MICHAEL OIKNINE: The main difference is the fact that we bring to the table 800 million user profiles containing first-party data. That is not something you can acquire just by paying for it, that is something that must be built from the ground up, which we did over the last three years. On top of this data, we’ve built a data science methodology to be able to create audiences of high value customers depending on the vertical. These could be action or behavior-oriented audiences that fit the marketers’ objectives.
The other differentiating factor is that we also provide a full analytics infrastructure to advertisers allowing them to measure the ROI of their campaigns and optimize future campaigns. You should always capture results off different segments and based on those results, optimize the ROI for future configurations. And without the analysis infrastructure that we have on top of the DSP, it’s difficult to do so.
What kind of first-party data are you collecting?
The kind of data that we capture includes usage data or what we refer to as action data -- Has the user opened an app, downloaded an app? And how long have they used it? -- and we also capture the user’s behavior inside the app, i.e., engagement data. And finally we collect purchase data through gaming data and other types of data that the SDK will capture, to give advertisers a full suite of analytics.
How many advertisers or agencies are you working with?
We introduced our DSP platform about six months ago with about 20 customers and we just got out of private beta and are now working with about 50 brands. On the analytics side, which is the backbone of our DSP, we’re working with thousands of apps.
Is the money you raised mainly going towards your DSP?
Buying in the mobile ad industry is still difficult since it’s very fragmented, so we want to spend the money to make sure that the product meets marketers’ expectations and addresses the pain points that they face. The money will also be used to expand our analytics offerings into different verticals, to allow us to capture different types of data, and also to continue to create more audiences. We are investing heavily in travel and shopping verticals because we see these two verticals as very important to the mobile ad industry.
What type of concerns do clients have when you talk to them about programmatic ad buying?
What we’ve found so far is that there is less concern about the method and more questions about meeting ROI goals. Marketers like that we can help them be more efficient and optimize their campaigns, but many have a clear yardstick and we try to get there through our targeting and optimization technology.
Can you give me an example of how you’re providing greater efficiency in mobile ad buys?
TinyCo, for example, has been running a look-alike targeting campaign with us, where we’re trying to find users for a specific game who would complete the game’s tutorial [and hence be more likely to continue playing the game.] So we got TinyCo’s most engaged users and did an overlap analysis of them and our user profiles to capture a lot of cross-app behavior insights. By correlating the behaviors and creating look-alike audiences, 90% of the users we delivered completed the tutorial.
What mobile trends are you watching?
As I mentioned earlier, one of the biggest problems is the fact that mobile advertising is still highly fragmented where you have a lot of ad networks identifying users in different manners. That creates a real attribution problem; a targeting problem and the fact that you have a lot of ad networks creates a lot of hassle in terms of media buying. It’s still early but we’re finally starting to see a rising trend in programmatic buying, which allows players like us and our competitors to use targeting technologies to start solving these problems.