SPEAKER_02
The Higher Ed Marketer podcast is sponsored by the ZEMI app, enabling colleges and universities to engage interested students before they even apply.
SPEAKER_01
You're listening to The Higher Ed Marketer, a podcast geared towards marketing professionals in higher education. This show will tackle all sorts of questions related to student recruitment, donor relations, marketing trends, new technologies, and so much more. If you're looking for conversations centered around where the industry is going, this podcast is for you.
Let's get into the show.
SPEAKER_02
Welcome to The Higher Ed Marketer podcast. Today, Bart and I speak to PJ Wensel and Marty Gray from Ring Digital. And they're going to help us explain to our listeners the changes that are coming in the ways that we can execute lead generation.
Yeah, Troy, I think there's so much
SPEAKER_04
attention going on in a live scene with so many clients, especially since the pandemic, really leaning into pay-per-click campaigns, whether it's Google and Search and Display or Meta with Facebook and Instagram and other ones. Those are really good tools. The playing field is going to change real soon because Google is doing away with some cookie-based metrics and the way that they're tracking people with cookies.
And so that's going to really change a lot of the ways that we're actually doing pay-per-click. And I really like the guys at Ring because they've kind of approached it from a different standpoint, from a behavioral standpoint of actually understanding those devices that we carry and knowing the location that we're at and what our spending habits are and actually how we behave and how that might be a better predictor of a lead for institutions. And so this is a great conversation.
I would really encourage you to kind of listen
SPEAKER_02
and take some notes. Yeah, we really appreciate PJ and Marty for helping us get this out to our listeners. Let's get to that conversation.
As we approach all the important information with PJ and Marty, I do want to ask one of you to tell us if there's anything that you've learned this week
SPEAKER_00
that's unique or interesting that you can share. Yeah, the very important information that I have to share with you, Troy, is that when I don't eat thousands of calories of carbs every week, I feel really good. I'm on poll 30.
And I'm like, I've never thought so clearly for my clients ever before.
SPEAKER_02
Thank you. I know poll 30 is a big thing for a lot of people and they've had great success. And by the way, everyone, that was PJ.
Both PJ and Marty are from Ring Digital, and they're going to share some of their wisdom and things that they offer their clients through Ring Digital. And Marty, if you would, if you can kind of introduce us to you and PJ and Ring Digital. Yeah, absolutely.
Thanks so much.
SPEAKER_03
So much, Troy. This is great. So PJ is our president and co-founder, fearless leader of Ring Digital.
And I'm a guy who PJ sought out to say, hey, I've got this idea on how to bring truth, transparency, and accuracy to the digital space. And I would like some help educating and, like PJ said, thinking clearly for his clients. So I've been guilty of the whole 30 a time or two myself.
SPEAKER_02
Thank you. And Ring Digital, tell us a little bit about what you do.
SPEAKER_03
Yeah, absolutely. PJ, were you going to take that?
SPEAKER_00
Oh, yeah, sure. Yeah, so Ring was founded in 2014. And we really got heavily into the digital space a couple of years after that.
And primarily what we do is helping connect our clients better with their target audience. We had clients who were really frustrated to put it lightly, that they didn't know who they were advertising to, were really unsure about the attribution models that they were getting. And just to put it very, very frankly, they didn't know if the ads they were buying were getting in front of the right people, and they didn't really know how to tell if they were.
And so Ring takes an approach that is, we think rather unique. And we really focus on connecting our clients with their target audience in a way that can be measured. And that they know going in ahead of time, who exactly they're targeting, like literally the names, the addresses, and all the information that they need to know about their target audience, we can actually tell them who they are.
In many cases, we can tell them a lot more. And often our clients in the higher ed space, we're going to get into this, I'm sure a little bit, they've got their own data. And so we're helping them use that data in a more effective way.
So that's what Ring is all about. It's about leveraging the power of digital, we think, in the next gen sort of connective way. Thank you, PJ.
And both Bart and I wanted to have you
SPEAKER_02
on the podcast to help us explain and demonstrate to our listeners the difference between behavioral, lead generation models and cookie lead generation models, and which one is better, which one's in the future. And that's something that your company has experience with. So we were hoping to educate everyone today on the difference and where we see the industry, especially for a higher ed clients going forward.
So if you would, one of you kind of explain the difference between
SPEAKER_00
the two. Yeah, I'm happy to do that. So, you know, on your last podcast, I was listening to you guys talk to Jay Baer.
And one of the things that you guys talked about was the need for universities to be collecting more and more of their own proprietary data. The question is, what to do with said data? What do I do with this? And so leave that there for a moment. The importance of that will become clear soon.
In the past, for the last, I mean, G's 10, 12, more years than that, the programmatic digital space. So digital ads, although they're through, you know, Google's ad network or other ad networks have all been based on a type of behavioral targeting, which is foundationally based on the cookie. So there, you know, when we talk about behavioral ad targeting, there's a couple of ways to think of it.
But online, you know, behaviorally online based targeting, you know, behavioral online target. So how do people behave online? And that is what cookies have been used to track and basically store that information. However, with the rise of automation and more and more bot traffic and less and more demand, frankly, for transparency, that model has stopped working.
Google has recognized that. And that's why they have started working on everything, you know, the flock flop, so to speak. We've heard about and then this cookie shelf or the cookie cliff, as they call it, you know, cookies are going away.
This model of targeting from an online behavioral standpoint currently is going away. So the question is, how do we, how do we target? And that's where the university's data comes in. And frankly, other hard data stem sources.
What, you know, instead of gathering online behavioral data from cookies, batched into segments by big companies like Oracle or Blue Chi, you know, who are, you know, selling that data to Google and others, instead of those cookie segments being used, what's going to be used, we think, and we think the more elegant use is simply to use proprietary hard offline data and match that to hardware specs. So let's say it's a device ID targeting or some other real live device type identifier that connects the user, the target, with the data that the university has. Because a lot of cases that data is really good.
And I'll take a step back there and just say also that the reason why Ring started down that road, and this is because that's how we target it, is more to do with the impact that we saw from offline based data. And that is to say, and this is not universally true, so don't push me all the way through on this, because online behavioral stuff is, it's powerful too. But if I go online to Men's Health, or to, you know, MSNBC or whatever, it doesn't necessarily mean, like it doesn't say as much about me as if I were to go into Dick's Sporting Goods and purchase something.
So in other words, what we do with our bodies in the physical world and what we do with our money in the world, whether it's online or in the physical world, what we do with our money and our time in the real world has a more significant impact than what website we happen to click onto or scroll down. And because that is true inherently, we need to be able to market to people based on that behavior, that real world behavior, if we really want to have an impact. And so that's where we start from.
And so I hope that's a little bit of an answer to what you're
SPEAKER_04
getting at. That's really good, PJ. And let me just kind of get my head wrapped around this, because I mean, you know, I don't think I'm atypical.
I carry my phone pretty much everywhere I go. My phone is a piece of hardware that if I recall, it's like got a MAC address or some weird name like that, that is unique only to that phone. And what you're telling me is that I that my my data is connected to that that piece of hardware, whether I'm sitting in a parking lot, or I just drove through campus and I'm with my kids on vacation, and we decided to swing over and just kind of do a quick walk through campus, but nobody knows that we're there.
I can be, you can you can identify that, because I'm part of your database, or maybe you bought a name, and you can say, Okay, this address, my home address, and I'm connected, my home address is connected to these pieces of hardware. All of a sudden, now you can start to understand my behavior based on my my hardware, but not only that, but another thing you said was that my spending. So the fact that I'm spending everything with my with my visa or my mastercard, I can also that's another piece of hardware, if you will, that can be tracked and and that behavior shows up.
Is that
SPEAKER_00
correct? Yeah. And yeah, that's right. So the the things that we do in the real world have been sold to companies like Visa, AmEx, you know, all the banks, all the travel websites, all of these folks, we have, we have long since made the trade off that we are okay with people selling our data, as long as we get a really good service.
And often it's a free service. I mean, that's the entire backbone of Facebook, right? So, you know, that theory, but we've had that theory working in operation in our society for decades now. And that's how the banks and credit card companies make money.
And in another way. So that data is all, it's always been available. You know, the direct mail companies have had it, and many other people have had it, but it's not been utilized very well by digital marketers.
And frankly, it's, you know, the location based services that you're talking about that that's part of the key. And so it's not just and it's not even just the MAC ID. I mean, there people don't realize there are many identifiers on your phone.
And when you travel somewhere, the location, there is going to be an app that allows for tracking of your location. And that app will provide that and it will be in the bid stream and that stuff will be pulled down. And yeah, that's super creepy.
But I'll just say this, people, you know, on one hand, they want their privacy and that's a good thing. But on the other hand, they want ads that are pertinent to them. They don't want ads that are superfluous.
I love getting an ad, for instance, that is going to show me a new, you know, gadget or something that I might be interested in. I want ads that are targeted for me. I don't, you know, and that's, and that's why I think it's going to be extraordinarily important, you know, for our clients and for others to realize the power of, of, you know, that offline data.
And it's just connecting everything in a different way. So it's all this data has always been available and it's getting better and better. But it's a matter of connecting
SPEAKER_02
it in a new way, if that makes sense. We talk a lot about it on the show. Schools are really struggling today to make the same ad spend work.
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SPEAKER_04
Barton-Troy sent you. Yeah, that does. That really starts to open up a whole lot of different things.
I guess I'm curious too that like your example of going to men's health versus walking into sporting goods and buying something, I have to guess that there's some inaccuracies in the data that we're relying on from this cookie. I've got a ton of clients that are ponying up a couple, $500,000 a month to do Facebook ads or Google ads. I've seen it work very well with bigger budgets, but smaller budgets, it almost feels like you're going to Vegas and just doing a little bit of a crapshoot.
Help me understand a little bit about how all that changes because I mean if there's inaccurate data out there, there's a lot of things that are coming in the net that
SPEAKER_00
aren't worth anything. That's right and big companies are able to do that because of the scale. They're able to scale, but I mean if you're a mid-sized business and you're spending maybe a couple hundred thousand dollars a year or a university that maybe is spending a million dollars on digital every year or a half a million, you don't have the luxury to be able to cast that wide of a net.
Frankly, nobody should want to do that. Nobody should want to waste money. The reason why it's become more and more inaccurate is just having to do with the way that technology has evolved.
Those cookies, it's all built on the back of a technology that was never meant to hold this kind of marketing. One way to check, and you can check your cookie footprint, so to speak, you can go to Oracle and request that. You would be shocked.
I didn't know that I was also a woman. I didn't know that I was in five age categories. I thought I was a young guy, but apparently I'm also 65 and older.
They've got me in every age category and they've got me in both female, male. They've got me with interests that I could care less about. I didn't know I took up fishing.
All these different things. Don't forget, PJ, you live in six different states. I know.
I know. I'm very affluent. These are the kinds of things though that when we started looking into this, but again, for a mid-sized business and a small business especially, when you're targeting your ads this way, you don't have the scalability that an IBM or Dick's Sporting Goods to use the example.
You don't have $35 million to throw into this, because for them, you've got to remember, it's not just about the sale, the straight sales conversion for them. It's a branding play. They're totally willing to brand to everybody.
Same thing with pay-per-click, if you think about this. The idea is not just about, it's not just about targeting a certain segment with that. You're really casting a wide net, because even if you did get a non-bot, right, Bart, that would click three of them, if it's a real person, how do you know? I mean, the minute, how do you know they're part of your target audience? The minute you want to do any kind of targeting, you want to bring targeting into the picture, even with pay-per-click, right then, you are layering on the same cookie, a backbone.
And so, you're still relying on that. And that's a problem. I mean, so that's what we're trying to kind of just educate people about and say, this might have been an elegant solution, and it is a really cool solution.
If you think about how the cookie model came together maybe 10 years ago, or 15 years ago, a long time. It's, boy, time is flying. But now, it's just with the rise of automation and so many other issues with the data, it's just become less effective.
And we don't think that universities can really afford to be that ineffective with such a competitive atmosphere.
SPEAKER_02
PJ and Marty, so is it accurate when I say that the pay-per-click or the cookie-based model would be described as a real-life targeting model versus where we would like to go, or what might be a
SPEAKER_00
more effective as the behavioral model? Well, right now, industry speak is a little, it's a little fluid. So, for instance, if you specify that, and which is why I think asking good questions is so important, when people say behavioral, some, we've encountered behavioral as people think of it as online. They believe online behavioral-based targeting, they're thinking online behavioral.
So, that's why we have to ask, what kind of behavioral targeting are you talking about? And so, you've just phrased it in a way that we don't encounter as much, but is probably actually more how it should be phrased. But yeah, behavioral targeting, that's why you have to get really like, well, do you mean based on purchase history or credit score, or something that people, like real data points, are you talking about online behavioral, like based on the websites that people have visited? And those are the kinds of questions
SPEAKER_02
you have to get down to. Thank you, PJ. So, keeping in mind that we're talking to higher ed marketers, if you can kind of guide us and the conversation to what are you recommending us to
SPEAKER_03
go to? Yeah, absolutely. This is Marty. Sorry, PJ, are you going to say something? I can- No, no, go for it.
All right. Well, this is where, this is the part that I absolutely love, is to take these concepts and these ideas that and bring them to reality for folks. And so, you know, there's always going to be new technology out there.
One of the things that we're doing is both creepy, but a lot of fun. Whenever we're talking with people and they say to us, wow, this is really effective as a consumer, or really effective as a marketer, but kind of creepy as a consumer, we know that they've got the concept down. And so, what I mean by that is some of the new stuff that we're doing is automatic content recognition, or for short, ACR.
And that is just simply put that if you are watching something on your smart TV in your home, and let's say you're a university and you're buying ad space on that TV through the digital means, you see someone get served with a university A ad. Well, let's say you're a university B, we can actually see what content is being displayed on that TV screen, that smart TV screen in that home. And then almost like race car, you can NASCAR, you can draft, and you could then a day later or two serve an ad for your university because you just saw that that ad was served for university A.
So pretty powerful stuff, but what is really exciting goes back to this real world data that PJ was talking about. When that is the foundational starting point, and the foundational building block of what you're doing, the real world behavior, we put that data to work, and then we're able to, the gold standard for us is the matchback or just the comparison of spreadsheet A as your list of targets, and spreadsheet B is now your list of enrolled students in your institution. So here's an example of that.
We had a top five SEC school come to us, and you know, they, this won't come as a surprise to a lot who are listening in on this, and that is that they spend thousands of dollars every single year on research. And that research is, who are my underserved markets? Who are the people that we need to be reaching out to? How do we get, and then naturally you're left with those questions, how do we get in front of those people? So this school specifically, as we were talking with them, they came across an underserved universe, as we like to call them, of students, which was low income gap schools for Pell grants. And so what they had was a list of 20,000 people that were on their Pell grant list target list.
And so what we did was along with their direct mail, along with their search engine optimization, their pay per click, their billboards, TV, radio, we injected this into the sum of all of their marketing parts. And so what we did was bring to the attention of these first generation students who thought that they may not be able to attend the university, that there was a spot for them. And in fact, the university wanted them to come to them specifically.
So what we ended up doing was taking that same list and serving digital display and non-skippable pre-roll video ads in browsers and apps directly into the devices within those same households that were on that literal Excel spreadsheet list. And then we narrowed that down to 3,500 students who raised their hand and filled out an application. So we narrowed down 20,000 applicants or possible applicants to 3,500 students.
And here's what we then found is we then took that list of 3,500 students and started targeting them with different messaging. Now that you have interest, your real world behavior is I'm interested in your university. And now we're going to continue to tweak that message and narrow it down and get to you specifically.
So at the end of the campaign, when we compared the two spreadsheets, it was who did we target because we predetermined that and we know that just like direct mail. We love to say all the time, this is like direct mail only for digital. And so what we do is we found that of the 3,500 students that enrolled, 3,000 we targeted, little over 3,000 we targeted.
And as a control group, we left off a little over 400 to target with only their direct mail and other means, but we left digital out. For those folks that received the injection of our digital marketing, 51% of those 3,000 students are now enrolled in the institution compared to only 25% of students are enrolled who did not receive our digital marketing. So the conversion on that lift yield is as you know, every, this is on the mind of every admissions and enrollment person in any institution.
How do I lift the number of applicants and then how do I yield or keep the most amount of those possible as they move through their enrollment matriculation process? So, you know, 51% to 25% having a 26% lift or a 2.26x increase in their conversion is staggering, especially when we know that these universities needs to be so careful with their dollars. And a lot of times, you know, these are public dollars, and you need to be able to account for every dollar, every dime, every penny that's spent on these campaigns.
SPEAKER_04
So let me just kind of tease that out a little bit, Marty, because I mean, you're talking about some, you know, large SEC school and, you know, university type schools. I know for a fact that just about every school, I mean, when you start even looking at schools that are, you know, a thousand and above matriculation of student population, they're, you know, everybody does student search and people have been doing student search for decades where, you know, it used to be the fact that you'd go and buy the ACT test registration list or the SAT test registration list. And, you know, you can still do that.
There's other places out there now that are offering similar lists that you can purchase, whether it's niche or, you know, there's a ton of them. But the point is, is that, you know, people are investing anywhere between, you know, I don't know how much money, but they're buying 500, you know, 50,000 names or 100,000 names, seniors, juniors, sophomores, and they're typically going through a traditional, you know, we're going to send them email, we're going to send them texts, we're going to send them postcards, we're going to try to generate some leads out of that. But what I hear you saying is that if I have a list and I have an address, that is my key to be able to then start to inject this digital elements that you're, that you're talking about.
So rather than relying on hoping that my prospective student is going to open their email or, or, you know, hoping that they're going to, you know, look at the direct mail, which is effective, you're telling me that I can also upload these lists to a tool like what you guys do, and then start injecting ads into the household as part of that campaign.
SPEAKER_03
100%. Yes. And that's going to get the quickest return because that's the lift yield nurture part of this. So you're 100% spot on.
And then PJ mentioned the data aspect of this is, you know, a lot of institutions that we're talking with both large and smaller institutions, a lot of folks, it used to be a requirement to have your ACT and SAT score. So they would buy those lists specifically. Well, a lot of institutions have, have dropped that because they see it as a barrier to entry for the student.
And so because, you know, the, all this data that PJ was mentioning, you know, we have, this goes back to the creepy part, like, there's up to 1000 different data points in our dictionaries of the, of, of identifiers of who people are household income, you know, credit score, you know, what type of gas do you put in your car, I should probably stop before people like it so creeped out that they click end on this thing. But, you know, it's so we can really do both the quickest return. However, that higher education is going to receive through, through a partnership in doing something like this is, is through their lift yield lists, because we all know this, right? It's, it's easier to, to have a conversation with someone or to start a conversation or continue with someone who's interested versus someone who is off the radar, may not know you or trust the institution or the brand just yet.
And so to your point, you know, we have, we have, you know, smaller university relationships where they've, they've purchased 90,000 plus names, and they're excited to put that data to work. And you can, you can bifurcate those lists, you can, you can sparse them out and say to the sophomores that we want to start having a conversation with, let's send them drip campaigns of, you know, just, you know, less frequent contact, but we're still getting in front of them. And then the juniors, you intensify that a little bit, and the seniors, you really ramp that up.
And so you can do both. So to answer your question, you really can do both with the nurturing and also the prospecting, but the nurture is absolutely where you're going to have the quickest return because folks are already interested in having a
SPEAKER_00
conversation. There's an interesting thing that happens to in the mark in the digital marketing world with when it comes to lists, to just to clarify, it's not that traditional digital agencies haven't been able to take lists and use lists before. But there is, so if you were to talk to an agency, can you take this SAT list? Can you take this in tender's list? Can you take this list, the yield list? They'll say yes.
But it's what do you do with that list? And so there's a difference between, for instance, this new way of approaching digital advertising that Marty just described for one of our universities, there's a difference between that and what traditionally folks have done with lists, because in the past, they might inject that list, they might take that. But what they will do is they'll take it to somewhere like a live ramp, which still is using a cookie based model. But what they'll do is they'll take that list of hard names, addresses, and they will model on top of that cookie segments.
So they'll say, we want to match these names and addresses to profiles based on online behavioral data that let's say an Oracle or someone else has. So what you're doing is you're taking really good data, and you're adding a level of uncertainty. And really, at this point in the game, bad targeting, you remember caddy shack, bad cadding, you're adding some bad cadding into it.
So this is just something for, if you're a marketer, you're a marketing director, and you're saying, hello, my agency, I'll ask my agency if they can do this, ask them, like, well, where are you taking that data? How are you going to approach this with this data? Because that's a really telling thing. If they're just going to upload it to live ramp or somewhere else, then essentially, it's all wasted. It's that you're
SPEAKER_04
back to square one, essentially. Okay. So just one thing I want to clarify a little bit, Marty, that on what you said, you talked about these hundreds and thousands of data points. One thing that went away, and I've got a lot of people that are listening on this show that are going to be faith-based institutions.
And up until about three or four years ago, part of the ACT, SAT, pre-test questionnaire was about your religious affiliation and your denomination. A lot of kids didn't understand that. A lot of kids didn't know what to put in.
But it was some data that they could say, I want to be able to buy a list of students who are part of the Baptist Church or part of the Presbyterian Church or whatever that is. That's went away. And so there's a blind spot now.
And there's places that they can go and get that and things like that. Does your data provide you, does the tools provide the big data? I mean, if we're getting down into the details of credit scores and things like that, I'm sure there's some ways to be able to identify or affiliate some kind of religious activity as well. Is that true? That is 100% true.
Yes. Yeah.
SPEAKER_03
So in the data, we've even been asked to do that before and have executed it. So it's
SPEAKER_04
absolutely in the data. Okay. Because that brings me to my next question is that now all of a sudden, if I bought this list, and I've got 100,000 names, it seems to me like I can give that list to someone like yourselves or somebody that does the work that you do, be able to then come back and say, okay, I want you to take this list and I want you to identify those people that have these key elements that I want. I want to have this kind of household income because I do want my first gen students and my Pell Grant students, but I also want full-paced students that I can make some net revenue on for my university.
I want to identify that. I want to identify some religious affiliation and understand that that household does have that as a part of their lifestyle. Then I want to be able to then take that 100,000 list and now I'm down to, let's say, 25,000.
Now I want to do something with that 25,000, even if it's a brand awareness campaign, before they get into my yield campaign that I'm going to do after they get accepted. Is that a possibility too that I'm starting to serve brand awareness ads on Hulu and things
SPEAKER_03
like that to those households? Absolutely. The awareness factor is also, like you said, very important. When it comes to the TV, there are lots of different ways to get in front of people, but it goes to what PJ said before.
Anytime you take that list, I like to think of it as that list is powerful because that list is direct. It normally has a first name, a last name, physical street address, city, state, zip, enter phone number, whether it's your mobile phone or your second mobile phone and a whole host of other things. Like PJ said, when you are taking that list and you're uploading it to a live ramp, for example, you're immediately diluting the power when the directness of that data.
What this does is then say whether you're a large school or you're a small school, to your in-state, out-of-state point or question, it's really interesting. There Midwest University, and they actually gave us three lists. Those three lists, their priority list was number two.
Priority list number two was out-of-state students trying to get them to come to the university. We did advertising for 75 days. When we advertised for 75 days, they had 39 students enroll from all three lists, but 33 of the 39 students, those were students from list number two that were out-of-state students.
So you can just like you said, do you want to bring awareness to your in-state students, to your out-of-state students, to your stop-out students, to your Pell Grant students, transfer students? There's a ton of cool things that you can do, especially when it comes to transfer students. I think the other thing to keep in mind here is especially when it comes to the TV, and honestly guys, like TV is probably a whole other segment in and of itself, so I won't delve into that too much here, but being able to actually not target an area by by a demographic or a media, yeah, so being able to actually go into the household and target on someone's TV based off of the list of that starting point gives supreme confidence in the directness of whether it is branding or it is specifically for the purpose of enrollment.
SPEAKER_04
That's awesome.
SPEAKER_02
Thank you, Marty, and just listening to you, and unfortunately we're going to have to bring our show to a close, but you just opened up another chapter that I'm sure that we could talk about for 15 or 20 minutes, and in a few minutes I want to give you an opportunity to share your contact information for those who would be interested in that next chapter, but we love to end our episodes of the podcast by asking if there's a piece of advice dealing with what we've discussed today that you could give a higher ed marketer that they could implement easily and
SPEAKER_03
quickly. Yeah, I would, the advice, I would, two pieces of advice. The first one would be, PJ alluded to this earlier, but ask good questions.
When you turn over a list, do you even, whether you're turning, so if it's your list, what are you doing with that list? What are you doing with that data? How are you using that list and data? If it's not your list or it's not your data and you are using it, do you own it? Are you leasing it? Like what is happening when you hand over any of your information or when you do so-called buy something from another organization in terms of data, do you own it and those kinds of things, but ask good questions. And you know, most of the folks that we come up against is probably the wrong phrasing, but a lot of the folks, they're open to describing what they do and how they do it. So have that conversation and look for ways that you can fill gaps.
As far as the advice that I would give, when it comes to all of the lists that people have in any institution, their low hanging fruit, so to speak, is going to be their lift yield list. Those who know the university have some trust in the institution. Those are the people, especially because there are fewer students and therefore more institutions going after those fewer students injecting this into a lift yield campaign, that would be my advice, is how they can use this to instantly see the return to help set their enrollment in motion in a predictable and demonstrable way.
SPEAKER_02
Marty, thank you very much for that. Both you and PJ have given us and our listeners a lot to think about and I think a lot to follow up on with that in mind. Would you both offer contact information for those listeners who would like to reach out to learn more about this topic
SPEAKER_03
or maybe some of the services? Yeah, absolutely. PJ, you want to go first? I'm just going to offer your information. Okay, so here's one going back to the beginning of the show here.
What I've learned is if you want more to do, call PJ because every time I have a conversation with this guy, I find myself with more to do than when I called them before I called him. So with that in mind, sure, yeah, my email address is marty.marty at ring.
digital, r-i-n-g.digital and there's no .com. We get asked that all the time. It's just marty at ring.
digital and the same thing is true for our website. If you check out ring.digital and then forward slash higher education, that is another great way to just to check out how we've done some pretty neat things in the higher ed space.
So and really, we love to educate. That's the most important thing. We love to educate and we love to see people succeed and as long as those two things are happening, then the world's the world's a better
SPEAKER_02
place. Thank you, Marty. Also PJ, thank you for helping us get this message out and hopefully broadening some minds and giving marketers something else to think about and letting them know what's in store for them in the future.
Yeah, there's so many really good things on this
SPEAKER_04
episode and I would encourage you to go back and listen to some of it and you might even want to go back and listen to a few other episodes. I remember Roosevelt Smith talked about big data on an episode a few months ago. Jay Baer as PJ referenced earlier.
We talked about that, I think, on episode 69 and I think that there's also a really good discussion in some of this with University of Illinois as well. So take a look at those and listen to those episodes, but I think the thing I want everybody to walk away with and think about is that what you've known as kind of the gold standard with the cookie-based type of ways of lead generation and generating PPC ads, that's going to change whether we like it or not. Google's policy of cookie is going to really change things in the summer of 93.
So we've got to really be ready and we've got to start looking and I think PJ's comment about asking the questions and really starting to educate yourself is a really good way to look at that and then also kind of open your mind to, I mean I spend, my wife and I are kind of addicted to a couple Hulu episodes, Hulu shows and then we watch a Canadian serial show called The Murdoch Mysteries and they run ads during that and I know that those ads are targeted to my home. I can tell that when I watch the ads, but I think there's a lot of creative things going on over the top television with the streaming devices and I think there's also creative things going on within our home that are being targeted to our IP and to our different devices and so just start to take a break and look at that and start to observe how you're being marketed to as a consumer and then kind of flip that around and say how can I do that for my institution and so I think this has been a great conversation. Thank you PJ, thank you Marty and I appreciate a lot.
Absolutely. Yeah, thank you guys.
SPEAKER_02
The higher ed marketer podcast is sponsored by Kailer Solutions, an education marketing and branding agency and by ThinkPak. Don, I almost made it through 29, 27. Thing without a mistake.
What's the timestamp, Bart? Thank you, I'm going to start that again. The higher ed marketer podcast is sponsored by Kailer Solutions, an education marketing and branding agency and by ThinkPattented, a marketing execution printing and mailing provider of higher ed solutions. On behalf of my co-host Bart Kailer, I'm Troy Singer.
Thanks again for joining us. You've been listening to the higher ed marketer.
SPEAKER_01
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