Honest Marketing

Michelle Bassett: How Smart Data Use Boosts Digital Marketing

• Honest Podcasts • Episode 53

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Do you feel overwhelmed by the waves of new technology strategies such as AI, SEO algorithms, and sophisticated data analysis? 

This episode dives into all these challenges providing valuable insights to boost your marketing. I’m joined by marketing pro, Michelle Bassett, with a diverse background in behavioral analysis, data science, and internet marketing. 

We traverse her interesting journey from working at Yellow Pages to becoming a data scientist, and how she combines her unique expertise to succeed in digital marketing. We also touch on the influences, like the role of psychology, and palpable challenges faced in the industry, shedding light on how to adapt quickly in this ever-evolving field.

Dig into this episode for some serious nuggets of wisdom from Michelle and fuel your marketing strategy.

Specifically, this episode highlights the following themes:

  • How data use and behavioral analysis shapes up internet marketing
  • Insights on the impact and implications of AI in SEO
  • The significance of clean data, budget considerations, and foundational principles in digital marketing

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And if you have a guest in mind who you think would be a great fit for this show, drop me a line at hello@honestpodcasts.com. 

Michelle Bassett [00:00:00]:
What I do is before I start anything, I make sure that whatever data I'm going to get will come through clean. So I make sure that all my Google tags are set up, I make sure all my conversion rate checkers are set up, I make sure all my goals are already in the system, and I test that first.

Travis Albritton [00:00:21]:
Welcome back to the Honest marketing podcast, where you learn proven strategies to grow your business without selling your soul. I'm your host, Travis Albritton, and my guest today is Michelle Bassett. Michelle has a very wide ranging background, from behavioral analysis to data science. And Internet marketing has been around since the very beginning or close to the very beginning of search engine optimization and conversion rate optimization and all those kind of things, working with big brands and small companies. And so we really touch on a lot of different topics. Definitely encourage you to use the chapter markers or the YouTube timestamps to skip around to the topics that are interesting to you. But we talk about things like how behavioral analysis feeds into conversion rate optimization, the value of data and understanding your data, and how to get clean data to be able to make actionable decisions about your marketing campaigns. What is a good sample size when you're thinking about getting enough data in to make the right decisions? And then how is AI going to change everything that we know about search engine optimization? So definitely make sure to use those chapter markers or timestamps so you can hop around.

Travis Albritton [00:01:23]:
But here it is, my conversation with Michelle. Let's dive in. Well, Michelle, welcome to the Honest marketing podcast. Super excited to have you here.

Michelle Bassett [00:01:29]:
Thank you for having me.

Travis Albritton [00:01:31]:
So, before we dig into some of the questions that I have for you, which I'm super excited about, why don't you give those listening to the podcast just a little bit of your background, your upbringing, your professional background and your expertise now when it comes to digital marketing in particular.

Michelle Bassett [00:01:47]:
Okay, cool. I don't want to go all the way back to 1988, but I kind of grew up in a rough and tumble area, some people call it the projects of New York. And, and so there were so many challenges there, kind of just growing up and kind of getting through the academic setting and one of the biggest challenges, which you wouldn't think was a challenge, but I couldn't actually read until I was like in the fourth grade. And I wind up accidentally teaching myself how to read because again, very long story. And if you want to get into it, I will. I kind of wind up breaking my leg and then I wound up sitting on the remote and then Lion King was on. And that's how I learned how to teach myself how to read. And so it was always this kind of seed of, I'm going to teach myself how to do these things because nobody else is going to teach me how to do it.

Michelle Bassett [00:02:49]:
And so that was very much the same approach when it came to my entry into Internet marketing. So I started off Savannah State. Go tigers. I started off at Savannah State and I got a bachelor's degree in Internet. I'm lying. I got a bachelor's degree in behavior analysis. I started off doing the computer science trick because I kind of wanted to be a practitioner of orthotics and prosthetics. I know those two things don't go together, but I wound up taking a lot of computer classes because I was going to make cyborgs.

Michelle Bassett [00:03:27]:
That is what I was going to do with my life. Grand plan, calculus. Three rolls around totally derails my computer science dreams. So I thought. And then I wound up switching over to the behavior analysis program. That's like psychology, but more like pavloonian conditioning and environmental stuff. And so when I graduated, lo and behold, I actually did have enough credits to get my computer science degree. So I have two degrees.

Michelle Bassett [00:03:54]:
So I have a bachelor's degree in computer science, which was an accident by the registrar's office, but they're not getting it back. And I have a bachelor's degree in behavior analysis from there. Coming out of school, it was like 2011. Life was still topsy turvy and upside down. For those of you who graduated around, like, the 2008 ish period, there was stuff going on, right? And so with a behavioral analysis degree, it was like you could be like an ABA teacher. So you're working with children with disabilities or autism, or you could go like, experimental route. Either way, they're making like $37,000 a year. And I was going to be broke, and I don't like poverty.

Michelle Bassett [00:04:42]:
Even though I came from it, I was like, I don't want to go back there. So right before I graduated, back in the day, before GDPR, and all this stuff kind of popped up, it was like you could just be on a random website and it'd be like a pop up. Like, oh, you won $1,000. Just click this link and give us your Social Security number. Right. Stuff like that. So one of those pop ups popped up and it was like, essentially, it was like, click these three buttons. In these three clicks, you'll learn how to make $100,000 online or whatever, right? And so I don't even remember what it was but I wound up paying 47 99.

Michelle Bassett [00:05:26]:
I was young and dumb, loose on the Internet streets, and I pressed the three buttons, didn't get $100,000, and I was just out of 47 99. But that kind of started the whole somebody got the money. So it kind of started this whole trek of, all right, if I not scam people, can I still make money online? And so that was around 2010, right before 2011. So that's when the Google panda update came out, and it kind of changed the whole SEO game as a whole. And so I got into Internet marketing via SEO. And then again, once I graduated in 2011, realized that I didn't have any job prospects whatsoever. My grand plans of making cyborgs just wasn't going to be a thing. And I got stuck, essentially in Atlanta, because by that point, I was in Atlanta.

Michelle Bassett [00:06:19]:
So, yeah, life had to fork a little bit. Long story short, wind up going to full sale, got a master's degree in Internet marketing. Because if you're like me, you took out a bunch of loans for undergrad as soon as you graduate. They're like, hey, where's my money? And it's like, I don't got no money. And then they're like, well, you got to go back to school. And I'm like, fine, I guess. Whatever. So I wound up getting the master's from there.

Michelle Bassett [00:06:49]:
The story is almost over, I promise. I wound up working for a lot of agencies. I still stayed in the SEO space, just kind of like, that's how old I am. It was called Elance. So a long time ago, it was elance, fiver, and upwork. Okay? Now it's just upwork. And I don't know if fiver is still fiver stuff. Now you go on fiver, it's like $500.

Michelle Bassett [00:07:15]:
That's not what fiver is supposed to be about. I got a lot of little small gig work, like elance, like doing spin, tax, a lot of gray hat ish type stuff. That was probably a crime, probably a crime against humanity that I was doing. And then I like the more legitimate stuff, and I did a few projects with the Semrush team as well. Long story short, I wound up working for a lot of different agencies. I worked for a lot of different individual businesses as well. And then health insurance reasons in America, for those of us in know, you have to have a job to have health insurance. It doesn't cost a million dollars a month, but even then, you still can't see a doctor.

Michelle Bassett [00:08:09]:
So it's fine. It's good. We're staying strong. So that's pretty much my career. And then I became a data scientist. That's a different story for a different day. I'm currently a data scientist, actually, but I guess I'll kind of dive into that just a tad bit. So, for those of you who know the term conversion rate optimization, I was doing that by accident.

Michelle Bassett [00:08:35]:
I didn't know that that's what I was doing. So when I was at yellow pages, I don't know if you guys remember those big, thick books that you used to get and sit on when you were, like, five, so you could actually reach the table, but the yellow pages had a digital department, and so when I was there, we had these regions, so I had south Florida, so Broadward county, so it's like Miami area. And all of my campaigns were doing really well by ad spend, census, and conversion rate and things like that. And it was like, it kind of put a spotlight on me that I didn't like, because now I got to do more work, because the more work you do, the more work you get. It's a trap, guys. Don't fall for it. But my campaigns are doing really well because I had all this data behind it. And so we had the regular Google Analytics, but I kind of set up my own charts and everything else so that I could see, okay, on Tuesdays, this plumbing company, it's all trash.

Michelle Bassett [00:09:36]:
We're not running ads on Tuesdays. So I was kind of doing it before all the programmatic AI, which we'll get into type stuff, started happening, and I was just doing it manually. I was like, all right, conversion rate sucks on Tuesdays for this plumbing company, or they're not answering the phone or whatever else. So I would just tweak it from there and just make it work that way. Then the yellow pages closed, so we all got laid off. And when you do such a big layoff, there's, like, laws and stuff. So they had to pay for education or training or whatever to kind of help us get into another either field or job or whatever. And so I decided that I was going to go to Emory and take data science courses.

Michelle Bassett [00:10:23]:
And so from then, I started doing really well, even better, just like a b split testing and things like that, and using big databases to look at not only ads and marketing, but just, like, company structures as a whole. And that is where I'm at now. But I know a lot of your audience doesn't really care about all the number mumbo jumbo, but that's what I do now.

Travis Albritton [00:10:57]:
Well, maybe not yet. Maybe we'll change their mind after this episode.

Michelle Bassett [00:11:00]:
Yes.

Travis Albritton [00:11:01]:
So you're definitely well traveled, lots of different hats that you've picked up and capabilities over time. And some of the things that I want to ask you about are like the crossovers of a lot of those different skill sets and backgrounds, because there aren't many Internet marketers or entrepreneurs or business owners that have degrees in behavioral analysis, which I think makes you a unicorn of sorts. Maybe a purple unicorn.

Michelle Bassett [00:11:26]:
Yeah, purple unicorn, of course.

Travis Albritton [00:11:28]:
So the first question I want to ask you is taking all these things and putting them together. Your expertise in behavioral analysis, your expertise in Internet marketing, are there any stories or specific instances where being able to combine those unique backgrounds was able to lead to a breakthrough or a big outcome for yourself or a client you were working with?

Michelle Bassett [00:11:50]:
Yeah. So a big part of behavior analysis is the analysis part, right. So you got the psychology and why people do what they do and everyone's crazy, and then you have the numbers that justify the actions. And so when it comes to any sort of marketing, any funnel, right. So that is a set of behaviors that you want to happen, and then you don't know if your funnel is doing good, bad, left, right, whatever, unless you have numbers. So they're very closely linked to the point where some would say it is unethical that how linked they are. So like doom scrolling and all that stuff, that's a part, there's a lot of psychology that went into those features that we now just see everywhere, even as far as TikTok, Google shorts, reels, whatever. It's a lot of psychology that plays into that.

Michelle Bassett [00:12:54]:
So if you are a marketer and you're marketing on TikTok, it's how do I get these people to stop, right. And so on Facebook for a little while, and I actually didn't take part in this particular venture for legal purposes. But on Facebook for a while, you saw a lot of red boxes around things, or you saw like little circles where the circle wasn't circling anything. You're like, what is this? But what is this? It made you stop, right? And so stuff like that really links it. So your psychology as a human, if you see a red circle circling something, you're going to stop, at least for a millisecond. But that millisecond is all you need if you have a really good hook. And so a lot of what I've been doing as far as consulting and even looking at people's ads and split testing and doing that divergence testing or whatever else it's why do ads in your space? Because if you're looking for a plumber, now we're back on plumbers versus you're looking for a credit card company. Right.

Michelle Bassett [00:14:12]:
Those are two very different sort of mindsets and intentions and everything else. Right. And so it's just knowing what that attention is at that time and then capitalizing off of that. So that's with a lot of what I'm doing. I can't get into too many details because NDAs and lawyers and I can't fight things. Sorry. But a lot of it is very linked and sometimes not in a good way.

Travis Albritton [00:14:47]:
Yeah, well, it's one of those things where with great power comes great responsibility. Right. Once you know the behaviors that you're helping to influence or, and sometimes coerce, if you're being very black hat about it, it's like, you know, like, well, this could lead to this outcome, which would be great for our bank account, but bad for humanity, as you put it.

Michelle Bassett [00:15:07]:
And sometimes we don't know at the time that it's going to be bad for humanity. Right. And so with Facebook, I don't think anybody at Facebook initially was like, oh, we're going to cause teenage girls to hate themselves for multiple generations. I don't think that, that the, the game plan, so to speak. And I think, what a lot of the newer technology, and I'm not a technophobe or anything, I think with a lot of the technology coming out, there'll be a lot of negative side effects that we didn't see coming, or if we do see them coming financially, it doesn't make sense for the events not to come.

Travis Albritton [00:15:50]:
Sure. Yeah. There are certain factors driving the innovation in a certain direction.

Michelle Bassett [00:15:55]:
Yes.

Travis Albritton [00:15:57]:
So you've consulted for a lot of different types of companies, sizes of companies, in all different kinds of sectors. What's the difference when you're thinking about helping with performance, with Internet marketing for a small business, versus a larger brand that has multiple moving pieces, global footprints, all kinds of verticals, what are the things that are different between those two different kinds of companies? And what are the things that stay the same that are just time tested? Everyone's got to do this. This is the blocking and tackling of marketing.

Michelle Bassett [00:16:27]:
Money.

Travis Albritton [00:16:28]:
Give me. Yeah, money. Is that big difference?

Michelle Bassett [00:16:30]:
Budget money. The answer is money. No. So what is different outside of money? Because when I look at campaigns in general, I'm always percentage based. Right. So here's your market. You're in Southeast America, here's your market, and here's the saturation in the market that you can get. And so that's actually probably one of the things that actually stays the same because I like to have consistence and footprints.

Michelle Bassett [00:17:12]:
And here's the marketing plan, here's the milestones. The foundational things will always stay the same, no matter who I'm talking to, regardless of size, budget, national campaign, regional campaign, international campaign, it doesn't matter. Those foundational pillars and principles will always stay the same. And the plan will. I don't want to say the plan will stay the same because sometimes markets change and there's seasonality as well. Like ad spends is at an all time high and there's only so many people that can get in front of a YouTube audience or whatever, right? And so that's something that would stay the same. The main difference is, and again, I keep going back to money, but it is the amount of data that can come through. If we're only talking about paid marketing, I'm not talking about SEO or like anything like that, but if you spend $1,000, that $1,000 only gets you, let's say 1000 people to come in.

Michelle Bassett [00:18:19]:
Now, if you're a lawyer, it might be five people, right? So it's kind of like the budget will determine the amount of data that comes in, and then the more data you have, the more you can change things. You can do variance testing, you can do a whole bunch of other stuff if you have more market outreach. So if you don't have a big budget, no, that's not a big deal per se, because now we can lean on more things like email, we can lean on more things like more organic influencer marketing, not like organic marketing, because I do like things to go a little bit more quick. So if I'm running a Facebook campaign and it's more know, a week out and I haven't changed anything, some's wrong, right? So some people, if I'm at an IBM company like Red Hat or whatever, and it's three, four days out now, something's wrong. But a lot of people have been depending on the programmatic aspect of Facebook or Google, they have their. And it's totally blanket on this right now, but Google has their performance max out right now and they have all their enhanced biddings that they had before, but the algorithms changed a little bit. So a lot of people, a lot of small businesses, even small agencies, are just dependent on that. And that can take you to a certain point, but it can only take you so far because it will only use what you give it.

Michelle Bassett [00:20:07]:
I know we're not talking about AI right now, but anytime you're dealing with any sort of AI or computer or any base system, garbage in, garbage out. There's no in between. But if you don't know you're putting garbage in, you got to put garbage in, look at what's going on, and then change what you put in. And the one thing that also stays the same, and a lot of my colleagues in corporate America might not agree with me on this one, but you can't be afraid to fail. Right? And then what's failure? You know what I mean? But you can't be afraid to fail. If you do this illustrious plan and you have everything planned out and you know for sure at the top of your funnel, you're going to have 1.6 million impressions, even though that doesn't mean anything, and they're going to trickle down, and your campaign is going to make the company $17 million in three weeks, and it doesn't happen. It's okay. It's okay.

Michelle Bassett [00:21:19]:
Go back, see what works, see what didn't work. Test, and it goes all the way down. Everything doesn't have to be done in three weeks. Some stuff might take three months, some stuff might take three years. Some stuff probably shouldn't take at all. Like, you shouldn't have did it. And so fail fast, fail early. It's okay.

Michelle Bassett [00:21:38]:
And that message was also the project managers, you know who you are, but some features aren't meant to be features. And that's okay. Let it go. Stop changing buttons for no reason. Thank you.

Travis Albritton [00:21:55]:
Yeah. So a couple of follow up questions for you there. The first thing I wanted to pick your brain on is, what is a sample size that you look at to know that you have enough data to make an educated change to a funnel or a step when you're optimizing. Because like you said, if you get five people to go through the top of a funnel, it's like, okay, my conversion rate is 20% because one opted in, but if I have 1000 people go through, maybe that conversion rate is 8%. And I didn't know that it was actually 8% because my sample size was so small. What's the amount of data that you want to see to get a good idea of the behavior of how the funnel or the campaign is working, to then make the appropriate adjustments.

Michelle Bassett [00:22:36]:
So conversion rate not standing right. So I always have, like, little micro goals in between. And some of those, if we're talking about a more traditional funnel outside of clickfunnels, it's just page page or interaction. Interaction. Interaction dependent. It's how engaged in general, before they get to a checkout page, before they get to be offered to get anything, to pay for anything, how engaged is the audience? And so, sample size aside, because again, we could be talking about international versus a five mile radius if you're a bakery or whatever. So for this region, if you live in a small town and there's only 500 people in this town, I'm not looking for 1000 interactions because at that point, I also failed because there's only 500 people in this town. So it's like, what's going on here? But sample size would be market specific.

Michelle Bassett [00:23:46]:
But if I can tap into, let's say, 10% of whatever market, and when you get international, that becomes an outrageous number. But for a small area, if I can get 10% of whatever before market research was. So let's say it's 500 to 1000 actual unique users. But what I do is before I start anything, I make sure that whatever data I'm going to get, here goes that data science hat. Whatever data I'm going to get will come through clean. So I make sure that all my Google tags are set up. I make sure all my conversion rate checkers are set up. I make sure all my goals are already in the system, and I test that first, right.

Michelle Bassett [00:24:34]:
Because a lot of times people, especially younger marketing people at agencies or whatever, they'll set everything up. They'll press go, and then they realize that there's no Google Analytics or Adobe whatever analytics on their pages. They're like, oh, no, the main website has it, so these pages have to have it. It's like, no, you made this in HubSpot or marketo or whatever. It's not attached to any of the data that's going. Or they will build these pages, click funnels, whatever. It sits outside of the main organization, but then they pay. So the customers will go through the funnel, but then the payment page is on either a company side or stripe page or something else, and it's not connected.

Michelle Bassett [00:25:28]:
So that was my little path over here on the side. So you can have a billion people, but if your data isn't set up and your footprint isn't set up properly and your data nets, lack of a better term, I made that up. So if you hear somebody else say data nets, they stole it from me. Trademark?

Travis Albritton [00:25:46]:
Pm.

Michelle Bassett [00:25:46]:
Yeah, exactly. If your data nets aren't cast and set out properly, it doesn't matter what's going on there. All right, back to your question about sample size. So, pending that everything's set up properly. I want to see whatever the market research told me was going to be there, number one. So I want to see about 10% of that in the first week or two. And then if not, and if I do have permission to, I'll expand to get more data. And sometimes people become frustrated, especially the actual brick and mortar physical places.

Michelle Bassett [00:26:24]:
They'll be like, oh, well, you're getting people from three towns over, blah, blah, blah, blah, blah, blah, blah, blah, blah. And sometimes you have to explain in the earlier part of the campaign, it's like, hey, I need these people and these people who are Joe schmo, these regular people that you actually want to come into your store. I need to see how they go through this funnel for this product, and I need to see how they interact with things. So these 300 people over here, I can't take that at face value. Walk away. I'm done. I did a good job. I got 300 people to see your washing machine.

Michelle Bassett [00:27:03]:
I'd made that up. Sorry. But it's like, I might need 3000 people. So let me do this. I promise it'll be like two weeks and then I'll scale back down. So it really depends on data nets and expectations. Not really sample size per se, but sometimes smaller business owners, they go on YouTube and they see things on Instagram or whatever, and it's just like, oh, well, I should have a 15% conversion rate. So if I spend this, then my dollar should make ten x and blah, blah, blah, blah, blah.

Michelle Bassett [00:27:43]:
And it's like, who told you that? Who you been talking to? What is going on? And so a lot of my job when it comes to consulting, especially with smaller companies, it's setting those expectations and then also stressing, making sure that the funnel is set up and that the data can see every single page. And what happens, a lot of time there is that they understand that they need analytics, whether it's free or paid or whatever, but they don't know how to set it up or set it up properly. And then they lose, I don't want to say faith, but they lose interest. There we go in the process of doing all this stuff because they thought it was, give this person $1,000 and they're going to change my life. And it was like, no, I need to do these 15 other things first. Do you have a team for that? I know a guy.

Travis Albritton [00:28:48]:
Yeah. Well, and that comes back to what you said before about you have to spend money to learn and so it's not going to be profitable, right? Off the bat, like, you still have to learn all the lessons of what works, what doesn't work, so you can hone it down to weeks or months later. Now we got it locked in, now we know what works, now we can scale it up and know that we're making money.

Michelle Bassett [00:29:08]:
And things change too. The whole landscapes change, algorithms change, people change as well. Just as far as having money, not having money, spending, not spending, it is a forever learning process.

Travis Albritton [00:29:24]:
You're saying if something works, that doesn't mean five years from now it's still going to work exactly the same? Is that what you're saying?

Michelle Bassett [00:29:30]:
That's exactly what I'm saying.

Travis Albritton [00:29:32]:
For the people in the back, right?

Michelle Bassett [00:29:34]:
Yeah. Yes. I'm not naming any names. Yes.

Travis Albritton [00:29:39]:
Yeah, definitely. So one of the things that continues to change and continues to evolve is search engine optimization, which is kind of like this in the minds of a lot of people that I know that aren't in the weeds of the data and understanding how things work. It's this magic pill, this fairy dust that you sprinkle on top of a website. And then lo and behold, a bunch of people start showing up and giving you money. But SEO continues to change and evolve, especially now with AI. Not just with Chat GPT, but Google having Bard starting to be built into their search homepage. And I'm curious what you're seeing as far as shifts in the SEO space and really its role holistically in how businesses think about Internet marketing. Because it's not a one size fits all thing.

Travis Albritton [00:30:27]:
It's not like, oh, if you nail SEO, all your problems are solved. It's one piece of a larger marketing puzzle. But how do you see that piece fitting in moving forward, as some of these other innovations start to become more mainstream and people start to use it more to find answers to questions.

Michelle Bassett [00:30:40]:
I think AI will do one of two things when it comes to it's actually Chat GPT, it's a plugin. But when I go on Google, it's like a little sidebar and it'll summarize, whatever, because I'm lazy, not even going to sugarcoat that. But SEO has been messed up, humble opinion for at least the past three years. And that was because companies with budgets, a long time ago, once upon a time, they figured out that if, okay, I spam this and pay this person and do this and do that, then I'll be at the first ranking of Google. And so even when you go on Google now, and Google has admitted this, as far as the higher ups, it's a lot of times when you're looking for something and you really need something, you can't find it on se. I think AI, whether it's bard or lambda or chat GBT or whatever, it's going to create a space where people will have their custom GPT. Even inside of notion now, there's like a little AI feature where if you have like five years of notion notes, like some people do, or you have a book idea or whatever, you can just use it on the side. And I don't know what program it is based off of, but it will look through your five years of notes and it will give you solutions or answer questions or continue writing books for you or whatever.

Michelle Bassett [00:32:25]:
But in your words, in your tone, grammar mistakes and spelling mistakes, same, right? Which is not a good thing. No one needs to know that I can't spell different. Why would you tell people I can't spell different? But anyway, that's a different story. But I think the role for it in SEO would be either taking people away from search engines altogether so that it's more of a customized, bigger echo chamber, which also isn't necessarily a good thing. It'll just pull down from different news resources or it'll pull down from different health resources or what have you, and then that'll be a more custom. This is Michelle's information spear. This is how she asks questions. This is what she's looking for.

Michelle Bassett [00:33:17]:
This is what she is going down. I don't like that, but that is a possibility. Another possibility as far as SEO goes is that Chat GPT specifically, when you're writing your 5000 word article or your 1000 word article or whatever, it will start to copy information from itself, but on somebody else's website. So it'll be a lot of misinformation going on, but you can rank higher because it knows exactly what good SEO is, right? And so that's a positive if you just want to write quick and dirty articles and rank up really fast. I guess that got real depressing real fast. But I really like AI, though. I really do. I've been talking about it for at least the past eight years, so I've really been into it.

Michelle Bassett [00:34:16]:
But that was sad.

Travis Albritton [00:34:19]:
Well, I think change is always hard in the sense that you don't know what's coming down the pipe. You don't know how it's going to change things or impact things. You just have to be agile and once things become clear, be able to adjust and to take advantage of opportunities and be a first mover. So, like, if chat PT gets sued enough times for scraping data, then maybe there's an opportunity to create the data that they do scrape and get cited from that. And it's like, oh, well, here's where we got that information. And that becomes a way to leverage AI to actually pull traffic to your website.

Michelle Bassett [00:34:58]:
There are some people in companies who are now saying, this was written by AI. And there's like, a hugging face is a website where they have a bunch of open source AI and pictures and whatever. So there's like, hugging face stuff where it'll be like, this is 80% written by AI. This is 90% written by a person, right. And so I think that there will be a market of consumers who would like their SEO ranking sorted by. All right, this is 90% person, right? And so I think the most savvy search engine company would come out with, you choose your own ranking. So people versus artificial intelligence. And so I think that there will always be especially an older audience who would appreciate.

Michelle Bassett [00:35:59]:
By older, I mean like me.

Travis Albritton [00:36:00]:
I don't mean like millennials.

Michelle Bassett [00:36:03]:
Yeah, well, I am close to 40 now. Jesus. I don't mean Arp, senior citizen discount people. I mean, like 30 to up. Where if I'm on WebMD, which I swore off many years ago because I chronically have brain cancer, according to WebMD, I went and got the scan. They said, no, there's nothing wrong with you. Stay off the Internet. But if I have something going on, like flu like symptoms or whatever else like I had last week, then I don't necessarily want a robot to be like, oh, you could have the flu, or you could have this rare disease that comes from Cambodia.

Michelle Bassett [00:36:53]:
Because then I'm going to go with, I have a rare disease that comes from Cambodia. Not, I have the know, just like having more like teladocs, right? If we're talking about the medical health space and just like, having the ability to reach out and talk to more people, I think, will become a very lucrative field. So if you're on a website or whatever and you're looking for an SEO company and you're going through the funnel, I think that there'll be more human touch points in marketing funnels moving forward because people want to see, okay, is this a person or is this a machine that was built by a savvy person? So I've been on way more Zoom calls recently as well, out of paranoia, both for my consumer and people reaching out to me like, are you real? I'm like, I think. I don't know. I don't know.

Travis Albritton [00:37:54]:
Last time I checked, yeah, I might be real.

Michelle Bassett [00:37:57]:
I don't know for sure.

Travis Albritton [00:38:00]:
Well, this has been super fun. Michelle, where can people go to connect with you if they want to chat with you about their own marketing needs or just see what else you're up to?

Michelle Bassett [00:38:09]:
Yeah, I'm always doing something random. So if you just go on LinkedIn, Michelle a Bassett. It's like a little purple unicorn thing on there. Just find me, talk to me. I'm pretty open. I've been having really crazy conversations just about the marketing data, AI, world domination type things. So if you just want to chat to a maybe real person, I'm pretty much on LinkedIn.

Travis Albritton [00:38:40]:
Awesome. Well, thank you so much for your time, Michelle. Really appreciate you being here.

Michelle Bassett [00:38:43]:
Thank you.

Travis Albritton [00:38:44]:
So my number one takeaway from my conversation with Michelle is when I was asking her about sample size. And the reason I asked her that question is because I've heard from a lot of different people some similar answers when it comes to selling things online or driving funnel traffic or things like that. And the sample size I'd always seen was basically a thousand. You want to get a thousand people to come through the top of your funnel or your landing page or what have you to get enough data to know this is a good sample, to know that this is a data set that I can use and understand. And what I appreciated about Michelle's answer is that it really does depend. So if you are selling in a more local market, there might not be a thousand people to even reach out to. And so you want to adjust the sample size and your test size for the potential size of your market. And so instead of thinking about a finite number of people, like a thousand, think about a market saturation number, like 10%.

Travis Albritton [00:39:38]:
So that's something that I've not heard before and really appreciated that alternative perspective. And so when you're thinking about your own campaigns, think about the number of people you're trying to reach. And instead of just looking at maybe 1000 clicks, what does that sample size really look like for you? Well, if you want to follow up with Michelle and connect with her on LinkedIn, that link will be in the show notes below. And until next time.