Diego. So we're based out of San Diego and then bend, bend, Oregon is my, my other, um, partners. They all live in bend. And, um, now there's direct flights for me from San Diego to Ben. So I'm super excited about that, but it hit me up. I'm, you know, we're all virtual now. We like easy to get ahold of

Speaker 1 (40:32):

Hell. Yeah. Yo man, this has been absolute pleasure, man. Thank you so much for jumping on.

Speaker 3 (40:44):

Thanks so much for listening to another episode of the rich ed or ed podcast. If you're like me and listen to podcasts on the go, go ahead and subscribe on Apple podcasts, Spotify, YouTube, and rich [inaudible] dot com slash podcast. And if you absolutely love the show, go ahead and leave a review and a comment share with a friend. If you do take a copy screenshot of it, email me zach@funneldash.com. Show me you left a review. I'll give you a free copy of the rich add or add book to learn more about the book. Go to rich ed for a.com to leave a review that a rich ed for at.com/review. Thanks again.