Transcription
We have just spent the last hour with an agent that we were totally underusing, and it has blown our mind. It is really the best co-pilot for marketeers, and we're going to show you four incredible use cases. Use cases that are going to transform how you think about doing your work. We're going to show you incredible research, amazing presentations, incredible data visualizations, and actual apps, all built within the same agent. You can get all of these use cases and more on this episode of Marketing Against the Grain.
[music]
Hey everyone, on today's show, we are going to show you the world's best market research agent at the moment. And this is an agent that marketers aren't using enough, but doing it is going to give you real insights into how to plan your own marketing, how to learn from the competition, and just quite frankly, how to grow based on learning from the best marketers out there in the world.
Kieran, we're here to talk about something very cool. The company we're talking about, there's actually two. The first one is Manis. Manis.im. And Manis just got acquired by Facebook recently and Meta, and is going to become part of the Meta family of companies, and it's a very good agent. And you and I were early, early users of Manis, I think like 18 months ago, and it's gotten a lot better.
But why we're doing this show today is because they just did a partnership with SimilarWeb. And SimilarWeb is one of the leading providers of market data, market research, specifically marketing performance data on the internet. And you can now very easily access this information on Manis.
Just to tee it up for people, why this is going to be interesting to you, I actually think this is probably the best research agent for marketeers. I'm pretty blown away by what you can do with Manis that is now connected to SimilarWeb. And you're going to, you're actually going to give an overview of like, why, what is the data you now have the ability for an agent to run against?
>> Yeah. So the very first thing I did is just like, what data do you have? You know, what information are you getting from SimilarWeb? And it says it's got YouTube channel data, get unique visit data, traffic source data, bounce rate, global rank, traffic sources, I'm not sure by what. Um, get total visits and get total traffic by country. And it breaks them down in terms of what's actually available. And so you can get traffic metrics, total visits, unique visitors, bounce rate, you can get traffic by geography, traffic by sources, which you and I know is really, really valuable when it comes to marketing, where they rank in the overall like traffic of an industry or of the world. And like, that's pretty cool.
Like you and I have used SimilarWeb for a long time. Full disclosure, I'm on the board of SimilarWeb. I am a shareholder of SimilarWeb. But I just thought this was really cool and wanted to do this because I love how accessible this partnership makes it. I will say, Kieran, the other disclosure is it consumes a lot of credits.
>> A lot of it's not cheap.
>> That's what I'm trying to. It's not like dollars. It's like tens of dollars to do these. So, I just want to make sure that when you're out there, I think it's, you're getting thousands of dollars of value.
>> But you need to know like, one of these queries is probably like five, 10, $20.
>> Yeah, it's not like running a clawed prompt or something like that. It consumes a real amount of credits. I have two things to show. Those two things cost me a lot of credits. A lot of credits.
>> Do you want to show one of your things first before we keep going?
>> Yeah, this one is kind of mind-blowing to me actually, because there's two parts of this because I'm going to introduce a little bit of our old friend NotebookLM as well.
>> We love NotebookLM. Go Google.
>> So basically, the first one I started with was to show you you can do a whole McKinsey. And I know this is really the tired, "Hey, this can all replace McKinsey level consultants," but uh, this actually is a kind of McKinsey level report using SimilarWeb data specifically for CMOs. And I want to kind of show you two parts of this. And so it creates a pretty incredible PDF. And so it has a whole breakdown of competitive intelligence on HubSpot. And it really does pull out some pretty interesting things. And so what we're showing here is the report it built based upon all of HubSpot's data. So it will give me a pretty great overview here of their traffic and audience intelligence. But look here, it kind of talks about seasonality. It talks about some of the overarching trends. It actually builds you these charts.
>> It's really good.
>> I think you're getting a lot of value for the money, Karen. Like this is, this is very good quality. It's really good quality. It shows you this audience profile. So I'm blending SimilarWeb data with external data it can pull from the web. So that's the other thing, right? You can actually blend in the SimilarWeb data. It gives you the traffic source breakdown. So again, it builds this from SimilarWeb data. Shows you what traffic is coming to HubSpot. It gives you the kind of channel mix here and it tells you how they're trending. And it gives you like actual context on their strategy.
>> This is incredible, by the way, to like a breakdown of anyone's marketing strategy for like 10 bucks is pretty incredible.
>> Real [snorts] quick, what we're showing you with Manis and SimilarWeb is basically a superpower, but it's easy to miss the nuances. Our team turned our entire workflow into a free AI toolkit. It gives you the exact prompt sequence we use to pull $300,000 McKinsey-level intel in about 60 seconds. If you want to see exactly how much your competitors are spending and turn that into a board presentation-ready deck without doing the manual labor, you'll love our toolkit. Get it right now. Scan the QR code or click the link in the description. Now, uh, let's get back to the show.
Look at this paid advertising intelligence. It will actually give you a breakdown of our entire strategy. It goes into ad copy and messaging.
>> Oh, that's so good.
>> It actually breaks down our search strategy, talks about the different ways that we acquire traffic, it talks about the different referrals. I went through this and there is so much incredible information in here. And right at the end, I think it actually gives you actionable recommendations. If you were the CMO, what would you change? And I'm going to show you this actual recommendation in a pretty mind-blowing way.
This is a bunch of text, right?
>> Yeah.
>> Now, it's a good report. If I want to impress my CEO and I'm the CMO, then I would probably want a more visual version of this. So, I go into Notebook.
>> Yep.
>> And I simply just create a notebook with this report and ask it to create a presentation.
>> All right. So, you created a new notebook in NotebookLM. You uploaded that report we were just looking at and you just build a presentation.
>> Build a presentation. I'm prepared to like have your mind blown, cuz I am.
>> Let's go.
>> So, look at this. Right. So it basically has a competitive intelligence report for HubSpot. Gives you a breakdown of our overarching business. Tells you the market share, revenue projection, year-on-year growth, tells you where our traffic rank is.
>> Starts to build like this.
>> The financial paradox, operational success versus investor fear. Talks a little bit about us as a public company. The inbound juggernaut owning the top of the funnel. Talks about the monthly blog visits, the domain authority, global. It's so good. How we build a content mode, breaks that all down in a really nice way.
>> See what we've done the last decade. It's so easy and trivial.
>> I know.
>> I know, right?
>> Look at this. The SEO blueprint, topic clusters, and funnel coverage.
>> Like, it pulled all of this from that one report.
>> Talks about how we did this paid defense and ecosystems referrals, paid defense strategy, branded keywords, competitor ads, ad messaging. Then talks about this referral ecosystem we have. So it pulls apart like where we're getting referral traffic from. Talks about the audience profile, competitive positioning, owning the easy and powerful sweet spot.
>> Look at this.
>> So good.
>> Enterprise features, ease of use. We're here, like this is so good. The feature gap where the battle is won and lost. Ease of use, integrated CRM, enterprise ABM, start and price, like it's just totally mind-blowing how good this is.
>> Here's the recommendations. By the way, the move up market campaign, develop targeted marketing for enterprise, create case studies, showcase complex use cases, aggressive AI monetization, shift messaging from "we have AI" to "AI delivers ROI," price cost reduction, international expansion. It picked up on the fact that uh, it feels we are saturated for search in English-speaking markets, but thinks that there's still a bunch of growth in a non-English market. And then this ends with this nice inflection point. HubSpot has won the S&P war. The next battle is for the enterprise to survive the next decade. HubSpot has to pivot from growing wider to growing taller. That's pretty cool.
>> It's an interesting strategy.
>> And then the, yeah. The investor checklist.
>> Agree with all of it, but it's pretty cool.
>> No, but like, as a first pass.
>> Yeah. I mean, you one-shot, you one-shotted this. You one-shotted all of this. You didn't edit the report and then you didn't edit the the presentation.
>> So, it's how quickly you can get from a single prompt to a first draft that you can start to like iterate and improve upon.
>> 100%. So, I think this is what's crazy is that market research like this used to take forever and be way more expensive. I think it's funny how one of the things we said is that this is expensive. It's only expensive in AI research terms.
>> Yeah. Not expensive in the real world, right? Like it's massively cheap compared to the real world. Uh, there are a few other things I did. One of the things that I would say that's simple that anybody can do that I thought was pretty cool, Kieran, is once you have all this traffic data, you can basically model and approximate um, a lot of stuff with it.
>> Oh, I like that a lot, actually.
>> Which is really cool. So this is what I did. I said, "Hey, I want you to look at the paid traffic sources found on SimilarWeb for salesforce.com, monday.com, and hubspot.com. I want you to break down the traffic, its sources, and then use cost benchmarks for those channels to estimate the direct response advertising budget for each of those companies."
>> If you're a marketer, the questions you always get asked are, "How much money should we be spending on marketing? How much is our competitor spending on marketing? And are we getting a good return on the money we're spending on marketing?" And double all of those if it's about advertising specifically. Right.
>> Right.
>> And so this is what it did. It basically runs through, it collects the data and it, Kieran, it's not just looking at traffic. It's looking at bounce rate and and everything to calculate what the budget actually should be. It goes through, gets a bunch of research and gets the traffic data and then it shows you that it's actually looking for benchmarks and so it's actually seeing what the benchmarks is per these channels for cost. And so you could go back and build a spreadsheet or build a model if you had more detailed information and cost that you had. But here, here's the key findings. Monday leads with an aggressive acquisition strategy of $162 million with 92% focus on paid search. Um, Salesforce maintains a conservative brand-focused approach with $53.5 million. HubSpot follows a balanced strategy with $45.6 million. And here's the breakdown.
>> I know some of these numbers, they're all a little low relative to the real world, but they're directionally right.
>> Yeah. And all these charts are built by Manis, right?
>> Yeah.
>> Like it actually builds these kind of charts for you, which is just incredible.
>> So good, right?
>> And so like all of these things you can visually bring to life and send to folks in such a small amount of time. I was actually really impressed by it visualizing the data.
>> It's very good data visual. And Kieran, what I found interesting, and you kind of talk about this in your ChatGPT joke video, uh, you can go back and look at the V3 video in that AI wants to keep you in AI, and so it's keeping these follow-up questions.
>> My biggest hot take here is that most of suggested follow-ups for marketing aren't that good.
>> Yeah.
>> Like, "Generate a new chart comparing the percentage of total traffic from paid channels for Salesforce, Monday, and HubSpot." It's not that interesting. "Analyze the strategic implications of Monday.com's heavy reliance on paid search versus Salesforce's focus on display ads." That's not that interesting. What I want to do is dig in on like specific bounce rates per channel and figure out where the arbitrage is against the competition. Like this is where I think being a craftsperson and really knowing, in this case, marketing, really changes the game because I just, it feels like it 10x's the best marketers is one of my big takeaways.
>> Yeah, I think this is the thing. If you use it and you don't really have clear ideas of how to use that data, you'll do some interesting stuff because you'll ask Manis to suggest ways to use it. But really, the best suggestions come from you.
I had this one here that I thought was like really good. So, one of the things you would want to know in a lot of markets is when could you actually spend money in a much more economical way on paid advertising? And so what this one here did, and this one cost me a lot of credits. So this one here took a fintech and it went through and it finds the biggest 10 spenders in fintech to see because if you're spending in fintech, then you're spending against everyone in fintech for those eyeballs. And so your costs are going to be inflated by everyone who spends money within that market. And so what it does here is I'm trying to look for the peak months of spend and the trough months of spend because during the trough months of spend I can actually spend probably more, cuz the cost will go down because for some reason these brands would spend less, and there's reasons for that. So, first of all, it pulled the 10 biggest like fintech companies, and then uh, it gives me the peak months, right? So, it actually tells me these are the months that they spend the most amount of money, and it will tell me why down here, and then these are the months they spend the least amount of money, the average spend across the 10 companies, the seasonal burst, right? So, Intuit is spending uh, a lot because of tax season. Uh, consistent high spenders, PayPal and Stripe, volatility-driven Coinbase, which I think is actually pretty interesting. I want to know why that is, and then minimal spenders or kind of the more traditional brands.
And then it says like, "Strategic examples: counter-cycle windows offer a better ROI when those brands spend less. Peak cost periods reduce your budget and efficiency gains."
What I think is about this, it was cool, Kieran, is it tells you about like how much spending in those peak times is actually affecting your budget. It was saying like, 20 to 25% reduction in your budget to spend on those peak times. And this is one of those things like the AI is giving you all this information, but you had to know that this was the angle.
>> Like this is the perfect win of like, I'm a good marketer and I can make really much better decisions with AI.
>> Right. This is actually a really good chart.
>> Oh, this is a really good chart.
>> Shows you the above-average months and the below-average months.
>> So basically what you want to do is go contra-seasonal. Spend in the below-average month to get leverage. Then eventually you'll force people to start spending in those months, and then you can go back to the other months.
>> Right. Yeah. Yeah, right. That's the game that we're talking about.
>> I'm definitely going to pull some interesting charts here.
Hey everyone, you know Kieran and I have been doing the podcast for a while now. We've been at this for a couple years. We love it. We could not be happier to be doing this, but we wanted to take things to the next level. We want to level up the impact we're having with Marketing Against the Grain. So, the next step of our journey is something we're really, really excited about. We're going to launch the Marketing Against the Grain newsletter. And the Marketing Against the Grain newsletter is going to be amazing. If you are a marketing leader, practitioner, you're in the trenches doing marketing every day, this is for you. We're going to deliver right to your email inbox and you're going to get all the behind-the-scenes frameworks, practices, tutorials from us, from guests we have on the show, and from people even beyond the podcast that we think are going to be helpful and really have an impact on your day-to-day, week-to-week doing marketing. You're going to love it. It is something we've been talking about for a while. We're really excited to have it out in the world. We've already got 100,000 marketers who are on this newsletter. Please join. It's completely free. We'd love to have you as part of the Marketing Against the Grain community. And it's easy. You can click the link in the description below or you can head to marketingagainstthegrain.com/subscribe.
Anybody watching this video, I think Kieran has been asked to do a competitive analysis report as a marketer. Do you agree with that?
>> Exactly. Yes.
>> So I wanted to see how Manis and SimilarWeb were doing on competitive intelligence. This is a classic use case for market research. Right.
>> So using data from SimilarWeb, do a competitive analysis of HubSpot.com and Salesforce.com. Please highlight strengths and areas for improvement. I want to make HubSpot.com better. So I tell it that, like I'm trying to make the website better. Okay. Something you and I talk a lot about. It's like, how can we make the website better and work better for us? And so what's cool, it does tell you how many credits it's going to use and everything. So I told it to proceed. So you're not blindly spinning credits. It goes through, does a bunch of thinking and gives me some really cool insights and we could go through and talk about these insights. It gave a cool report and graphs, but then I was like, "Can you just make a slide deck of these findings?"
>> And do you want to see the slide deck here?
>> Oh, wow. Actually,
>> Hold on. I'm going to open the whole deck for you. You ready? This is literally [laughter]
>> Oh, mind-blowing. I I thought it was cute you were putting it in Notebook.
>> I didn't even think about it.
>> Here.
>> Wow.
>> Quality over quantity. Scale disadvantage. Salesforce attracts 169% more visitors, demonstrates significant scale advantage. Engagement. Excellent. HubSpot achieved superior user engagement with a bounce rate of 22.56% compared to Salesforce's 35.73%. Um, our our rankings have declined. There's a referral opportunity. Salesforce commands more traffic. It's pretty good.
>> It's so good.
>> This wouldn't be a board-level presentation because it's really more about the website than like total business strategy. But
>> This is as good as NotebookLM or GenSpark or any of the other
>> I think it's using NanaBanana.
>> Ah, okay.
>> Because remember, and a lot of these agents are aggregators. They're using the best model for the best use case. And so it's creating this kind of all-in-one experience. Scale paid advertising to boost visibility. Like it's pretty good. And these were shitty prompts. And like if you and I jammed on this for like 20 minutes with Manis, it would be very good.
>> Oh, you could make it amazing.
>> It gives you a 90-day action plan Q&A. Like, and I gave nothing about like the format, what I want covered in the deck. This is just like what it thinks is right. I think that's the thing we're kind of showing how impressive it is with the SimilarWeb data. I think that is like one of the things that makes it unique. SimilarWeb data is an incredible set of data, especially for marketers. But it is an all-round agent. It can like pull in information from the web. It can reason. You're showing that it can actually create incredible presentations. It can actually create incredible graphics. What we showed as well, the data visualization. I'm incredibly impressed by it. I think I've been underusing. It's a really good product that I think we both have been underusing.
Well, one of the things I think it's really important if you're watching the show today, you're a founder, you're a CEO, you're a marketer, you can have the smartest individual model in the world, it's only good for certain things. So these aggregator agents are really good. And then if you want to take these aggregator agents to the next level, that's what context is about. And I think one of the things you and I believe, Kieran, is that the best AI is not the smartest AI, it's the AI that has the most context. And this is an example of, hey, we have all the SimilarWeb context in Manis now, and there's a bunch of cool stuff we can do for marketing.
Can I show you one other thing that I did, Karen?
>> Let's do it. Let's leave it with a bang.
>> I like that this podcast is awesome. Often just you and I like showing what we
>> Yeah. Well, this is a good version of the podcast because like, it's literally just you and I re-educating ourselves on an agent that we're going to start to use all the time.
>> Totally. Okay. So this is the rest of the thread I actually started the show with, which was, oh, this is the type of data you can get. So one of the things I've always been fascinated by, Kieran, and I I still can't do unfortunately, is I always want to know like, what are the top 100 or 10,000 fastest growing websites and what are they doing that I should be doing?
>> Yeah.
>> And unfortunately, you can't do that, but you can do it by industry.
>> Yeah. And so what I did is I was like, "Okay, just give me the top 10 SaaS websites by traffic growth." And it goes, "Ask me the credits." Yeah. Yeah. Yeah. Shows me what those are.
>> Um, but and this is not by total visits. This is by growth rate. Growth rate. Very specific because
>> This is really interesting.
>> It's very interesting. And so it gives us this really cool report, which is awesome. It shows what these companies are. And Kieran, I think what you're going to be impressed with is some of the observation. Post-pandemic normalization. Totally agree. AI AI power tools are thriving. Enterprise versus SMB. It tells you the methodology and then it's showing you like who the winners are. And these results suggest consumer-facing SaaS platforms and the AI productivity tools. It also gives you a CSV of the actual data too, Kieran, so that you can go do stuff with it, which is wild.
But uh, you can go through and I had it do a more detailed analysis than that first one, and like how are these companies growing? Product-led growth, searches, acquisition, paid channels, and give us an actionable playbook of what to go and do. And that would be cool. And like I can show you what this is, and it's like breaking down all of the playbooks and like, oh, this is Shopify's playbook and what you should do. But you know what would be better than that, Kieran?
>> Is I had Manis go and break down three different homepage designs for HubSpot.com based on these lessons and it mocked them all up.
>> Oh my god.
>> So [laughter] So there's three different uh
>> Okay. So yeah, using NanaBanana.
>> Yeah, a homepage mocks here and some of the font and stuff isn't great, but you can kind of see what's actually built them.
>> Yeah, [laughter] of course.
>> Oh my god, this is insane.
>> And you know, "Stop losing deals to disconnected tools. HubSpot's all-one platform unites your marketing." So it's doing the copy. It leads with customer proof. I actually think there's a lot of this homepage that designed that I really like. Like that's a good graphic, actually. I can't believe that it coded all this up from. This is actually really impressive.
>> It's really good.
>> It's kind of doing what like Lovable or Replit or these things would do in the webpage.
>> Now you know why Meta acquired them.
>> Yeah.
>> I thought these feature call-out boxes it did for marketing.
>> Nice little hover function.
>> Yeah, it's really good.
>> And Kieran, this is just one of the options it coded up for us. But what's really cool is the speed of which you can take these insights of like, oh, let's go research what really good companies are doing. Let's learn about what those really good companies are doing, and then let's apply them directly to what we're doing. And by the way, Kieran, you can then go and publish this to share it with people immediately.
>> I have a really good idea. I won't say that loud 'cause I'm going to build it and then we'll do a show on it. I have a really good idea to do something and give it away to our listeners. Like something we can build that would help them a lot and give it away.
>> Uh, you heard it here first. This is super important.
>> Subscribe if you want what Kieran's about to drop.
>> What I think the main question was as we wrap up here is, "What the f do I cancel so I can pay for this one?" Because [laughter] it is becoming unwieldy the amount of money I am spending on AI tools, and I don't know, they're all so good. I kind of feel bad. I I feel like I can't not have them all, but like, this kind of can do so much. You were a total Manis detractor, and now you are like, "Hey, I want to be a top-tier Manis subscriber."
>> I want to be a top-tier Manis subscriber.
>> I I want to jam on some of this stuff.
>> I am going to try to build a little premium app using Manis, something you just did actually, but put into a little app and give it away to our listeners on a future show.
>> So, hit subscribe if you want to get that from Kieran.
So I I think the big thing here, the big takeaways from today's show is context-aware AI agents are the best, and Manis with the SimilarWeb data context now unlocks some really high-value, high-ease-of-use use cases for marketers, right? And if you're a marketer and what we showed resonated, you should go and build and try some of these. The second thing is these all-in-one agents that are using multiple models are really valuable because it allows you to switch type modalities there where you can go from research to design to building all in one thread, which is really, really powerful, and you're using the best model for the job. And I think those two things are really important takeaways. And if you go and you use this or you've been using the Manis-SimilarWeb integration and you've been building cool stuff, drop us a comment. We'd love to hear what you've learned, what you've been building here.
Kieran, anything else before we close out today's show?
>> No, I think this is an incredible new tool that maybe most marketeers are sleeping on, and so I think it's a tool worth adding to your arsenal.
>> I think this announcement really flew under the radar. Manis has flown under the radar, and SimilarWeb, I think quite frankly, flies under the radar sometimes, and this is like, I think now should be in most marketers' tool belt. All right, go get it.
>> Thank you everyone. We'll see you real soon. Hit that like. Hit that subscribe. We'll see you real soon on Mark the Grain.
This data is wrong every freaking time. Have you heard of HubSpot? HubSpot is a CRM platform where everything is fully integrated. Whoa. I can see the client's whole history. Calls, support tickets, emails, and here's a task from three days ago I totally missed. HubSpot. Grow better.