Elizabeth Cooke: Mike, please tell us about your background and what led you to your current role at AudienceScience.
Mike Peralta: I’ve worked in digital since the late ‘90s at several different companies, including startups, startups that have been acquired, and big companies. I’ve worked on the publisher side as well as the network, data, and technology side. During the last few years, we’ve seen a lot of different technologies pop up, which has made it much more complicated for marketers to buy on digital channels. I came over to AudienceScience because they are offering a radically different model, working directly with marketers in a transparent way which reduces millions of wasted dollars, normalizes frequency and keeps data safe. Basically it solves for a lot of the major problems that I’ve seen arise as the market has gained complexity over time. Many marketers might think that they are solving for these things, but when you’re in the middle of the supply chain, you see how wasteful it really is. AudienceScience puts the control back in the hands of the marketer.
Please tell us more about AudienceScience and AudienceScience Gateway.
AudienceScience has been around for over 10 years and was the first company to come out with a whole platform that managed data. Over the years, we’ve realized that our platform could help make it more efficient for advertisers to buy online. Our product, the AudienceScience Gateway, is an enterprise-class platform that does a number of different things. It manages all of an advertiser’s data — first party, second party, and third party. Our system also has a media execution component, which allows you to not only manage your own data but take that data and action it across a variety of different media sources, all in one platform. This allows you to see your users, activate your users across any type of media, and then obtain full reporting across the board.
How does AudienceScience Gateway help marketers in the digital space?
The two key things that big brand marketers like about our system are its control and its transparency. Looking back 10 or 12 years, the Internet advertising space was pretty straightforward. You had the advertiser on one side, the publisher on the other side, and they did business together. Over the years, a lot of things in the middle have popped up. Today, there could be a hundred different steps between the advertiser and the publisher. We take all of that stuff in the middle and put it into one platform, giving advertisers a central dashboard and control system that allows them to deal directly with publishers. The platform offers transparency, helps advertisers understand their true frequency, and lets them know whether they are actually hitting their target.
Why do marketers need a technology platform like AudienceScience Gateway?
When a marketer wants to advertise a particular product to a specific target audience, he or she usually has an understanding of the target age group and gender and gives a brief to the ad agency. The agency then talks to several different publishers and publishers respond by saying that they can hit the target audience at an average frequency of five. The challenge for the marketer, though, is if there is an average frequency of five, it could mean many people saw the ad once and one person, or more likely one robot, saw it 10,000 times. It’s not a true frequency measure, which means that the marketer is wasting up to 95 percent of the impressions that he or she is actually buying.
Our system manages all of a marketer’s user data. Rather than saying to the publisher, ‘I’m going to buy a certain amount of impressions at a certain CPM and you tell me the target that I’m hitting’ — in other words, classic “share of voice” ad buying — audience targeting works in reverse. The advertiser says, ‘Whenever one of my users shows up on your site, I want to buy the impression of that user.’ And they can do that across multiple sites, which means that, first, they spend money only when they see someone valuable; second, they have better control over whether or not the actual user sees their ad; and third they can control for frequency across multiple publishers.
And what we’ve found is that for large brands, controlling for frequency is by far the largest cost savings. Let’s say they want to target me because I’m a digital dad. I go to the site and they see me and show an impression to me. That counts as one impression. With our system, if I go to a second site, and they see me again and put another impression in front of me, that counts as impression No. 2. In other systems, no one is managing frequency across publishers. So for each site I visit, that publisher thinks they’re showing me impression No. 1. This means that at the end of the campaign, I could have seen an ad a hundred times but it would still report back as a frequency cap six. And that “six” frequency is reported as an average, which means some people like me could have seen the ad hundreds of times while others only once. We’ve seen up to 94 percent waste from these two factors. Our system helps control that measurement.
So AudienceScience Gateway puts the power back into the hands of marketers while also helping with their spend?
Absolutely. In the U.S., digital advertising is about 17 percent of overall online ad spend. The UK has a higher percentage, about 27 percent, of online ad spend. But if you separate out the big brands, those companies are only spending 5 to 6 percent of their overall ad budgets online at best. My experience is that one of the reasons they’re doing that is because they’ve never really understood what’s worked and what hasn’t worked online. They’ve never really understood where their money is going when they use online advertising. A system like ours can help big brand companies figure that out.
What results have your clients seen?
We developed this concept of PMQ, which is your “productive media quotient.” What that really aggregates is all of the different layers of spend, both in terms of fees and margins for different companies as well as overused frequency, out-of-target impressions, and the like. Today, there are about 50 different steps in between an advertiser and the impression that is eventually served, and all those 50 different steps take a little cut of the actual ad spend. By the time one dollar leaves the advertisers hand, only five cents ends up getting to the publisher. In other words, 5 percent of a digital media budget is productive. The challenge, especially for big brands, is reducing that waste. Our system has helped a number of different advertisers save anywhere from 50 to 80 percent of their actual ad spend when we expose margins and control for frequency and targeting. From an ROI perspective, we’re seeing anything from double to six-X better return on investment. This takes into account the use of different types of brand engagement metrics as each client uses a different formula.
What is PMQ exactly?
When you look at all the different levels of spend, PMQ is when you actually run a piece of advertising, when your media dollar was actually productive. The real piece to pay attention to is the rest, the unproductive majority of your spend. For example, what are all the components that go into digital media? One component is actual frequency, so you’re saving a factor of two or three just on frequency. In addition to frequency, there’s targeting. A lot of times, if you don’t know your user, you’re actually getting an inference of targeting with overlaps across different providers. Each site has their own logic and not a ton of visibility. One of the challenges occurs when a publisher site says, ‘Well, we have the highest number of visitors, but there’s a 50 percent chance that the user is going to be a male.’ One of the hardest things to do right now is figure out whether the user you see is male or female, because publishers use all sorts of inference models. But because we help you store your data — which has your own prompts and registration data — we can tell for sure whether the user is a male or female. In addition, when you look at the different layers of technology that folks are using, there are different margin components. You may not know whether a network or a demand-side platform is taking additional margin off the top of your campaign. We help reveal all of that in a very transparent way. PMQ adds up all of those different levels of inefficiency in the marketplace.
How do you illustrate this to prospective clients?
So, in the end, out of that $100 million spend, $50 to $80 million either is wasted or goes to margin or vendor fees. Of that $100 million that you wanted to spend and thought was going to advertising or impressions that actually reach your user, maybe $80 million of it isn’t, so you end up having only a $20 million spend that’s actually effective — in other words, you have a 20 percent PMQ. Our goal is to turn that upside down and make sure that, out of that $100 million, you’ve got 80 to 90 percent that’s actually hitting what you needed to hit.
Can you provide any examples of cost savings that existing clients have experienced?
I can’t talk about specifics. A lot of the big brands that we’re working with don’t like to tell other big brands what they’re doing. But from a range perspective, our clients are seeing anywhere from 2 to 6X in terms of ROI and anywhere up to 80 percent in savings. It is a significant change from the norm of trusting an agency to spend your money without any form of transparency or marketer-owned technology to control that spend.
It is an effort and commitment on the part of the client to realize that they need a direct technology to ensure that their money is being spent effectively This is a different school of thought. In many ways, the client almost has to drink our Kool-Aid on this and, once they do, they realize that the benefits can be huge, but it’s not something that everybody is ready to do. Clients that understand that it takes some effort, at least in the short run, get the most out of our system.
What problems are marketers most challenged by today? And how does AudienceScience help solve those problems?
One of the main problems is complexity. If I’m a big brand client and I have $100 million to spend and I’m talking to a TV guy, that TV guy can probably write a media plan on the back of a napkin to help spend that $100 million real easily. But if I have $100 million to spend online, what do I do? How much should go into social? How much should be search? How much should be a homepage takeover? How much should be a sponsorship? How much should be targeted? Should it just be run at network? Should I put it on network? Should it be contextual? I’m getting a headache just thinking about all the different choices. And because of this, at a lot of brands, the agency handles digital budgets and the brand really doesn’t see what’s going on.
Our system helps marketers see and test all of these different ways to advertise digitally. It offers a holistic view of their users and what they are doing online, giving marketers a much better chance of coming up with the best mix in terms of digital advertising.
How does AudienceScience analyze all that data to enable a more targeted, effective interaction between organizations and their target customers?
We recommend that you use a holistic system that connects your data with your media. There are a lot of misnomers about big data. You could have all the data in the world and analytic reports showing you how to use that data, but if you’re not able to actually take action on that data, then the reports will just take up space on a bookshelf. With big brands, we also recommend that, first and foremost, they manage their own data and own the system that manages it. A company’s own data is extremely valuable and needs to be protected. But data that is isolated in silos doesn’t add much value to a company. Every company wants to push product and take action on their data. Our system helps our clients both manage their data and take action on it across different media sources. This is a big differentiator for us. Many data management options are isolated from that action, so any time you want to use that data, you have to ship it to another vendor, which compromises data integrity and performance. You have no feedback loop to improve over time.
Should CMOs focus on specific channels over others in today’s digital world?
In my view, marketers should be in a constant test-and-learn environment. The beauty of online advertising is that there is lots of data and when you’re running something, you get feedback right away. It’s important for marketers who want to run online campaigns to take an evergreen approach. They should always be testing and learning about what’s going on in the marketplace. Looking at campaigns from a calendar base or time base, you could say that social and mobile campaigns work better at certain times of year, while design efforts, sponsorships, or homepage takeovers work better at other times. The same thing does not work all the time, so you need a system that helps you manage the different channels and advertising that you need to use.
If you’re a direct marketer, you may want to max out on search, use affiliate, and then do performance-based advertising through display. If you’re a brand advertiser, you may want to have some balance between social and direct buys on publishers. But both groups first need to understand their users, manage their own data, and then build from there.
Advertising on digital channels sounds like more of a sharpshooting exercise versus scatter shot, which is what traditional advertising or marketing has been. Is that a fair assessment?
Ten to 12 years ago, it was tough to really understand how to do one-to-one marketing in a mass-marketing world. We’re getting closer to one-to-one marketing in digital. I don’t know if we’re there yet, but we’ve got such processing power across lots of different servers and computers and can collect a lot of data, which means it will probably eventually be one-to-one. Depending on the audience, you could put the exact message that you want users to see in front of them. I don’t think we’re there yet, but we’re heading in that direction.
Are traditional marketing channels going to be obsolete in the next five to 10 years or are they still an integral part of a marketer’s strategy?
In the U.S., big brands still spend 95 percent of their ad budget on traditional channels. That’s still where a lot of the money is. But on the flip side, all their users are online, on mobile devices, or on tablets. What’s the most effective way to reach those users? In the past, with digital, we haven’t had the best answer to that question, but a system like AudienceScience Gateway that allows companies to really understand their users and then find them wherever they are online is the right approach. In the near term, there is still going to be a lot of onus on channels like TV, but eventually companies are going to be much more efficient about targeting the right user online.
If you look overseas, China already has 500 to 600 million handsets. In that country, advertising is going to be much more about mobile and much less about the desktop. It will be a little different in each global market.
With people using their mobile devices for so many different things, what does the modern customer expect from the content they receive? How should marketers cater to these expectations?
The Internet has put a lot of power in the consumer’s hands. I’m a researcher by nature, and it takes me a year of research just to buy a TV. I’m exaggerating, but the key is to provide the right type of information to the right type of audience. I like detailed information around a product and want to know what other people think about it. If a company knows me as a user, it should provide that kind of information to me. Other folks like a good deal, so if you show them content around a good deal, they may be more likely to act.
Modern consumers have much higher standards about what they want to see, whether it’s regarding a product or a company. Advertisers have to provide quality information in interesting, creative ways to break through the clutter on the Internet. That’s why it’s so important for marketers to be able to control exactly what message gets in front of exactly which user. It’s going to be even more important five years from now than it is today.
How are marketers measuring that engagement and the results being driven by it?
We’re still in the early days of knowing exactly which measurement matters. Each big brand has its own model for engagement. What we’re doing at AudienceScience is helping our clients use our system to measure their engagement online, and the fact that you manage data and media spend in one place is the only way to gain insights and act on those insights. That engagement could be anything from surveys to how many views a user has had on an actual site to how long a user looks at a video. The system segments the various models and then ties the engagement all the way to store purchases. The key to that measurement is the data and understanding your user. If you understand your user, you can segment your audience and then put the right measurement tools in front of the right user. This helps you be more effective whether or not you’re actually engaging the audience.
What trends do you expect to see in marketing in the next few years?
Over the next year or two, there’s going to be some consolidation in the marketplace. There’s too much complexity today. We need to make it simpler. If you look at the number of point solutions a typical brand employs to run an average campaign, it’s unmanageable. I also think from a marketer’s standpoint, video will continue to become more important in the online mix. We’re seeing some interesting things happening in terms of how to measure video and the types of video units that are available. Internationally, maybe toward the end of the year or the beginning of next year, we’ll see more traction around mobile. With mobile, we have to figure out how to track across multiple screens and how to display content. Because the screen is much smaller, what kind of ad formats can we use that are actionable, more engaging, and can capture the consumer’s interest better?
More marketers are going to look at ways to control their digital ad spend in-house. It’s too important not to have the keys to the system, and we’re definitely seeing more and more marketers interested in getting that piece of technology in-house — not necessarily managing it themselves but actually having access and control over it is going to be key this year and next.
How will AudienceScience evolve to address some of these new developments?
If you look at our product road map, especially toward the latter half of the year, we’re doing a lot of interesting things on the video front both here and overseas, particularly in Asia, where video is already huge. Toward the beginning of next year, we’re going to dive more deeply into mobile and more robust cross- device data management. In terms of measurement, business insights, and analytics, we’ve got a big push in the second half of this year to take our reporting and insights to the next level.
Overall, philosophically, we look at ourselves as a centralized platform. We’re not necessarily out there to address every new medium or development. But we are going to make sure that our platform is interoperable and scales for our core clients, which are global brands, because every region and every country has something new and interesting that advertisers may want to test and we want our platform to work for everyone.
Mike Peralta, CEO of AudienceScience, oversees the sales, marketing, and business development teams with primary focus on ensuring the successful adoption of the AudienceScience Gateway technology platform for clients. With more than 20 years of business experience, including 12 years in the advertising technology sector, Mike is extremely qualified to enable the successful execution of the company’s strategic initiatives and vision. He has held numerous executive positions in the industry both in the United States and Europe, including nine years with Advertising.com and AOL, moving up through numerous positions in strategy, sales, account management, and business development. Through his support, the company grew significantly and eventually merged into AOL’s Platform A.
Mike holds a degree in civil/environmental engineering and management from Rensselaer Polytechnic Institute and has done graduate work in management and public policy at New York University.
Elizabeth Cooke is a member of Argyle Executive Forum’s content team. Argyle Executive Forum is a professional services firm that convenes and connects business leaders from highly targeted business-to-business communities for strategic collaboration and business development. More than 25,000 executives participate in one or several of Argyle Executive Forum’s communities, with more than 200 new members joining every month.
Prior to joining Argyle Executive Forum, Elizabeth worked as a senior search consultant for a boutique executive recruiting firm covering the investment banking and private equity markets. Additionally, she was a senior sales executive at the New York Stock Exchange, calling on C-suite executives and venture capital firms. She holds a Bachelor of Science degree from the University of Colorado at Boulder.