Hyperlocal Advertising Campaign Setup with Factual

Video Transcript: Hyperlocal Advertising Campaign Setup with Factual

Welcome to episode number 65 of The Great Reset. My name is Robert Brill and I'm the CEO of BrillMedia.co. We are an advertising firm that helps companies achieve business results with the best paid media, data, and targeting available in the marketplace far more than Google and Facebook, the full breadth of programmatic advertising capabilities in-house.

We're here five days a week talking about marketing and advertising for senior marketing executives, entrepreneurs, and anyone who is looking to grow their company. Today we'll talk about some of the setup that is necessary to turn out a location advertising campaign and we'll focus on a tool called Factual, which is a fantastic interface and in my opinion, one of the best tools available in the marketplace for location advertising. I like it because it's easy to use, intuitive interface, and it gets a lot done, and finally it really just connects right into the larger programmatic ecosystem in the tools that we use to run advertising.

So there are two parts to the tool. One is proximity, one is audience. Proximity looks at locations, so where people are at the current moment, and audiences looks at the past, where people have been recently in the past, and with the ability to filter audiences by age, gender, demo, and lifestyle activities.

So we're going to go to five different examples that I have prepared for this video of how the data is used. And we're going to look at auto sales, so competitive auto sales, targeting ads to fans of Mexican restaurant food, people who have been at a specific walk to Walmart in Los Angeles. We're going to target two miles around of five guys in Los Angeles, and we're going to talk about how Topgolf, for example, which I like Topgolf.

I've been there. I had a great time. Topgolf in Vegas would want to grab people from casinos, MGM casinos that are around there, and get them into the Topgolf location for a fun pool-filled day of Topgolf and fun with friends.

So here we go. I'm going to change my screen. So here's what we're going to look at.

We're going to first look at Factual. So Factual, as you can see here, Factual is now owned by a company called Foursquare. You might remember Foursquare, the company that made it possible to check in and be the mayor of different locations about a decade ago, is a very valuable, very important data company, and they just bought Factual.

So when you look at Factual, there are two different sections, Audience Designer and Proximity. Proximity tells you where people currently are. This one lets you reach people based on where they have been in the real world.

Now let's jump right into Audience. So this is Audience Design number one. And what Audience Design number one is designed to identify competitive conquesting for Honda dealers.

So let's say you're a local Toyota dealer, and you may want to identify people who have walked into a Honda dealership in and around your area in Los Angeles over the last 30 days. Because the person who walks into a Honda dealership, if those people haven't bought, it's a clear indicator that they're in market for a car, they're in consideration, and you want to tap into that audience. So what we do is we go into the behavior section of this tool.

I've already typed in Honda. So what I did, I went to this section right here. I typed in Chains.

I typed in Honda. And what this identifies are all the people in, and I filtered into Los Angeles, by the way, because I'm not interested in people who are in New Jersey going to Honda dealerships. I want people who are in my immediate vicinity interested in buying a Honda, and I want them to end up buying a Toyota, for example.

So all of these red dots indicate Honda dealerships. So that's Culver City Honda. That's Honda of Santa Monica.

So if I'm Toyota, I want to get people to my Toyota dealership. And so basically what I do is I do a search. I go to Add Places.

I go to Chains. I go to Honda. And I use Honda dealerships.

And by the way, just to give you some details, like for automotive, for example, you can target any one of these dealers. Buick, Cadillac, Dodge, Ferrari. It's a whole slew of places.

If I go to Categories, I can go into a lot more detail. I can target people who are into automotive. I can target people who have been at advertising and marketing firms, people who do art restoration, people who are at their corporate headquarters, who are in the media business, who work or have gone to banks, people who are interested in loans and mortgages based on the fact that they've been at loans and mortgages locations.

So there's a slew of valuable information here. Okay. So I'm then going to filter.

I can filter by state. I can filter by just a general area. So I can target Atlanta, for example, or the Los Angeles DMA.

But the DMA is a large area. I don't want to just target the DMA. I want to actually target specifically Los Angeles, the city of Los Angeles.

So I target that. Click here. And basically what this is telling me is that there are 52 places that allow me to target the Honda dealer in Los Angeles.

And what this says is these are people who have been at the Honda dealer in the last 30 days. Now I can target a radius and say anyone who's been near a Honda dealership, but that's not nearly as value as people who have been at the location. In the last 30 days.

And you can change this to two months, three months, a year, or a specific time frame. Okay. So like for example, you can say I only want people who are in market from June 8th to June 21st.

So whatever it is. So what I'll say, I'm going to look at the last month. I'm going to add this to the design.

I'm going to calculate reach. And this is directionally accurate data. And what this will tell me is how many unique devices are available for me to target based on this specific set of targeting parameters.

And we'll come back to this to see what it looks like. You can also further filter. Maybe I don't want 18 to 24 year olds who have been at a Honda dealership recently.

I want 25 to 54 year olds because those people are much more interesting to me. Or I'll go in. So I can keep this as all Honda dealerships.

Or I'm going to add this to the design. Now I'm filtering to people who are 25 to 54, let's say. So there are 210,000 people who meet this targeting.

So now I know that there are 210,000 people that are available for me to target using this mechanism. All right. Next up we have a Mexican restaurant.

Let's say that the Mexican restaurant really is interested in targeting people who have been to other Mexican restaurant places in and around their town. So there's a few ways we can do this. And what I'll do is I'll first go in to the category.

And with food category it's pretty straightforward, right? Like I can target people who are in the business of food, who are in candy stores or cheese stores or chocolate stores or farmer's markets or breweries, bakeries, barbecues, buffets, Chinese foods, delis, diners, fast food, Korean, Mexican, Middle Eastern, pizza, and so forth. There's a lot of targeting available.

So first I want to say I have a high-end Mexican restaurant. It's expensive. I want to target people who like Mexican food.

Cool. Click on that. Now I'm targeting, and I already have this here, I'm targeting people who are interested in Mexican food.

And let's say my restaurant is somewhere here in Hollywood, right? So I don't want to target people in Santa Monica because if you know anything about Los Angeles, Santa Monica to Hollywood in most cases where there's a lot of traffic is geographically undesirable to say the least. You really got to plan that drive out.

So you really want to target that two to five mile area. So let's say my restaurant is somewhere around here. What I can do is target restaurants in a specific set of zip codes.

So what I do is I go to advanced. I go to postcode. And I'm targeting people who are in these areas.

So 90027, 080, and 038. I'm targeting people who have been to a Mexican restaurant in these areas in the last 30 days. And I can go back to a year.

And these are people who have been at the location. Now look what happens if I take it off. I may take off these zip codes.

And now I'm going to get people. I'm going to go back here and type in address contains and type in Hollywood. And I'm going to get people in a larger area.

Close this. This. All right, so I'm going to go back here.

Filter. Advanced. Address.

Contains Hollywood. All right, so now I'm in this area. But let's say I just want to target everyone in Los Angeles.

I'm going to take this off. And I'm going to target everyone in Los Angeles. So by geo, I'm going to go to DMA.

I'm going to go by locality, Los Angeles. All right, so these are people in Los Angeles. And you can see some of the names of the restaurants.

Prado restaurant. Las Cabanas. De San Pedro.

Perfect. So now I'm going to add that. I'm going to update.

And now I want to say I don't just want to target everyone who's been to a Mexican restaurant. I really want to filter to people who have higher income. So let's say $75,000 and above.

So you choose the income here. And there you go. And now we have a set of people who are available to be targeted.

Who have been at a Mexican restaurant. And who have at least $75,000 household annual income. So now let's take a look at people who have been to a specific Walmart.

Because one of the examples that we've discussed recently was, you know, we have distribution in two Walmart stores as a test. We really want people to make this product fly off the shelves. And so really our buyers are anyone who walks into that Walmart.

So if you don't walk into that Walmart, you will never be able to purchase because we're in a test phase right now. So again, you go back to chains. I'll take this off.

Type in Walmart, Walgreens, whatever the case is. You type in Walmart. So that's selected.

And the locality contains Pomona. And what happens here is I have two places in Pomona out here in Los Angeles. And I have these two locations.

One here, which is Walmart on Rancho Road. And this is the Walmart neighborhood market. So again, these are people who have been at the location in the last month.

But you can go out further than that. But you figure last month these are people, these are active shoppers at Walmart. There you go.

You have a calculated reach and you can serve ads to these people. Again, you can go in and filter lifestyle, for example. If you're selling something healthy, you might have the opportunity to target gym and fitness people.

The only thing is if you target too granularly, you're going to make it so that you don't have enough people to target to begin with. So we had about 50,000 to 75,000 people in the last two data sets. This might be unnecessarily narrow.

Okay. So we're going to go to, yeah, 43,000 people. Yeah, that's an addressable audience.

Okay. Now let's go to the example of a Five Guys Burgers and Fries. Boy, do I love me some Five Guys Hamburgers.

They are delicious. So I'm a Five Guys. Let's say I'm a restaurant franchisee.

And I know that people will travel two miles around my address to target people who will come to my Five Guys hamburger. Fantastic. So what do I do?

I identify my address, and I can identify that just by uploading my address or uploading my latitude and longitude. And so I can go this way, categories, chains. I can type in Five Guys Burgers and Fries if you have a name brand chain.

But certainly if you don't have a name brand chain, if you're a small burger joint, you can use the same by uploading your latitude and longitude, which we'll show you. And basically just set the radians, geofence. And what this says is that anyone who has been within a two-mile radius around this address, anyone who is here right now, they are eligible to see our ad.

And what that means is if you're on your mobile device or there's some data that is being passed about your location in any capacity, now we have identified you as a person who is in our selected filter, and we can serve ads to these people. So if I'm going to calculate reach, this is going to take a moment. But at the end of the day, what we're saying here is there's going to be a certain number of people that are available in this data, and that's the available reach.

And now this is really viable, right? So there's 177,000 devices. I would really focus in on this number.

I don't care about this so much because this is a ridiculous amount, and we're not going to serve 518 million impressions to serve people two miles around this address. What this does is give you directionally accurate data about the scale of the audience. What I can say here is that there's a lot of impressions available to reach 177,000 devices for this campaign, and that's good.

Now I can set up a frequency, and on a different video, we'll talk about frequency forecasting. And then finally, what we'll look at is MGM for Topgolf. I love going to Topgolf.

So this is Topgolf right here. It's right next to the signature at MGM Grand. This is in Vegas.

So let's say business is struggling and people are shut down, but there's definitely some people going to Vegas. And let's say you want to capture people at these specific places. People go to ARIA, Park MGM, and MGM Grand.

These are your feeders to walk into Topgolf. Why? Because it's easy to access.

It's nearby. It's just overall geographically desirable, even though overall the strip on Vegas is completely geographically desirable. And let's also say that the people who visit Park MGM, ARIA, and MGM Grand are the right customers, meaning they have the right income.

They're maybe higher income. Maybe they have a greater propensity to golf, whatever the case is. The point is these are people who you want to reach.

For some reason, I'm sort of like making some general assumptions here. Maybe you don't want to target people who go to Excalibur because people who, you know, like let's say Excalibur is a lower overall cost casino. These are lower income folks maybe, and these are higher income folks, and you definitely want higher income.

Let's say that's the assumption that you want to make. Straightforward. Anyone who is in these radii have the ability to see your ad when they are in this space.

And all we did is we go to MGM Resorts. So we get to add places. Go to MGM.

We have MGM Resorts, MGM Grand, Skyloft at MGM, MGM Grand Buffet. So the point is I care about the area here. So I chose 600 feet.

Anyone who's in these places right now, they have an opportunity to see your ad to get them over to this Topgolf that is next door. And then on a separate type of campaign, you set this up so that anyone who's been at the MGM recently, if they're still in Vegas, they have the opportunity to see your ad. But the point is you can place a geographic filter here so that you're only targeting people who are in Vegas right now.

If you are not in Vegas right now, this targeting is completely unnecessary unless you're targeting a campaign for future accessibility. And then finally, what I'm going to do here is show you Topgolf. So I'm going to show this is the address for Topgolf.

I'm going to put a location on the map. And what I'm pointing out here is the latitude and longitude. So another way to make this targeting more granular in case your information doesn't show up on the map is to target this latitude and longitude.

36.106012 by negative minus 115.164236. The point is, in an earlier video, we talked about latitude and longitude and how granular this is. So, I mean, I'm not worried about that this is the side of the road.

This is exactly, these are where people are. The point is, it gives you some insight into what a latitude and longitude looks like and how you can then grab that data and upload latitude and longitudes back into this platform on Factual. So you can see that location targeting is versatile if you know how to filter audiences and use this precision data to reach customers.

So next, we're going to talk about where ads appear for these types of targets. See you tomorrow on The Great Reset.