#34: What do 34,000 landing pages have to teach you about yours? Featuring Sahil Patel from Spiralyze

Summary

Podcast Summary: B2B Agility™ with Greg Kihlström

Episode #34: What do 34,000 Landing Pages Have to Teach You About Yours? Featuring Sahil Patel from Spiralyze

Release Date: December 31, 2024
Host: Greg Kihlström
Guest: Sahil Patel, CEO of Spiralyze

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Introduction

In Episode #34 of B2B Agility™ with Greg Kihlström, host Greg Kihlström delves into the intricate world of landing pages with Sahil Patel, CEO of Spiralyze. The discussion centers around Spiralyze's extensive analysis of 34,000 landing pages to uncover actionable strategies for enhancing conversion rates in B2B marketing.

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Guest Background

Sahil Patel provides an overview of his role and background at Spiralyze:

"[...] I'm the CEO of Spiralize. We're a conversion rate optimization company headquartered in Atlanta. [...] I play guitar in a Rush cover band."
[02:25]

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Deep Dive into the 34,000 Landing Pages Study

Process and Learnings:

Sahil explains the methodology behind analyzing 34,000 landing pages:

"We crawl thousands, 34,000 in fact, websites to find everyone else's A/B tests. [...] Most of the companies we work with are Enterprise Fortune 1000 and above, trying to get someone to take a high intent action."
[05:36]

Key Insights:

1. Borrowing from the Best vs. Anecdotal Practices:

   • It's essential to look beyond anecdotal "best practices" and focus on data-driven strategies.
   • Spiralyze's approach involves finding statistically significant A/B tests relevant to similar companies and industries.

2. Creating a Prediction Engine:

   • Spiralyze leverages the "wisdom of the crowd" to identify effective strategies.
   • This data feeds into a prediction engine that helps clients optimize their landing pages based on proven results.

3. Understanding the Applicability of A/B Test Results:

   • Not all successful tests are universally applicable; context matters significantly.
   • Spiralyze emphasizes testing within the client's specific environment to ensure results are replicable.

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Addressing Common Challenges in Conversion Rate Optimization (CRO)

Pouring Money into Traffic vs. Optimizing Landing Pages:

Sahil critiques the common pitfall where companies focus heavily on driving traffic without optimizing their landing pages, leading to poor conversion results.

"First of all, I would tell them just you're in good company. A lot of really good companies spend a lot on traffic and haven't invested in optimizing the landing page."
[08:26]

Optimizing Before Scaling:

He advises optimizing landing pages before increasing traffic:

"You should optimize that landing page. [...] Give them a dog food landing page."
[11:14]

Restaurant Analogy:

Sahil uses a restaurant analogy to illustrate effective landing page strategy:

"Think of your homepage as the front door to your restaurant. Think of landing pages as the drive-thru window. It does a very specific thing in a very specific way."
[09:05]

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Debunking B Testing Myths in Enterprise B2B Marketing

Common Myths:

Sahil identifies three prevalent myths in B2B enterprise A/B testing:

1. Myth: Show the Product

   • Truth: While showcasing the product is important, it's not always the most effective strategy alone.

2. Myth: Make the Page Easy to Skim

   • Truth: While skimmable pages are beneficial, they must balance with engaging content.

3. Myth: Video Enhances Conversions

   • Truth: Contrary to popular belief, video can cannibalize conversions by consuming users' limited attention.

"The truth is video often cannibalizes conversions. [...] A single beautiful, crisp image of your software beats video."
[14:20] - [16:00]

Detailed Discussion on Video Usage:

Sahil elaborates on why videos might hinder conversions:

"Video uses up people's attention. They have a finite reservoir of attention. [...] Your brain immediately sees, ooh, this looks interesting."
[15:32] - [16:00]

He suggests strategic placement of videos to cater to different intent levels:

"Move it lower on the page. [...] A beautiful product screenshot [...] allows the highest intent audience to continue their journey."
[16:00] - [17:09]

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Balancing Statistical Significance with Business Agility

Optimizing Test Duration and Significance:

Sahil discusses the balance between achieving statistical significance and maintaining business agility:

"The job of CRO, especially in enterprise, is to make the cash register ring. [...] Go fast, kill the losers, kill your darlings, find the winners, be skeptical of the winners."
[17:58] - [19:19]

Scaling Successful Tests:

He advises caution when scaling successful tests:

"Run at least five different experiments on a page before [...] putting more fuel in the tank. [...] Be skeptical of learnings from a single experiment."
[19:49] - [21:33]

Continuous Improvement Over Static Learnings:

Sahil emphasizes the importance of continuous experimentation:

"The world is dynamic. [...] Run a lot of experiments, you have a lot of data."
[22:55] - [23:45]

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Future Trends and the Role of AI in CRO

Network Effects and AI Challenges:

Sahil highlights the increasing complexity introduced by AI-generated content:

"In the era of just AI-generated stuff, it's just harder to cut through the noise. Good landing pages that deliver user delight are a way to cut through the noise."
[24:16] - [25:13]

Integrating Brand and Performance Marketing:

He underscores the inseparability of brand and performance marketing:

"Performance is brand, brand is performance. [...] Both are there to make the cash register ring."
[25:13] - [26:10]

Strategic Alignment Between Branding and Conversion Goals:

Sahil warns against strategies that either ignore branding or overly rigidly adhere to it, advocating for a balanced approach that supports conversion objectives.

"If you run a B tests that don't honor the brand, I don't think it works. [...] Brand tends to be a little more of a longer-term play."
[26:10] - [26:44]

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Conclusion

The episode concludes with Sahil Patel reinforcing the importance of data-driven optimization and the continuous interplay between brand and performance marketing to drive successful B2B outcomes.

"You can't have one without the other. They're both there to make the cash register ring."
[26:11]

Final Thoughts:

Sahil encourages marketers to embrace continuous testing, leverage data from a vast array of landing pages, and maintain a strategic balance between branding and performance to enhance conversion rates effectively.

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Key Takeaways

1. Data-Driven Optimization: Leveraging extensive data sets, like Spiralyze's analysis of 34,000 landing pages, can uncover effective strategies beyond anecdotal best practices.

2. Strategic Use of Video: While videos can engage users, their placement and length should be carefully considered to prevent them from hindering conversions.

3. Balanced Testing Approach: Combining statistical rigor with business agility allows for swift identification of effective strategies while maintaining flexibility.

4. Integrated Brand and Performance Marketing: Successful B2B marketing requires a harmonious blend of branding and performance-driven tactics to drive conversions.

5. Continuous Experimentation: The dynamic nature of the digital landscape necessitates ongoing testing and optimization to stay ahead.

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Notable Quotes:

• Sahil Patel: "The truth is video often cannibalizes conversions."
  [14:20]

• Sahil Patel: "The job of CRO, especially in enterprise, is to make the cash register ring."
  [17:58]

• Sahil Patel: "Performance is brand, brand is performance. You can't have one without the other."
  [25:13]

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Further Information:

To learn more about Sahil Patel and Spiralyze, listeners can follow the links provided in the show notes.

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Transcript

[Greg Kilstrom]

What's the state of your website? If you're looking for a new digital experience platform or DXP to run your digital experiences, I have the book for you. The Agile Brand Guide to Digital Experience Platforms is part of my best selling series of MarTech books. In this book I explore and demystify DXPs and look at the roles a digital experience platform should play, the different types on the market, as well as how to initially evaluate platforms, then how to best implement a DXP once you've selected it. The book also features a forward from Rupali Jain, Chief Product Officer at leading DXP provider Optimizely, as well as several other thought leaders in the industry. Learn more and get a copy in print or digital now by going to the Agile Brand guide website at www.agilebrandguide.com.

[Co-host]

The Agile Brand.

[Greg Kilstrom]

Welcome to the B2B Agility Podcast where we look at the factors that drive success in B2B marketing with a focus on the people, processes, data and platforms that make B2B brands stand out and thrive in a competitive marketplace. I'm your host, Greg Kilstrom, advising Fortune 1000 brands on MarTech marketing operations and CX best selling Author and speaker. Now let's get on to the show.

[Co-host]

Are your landing pages truly working for you? Or are you caught in a cycle of driving traffic to pages that fail to convert effectively? Today, we're excited to welcome Sahil Patel, CEO of Spiralize, a company that's crawled 34,000 landing pages to find everyone else's AB tests. He's here to share actionable strategies for improving conversion rates, debunking common testing myths, and escaping the trap of underperforming landing pages. Welcome to the show.

[Sahil Patel]

Sahil Craig, thanks for having me. Really glad to be here.

[Co-host]

Yeah.

Looking forward to talking about this with you. Why don't we, before we dive in here, why don't we start by you telling us a little bit about your background and your current role at Spiralize.

[Sahil Patel]

Happy to do that. I'm the CEO of Spiralize. We're a conversion rate optimization company headquartered in Atlanta. Personal stuff on me. I've been in Atlanta a long time, love it here. Moved all around the country and this is, this has been home and I have great family, wife and two daughters. And in my spare time I do music. I play in a Rush cover band which is like the nerdiest thing ever.

[Co-host]

Nice.

What, what instrument?

[Sahil Patel]

I play guitar.

[Co-host]

Nice.

Nice.

Awesome.

Cool. Well, yeah, let's, let's dive in and, and talk a little bit So I want to, I want to start with the, the 34,000 landing pages here. So can you talk a little bit about, you know, what, what the process was and, and just what the learnings were from, from looking at, at so many A B tests.

[Sahil Patel]

Yeah. So the learnings here is you can, first of all, you should borrow from the best and a great place to start. If you're doing any kind of just website design, rewriting your homepage or, you know, gold standard, running an A B test that's producing a statistically significant outcome for your website, a great place to start is just see what other people have done. Yeah, that's not an insight that is new. Lots of people do it. There's swipe files, there's tons of people posting on LinkedIn, do this, do this. And here's the reality. A lot of them are thinly disguised anecdotes dressed up as best practice. Why is it a practice? Because someone calls it a best practice. So certainly one way it's probably better than doing nothing or just sitting whiteboard and being like, well, could we do this? Could we do this? Those kinds of things is how you end up with like the dog CEO on the, on the homepage, someone's like.

[Co-host]

Oh.

[Sahil Patel]

Our competitor did it, let's do it too, or joy boy, wouldn't that be nice? I think a better way to do it is, you know, get, get a sample size of more than like two, right. Maybe 10. That's a good starting point. Now what's even better is can you get a bigger sample size where it's big enough where you can actually say, let, let's, let's find the ones that are relevant to us. They're companies like us, solving problems like we do. Okay, great. Now how do you know which ones to do? Because if you look at five companies, they might have five different homepages and presumably they all are pretty good or they wouldn't be in business. So what we do that's unique is we crawl thousands, 34,000 in fact, websites to find everyone else's AB tests. These are other companies, not customers of us, that are running these tests where they have two pages of their homepage, for example, or a landing page, and half of the visitors see one version, half see the other. They don't know that they're part of an experiment and then they measure the difference. What is the difference? It might be someone clicks, put the shoes in the shopping cart. It might be in an, in an enterprise context by most of the companies we work with are Enterprise Fortune 1000 and above is they're trying to get someone to take a high intent action. Click that talk to sales button. Click that see demo. Now start that free trial. Sign up for that webinar in B2B World, Enterprise World. That's, that's the things you're trying to get people to do. And that's the gold standard. Can you get more people and get if and what we do is we go and find everyone else's A B tests and then we find out which ones work for what kind of companies. Because maybe for cybersecurity companies that sell into really big Enterprise Like Fortune 100, some things work well and maybe for HR tech selling into the mid market, different things work and that's what we do.

[Co-host]

So then, so essentially you've built a prediction engine based on this, right?

[Sahil Patel]

So that's exactly right. That's the data for the prediction engine. And we're doing two things. We're using the wisdom of the crowd to find the signals out of all the noise. And then when we find those signals, we run those with the client, with our customers and that helps us. When we do that, we know exactly what works and doesn't work because we're actually working with those companies to run those A B experiment, A B tests. Experiments on their website.

[Co-host]

Yeah, yeah, but yeah, I mean it seems so then you're benefiting both from your own engine improving itself based on customers, but you're also benefiting from, you know, someone has some crazy idea out there that isn't a customer, but it really works.

[Sahil Patel]

But it works. It works. And the question is, will it work Again, I think the fallacy of a B testing is or one of the fallacies of AB testings because it worked for someone, it'll work for me. Now it doesn't mean you shouldn't at least try it, but often what made it work? And there's no way to know if you're not inside the company, how do you go from the outside in and know like, why did it work? By the way, what does the definition of work mean?

[Co-host]

Yeah, yeah.

[Sahil Patel]

Was it a lot of lift? Was it a little lift? Sometimes people say, hey, I, I have a new, I have a page that just looks better. It's a better ux, it didn't improve conversions, but it also didn't hurt it. That's good enough. I'm just trying to modernize it and make sure I don't do harm and tank my sales pipeline. That could also be work. If you take that idea and you're looking to get like a 10% increase in conversions, you might be sorely disappointed.

[Co-host]

Yeah, yeah.

[Sahil Patel]

So the question is, is it repeatable and is it repeatable in a set of circumstances that apply to you? Because what works if, if you're a, if you're selling into the big, big enterprise and you're a cybersecurity company and you do some kind of really out there idea, take a big swing and it works. I don't know that that necessarily works. If you're again I'll use exam for you're selling into mid market HR tech and vice versa.

[Co-host]

Yeah, yeah.

[Sahil Patel]

So by all means do out there things, try be an experimenter. But your best chances of success are has the result been repeated?

[Co-host]

Yeah, yeah. Well.

And so those that also are struggling to get those results, a lot of them are just pouring money into driving traffic.

[Sahil Patel]

Right.

[Co-host]

You know, it's, it, it's like if you can't or if you don't know how to improve your page or lack the capability to, then you know, I guess the solution would be let's throw money at the problem and, and a lot of advertising. So you know, we've got a lot of companies investing heavily in paid traffic to landing pages but they're not seeing results. What, you know, what would your advice be to, to these companies that are, that are pouring, you know, good, throwing good money, potentially not after good results.

[Sahil Patel]

First of all, I would tell them just you're in good company. A lot of, a lot of really good companies spend a lot on traffic and haven't invested in optimizing the landing page. And you know, the first problem mostly often is dog food ad, cat food landing page.

[Co-host]

Yeah, yeah.

[Sahil Patel]

So if you have a, if you have a great hook on your ad, which means someone clicked on it, you're getting, and you're getting the right people to click on it. You should just repeat that and it should be obvious when someone reaches that landing page number one, number two would send that traffic to your homepage.

[Co-host]

Yeah.

[Sahil Patel]

Here's think about it this way. I'll take a restaurant analogy. Think of the homepage. Think of your homepage as the front door to your restaurant. Think of landing pages as the drive thru window. It does a very specific thing in a very specific way. And if what you want is takeout food or you want to go to the drive thru because you're going to get a certain kind of experience, can be in your car, you're going to speak to someone and pull up, you pay and you get the Food that is not the place where you want someone to welcome you to the restaurant, ask how your day is, encourage you to have a drink and linger.

[Co-host]

Yeah, yeah, well. And I mean some of this also speaks to, and you, you touched on this already as well. Is like what is the measure of success? You know, of success. So in other words, like if the measure of success is that you get a high click through rate on ads, then to your point, if lots of people click on dog food ads, but you're really selling cat food, that advertise, the advertising team is like, yay, you know, we did a great job, we got a lot of people to click. Landing page team, not so successful. Right, yeah. So.

[Sahil Patel]

And sales team even worse. Or the leads.

[Co-host]

Right, right, exactly. So I mean, is this just, is some of this at least just indicative of the need to close the loop and see what actually dry, you know. So in other words, a landing page is only as successful as the inputs and the outputs.

[Sahil Patel]

I might put it a little bit differently than it's only as good as the inputs and the outputs. If you're, if you're, if you're, let's just take the scenario of paid landing page where you're getting paid traffic, a search engine ad or say a social media platform that brings people there. There's a pretty good chance, let's say it sends you a hundred people a day. If you're lucky, one of them will convert. The data shows somewhere in that other 99 there's people that want to convert. You just didn't give them an experience that they found compelling.

[Co-host]

Got it?

[Sahil Patel]

Now you could spend money to, instead of a hundred people coming to your page, you get 200 people to come to your page. That might get you one more person. But before you do that, I would say optimize that landing page. You're going to have actually the same inputs, right. The same traffic, same quality. You're not spending more, you're not changing your keyword bidding strategy.

[Co-host]

Right.

[Sahil Patel]

You have a great, you have a dog food ad, give them a dog food landing page. Now let's, let's apply that to Enterprise Fortune 1000. No one's selling dog food here. You're selling enterprise software. That's complex, a long consideration cycle. No one's buying cybersecurity vulnerability, scanning perimeter security platforms based on, you know, an ad or, or even a landing. Yeah, but they, but if you, if they find something that's compelling, I might go, oh, well, I clicked on the ad because I was looking for something in this Category, especially if it's a non branded search term. And this looks interesting. I do want to talk to them or I do want to go to their webinar or I do want to read this article or this white paper. And somewhere in that 99 out of the hundred that didn't convert, there's a lot of opportunity. There's going to be a mix of the higher intent, the lower intent, middle intent. That's what the game is mostly one in the middle intent. Yeah, the high intent. They almost are going to convert. You could do anything. You could give them the world's worst landing page. They're just so high intent they're going to do it anyway. And the low intent, they're just not, they're not there to convert today. They're, they're learning. This might be the first time you might be a challenger brand to them. They just might be doing some research. Totally fine. Maybe you don't, you, you want, you don't want to turn them away, but that's not where the game is. The game is one in the middle and ten.

[Co-host]

Yeah.

So I mean, you've seen a lot of landing pages. Obviously your, your software has seen thousands and thousands and probably many variations of each of those tens of thousands. What are some of the, you know, myths, misconceptions that you know, that you've encountered when you have customers or people approaching to do a B testing with their landing pages?

[Sahil Patel]

Yeah, I think there's three, three myths that I can share specifically in the kind of the enterprise world of a B testing. So number one is showing the product. Number two is making the page easy to skim. Number three is I'm not giving you the myths, I'm giving you the truth. So the truth is show the product. The truth is make your page easy to skim. The truth is video often cannibalizes conversions. Okay, so let's, let's, let's unpack those. Which one? Actually, Greg, maybe you know, the audience. This is your audience. Which one of those three do you think you've seen most often or do you think maybe the people listening today will find most. Most interesting and we can, we can unpack one of those.

[Co-host]

Yeah, I mean, I think the video one might be, might be interesting.

[Sahil Patel]

Yeah, yeah, video is a good one. So our data shows video tends to cannibalize conversions. Surprising to, to companies I work with and they have these high. And it's not. The videos are well produced, they're compelling. They're right. And they, and they hear me saying, oh, Video conversion. How could that be true? Video uses up people's attention. They have a finite reservoir of attention. They might be willing to spend 30 to 60 seconds on your website and you have a 40 second video and now you leave them with 20 seconds to do everything else. And the answer is not okay, let's make the video 15 short. Video is of course, has a place. What video does is it sends your highest intent audience off onto this thing that eats up their, their attention. So what, what I've seen work. Well, first of all, it doesn't mean kill video or all video is bad or video by the way, doesn't mean video doesn't work. I was literally on the phone call before we got on today looking at an a B test where video beat something else.

[Co-host]

Yeah.

[Sahil Patel]

So again, you should test it. Don't. None of these are. That's, that's why you test everything or you should test everything. So here, here's what I'd say for especially on like a landing page or a high intent page, should keep video but move it lower on the page. And what works instead, what the data shows, is that a single beautiful, crisp image of your software beats video.

[Co-host]

Interesting. Yeah.

[Sahil Patel]

Why? Here's why. Number one, it's easy to scan. Number two, it doesn't eat up your attention. Number three, your brain immediately sees, ooh, this looks interesting. And it makes them want to learn more. If they're that highest intent audience, the image then releases the audience your. Their attention and lets them continue on the journey. The highest intent, they're there to convert your medium and lower intent. They're not quite ready. They're going to scroll. And that's a great place to give them the video. Yeah, yeah, the video absolutely can work. And then they're like, hey, I've never heard of this brand. I put in a category search. I put in vulnerability scanning software. I'm not looking for any one particular brand. I come to this landing page. I see a beautiful product screenshot. I see copywriting that lines up with the ad I clicked on. Highest intent goes great, I want to learn more or I'm ready to do this. The medium intent go. Hmm, this looks interesting. I need to read a little more. Watch a little more. They're going to scroll. Maybe first or second div, show them the video, how it works, how it integrates with your tech stack customer testimonial. That's a great place to put the video.

[Co-host]

Yeah, nice. Nice. Great.

Well, yeah, definitely, definitely some things to think about. And I like, you know, the recurring Theme here of, you know, you've also got to test this stuff for, for yourselves too. So it's like, it's, it's. No, no two cases are exactly the same. It's, you know, and along those lines, you know, there's, there's often a in, in testing and, and research. There's a, there's an emphasis on achieving statistical significance is how important is achieving the optimal statistical significance versus moving quickly and learning and, and all that, you know, like, is there a, is there an equilibrium there? Or, you know, is there a point where there's too much focus on one or the other?

[Sahil Patel]

I think so. I'm probably going to, there's some CRO people that are going to cringe at what I say and that's okay. I have a commercial sensibility. Look, I think the job of CRO, especially in enterprise, is to make the cash register ring.

[Co-host]

Yeah.

[Sahil Patel]

Full stop. So when you run a test, three things that can happen. The test is a big loser. The test is kind of neutral, a little good, little bad, or it's a big winner. If it's a big loser, you should run it long enough to know that it's, it's a real loser. I don't think you need 95% statistical significance to know something's losing. And I rarely see it flip.

[Co-host]

Yeah. Yeah.

[Sahil Patel]

Okay. Something's neutral. Some edge cases aside, same tested. Big winners are the ones I want to be skeptical of and I want to run those long enough. And I think you should put a lot of scrutiny on any test that's delivering double digit lift. But by the way, if, if you apply that scrutiny and it still wins, you have a real winner. That's, that's stuff dreams are made of. That's why we play the game is to get that kind of double digit lift. Um, so that's, that's my take is go fast, kill the losers, kill your darlings, find the winners, be skeptical of the winners.

[Co-host]

Yeah, yeah.

Well, and then when's the right time to scale? You probably, you kind of answered this, but you know, when's the right time to scale a successful test? Like what, what do you need to know?

[Sahil Patel]

And yeah, tell me more, Greg, about what you mean by scale. A successful test.

[Co-host]

So some of this could be, you know, throwing more ad dollars into driving traffic or potentially rolling out copycats or something like that as well.

[Sahil Patel]

Yeah. So we'll take the first one. You find a winning test. Should you then start, put, put more fuel in the tank and really drive more traffic. I would be cautious on like getting one winner. I like to run at least five different experiments on a page before I. Because what you really want to do is find the winner of the winners. I'll give you an example. I've seen two very different tests. One that goes strong on showing the product, big product screenshots, really giving people that visual enticement. One that goes heavy on social proof, showing logos, trust badges, testimonials, case studies. And both beat the original control because the original control is just not that good. But you gotta pick one version. So you ought to test both and then maybe you ought to run both in a head to head against each other. Yeah, I would do those things before I say, okay, now I'm gonna add 30% more spend and get more traffic here. That's number one. Number two, again, I would be cautious before saying, okay, we did this and therefore we quote, learned something and now we're going to do this for all of our landing pages. I'm very skeptical of learnings. I'm skeptical of the learning, just the world of learnings. And again, there's some very smart, very capable people know more about CRO than I. They're going to super disagree with this. I think most of the time what you learn from an AB test, whether it won or lost, is that it worked for this page, for this audience on this time period.

[Co-host]

Yeah.

[Sahil Patel]

And that's it, full stop.

[Co-host]

I mean, I would agree with that too. I mean that's, that's the whole, the whole idea behind, you know, continuous improvement and all that is, you know, the world doesn't ever stay the same. Right.

[Sahil Patel]

So it's, it's deeply unsatisfying because there's a whole, I think, cottage industry of people who, who've created this, like this. Yeah. Cognitive like learnings. Oh, we learned we're gonna learn something from this losing test. And that means we should never do this again on our website. And I just like, I don't think you know that. I think we can, we can tell ourselves and we want to impute this learning. We, we ran a test and when we showed the customer logos below the call to action, it failed to beat the control. So learning social proof with logos doesn't work. I was like, I don't think you know that.

[Co-host]

Right, right. Well, yeah, I mean it's, it's hard to like institutional knowledge in a very quickly changing world is I, I think it can be a dangerous thing in, in that regard. So. Yeah, yeah, yeah, it, it, it is.

[Sahil Patel]

And it's just not satisfying. It's like, oh, well, we learned something.

[Co-host]

Right.

[Sahil Patel]

The world, it's dynamic. That's why, that's the whole point of a B testing is you're trying to, you're trying to run this kind of clinical experiment and you're attempting, I want to say this, you're attempting to control the variables.

[Co-host]

Yeah, yeah.

[Sahil Patel]

And you can do some things to give yourself control, but don't. I don't. I think falling for the illusion that it's a perfectly controlled experiment, which means you can make this extrapolation. And we learn something now, especially from one experiment, even a few experiments now, I think there's a longitudinal learning that absolutely happens. If you run a lot of experiments, you have a lot of data, by the way, I'm not talking about an outside third party. They have a different kind of learning because they just get reps, repetitions. But I think if you work inside a company, you're working in Enterprise, Fortune 1000 company, and you run experiments for a year, I think you can draw some learnings from that. You can say these kinds of things tend to work and these kind of things tend not to work. And. Okay, great.

[Co-host]

Yeah, yeah.

So one last question before we wrap up here. Just wanted to get your, your thoughts on, you know, what's, what does the future look like? I mean, you know, we, we've barely talked about AI, which is a surprising thing for a podcast in 2024. But you know, what, what's coming down the pipe? What do you, what are you looking for as far as emerging trends or just technologies that are going to help, you know, companies like Spiralize, you know, just do, do your work and do it better.

[Sahil Patel]

Okay. So one, I don't make this an infomercial about Spiralize. Our business has a network effect, A network effect built into it. So that's one of the reasons I'm excited about it. It's not just based on us acquiring more customers and running more tests for customers. We gotta do that. It's how we make money. So we see in business every time someone runs an A B test, but there's many more people running AB tests that don't work with us than do work with us. Sure. And we're crawling the Internet to find all those AB tests. So to our customers, they're benefiting from everyone else's AB tests. And I think that's, that's pretty cool. It's the definition of network effect. The value of the users grows as the number of users grows. Okay, I'm geeking out a little bit. There on network effects. I think in the, I think in the era of just AI generated stuff it's just, it's harder to cut through the noise.

[Co-host]

Yeah.

[Sahil Patel]

And I think good landing pages that they should not surprise people by being bizarre. But I think that deliver user delight are a way to cut through the noise. And there's a false. I think it makes for like good clickbait and I think it makes good like it's kind of like having a beef on LinkedIn which. But I don't do that. But there's a whole school thoughts like you want to create, you know, have something to rail against right there. There's like you know, brand on the one side and then performance marketing on the other side and that they somehow are at odds. And I fundamentally disagree with that. I think they're actually, you might say they're flip sides of the same coin but they're a hundred percent the same coin. And you should do things. Performance is brand, brand is performance. You can't have one without the other. They're both there to make the cash register ring. Now the way you do that performance marketing tends to be a little bit more near term.

[Co-host]

Right.

[Sahil Patel]

You're running ads, you're doing demand gen, you're doing gen capture. And brand tends to be a little more of a longer term play. You ought to be doing some of both. But you know, if you run a B tests that don't honor the brand, I don't think it works. And I think if you let branding kind of get calc and calcify your landing pages where no one is willing to do anything different, I think you also then you damage the brand because both things are going to make, they're gonna, they're gonna hinder your ability to make the cash register ring.

[Co-host]

Yeah. Yeah. I love it.

Well, thanks again for, for joining today.

[Sahil Patel]

Again, I'd like to thank you for having me.

[Co-host]

Yeah, of course.

Yeah.

I'd like to thank Sahil Patel, CEO of Spiralize. To learn more about Sahil and Spiralize, you can follow the links in the show notes.

[Greg Kilstrom]

Thanks again for listening to the B2B Agility podcast. If you enjoyed the show, please take a minute to subscribe and leave us a rating so that others can find the show more easily. You can access more episodes of the show at www.b2b agility.com. that's B2 to be agility.com. while you're there, check out my series of bestselling agile brand guides covering a wide variety of marketing technology topics. Or you can search for Greg Kilstrom on Amazon. Until next time, stay focused and stay agile.

[Co-host]

The agile brand.