Adelphic Mobile announced the launch of its company and its “Predictive Data Platform” which it says features AudienceCube, “a new targeting technology that leverages data predictive of campaign performance to find and engage mobile audiences.” Read the release.
Co-Founders Changfeng Weng and Jennifer Lum, whose mobile ad experience includes Apple iAd, Quattro Wireless, Nokia, Enpocket and m-Qube, discussed the company and its offering with AdExchanger.com.
AdExchanger.com: What’s in a name… “Adelphic Mobile”?
JENNIFER LUM: It comes from the Oracle of Delphi, who is the all-seeing oracle. We feel like it encapsulates and represents the spirit of technology in our company because we are focused around leveraging and using data intelligently to see and understand everything that is involved in an ad transaction.
AdExchanger.com: Can you talk a bit about how the idea for the company came about?
CHANGFENG WANG: My background has been a mixture of dealing with high performance data mining and data processing. For example, my early work at Engage provided an understanding of how to make an ad effective. Looking at the difference between online advertising and mobile advertising, it became clear to me what was missing in the pie and what would become important. So we began working on this idea and how to get this for a long time.
JENNIFER LUM: The one other thing is that through Changfeng’s later work at both Enpocket (acquired by Nokia) and Quattro Wireless (acquired by Apple), he was able to implement algorithms and other pieces of technology that substantially improved the performance of both of those networks. Changfeng and I came to know each other through working at Quattro together where I was his main internal customer. We developed a great relationship there.
As I was trying to figure out my next move after transitioning out of Apple iAd, Changfeng approached me about what he’d been working on and invited me to partner with him and I jumped at the chance.
CHANGFENG WANG: The problem that we’re solving is the data – the data intelligence and that’s what we see missing in the ecosystem. If you look at how the Internet and mobile advertising work, they work similarly. One piece is ad serving and the other is to get the data to work. The last wave [of innovation] was about trafficking, serving and little intelligence.
Why is it necessary with your offering that you serve both the buy and the sell side? Doesn’t that present some sort of potential conflict of interest?
CHANGFENG WANG: What makes ads work is if you know the media and the ads? With media, it’s about matching the buyers and sellers together. We don’t see a zero sum game.
JENNIFER LUM: We’re actually helping to create incremental value in mobile media because we are bringing more sophisticated and relevant data services to the various partners that we work with. So for media owners, we’re helping to make their media more valuable and making their media perform in a stronger manner. On the buy side, we’re working with marketers and agencies to help their campaigns reach broader audiences in a targeted manner and perform at a higher rate.
CHANGFENG WENG: We don’t view it as a conflict of interest if you look at [the way we do] optimization. From a buyer’s perspective, It’s finding the the audience that they want. The next thing is about pricing. The advertising market is a fair market value and we’re not about overcharging.
AdExchanger.com: Who is the target customer?
JENNIFER LUM: The objective is to enable a greater percentage of direct buy and sell ad transactions between two parties. So on the media owner’s side, it’s whoever has media for sale to make their media more valuable. And then on the buy side, it’s helping to find an audience that wants it in a targeted manner to achieve great results.
AdExchanger.com: Could this solution also work for PC based display advertising? Take me through a use case.
CHANGFENG WENG: In theory, yes, but we are focusing on mobile.
A typical use case is this: a big agency or advertiser that has one million dollars to spend in X amount of time for a campaign and they are looking for audiences. They will come to our media platform and browse through the inventory and define their campaign. From our portal, they will find the type of audience that they want, and then they can launch their advertising from there. The core of what we provide is what we call the “AudienceCube” – a next generation targeting technology, which we developed expressly for this mobile space. And it goes beyond what is traditionally behavioral targeting, contextual targeting, etc. We’re able to systematically extract what is predictive of a campaign’s performance. And on top of that, we can provide taxonomies for the buyers to define their own target segment dynamically.
AdExchanger.com: Do you use cookies to define your segments?
CHANGFENG WENG: That’s part of the user identification problem. User identification in mobile is pretty tricky, and cookies would be a part of the picture but we don’t rely on cookies.
AdExchanger.com: Is your solution more about the mobile web or mobile app advertising?
JENNIFER LUM: We’re not favoring one media type over another. We want to ensure that we can provide media companies, publishers and marketers with a technology that can equally cover both mobile web and app. Right now, what we’ve seen is somewhat of a bias towards “app” recently, but I do believe that there will be a swing back to the browser.
AdExchanger.com: And can any publisher potentially join your platform?
JENNIFER LUM: Right now, it is a relatively simple process but it’s one that we do through a managed process. We will be launching a self‑service portal in Q2.
AdExchanger.com: According to the release, you’ve raised two million dollars in seed financing. What do you think you’ll be using that money for?
JENNIFER LUM: It’s primarily going to be allocated towards hiring and building out our team. It will be in product and business development.
AdExchanger.com: How do you think your past experiences at Quattro, Apple, Enpocket and Nokia, will help inform the development of Adelphic?
CHANGFENG WENG: Definitely the lessons learned about what data works, and how to make the system work better.
JENNIFER LUM: And the firsthand knowledge of understanding the key challenges that we worked through with our clients – both on the publisher and the developer side.
By John Ebbert
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