The Secret to Using First-Party Data to Scale Ad Campaigns 20X with Higher ROI

Speaker 1: 0:01

You're in the marketing world and you're looking for inspiration, or you're a business leader who wants to understand what good marketing looks like. You're busy. You don't have time to sit around listening to a rambling 3 hour podcast. We get it. This is the Remarkable Marketing Podcast, where we celebrate the marketing rock stars that deliver truly remarkable marketing, when you'll hear short interviews with marketing execs who share stories about the best marketing they've ever done, how it delivered a huge impact and how they overcame all the challenges to make it happen. If you aspire to be remarkable, you'll walk away with ideas on how to do truly epic marketing. Getting right to the content of what you need for busy professionals, this is the. Remarkable Marketing Podcast. Now your host, Eric Eden.

Speaker 2: 0:56

Welcome to the Remarkable Marketing Podcast. Our guest today is Josh Muskin. He is the VP of Sales and Marketing for Web Mechanics. Welcome to the podcast. Thanks for having me. Eric, appreciate being here. I understand that, among other things, you are a dad, an Ironman athlete, and you can solve a Roost Cube in less than 38 seconds. Is that right?

Speaker 3: 1:19

I can do all of those things. It's a very strange sequence of habits, but we somehow got here.

Speaker 2: 1:25

Awesome. You have about 12 years of experience in digital marketing working with the agency there, web Mechanics.

Speaker 3: 1:34

Yep Started in the fall of 2011 officially and did some of my own work before that, but it's been quite a while here. It's been fun.

Speaker 2: 1:42

Nice. Here we are in 2024. Very interesting times that we live in. We've worked with hundreds of marketing leaders at startups and at big companies, Fortune 500 companies. I was wondering if you could share a story of some of the most remarkable marketing that you've gotten to do for your agency or with your clients.

Speaker 3: 2:04

Sure we're happy to. There's one story in particular that comes to mind. We have a client in the financial services space debt consolidation and management, helping people get out of debt and credit card debt. Things have changed quite a bit over the 12 years that I've been doing this. It used to be such that when you wanted to target somebody or a group of somebody, you could be really, really specific. I want to target this particular age, this gender, these seven interests. In some cases, that ability is going away, which sounds strange. We're getting bigger and better technology, but we're able to target people less and less compared to what we used to. A lot of that has to do with the rising awareness of privacy People not wanting to be found quite so easily as they were before. That's particularly relevant in all of financial services. We've been doing Facebook and meta-marketing for clients like this for a number of years, when they used to be able to say this really particular niche. Now Facebook has actually taken away their ability to target general demographics age, gender, household income, in some cases, geography. That makes marketing for people who need these services in some cases quite difficult. We'd want to say, hey, I want someone with nine credit cards open and not that much income would have you Our client, who had been running a very successful marketing campaign for a number of years. Suddenly it stopped working. They had targeting removed. We were left not necessarily with the madman challenge of needing to come up with the perfect campaign, but the one where we had the perfect campaign and the ability to put it in front of the right people vanished. There have been interesting developments in that where you're not able to go in platform and say I want to target these individual people. There are ways that we had to be very creative to get around this challenge. One of them was starting to think about the sphere that people have when cookies go away and you're not allowed to use third-party data anymore and say, okay, if that's our future and we don't have really good target anymore, what exactly can we lean on? The answer is starting to get a head start and really leveraging first-party data that this client had available to them people raising their hand and giving us information straight from the source. The challenge ended up being we have to figure out what information we're getting really tells us that these people are going to be the right client for our client. In this case, it ended up being some particular places, about where they told us they lived, about how much money that they said they had in debt. That was all we were able to legally collect at this stage. We had to go out of our way to build a model that said, if people meet these criteria, they're probably going to be pretty good. If they don't meet these criteria, we can probably ignore them. Instead of turning it into targeting, turn it into a data point. A data point be a thing that we can use for Meta, for Google Ads, for the other advertising methods that they were using, to say, hey, we don't have to tell you who they are, we don't have to ask you to find these combinations of demographics and information. We've already found that. But here's a data point that we want you to use. Every time you get this data point from us, we want you to go and use that to find other people. While that seemed really strange to us going from really narrow targeting from the perfect audience to going to people in the United States over 18 years old and they have a pulse that sounded like the marketing would get worse. But when we accompanied that with this very specific piece of data that we were giving these platforms, we actually saw quite the opposite effect. It's something we've started to use elsewhere. The effects are essentially when you broaden an audience, your costs to reach that audience go significantly down. You start to get cheaper traffic because the audience pulls so much bigger versus a very expensive audience with a small number of people. Your audience cost goes down. Your reach also goes way up because you're saying, hey, I'm willing to target anybody in this space whatsoever, but the platform is responsible and has the responsibility to use the data that you give it to go get you more of what you've asked them to get. In our case, get us more of this very particular data point. In doing that, it became very good at taking our good creative that had worked for a long time, placing it in front of people that this data point suggested had very similar demographics, capabilities and background to Doing that at a lower cost than we did before. Instead of only being able to spend $100,000 a month through these platforms to get a 10x return, suddenly we could spend a million, a million and a half, $2 million a month to get actually a higher rate of return. Because of that combination of factors a better series of targeting through a data point and the lower cost of that traffic. It's been a really interesting theme where it's been harder to get to really niche targets over the years or it becomes increasingly expensive and cost prohibitive to narrow down to a really specific audience, to use a method like this where you're actually targeting via data and information more than you are in platform. It's been an interesting look into the scientific half of marketing versus the artistic part. When done correctly and in conjunction, the scale and opportunity becomes something that we weren't given access to five or six years ago.

Speaker 2: 7:12

It's interesting because if the privacy rules hadn't changed that targeting ability with Facebook, it was so good at doing the targeting, it was just like printing money. I think I would be retired on the beach right now somewhere if they hadn't changed that. It was just so good at the targeting. But understand why we're here and the changes that have happened there have forced this change in tactics and way of thinking about the use of first-party data. Like you were saying, using that data as a data point. The twist is interesting is a much broader audience. With the first-party data, usage is driving exponentially higher rate of return and you're getting to reach a lot more people. Do I have that right?

Speaker 3: 8:01

Yeah, and it's where we're expecting these things to go, because you see this in a bunch of different places. Meta was the first to do it for their protected categories, they did it for housing and they did it for employment and then credit or financial. But you also see platforms like Google announcing things like Performance Max, which is their version of hey, just give us some ads in a data point and let us figure out the targeting. And LinkedIn now has a version of this and Meta's expanding on it. And if you follow that into where it could go, these ad platforms very likely in a few years could be upload some ad creative. Give us the event you want us to do and there is no middle, there is no defined targeting, there is no demographic drop-downs. So if you're starting to prepare for that future, it really is a matter of doing something really useful with your first party information and making sure that you're creative and speak to that audience and assuming that at some point, we're not going to be able to define targeting in the way that we've been used to.

Speaker 2: 9:00

What do you think the key is with collecting first party data, because everyone is sort of saying that's the answer now, but have you found a secret or a best practice around that? That's been really helpful, in addition to just making the audience more broad and using a data point. That's a good insight, but other insights about first party data collection.

Speaker 3: 9:20

Yeah, the big one is people will jump to be greedy. They're like, okay, well, if I can't buy your data now, I have to ask you all the questions. I need your first name, last name, email address, social security number, first born child's name. Right, and they'll go way too far in one direction to just try to get as many data points as they are already are used to when what we've found is that when we're collecting the information we need to do generally what I described. It usually boils down to like one question. There's usually a question, the first one the sales team will ask to qualify a lead. It's the first thing you look for in a lead record to figure out like, do I want this company or not? And a lot of times it's company size, geographic, how much revenue they make, what their tech stack is. There's some defining quality that says they are or are not good. That can be the only data point you collect and you can still get 90% of the way there with all this other stuff and targeting and strategies, but it's not as intrusive to the user that you're working with. So figuring out what that one really strong leading indicator question is is 90% of the way there, versus just trying to collect everything for the sake of having it.

Speaker 2: 10:29

Yeah, that makes sense, because people don't really love filling out long forms and I think every additional field you add, the response rate goes down by 12%. So that makes sense. Just only collect what you really need or focus on the one data point that really qualifies it. That's great advice. So what was the impact when you did that for the client? What sort of result did they see?

Speaker 3: 10:55

The easiest way to describe it is they went from a 10x return, spending about $100,000 a month in ads, with an inability to scale that. They would add $10,000 or $15,000 to the budget and their return would go down. And I think last month that client spent about $2,011,000 or $12,000 x rate of return and just the ability, the unlock of that scale, with even slightly better improvement, made it a no-brainer to continue investing.

Speaker 2: 11:20

Wow. So they were able to get 20 times the reach by broadening the audience and still maintain the same rate of return. That's pretty awesome scale. That's great. I had one other question I wanted to ask you. That's a little bit not necessarily on this same topic, but is something that I think everybody is wondering about and discussing these days is the role of AI in digital marketing. I'm just curious if you've been seeing any interesting trends on that, with working with your clients.

Speaker 3: 11:55

I have and there's a. At some point it may be perfect enough to use as a solution, but today we've found that it's most useful as a tool. So an example of the way that we're using it and have found great use in it is in the content vein, but not in the way of some people will say hey, I just got to chat to you. I say write me an article about digital marketing, I copy it and I publish it on my website and if I do that 50 times a day, I'll have more content than you and more people will find me and I will rank and all the things. The challenge with that is search platforms and whatnot are getting pretty good at understanding what a person wrote versus what got spit out from chat GBT. So there are detriments to using only AI sourced content. However, we've found great use in it in the planning perspective. Hey, we want to write content about this topic. These are the headlines that we've so far included. What's missing? What would our competitors say that we've not mentioned yet? What other angles or solutions should we consider adding? Using that to get a really good plan around the content that you're going to produce and then having an actual for now, human expert fill the gaps in the paragraphs. In those ways there's tremendous use in leveraging it in a contextual way that was not previously available with search. But we've not found it useful in such a way yet where it's like a point and click solution.

Speaker 2: 13:18

Okay, if you've done anything with AI to actually create different variations of ads yet.

Speaker 3: 13:28

We've done it for helping create variations of headlines, different copy, picking the ones that seem to make some sense. But that has been useful. We've used it here and there for the image creation piece. Just sometimes you really need to duck in a top hat on a boat and you can't find a getty image of that. With enough prompting you can get something that's quite useful in the image side. You can't exactly pass it off as not AI. It's still, for the moment, relatively obvious that it was made by some platform, but sometimes you need an image that's not there, and that's been helpful too.

Speaker 2: 13:58

Makes sense. I believe that your agency has some resources that marketers could look at if they want to learn more about this topic. We do.

Speaker 3: 14:11

There are two main places that you can find them. One is going to be our newsletter, digital Marketing Insider. We've got to sign up for that, right at the bottom of webmechanicscom. Then the other shameless plug recently launched is a platform where we're going to house all of our internal documentation, all of our premium content, free to get into. It's going to be housed in a place called WMXtra, which is Xtrawebmechanicscom. For you to sign up, you can use LinkedIn, google, what have you, but that's where all the stuff we used to gate or charge for or otherwise using consulting agreements is going to live. You can get there now, as we're starting to upload some things there too.

Speaker 2: 14:48

Awesome. Well, thanks for making time to join us today, josh. I think your insights on how to use first-party data in order to scale add campaigns is pretty remarkable. Thank you for sharing that with us today. We appreciate it.

Speaker 3: 15:03

Of course, Eric. I got a whole lot of fun being here. I appreciate having me.

Speaker 1: 15:33

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