Why Gemini 3 Is A Godsend For Marketers

1 Dec 2025 · 23 min

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Marketing School Podcast: Episode Summary

Episode Title

Why Gemini 3 Is A Godsend For Marketers

Hosts

  • Neil Patel
  • Eric Siu

Episode Overview In this episode, Neil and Eric discuss Google's Gemini 3 and its implications for marketers. They delve into how advancements in AI tools like AI Studio, Nano Banana, and VO 3.1 are changing marketing workflows for SaaS founders, AI tool developers, and the overall marketing landscape. The conversation also touches on the competitive dynamics between Google and ChatGPT, the impact of AI on startup economics, and practical insights for optimizing marketing methodologies.

Key Concepts and Discussions

  1. Gemini 3's Impact on Marketing
  2. AI Studio: A tool that allows marketers to create and manipulate content efficiently.
  3. Nano Banana: Enhances creative content generation.
  4. VO 3.1: Facilitates video and audio creation with ease.
  5. Real-world Applications: The hosts share how these tools can streamline marketing tasks and improve productivity.
  1. The Competitive Landscape
  2. Google vs. ChatGPT: Neil argues that Google's vast data resources will allow Gemini 3 to ultimately outpace ChatGPT in the long run.
  3. TPUs vs. NVIDIA Chips: Discussion on Google's Tensor Processing Units and how they lessen reliance on NVIDIA technology, affecting market dynamics.
  1. Startup Economics and AI
  2. AI Startups as a Bubble: Eric shares his belief that while many AI startups may be overvalued, established companies are making real progress.
  3. Efficiency vs. Adoption: The hosts discuss the challenges of AI adoption in companies, focusing on the need for better efficiency and reduced "AI slop."
  1. Hiring and Team Scaling
  2. Hiring Practices: The conversation includes how differing generational attitudes affect hiring practices and the importance of candidates understanding business metrics.
  3. Scaling Teams: Neil and Eric emphasize the importance of setting standards and processes when scaling teams in growing businesses.
  1. Quantifying Success in Marketing
  2. KPI Focus: The need for marketers to align their strategies with key performance indicators (KPIs) and business outcomes is reiterated.
  3. AI Literacy: The hosts discuss the varying levels of AI fluency among their teams and how this impacts overall marketing effectiveness.

Episode Highlights

  • Personal Experiences: Neil and Eric share anecdotes regarding their own companies' growth strategies, hiring practices, and how they navigate internal bureaucracy.
  • Tools and Strategies: Discussion of various tools and workflows that can help marketers improve productivity and creativity.
  • Future of AI in Marketing: Insights about where the AI industry is heading and how marketers can prepare for upcoming changes.

Conclusion The episode wraps up with a call to action for listeners to implement these insights into their marketing strategies. Neil and Eric encourage engagement with their platforms for further learning.

---

Additional Resources

  • Growth Newsletter: [Leveling Up Newsletter](https://levelingup.beehiiv.com/subscribe)
  • Marketing Assistance: [Single Grain](https://www.singlegrain.com/) and [NP Digital](https://npdigital.com/)
  • Recruiting Marketers: [Marketing School Hiring](https://marketingschool.io/hire)

Episode Credits

  • Hosts: [Eric Siu](https://www.youtube.com/@LevelingUpOfficial) and [Neil Patel](https://www.youtube.com/@neilpatel)
  • Subscribe for daily marketing insights!

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Transcript

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0:00Dude, have you seen Gemini 3? Yes. Have you been using it? Yes. I think it's a godsend for marketers. You look excited about it. I can tell you've actually used it. This is not BS. So how do you feel excited about it? What's so exciting to you? Haven't I been saying since the beginning that I believe Google is going to catch up and dominate and not necessarily make ChatGPT go away, but they will become a dominant player in this space? You have. To your credit, since the beginning, three, four years ago, you have said this. because I'm a big believer that data helps you create the best LLM and Google has more data than anybody and than anyone else.

0:37And if you look at the person who created ChatGPT, they came from Google. And then Sergey Brin decided to come back in and just handle crap himself when they lost their person and eventually losing their race. What is this bureaucracy? This is stupid. Have you seen the All-In interview? This is so dumb. No, we're just going to do this. He's like, and then someone gets in his way. He's like, he goes, what's his name? Sundar. It's like, Sundar, just deal with this person. Like, he just doesn't have to deal with it, you know? But only founders can do that in an organization. Founders have a Jason Cohen.

1:05Remember Jason Cohen from WP Engine? WP Engine, yeah. Yeah, so when I did the interview with him, he's like - And smarter bear. Yeah, and smart bear. A smart bear. So he was like, founders have this invisible hammer where they have the only power to actually go around and make these types of moves. And when someone comes back in and does this, only the founder, not even Sundar, can do this. Yeah, because you know what? When founders want to do stuff - And I'm not Sergey Brin and I don't think like him. I'm not a crazy mathematician or anywhere near as smart or successful. But generally speaking with founders, we don't look at things like budgets and, oh, this is what's realistic.

1:46It goes right over my head. We're planning and politics. It's like, well, I just want to do this. I don't really give a crap what anyone else thinks. I want to do it. And the same goes with our company because we're recording this podcast literally on Black Friday. Yeah. And we have most of our 2026 budgets set in stone. So I get a text message from Mike. Co-founder Mike? Okay. My co-founder Mike, right? And Mike's like, yo, you know, I want to hire this developer and get him to start sooner because we already have a hiring planned out for 2026. Okay. Keep in mind, we haven't started the year yet.

2:24So you know if this is how we start the year? Yeah, it's going to go off. It snowballs and makes it even more worse. It's probably going to irritate people over time. So the question is how quickly will it irritate? Not if it's more so how. So like this is our budget for 2026. You didn't say that. Your finance said that. Our finance says. So they send us the budget per division. So Mike and I hop around different divisions whenever we decide right now we're in the software division. when you hire an engineer as you know it's not necessarily that you have a budget for 2026 per engineer it's also when do they start because if an engineer costs to keep the math simple 120 grand a year that's 10 grand a month i know there's other miscellaneous costs payroll costs hr etc yeah yeah but let's just say it's 10 grand a month well if this person was planned to be hired middle of the year you would only have 60 grand worth the expense and not 120 grand so Mike's messaging me the other day and he's like yo dude I want to hire this engineer sooner and do this and oh by the way it'll cost us 96 grand that's not budgeted yeah and him and I are looking at him like well we have to make all these product changes to really get the product to where we want so I need maybe more engineers yeah so I'm like so why are we waiting to do this well this is the budgeting plan that was created.

3:47And I'm like, yeah, we were both texting him like, eh, who cares? It's our company. Yeah. Let's just hire him. How quickly can we get him? Well, it's going to take 30 days to recruit him. We already started recruiting. Yeah. Right. And this is for engineers that we're supposed to hire. No joke. That's like give them six months out. Yeah. He's like, we already started to recruit for how many of the engineers? He's like, well, the ones that we were supposed to hire in beginning of the year, we already started. but already started for the four that we're supposed to recruit middle of the year. That's not part of the 96.

4:23He already found one. So you're at 400 now. Or whatever it's going to cost. I don't know what we pay engineer, right? But probably more than that or more than 100 grand a year, depending what country we're recruiting him from. And I don't know what countries we're recruiting him from. But he's just like, yeah, might as well just start getting him now so we can just do all the stuff we want. I was like, okay, sounds good. same with other bureaucracy in a business like the reason our product moves slower check this out so when you have products you have monthly pricing plans right for sass as you know and then we have these things called add-ons so that way people can just like upgrade for different parts of it did you know the add-ons on our system because it has so much more logic it slows down development at estimated 40%.

5:11Wow. 40%. 40%. 40%. So I'm not an engineer. You know this. So I just got on the phone with the engineer. I'm like, so plans are less efficient, right? He's like, yeah. I was like, all right, I got a solution for you. He's like, well, remove all add-ons. He's like, Neil, this would be too complex. What would we do instead? Create a plan for every single add-on. Wait, add-ons for Ubersuggest? What are you referring to? So you're talking about like feature add-ons. Feature add-ons, or I'll give you a very specific example. Let's say you are tracking your rankings and your visibility on chat GPT and you want to do it for Gemini.

5:48It's add-on. So I say, forget the add-ons, just keep plans that we have in our backend that aren't visible on our pricing page. And you can do a new plan for someone who has chat GPT plus Gemini. And then if they don't want that, just drop them to the older plan that just has chat GPT. So a la carte and different bundles, Is that what you're saying? Kind of. I'm just grouping all the add-ons. So let's say if we only had four plans, just have 30 plans. And I broke the sound with my engineer. He's just like, yeah, if you end up doing that, then we wouldn't have. And that speeds up capacity, your development rate.

6:26Yeah, yeah. And I was like, all right, sounds good to me. And he's like, yeah, that works. He's like, you okay with 30 plans? I was like, yeah. 30 plans. How's that going to look? Not visible. on our backend so it wouldn't slow things down. Got it, got it. Okay, that makes sense. This is interesting because literally I'm doing the same thing right now. I was like, there's a sales guy I've been trying to recruit for the last three years. I also talked to my co-founder CTO. I was like, hey, how many more engineers do we need to move this a lot faster? How much faster are we going to go? And none of this is budgeted right away.

6:55This is a bet on the future, right? But all that to say, so going back to Gemini 3 is a godsend for marketers. In what ways are we using it right now? because I've seen so many examples. I'll give you an example. So we've talked about Replit. We've talked about Lovable. We've talked about these vibe coding tools, right? And Google, Gemini, the Gemini AI Studio, the things you can build now is absolutely insane. Like, I don't know if you've tried this, but literally I designed, so I built the front end for a product, right? And then I designed it. I literally went to a website. I took a picture of a product that I thought was cool.

7:30I said, make it look like this. Boom, it makes it look like that, right? And then it's actually finding, because I keep talking about Juicebox and recruiting tool. I was like, I wonder if I can make a Juicebox for like sales and for like partnerships and like conferences and all that, right? And what do you mean by that? I'm a little confused. Juicebox does outreach for recruiting. I already got that part. So what this product is called is Nexus. Gemini actually named this product Nexus, right? So it will basically look for people that we should reach out to partner with, that we should do content collaborations with, that we should do sales with.

8:02and it'll make like a web and like it shows me who I connect with over time and the web will just continue to expand and it will do it automatically like Juicebox so I can make agents doing it. And so I'm just working on that right now and like it's finding real emails, it's finding the right people and I'm like, dude, if I just keep playing with this for like a couple hours a week or whatever and I do it over a couple months, like I can actually build something real, right? Imagine how this is going to be in a year but like this is the first time like sure, Repplet's kind of cool, you know, Lovable is cool but like it hasn't, it's not at this level.

8:31Dude, I think I know everyone's like Lovable is a big company. 200 million. They just broke 200 million. Yeah, in ARR. And they crossed the extra 100 million in like four months or something like that. Yeah, really fast. Yeah, really fast. I believe Gemini and Chad GPT and Anthropic are going to end up in the long run crushing the Lovables. Not necessarily meaning Lovables is going to be worth$0. They're going to take over the market share for that. Dude, because at least for right now, AI Studio, Gemini is not charging me for it. or maybe I'm paying for the pro version, right? But they're not going to, like, they don't care about that so much because they just want to have people using their products and they want them in their ecosystem.

9:10That's how they make their money. It's not from the SaaS revenue. Yes. Yeah. And you've played around with the new Nano Banana, right? The new Nano Banana, you can take a picture of like this and then drag in like a scene that you like and then make like an Instagram feed. Like there's so much you can do with this. I wish we were like 20 years old again because we'd have a lot of time to mess with this. We don't have as much time today. No. Yeah. But yeah, like these people, products that google's creating i think they're moving at a faster pace and doing a better job than chat gpt i think so too and i think this is where um i read something on the information last week because i still have a subscription to the information and it's like sam altman is like basically the article is like how sam moments like oh crap there's like oh crap moment and like internally he's like trying to push the team now because they need to be pushed because this gemini situation like they are starting to get laughed so yeah yeah and i think this is going to really change what is going to happen in the whole marketing ecosystem.

10:06And their TPUs too. So they're not as reliant on NVIDIA chips as the other companies are. You saw the Facebook deal, caused NVIDIA stock to go down. No, what happened? Facebook bought Google. TPU? I don't know what the exact name is, but yes, it could be TPUs. They also have, I know it wasn't their quantum computing. Tensor processing units. Yes. I know it wasn't their quantum computing chips because I'm assuming they're not for sale. But they bought their quote unquote NVIDIA copycat clone. I'm not trying to say it in a bad way. I just don't know which version they bought. But it caused Google stock to go up.

10:43It got close to a$4 trillion market cap and NVIDIA went down. NVIDIA announced a statement. You know how they love their partners. They can do Google because they're a big buyer. But they talked about how they're like a decade ahead of everyone else. and I'm like, you may say you're a decade ahead. Everyone can catch up very quickly and they don't need a decade's worth of time. When your margins are that high, it invites competition, right? And so I think they're probably like three to five years still very, very, very solid. I think NVIDIA is still very solid. That's what I think. What do you think?

11:11It is a solid company. Yeah, this is not financial advice, guys. But Google and all of them will just start dumping a ton of money in and catch up really fast. Yeah, when you have a cash machine like they have, like it's, you know, I was talking to my dad yesterday about this. Like, do you think AI is a bubble? And I'm like, because you have these companies that generate so much free cash flow that are kind of reinvesting into this space, I don't think that is. And then we're actually seeing real world use cases from the AI side of things. And then you look at if we're talking about NVIDIA's, you know, PE, it's not crazy.

11:40I think maybe 90 to 95 percent of these AI startups are a bubble. And what I mean by that is there's a lot of like, I don't know if you're reading this, but I'm seeing on Twitter now, like one of my friends retweeted us. He's a VC. You actually know him. But what's happening is these AI companies will raise a bunch of money. And then what will happen is they'll keep the money. They won't talk to the VCs anymore. And that's how easy it is to raise money in the AI space right now. So I think 95 % of these AI startups are a bubble, but I think the scale-ups are not. When it comes to raising money from startups in the AI world, I believe it was easier six months ago.

12:17I think it is actually starting to die down because there's too many AI-funded companies and they're not doing as well. And we're seeing them. We were talking about Clueli, right? It's obvious they're not doing as well. I'm not saying they're not growing or anything like that, but they must have retracted backwards. They should just become like an influencer agency. That's what they should do. That's not a venture-funded business. It's not. It's not. But what are you going to do? They're very good at finding virality, right? It's like maybe they should just return to capital and go do what they're good at.

12:48Yeah. That's just my thinking here. Um, so anyway, that's why we think Gemini three is a godsend for marketers, also for business businesses as well. I mean, the, the, the AI studio stuff, um, nano banana VO 3.1 is available. Amazing dude. I can, you know what you can do? I mess around with this. I was like, okay, find me the best, like Coca-Cola ads. Right. I took that YouTube link and I went to, um, Gemini for this. And then I was like, Hey, give me a script for VO 3.1. And I just dumped that script and then just like alternated a little bit. So we should be able to get a lot more creative, which leads to another question.

13:23What percent of your company right now do you think you're happy with from an AI fluency standpoint? Like 10%, 20%, 50 %? Per employee, are you talking about our progress in leveraging? Because two different things. Second one. The second one was our progress overall in implementing. I would say I'm probably 30-ish, 40-ish. 30 % of people. 30 % to 40 % satisfied? Call 35%. 35 % adoption rate where it's like, hey, these people know beyond just ChatGPJ, they can do other things that are a little more advanced. For our specific industry and field being marketing. Yes. Yes. Okay. So are you saying 35 % satisfied or 35 % adoption rate?

14:0735 % satisfied. Okay. 30 % to 40%. So we'll take 35%. What do you think the gap is right now?

14:15our biggest problem isn't the adoption our biggest problem is the efficiency so let me give you an example i'll use one that everyone who does marketing can understand let's say you use ai to do keyword research you then take the keyword research you find the gaps between you and your competition and then you focus on writing content and let's say you have humans in the loop and then you're modifying the content okay i would say 35 of the output 30 out of all the people in the organization i'm happy 35 of the time the biggest issue isn't the usage of the product the biggest issue is the slop that's being created with ai part of that slop is technology which i'm assuming you agree with part of the slop that a lot of companies don't want to talk about is the actual people using the ai and not working better at prompting or training and checking uh-huh and checking checking i put as standard if they don't check there's a problem with them and they shouldn't be in the organization if you're not willing to check your work but a lot of it is i wouldn't call it human error it's how humans use ai and if you don't get what you want, you can modify it.

15:38The easiest way is if it's giving you wrong information, you can then end up going and being like, okay, go pull from this source. You can leverage MCPs and you can say, hey, I'm going to use MCPs so then that way I can get a better output when I'm using AI. We already pay for all these tools. We have access to a lot of this stuff, but are they using it correctly and what i find is 30 to 40 percent of the time some of it is people some of it's time but i would say 30 to 40 percent of the time we're happy the other remaining portion we're not yeah and it's just fixing these little things and it's not by age either what we're finding is it takes a little bit longer for us what we've experienced for getting older people to adopt not always but i'm seeing that and not just in my company but across the board but on the flip side with the younger people they're quick to adapt but a lot of times when you give them feedback they believe they know how to do it better and they don't keep in mind business metrics like they'll show like look at all this cool stuff like there's this guy in san diego he's really on top of with ai crypto uh social media marketing specifically out of all marketing channels and he has this gen z lingo like he'll use words like bat not no and stuff like that so sometimes i have a hard time keeping up with him but he updates me on the lingo and what it means and i'm like instead of not no why don't you just say yes but he's like no dude that's not what people say i'm like all right i still say yes or no instead of the not no not no but he'll tell me like, no, dude, this is what's wrong to do marketing with this crypto company.

17:26This is what we need to do. And I'm like, he's like, look how cool this is. And he'll show me something. I'm like, dude, I get this, but this doesn't actually move the bottom line. This company will eventually want to go public. They're large, or they're going to want to sell to someone. They've already raised a ton of money. If we're not getting more depositors and the depositors don't keep trading, it doesn't matter. But look at this cool campaign in the long run, it'll work. I'm like, dude, this is not tied to any KPI. We're getting paid to help remove the KPIs. Dude, like it's just going around in circles.

18:00Dude, you know the Rippling CEO, right? Parker Conrad. So, you know, Brian Halligan, the CEO of HubSpot, I started a new podcast. And I was like, oh, he's interviewing all these CEOs. I'm gonna listen. So I listened to Parker and this is a really interesting tactic that I started trying actually as soon as this week. And so what you just mentioned, if we're talking Gen Z, even a lot of people struggle to be held accountable or talk in terms of metrics. You would agree with that, right? Many people. And so what Parker does is he actually sends recruits that he's going to talk to. He sends them the investor decks, all of these things, the strategy around the company.

18:34His expectation is when you come into the meeting with him, you're going to talk, you're going to have questions and you're going to have a deep strategic conversation. And you can tell by that conversation over 30 minutes or so if that person is, they know what to talk about when it comes to metrics and how they think, how their motor is, right? Then after that, he just focuses on backdoor reference checks and really focuses on, hey, here's the goals of the company. Here's what we're trying to do. But I think that part is interesting. You can share your strategy for the next, let's say you don't have investors, right?

19:01You can still share your strategy for the next six to 12 months or so and see how that person communicates with you if they're just kind of pie in the sky or are they nailing down brass taxes? Hey, what's your net revenue retention? What's MR going to be? Okay, what's your hiring plan? And then it's like, okay, you know that you can have a deep conversation. this is how it's going to be working with this person. I thought that was interesting. That is interesting. Yeah, we're trying. I tried it this week. I tried it on one person, okay? And she could not hold it together. She was just like, she kept talking about herself.

19:31She kept going back to herself. And she might've just asked like two or three questions around the document that I sent, which is the plan for next year. So what will you do with this person? We will not hire this person. Okay. Yeah. And what will you do with, you have a good amount of people on your staff, right? and they probably all don't fit within this formula that you just tried. No. What are you going to do? And unfortunately, so what I would say is, and I think this is a broader thing, which is, this is good. This is actually one of the topics I had in my mind too. I think every time you double as a company, like a lot of things are going to break.

20:04Processes are going to break. People are going to break as well, right? And so some people will scale, like Noah has seen this, right? Some people will scale, some people will not be able to. And it's all about making sure that you're setting the right standards, right? And this is one of the standards. but you also can't like what I've learned too is you can't set too many standards at once. It's gotta be like one big thing at a time. And this is one of those things. It's like, hey, like if you're gonna be a leader on the team or anybody on the team, you gotta be able to speak and tell stories in terms of the numbers because like nobody cares if you bring like, we have the same people on the team too.

20:32They're really on top of like, oh, we're using Figma over here. We're using this over here. Oh, I found this new VO 3.1 hack over here. But like at the end of the day, who cares if it doesn't drive business value? That's right. Yeah. So anyway, that is it for today, guys. Please don't forget to rate, read, subscribe, and we'll see you next time.

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Neil and Eric break down why Google’s Gemini 3 is a godsend for marketers, how AI Studio, Nano Banana, and VO 3.1 change marketing workflows, and what this means for SaaS founders, AI tools, and the future of marketing. They talk Google vs ChatGPT, TPUs vs NVIDIA, AI startup bubbles, and real-world AI adoption inside their own companies so you can learn how to scale teams, budgets, and output with AI while avoiding “AI slop.”

Chapters:

(00:00) Gemini 3 is a godsend

(02:00) Founder overrides, budgets, and hiring

(04:50) SaaS pricing, add-ons, product speed

(07:00) Gemini AI Studio and Nexus idea

(09:00) Gemini vs Lovable and AI tools

(11:00) Google TPUs, NVIDIA, and AI chips

(12:40) Is AI a bubble for startups

(14:30) AI slop, prompting, and MCP usage

(16:20) Generational AI gaps and KPIs

(18:10) Hiring for metrics and strategy

(20:00) Scaling teams, standards, and AI value

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Welcome to Marketing School, one of the top business podcasts with over 61 million downloads. Each episode delivers actionable marketing tips and strategies from two entrepreneurs who truly practice what they preach. The show is hosted by Eric Siu, founder of Leveling Up and Single Grain, and Neil Patel, co-founder of Neil Patel Digital and recognized by Forbes as a Top 10 Marketer.

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