Mark Zagorski is CEO of eXelate, a data marketing technology company.
As part of its "State of..." series of articles with industry executives, AdExchanger.com spoke with Zagorski to discuss his company, his views on the space, and the state of eXelate today.
Click below or scroll down for more:
- eXelate Data Exchange Update
- On RTB and Programmatic Buying Trends
- Target Market and New Products
- Unstructured Data
- Revenue Momentum
- Regulatory Landscape
- Milestones Ahead
MZ: To put it quite simply, our driver is to help marketers make better digital advertising decisions. And we're doing that through providing unique and proprietary data at scale. The unique data by creating exclusive relationships with offline data partners, online data providers and the proprietary being to create custom modeled datasets so those advertisers can better target audiences based on their specific needs. So the exchange is more or less a means to an end for us and that end is helping advertisers and marketers drive better digital advertising decisions.
Does the exchange model exist today with eXelate?
Yes. The concept of an exchange can be taken in a lot of different ways. We still have a model in which there are buyers and sellers of data. Data, in which we ingest, segment, score and deliver - so that the exchange to which we're connecting can absolutely exist. Where it starts to morph into something different is the concept of creating a private exchange. It's how we connect specific buyers to specific sellers in their own proprietary relationship. And then the concept of not just connecting a buyer and seller of a constructed piece of data, but also taking that data and building something totally new out of it.
So, where an exchange or a marketplace considers the idea of someone bringing a product in and selling it directly to a buyer, we're now moving into a world in which someone brings a product to it.
We sell it to a buyer, but we can also take that product and make something totally new out of it, then sell it to a different buyer and create greater value across the board - both for the people that brought the data to bear, as well as for the buyers themselves.
How would you define programmatic buying right now? And, what are the ways people are using programmatic buying in their ad spend today?
The way people use programmatic buying as of right now is they're separating direct-to-publisher branded buying in one bucket and programmatic buying in another - which is kind of automated through a DSP - or through an SSP, or an exchange in another bucket. So, most programmatic buying is being bucketed into audience buying or audience targeting and then the rest is, "I'm buying a branded site. I'm buying ESPN, or 'New York Times,' or 'Time,' et cetera." Where those things will start to morph is through private exchanges, more transparency and the programmatic buying world. And that is more of the classic budgets that we're focused on in branded buying that will move towards programmatic audience buying, but with refined sources of media.
The efficiency is in programmatic buying. You're removing the inefficiencies of pricing and of people and replacing them with product.
Have you seen the impact yet of agency trading desks?
Absolutely. The agency trading desks (ATDs) are taking a much more prominent role in making - not only decisions for the agencies and the brands themselves - but they're impacting how publisher media is bought all together. So again in looking at that break between branded buys on a publisher and programmatic buys, when the agency actually has the buying desk or trading desk in-house, those discussions can be held internally. Those buckets can start to be mixed. ATDs are a real force right now in how media is being bought. They're going to continue to grow in their prominence. It's a positive and aggressive step that the agencies are making to stake their claim in this new, programmatically-bought media world.
If you think of who our real end consumer is, if you compare this to a retail analogy, our end consumer is the advertiser or the marketer. And sometimes that advertiser or marketer is represented by an agency and sometimes not. Our retailer, the person we work with to distribute the product, are the DSPs, the agency platforms, the SSPs and the ad networks. Those are our retail partners. We create a product. We have a distribution partner - that's a retailer.
How does your new maX Data product represent the direction that eXelate is now taking in the market?
If we look at our strategy, we've got two ways we're heading with our strategy. The first is ensuring that we have unique data from both online and offline partners. The second is building out our own proprietary data sets and ensuring that those datasets are helping advertisers and marketers better reach their target audience.
The building out of Max and the Max model data is a part of that latter strategy which is building a proprietary data product that meets the specific needs of an advertiser in real-time and making sure that data product or that model data product can morph over time and learn how it's working and responding. It's driven by the demands of the advertisers with the fact there are a lot of cookie cutter data sets out there right now.
Can you walk us through a use case of maX?
Sure. In the case of a maX or a modeled audience extension buy, generally, we work with the agency or the agency platform who represents a client. And let's say in this case, we have an auto client. That auto client may have a website in which there's a viewer locator or a "car configurer." This is a car configuration tool that leads [the consumer] to a dealer. What we can do is take the user activity specifically from that interaction with that tool and model those users and taking potentially an audience of, let's say, 50,000 uniques and model them out to an audience of five million uniques.
In this case, we're able to take a seed of data, model out around that data and give an advertiser the ability to retarget an audience that is high performing around a specific activity - driving a lead to a dealer. And we can do so at scale so they can create reach.
We deliver that data through any media platform that an agency wants so we're not tied to a media platform or a network. And we're able to provide a response to an advertiser based on a customized data set that is specifically built in real-time for their needs.
Where does this relate to the world of DMPs? Do you guys consider yourselves a DMP in some way?
We have what we call a data marketing platform. In the classic sense of the word where somebody is going in and managing data and moving it from point A to point B, that's not a business that we're in. We help data owners make money from their data through our data links platform. Since we are a single-focus company - helping advertisers make digital adverting decisions through data - it's allowed us to have an unconflicted and singular approach, which means that we work with all the major DMPs out there. If an advertiser or a publisher is using a DMP to push data out or ingest data in, we work with those platforms.
Can you be more specific on some of the verticals that you are particularly strong in?
There's always the classic auto, travel, retail or shopping that do well for us and that we know are constantly looking to leverage data. Where we see interesting growth in targets for us are specifically in the consumer brands or CPG companies because they haven't had a lot of opportunity to target in the past other than just using straight demographic targeting. And then the second group is telecom and finance/insurance. And again, those are areas in which modeling can start to move the needle for them. They are constantly spending money to acquire new customers. For example, people like Verizon and AT&T are constantly looking for new customers all the time. They spend money because they're looking to drive direct response business. The traditional data segmentation and targeting just doesn't work for them. They need a model that moves and grows as they do. And if they can find a model that works, they're going to consistently spend money with you. So we see financial services, insurance, mobile or telecom as being targets for the modeling aspect.
There's been a lot of talk in the marketplace about trying to make sense of unstructured data and specifically social unstructured data. Do you see that as a big opportunity out there - the unstructured data world?
Absolutely. If you think about the space where we're playing right now, the idea of “big data” has many definitions, but one of the most prominent is unstructured, large flows of data. And if you think about what eXelate does, we ingest data that is unstructured, online, behavioral and intent data and it doesn't have any real rhyme or reason. It's a certain type of activity. We try to cluster that into propensities; a propensity to purchase a ticket to Paris, a propensity to go to a new car lot and look at a car. A lot of what we're doing right now is actually a small piece of the big data puzzle, which is how we analyze online behavioral activities and cluster them into similar relationships.
Our maX Data product is again another attempt at looking at disparate data points that have no seeming relation to each other whether it be a piece of structured data like a demographic information or something totally unstructured like the visits to certain types of websites or browser types. Bringing those things together in some type of structured segment and a model like we do with maX is another look at taking on what this big data concept is and shrinking it down into something that's very actionable.
How do you describe the difference between transparent data sales and anonymous data sales?
Think of the transparent data offering as being more or less a private exchange. It's when the seller of the data actually knows the buyer. They know who's providing the data set and what is comprised of that data set. Whereas the anonymously segmented data set is where we do our work in taking that unstructured data, putting it into segments even though it's coming from multiple and different sources –and then delivering it to a buyer based on our interpretation of that segmentation. It's two kinds of directions of the same kind of marketplace model.
We won't share exact revenue numbers, but I can say that we've grown at over 2x year over year, in the last two years. The number of data points that we're collecting continues to grow - last year by about 75%. This year we'll see the same. We've got more data coming into our audience data cloud, which generally means more revenue for us and for our data providers or partners.
What about the service side to the products you offer? Do you consider that an important part of the business?
We consider ourselves a data business. But at the core of everything, there's service and both our data providers and publishers need to feel that they are not only getting the most value for their data by working with us, but also understanding where that value is coming from. And they must have a good understanding of their audience, which we can provide for them through our analytics tools and ensure them that the technical integrations that we've done with them are robust, while meeting certain privacy requirements. We act as their partner in this process as opposed to just looking to generate revenue off of their backs.
So even though the core part of our business is highly scalable, which is the data marketplace, there's still a lot of education that needs to be done on both buyers and sellers sides that we're responsible for. There's a lot of compliance that needs to be done from the privacy perspective that we're responsible for. And then there's a lot of education. This isn't a formula yet. Everyone is still learning so we've got to help provide that learning.
The statement from the White House [recently] and their Consumer Privacy Bill of Rights is totally in alignment with where we've been from day one. The concepts of control and transparency are all things that eXelate has focused on and been ahead of the curve on. It's been our preference manager that gave consumers total control and access over every piece of data that we have and our recognition of the "do not track" header, which we did early on in the game before it was required - and we’ve maintained key relationships with groups like NAI, Evidon, IAB and so on.
The position that the government has taken, particularly in respect to acknowledging the IAB and the DAA's role in forming self-regulatory processes, has been solid. We'll finally as an industry be able to get on board with it and say, "Yes. This is great. We're together in this. We believe that consumers need to be treated with respect." And the real solid and good guys out there, the positive players, have been doing this for a long time and the guys who haven't need to get in line.
We're looking at a couple of things. The first being global expansion. We're doing some business in Europe right now and we expect to grow that substantially over the next 12 months. The second is moving into different media. A majority of our business right now is focused on online display, but there are obviously huge opportunities that we believe are in mobile, addressable television, offline data and content optimization. Those are areas that we think are a bright, great opportunity for us as well.
And then to just take advantage and grow our core business in the US by working more closely with the platforms and the RTB bidding engines so that we become part of that machine. So if you think of three tiers; it's global expansion of our core business, continuing to expand that business into new verticals and then continuing to enhance our business here domestically by creating new products and services that allow us to take advantage of the RTB growth.
By John Ebbert