In this live Q&A replay, Neil Patel, Eric Siu, and co‑host Jerry Chen discuss three main themes. First, they explain why their agencies have not merged, highlighting fundamentally different business models: Siu’s pay‑for‑performance focus versus Patel’s volume‑driven, multi‑office approach, and the risk of strategic misalignment. Second, they detail the data pipeline behind Patel’s coronavirus articles, describing a blend of third‑party providers, agency client data, and Ubersuggest’s own database, the massive scale of the dataset (millions of sites, with chart‑specific samples ranging from thousands to hundreds of thousands), and the technical and legal constraints such as privacy laws, anonymization, and Google’s strict data‑access policies. Third, they address the ethical question of profiting from a crisis, with Patel asserting a philosophy of helping people rather than exploiting the situation, noting that while monetization is possible, it should not compromise public trust or cause negative PR. The conversation is informal, conversational, and balances practical insights with ethical reflections, providing a snapshot of crisis‑marketing strategy, data methodology, and moral considerations.
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Why have yourself and Neil not yet merged to create one agency? This is from Justin Lester.
That's a good question.
I think different approaches. Eric started before me.
Technically, you started before me.
No, you had Single Grain before me.
No, but you had ACS.
Yes, but then when you had Single Grain, I had no more ACS.
That's right.
That's right. You had Single Grain. And then I think our agencies just have different strategies and overall concepts. You know, merging could work. There's nothing wrong or right with it. It's just, we have our different strategies.
I think it's a different approach, right? Because if you think about it, Neil, like you and I, we talk about this a lot. Like my approach long-term is to build a pay-for-performance type of thing, right? Correct.
I was just going to mention that. You're trying to go performance.
And, but for you, like you're building, you're building a lot of, you're building volume and you have a bunch of offices around the world, right? So it's just, to me, it's a different business model.
Correct. So when you're thinking about merging with someone else, you want to make sure you're merging with someone else who has a similar strategy, because the last thing you want to do is derail what you're doing and adapt a different strategy or have too many strategies going at once. It doesn't mean that the other person has a bad strategy. It's just each person has to figure out what's right for their business. And if you're growing and you're happy with your growth, the last thing you want to do is Start going in 10 different directions because all that's going to do is just create chaos.
Exactly. That was a really good question. So Jerry's actually got 2 questions and 2 upvotes over here. Noah, do we want to make him go live? So Jerry, make sure you put on a shirt and then we're going to answer you live so you can ask this.
Let's see.
All right.
Jerry Chen is the co-host now.
Oh, wow. It's full-on podcast setup.
Yeah. Hi guys.
Hey.
Good to see you. Hi, Neil. A big fan of yours for years.
Thank you.
So let me go straight to the heart of the question. So I read your article regarding the coronavirus situation. It was a very, very nice thought-out article. My main question was where the data came from. And then the follow-up question is, you know, there's a bit of a fine line between exploiting the situation versus profiting from it. I hear both sides of the argument. So I would love to have your input on that. Sure.
So data comes in combination between third-party providers that we buy data from. EX Data for SEO is like one of them. We have a ton of third-party providers that we buy data from. Second place comes from my ad agency. We just have a ton of data, so many customers because we have 7 offices around the world. And then third place is Ubersuggest, of course. A combination of all of them and then engineers doing their magic is what allows us to come up with data. It's also why when my article, I broke down, sometimes I don't have all of the data, like with the paid stuff. I didn't have— I did 2 coronavirus articles, but in my first one, I couldn't do as many charts when it came to paid traffic in related to coronavirus, because I just didn't have enough of a large enough dataset, if that makes sense. Because you would have to have a large enough dataset for each industry to get the results. And then as it comes from exploiting it or not, I'm a big believer in just not trying to exploit things. Yeah, you can make money. It could not— maybe you don't get any bad PR. Most people don't actually get bad PR from exploiting it. Just ethically, I'm a big believer in Helping people out in a time of need and not worrying about yourself, because there's always someone out there who's struggling more than we are, right?
Yeah, for sure. So thank you for that. So back to your first answer, how big is the actual dataset that you were looking at to compile that data? Because, I mean, we're only as good as how reliable our data sources are, right?
Sure. It's in the millions.
Got it. Got it.
It's a lot of data. So depending on the chart, some is in the thousands, not like 1,000. I'm talking about like tens of thousands or hundreds of thousands. I don't have the exact answer on the dataset, but like we literally have data on millions and millions and millions of websites. Now we can't use all of it. So it's not as simple as just saying, here's someone's traffic stats. There's a lot of privacy laws. anonymizing data, but majority of it, we actually buy through third-party providers versus using our own database, because we tell our customers when they sign up, we won't do malicious things and abuse our privileges, because that would just be wrong. Plus, people authenticate through Google. Google's very strict on what you can or can't do, so they protect users very well. Shockingly, it's not as simple as someone signing up for Ubersuggest and us being able to do whatever we want. One, we wouldn't do that, but Google's very protective on what you're allowed to do and what data you're allowed to see.
I see. Awesome.
Cool. Thanks, Jerry.
Thanks for your question. Thank you.
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