Vericast: Shaping the Future of Restaurant Technology

But before we talk about Vercast, Marc, why don't you introduce yourself to our audience, talk a little bit about who Marc is, and then we'll talk a little bit about what you get to do for a living.

I spent about 10 of those years working in the promotions and coupon space, building digital coupon solutions. And for the last four years I've been working on a really great project to build a first party data Marceting platform for our clients. So this has been an exciting journey over the last couple of years, and we're just about to ready to bring that product to Marcet. So

So if you could talk, bring me back in time and just share a little bit about where you guys came from, because I think it's, I important for everybody to see the history and then we'll talk a little bit about where you guys are going.

Back then somewhere around 2008, we acquired a company called Advo. In the direct mail space, and that's what brought us our cooperative direct mailer. Because we started to see at that time, if you remember, 2008 right? Newspaper industry wasn't doing so great. And the company saw that we were gonna have to find a new course for, getting coupons and incentives out to customers. So there was an acquisition of this advo company who essentially does this cooperative mailer.

At the time, we were distributing to households under the name Red Plum. The new brand that we distribute under is called Save or save.com. You'll see the logo over on a mug over my shoulder. For those of you that are watching on the visual.

I, I've also been dabbling a little bit in the grocery space and, the grocery media networks. I wanna talk a little bit about that as well. But but talk to me a little bit about kinda how was a restaurant interact with your guys' products and services as you guys have done that over the last number of years?

Small operators, with, 1, 1, 2, 3, 4 stores up to very large national, brands that are distributing across our entire network, which is currently, I don't know, 120 or so million households. I. That we can reach through the shared mail product. So we have a huge sales force that work directly with either the agencies or directly with the operators to sell flyer or sorry, more like insert advertising. That makes it into our cooperative shared mailer.

Just to explain that a little bit, I keep using the term cooperative mailer. That's really important, right? Because what we're doing is. we're sharing the cost of the postal burden with a number of advertisers. So we have the ability to, through our manufacturing technology, to insert many advertising inserts into a single package and mail it as one big package out through the mailboxes, which, brings a, cost efficiency to every brand that works with us.

It's a single one-off restaurant, and ultimately we went there and spent a hundred bucks and I would've had 10 bucks off. Had I brought the coupon, it's still sitting on my counter, so they're probably gonna get me come back because the food was really good. But from an efficiency and an effective perspective, people are still using them every day up and down Main Street. Is that, is that correct?

The restaurants know, need to know a lot about them. Talk to me about that shift and how you guys are thinking about digital and how you're thinking about that interaction in addition to mail, because I don't think mail is going away. I think it's in addition to.

we're able to insert ads there video on your YouTube channel, right. We're able to distribute, distribute video there. So any digital channel that you can think of. Social search, right. We, we've been doing that for quite a while. The project that I've been working on ties all those worlds together and then takes the great amount of data because we do all this advertising and puts it to good use. Right? So just imagine I talked about those 120 million or so households.

Imagine the amount of data that we have at the household level because we're doing that advertising, because we're doing that targeting on behalf of our customers. We have this massive amount of demographic, psychographic, geographic data about these customers, and we're able to. Put that to use to help our clients first, in the first case of digital over the last couple of decades, it's been targeting, right?

How can we, how can we create a perfect audience that's gonna drive a certain response for you and, and put that out into the Marcet, and then drive people either into a store, into some type of acquisition funnel. And that's where we've been focusing. But this most recent effort is more about first party data, right? So I want to get into that a little bit. what is first party data, first off, right?

it's it's all the data that, that a brand can collect because of their first party relationship with a customer, right? So it's, yes, it's things like email address, like when you sign up for a loyalty app. It's, but it's also What you may have purchased, right? And sometimes that's associated if it's done through the app, right? What you might purchase is attached to your profile, and that's first party data information also. But then there's also anonymous interactions, right?

You might, you might go into a store and you might use cash, or you might not identify yourself as a loyalist, or you might visit a website to get information or download a coupon or whatever it is. That's all first party data, right? Super valuable. Right? Especially in this, new world of, of constraints and averaging leveraging data. But we're able to, we're building a platform that's essentially gonna allow you to tap into your first party data, take all the great data that we have.

From collecting against all the households and all the digital devices that we touch, marry it together ultimately to give you effective advertising. that's the basic plan.

Talk to me about that challenge, Marc, because it, it's a challenge. You, you've got this vast amount of data about all of the consumers, but now how do you target Jeremy, Julian with four kids and, and a wife and lives in a upper middle class neighborhood and, in the suburb of Fort Worth? Like, like, those things change the behaviors of me as my, with my family. And if I don't identify myself with that 10% off coupon and now tie that to the POS data, it's hard.

It's hard what you guys are doing. So talk me through your guys' thought process and how you guys have been doing that. Because advertising is great, but if I can't tie it to the behaviors, it's that spray and pray thing that, half of advertising works, we just don't know what half. Getting to a place that, that, that we can do that is really where I know a lot of people are, are looking towards that future year.

So the first task is how do you identify all those different data sources, right? And how do you pull them together? What, what we've done through our. Next Drive platform, right? That we're, we're actively building. Next Drive is a cloud centric solution, and it's, it's, what we're looking to do is unify all those disparate pieces of data. So that's task number one. Identify the data sources all over the organization for the client.

Some of it might be coming from the e-commerce platform, some of it within loyalty, some of it from their app, their website. How do we feed that all in and unify it into a single cloud structure so that we can start to clean it, de-dupe it, make some sense out of it. Then the next step is, I think where you were getting at is. I might have multiple interactions from the same person in that data, but I don't know that, that they're not unique. And so we use a process called identity resolution.

Which is able to identify those different streams. And pull as much of that together as possible, right? So we might have a, a William, a Bill and a Billy, right? All in the system. They're exactly the same person, but our data sources don't necessarily know that till we run it through the identity resolution process. And we're able to unify those information.

So now we have maybe some app information, of William, but we've also pulled some website visitation and promotional downloads from the other two, and we were able to unify it into one sort of holistic view of that customer. So that's that's the first step.

In the very next step, we do a little bit of what I talked about earlier, which is we take all of our proprietary data that we've gleaned from our shared mail network, that we know about the household at the mailbox level, information that we know about the digital user from their device level, right? And where they're, where they're accessing our. Digital advertising if we contacted those consumers before, and we overlay that with the customer's data.

So we're going through an enrichment process using our proprietary data and laying it on top of the customers. And that's important because most retailers, including restaurants, have gaps in their data, right? they might only understand that somebody is an app user and that they've made certain purchases. But they don't understand the full demographic understanding. They don't understand what other interests that they might have.

They might not understand what other websites that they might visit or stores that they might purchase from. So we are overlaying that data on top of what they already have, and we're able to produce more of a holistic view of that, of that customer. Then, so once the data has been elevated, now. You have to be able to put it to use. Right. And the good news is Vericast is a, distributor of advertising at large scale, right?

So we're able to help our clients take that data that we've elevated and make audiences based on. A number of different factors, some of which we're using very complex data science algorithms, some of which are very simple queries, right? To build segments against audiences and then deliver advertising out in a really smart way. So, which is hugely important, right? In terms of personalizing advertising messages to the right customer, drive them back into the store from a retention standpoint.

Using more advanced concepts like lookalike modeling to take, those audiences and then amplify them out to the world and find people who are not in your app, right. That you, I. That, that look like them or have the same behaviors and then use that criteria to hit them with an advertisement to drive them into your funnel.

So now maybe they can become an app user at some point in the future, which is, another, another gap that most restaurants have, which is, they only see the world of the people who are coming into their stores or using their apps. And how do you grow that without reaching outside? So that's, that's an important part. And then we layer on top of that, we're not done yet.

There's a whole learn aspect of what we do, which is we, we build an analytics platform into the, into the platform where, you know, the, the. Our clients are able to look at the performance of all of their data. They're able to understand their customers, run queries against it, run reports against it, and then when we run advertisements, they're able to see the performance of those campaigns.

Then we take the byproduct of that, of those campaigns that run, and we ultimately feed it back into the platform so it becomes another enrichment source, which will help you predict where your next advertisement might be more effective.

So talk me through how you guys might work with a brand to understand that. Because all of the data in the world means nothing. If I can't drive the behavior that I want to try the new LTO to get them to upsell to the appetizer next time they come in or to, to drive some behavior that you're looking to do to drive higher volume or higher, higher margins or, or what, higher frequency, whatever those things are that are part of your. Your desire to work with a brand and, and a product like this.

So talk me through what that looks like as a CMO or as a Marceter or, somebody in a brand that might need to do that.

I, I always like to use the analogy that like, I'm, the, the good news is I have a ton of data. Right. Covid enhanced that, right? Suddenly, restaurants started collecting more data than they've ever had before, and they were playing catch up, but now they're, they're drowning in it, right? Because it's like, it, it can be overwhelming. How do I, if I can't make sense out of it, I can't make strategic decisions for my Marceting and, and, but they all know they have to do it, right?

They all know that. Data is what needs to tell them, right? Where they need to spend and how they need to Marcet. But trying to get to those actual activations is the hardest part, right? So you need a partner, you need technology. And I always say it's not just the technology either, right? You can find analytics tools, you can find softwares. You can find platforms like ours similar anyway, or have the same value proposition, and they're typically plopped with.

The CMO or their staff and said, now go do your job. That's not necessarily any better because now you've got the tool, but you don't necessarily have the time to do the work that's necessary. So you also need a partner that's gonna help you along that journey. I think that's where we've. Decided as we bring our next dry platform to Marcet, that it's going to have this consultative layer, right?

It's going to necessarily have the experts who are gonna help you use the platform to make those decisions walk with you down the journey. Because it's also, it's a quite a pioneering journey as well, because things are gonna change rapidly in the next. Several years and you're gonna need somebody to help you navigate all those changes.

Everybody's trying to know who their customer is so that they can increase that value proposition. One of the other things while you were talking through that, your description of where you guys are going, Marc, is the customization. I happen to be a family of six. I have four kids, I've got three teenagers and a, and an 8-year-old. My spend patterns are very different. My spend patterns are very different.

When I'm on the road at the same exact brand I might be on the road and I'm going there for a business. And when I'm home I'm with the family and it, it's very different. Talk me through even that because the journey might be different for what I eat. Where I spend my money and how, how often I order an appetizer versus a dessert again, just looks different depending upon how I'm interacting with the brand.

And how does that come back to you guys from that consultative approach and as well as in the data?

And it's updating on a regular and frequent basis, and it's constantly learning from those behaviors and it'll, it'll ultimately change over time and the recommendations that we're gonna make for. A campaign that's gonna reach your household might look one way today. They're gonna look different, tomorrow and the next day because it should be constantly learning and being updated.

So as you make different purchase behaviors and it shows up in your app or some other signal that is being fed into the. Unified data instances, it's ultimately gonna update the recommendations at the same time. And you might fall out of a, a segment or a cohort because of the change in behavior. And it's gotta be dynamic in that way, otherwise, it's not gonna lead to effective advertising.

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And so, I thought we were gonna get through a whole episode without talking about the machine learning and ai, but talk to me a little bit about how machine learning and AI is playing parts in the analysis of the data. 'cause you've got so much, but being able to. Serve up those suggestions that are gonna be able to drive that behavior is important. And, and I had asked our CTOA few months ago, I was like, why is it that this stuff is, is coming?

He goes, 'cause computes gotten so cheap, storage has gotten so cheap. And these, these tools have gotten to a place where you can ask it just about anything and it's gonna give you some suggestions. Obviously you gotta pressure test it, make sure that it's valid. And at the same time, being able to say, Hey, what would happen if I sent this coupon out to Des Moines to this set of stores for casual dining? You can test that hypothesis and figure out what potentially could happen from it.

So what data science is, and I, I like to call it a art form more than a, it has science in the name, but it really is much more of an art form than anything else, right? So what we do with our system is first we build models that ultimately we can train with. Tons and tons of data. And then the element of time, right?

So if we can see certain patterns in behavior, like we can start to identify when your son's away at college or whatever, and we start to learn that this happens over time, we can make assumptions that that is going to happen on a relatively frequent basis, and we're able to fill in the gaps of that data. So we use. Data science in that way. Not true ai.

Generative AI is, is hitting all the headlines, but AI from a traditional standpoint in that this is, these are data science models that are being trained from the data because it's happening over time. And that's filling in those gaps and helping to draw more of a pristine picture of each consumer machine learning. Is the automation of that, like being able to take that and have it happen on an automatic basis? When I talked about the feedback loop between.

Advertising performance data and having that feed into a recommendation engine, that's a practice of machine learning because it's happening on a regular basis. And those data science models are looking for the inputs and ultimately being able to update and make and fill in those gaps and make those recommendations. Other places where we're working with AI is more on the front end. So if you're a Marceter, and you.

Have a hard time understanding of I'm not quite sure what I should ask of the, of all this crazy data, right? And I could give you a massive screen full of a bunch of different search boxes and you're gonna sit there and you're gonna struggle. But if you can na, ask it a natural language question like. how many customers visit my store in, this circumstance or that circumstance. And it's able to produce those results.

It's suddenly leveling the playing field because Marceters don't have to be data scientists anymore. They can just simply ask a question and interrogate the data and get back the necessary response. So I feel like it's making. Data intelligence more accessible at that level.

And I feel like if, if AI is gonna have an impact on Marceting in the next couple of years, that's where it's going to be, is leveling up the skillset of, of the Marceter to be able to do a more technical job with, without having to have the knowledge that a data scientist or an engineer or even an analyst have.

So you have to keep them engaged. I think personalization is really important from a customer engagement standpoint for that retention purpose. So hitting them with the the right offers at the right time. Because we've overlaid that enrichment source to the data, we're able to help you build segments within your audience base that's gonna help you do that personalized outreach in a much more efficient way. And, and let's face it, every dollar you spend in Marceting is critical these days, right?

That's even become, with all the pressures from supply chain and food cost inflation, when you spend a Marceting dollar, you'd better sure that it's actually, driving, driving something off your off your menu.

You have the trust relationship with the customer, you might as well be using that for personalization, right? To ultimately craft a, an experience that's gonna drive somebody, to, to purchase. And that's hugely important. I, but I don't think it stops there. I think at that point, all you're really doing is engaging with the people that you already have and you're driving them back into the store and that's great, but now you need to reach outside, right?

You need to find people who are outside of your funnel and drive them in, right? You want them ultimately to be app users. You want them to be regular customers of your restaurant. So how are you gonna do that? I think that's where Vericast has unique value proposition because most of our media types, including our cooperative shared mail package and our digital advertising, they're really suited for. Acquisition programs.

And one of the things that we focused on with the Next Drive platform early on was this concept of being able to do really smart lookalike modeling at that, at a geographic level, which works really great for brick and mortar, right? Trying to find people within a geographic radius. Who look just like your customers, but may not be identified as actual customers, right?

And then being able to target them through digital advertising at a relatively inexpensive cost and driving them to a conversion like, Hey, sign up for the app, or get this coupon and come to the store, starting to get them, interacting with your brand.

I might get the brand name and the title of the email, but. At the end of the day, I stop reading it and I'm probably not disciplined enough to go unsubscribe from them because I still like the brand and I might want to go there, but the advertisement's ineffective and at the same time as a consumer delivering relevant ads to me changes my behavior.

I, I, living in this space, having known you guys and others that do what you guys do, I know it changes my behavior, just evidenced by that 10% off coupon. Made us go to this local Chinese restaurant that we'd been to. One time before I got the mailer in the mail, I, I looked at my wife and said, I don't feel like cooking tonight. Where are we going? It's sitting on the counter. She goes, we're going here. And then the kids forgot to grab the coupon and we missed our 10% off. I

So I'd love for you to talk through not just driving that behavior of the, the discovery for the brands, but also the consumer, whether it's digital or it's in print, is also a huge benefit that I think Marceters and quite frankly, CEOs and other restaurant owners need to understand.

I'll tell you another thing that happens on a frequent basis in my household is I might get three mailers, like in the household from the same brand, right? And like, no, I've noticed that they've had to pay postage like three times to hit my household.

But in the restaurant space, like, I wanna hit you at lunchtime, I wanna hit you at breakfast, I wanna hit you just before your drive time for dinner. Right? So that I can actually affect that, affect that behavior. And I think that is, that is hugely important

There's the atmosphere TV guys that have been selling advertising for a while inside of different brands. Talk to me a little bit about how you guys think of, on-premise advertising, on location advertising in a digital way, whether that's through grocery or, or retail or in in shopping malls and all of that. Because I think that's another key area that I think everybody needs to keep their eye on if they're not already thinking about it. I'd love a little bit of.

You to riff on it for just a few minutes to educate our audience if they haven't thought about it.

So they have this. Inventory that has had been underutilized for, for many years. So they started to realize, heck, if we package this together and either work with agencies, and in some cases some of the larger retailers built their own media networks, right? And now you have to go through them to purchase that inventory. So hugely valuable. I think the next frontier of that are digital screens that live within the stores, right?

That hasn't really been cracked in any big way, and Vercast is actually investing in that as well. Like how do you hit, I. the digital screens that you see above the deli counter there's, they're starting to see, I don't know if you've seen any in your area, but they're taking the freezer doors, right? And they're turning them into LCD screens and putting relevant advertising on them as well. we're in the process

Selling that advertising space to, to push Budweiser over Coors versus, having it, a lot of people have Zs, Oscar, where the Presto device is at the table to drive some of that behavior. So figuring out a way to get in front of, again, a friend of mine Kevin and this guy Doug, are working for this company called Pammy. They've got a whole new thing that they're doing digital inside of retail environments. And so putting these digital screens to drive behaviors, I think.

Whether it's grocery or it's restaurants, or it's retail establishments, or you own the whole mall and now you're gonna drive the behavior to get people to go different places, that's valuable real estate and those eyeballs are really critical to driving the behavior that you're looking for.

They're inside that store. At point of sale. At the deli counter, at the freezer. At the freezer door. Inside restaurants, like you mentioned sometimes at the table, right? In case of digital menus or iPad, iPad ordering devices that are sitting right there, and that advertisement could be something that drives it. What, what nobody has done well to this point is build a network to be able to access all those screens from a central point. Because if you have to do it.

One purchase at a time, contacting each store and saying, Hey, can I put an ad in your device? Right. It's gonna be, it's gonna be critical. It's gotta be done in a very programmatic way where it's a Marcetplace where you can go in and you can buy these screens as a brand or retailer trying, or a, if you're a manufacturer like Coca-Cola, right? Somebody like that, trying to reach somebody at a bar. You wanna be able to buy that programmatically and hit all the screens at once, right?

Or. We've seen them wanna do things like buy out entire grocery store change for the Super Bowl. Right. To try to drive, purchase behavior around that. And trying to build that network is what our company has been focusing a lot of time on. And I think we're going to, we're gonna be one of the very first and

To our audience guys, we know that you guys got lots of choices, as I said on the onset, so thank you guys for joining us. If you haven't already done so, while you're out going and checking out Bear Cast, go subscribe to the newsletter. Once a month, you'll get an email with all of the shows to make sure that you don't miss anything. Marc, thank you so much and to our audience, make it a great day.