When the digital advertising company Rocket Fuel was founded in 2008, programmatic media was promising, yet unfamiliar. Seven years later, Rocket Fuel has positioned itself as a leader among programmatic ad firms, but it still finds itself embracing relatively new terrain: mobile.
Street Fight recently caught up with Ian Dailey, the company’s senior product marketing manager for mobile, to talk about bringing the efficiencies and advantages of automation to mobile advertising.
Rocket Fuel has spent the past few years building a big programmatic business on desktop. What’s different about the mobile advertising industry’s relationship with programmatic?
Overall, mobile programmatic is a few years behind. A lot of desktop exchanges have moved into the mobile realm; companies formerly added networks like Millennial [Media] to transition to programmatic, making inventory available through these exchanges. The adoption curve between companies like us and marketers is a few years behind… programmatic and real-time bidding have been around earlier than mobile.
When you think about programmatic on mobile — what’s the biggest challenge?
We’re used to commonplace things in the desktop realm, like attribution or the availability of data from third parties. All of those things are in various stages of maturity, so I can’t even pinpoint one exact thing, because compared to desktop it’s all maturing. At the end of last year, we started to see a lot of partners go: “Okay, now we’ve got our data mobile solution, now we’re giving you the attribution that is pretty common in desktop.” The dollars that we’ve seen in terms of revenue growth and industry growth are quickly catching up.
Can you talk about the nuances of mobile advertising for brick-and-mortar stores that may not necessarily have their inventory available online, or don’t have a large online presence?
This is where mobile is totally differentiated from desktop today in the ability to be relevant for these types of companies. The availability of hyperlocal data — latitude and longitude — means that we have lots of levers to pull in terms of finding, reaching, influencing and driving that foot traffic.
When you’re talking about geolocation in desktop — I can reach somebody in L.A., but that’s not great if you have outposts in Santa Monica and West Hollywood; reaching Orange County isn’t helpful. There’s a lot of data available that is really interesting, but we only have it on a few thousand customers anonymously, so it’s not going work nationally.
You can boil it down to the fact that we all carry around advanced computers in our pockets. People have developed apps that require GPS-like functionality: chat apps showing nearby friends, dating apps, social games, all sorts of different stuff. All of these apps are collecting very granular data, anonymously. That information is passed through these ad exchanges to a huge degree. We have the ability to go in and influence at the local level. We’ve worked for chains, auto dealerships, a number of different companies that rely on foot traffic.
There are a bunch of mobile local-specific ad firms out there. Do you see these firms as direct competitors?
Specifically around mobile hyperlocal, yes, there are a number of companies offering pretty innovative solutions that are leading the charge on how location can be used. We’re at a maturity and size now where, for the types of customers we serve, we look at location data as a very, very important data source. Twenty years ago, we had the concept of cookies that leads us to consumer interests. A whole industry is built around this.
More recently, it’s been: “We can actually see where people go now.” We’re just scratching the surface on what we can do with that. As we grow, we find out that this type of data can be leveraged many different ways. As we go into the future, it’s like, this location data can feed into all sorts of different marketing activities, whether that means we’re using it for insight — “hey, look at your consumers, here’s what they look like in aggregate at an anonymous level” — and for for positioning. When somebody lands on your page, past real-world behavior might influence what it looks like. All of this is very new, and we’re trying to get used to it.
What advantages are there to operating a desktop and mobile campaign from a single vendor?
We ran a campaign for a casual dining company that wanted to drive adoption of efficient orders online. We tested a lot. They wanted customers to order online and pick up in-store. First we ran a media that had desktop only, which had a very good cost per order. Then we ran mobile only and it was not quite as good; the experience was basically optimized to desktop ordering.
When we ran cross-channel, we had opportunity to reach individuals on desktop and mobile, and the cost of order went down 3x. Cross-channel advertising is more effective, ROI is much better. And we can identify individual users. We want to talk about people, not IDs.
There’s been a lot of discussion around fraudulent traffic on desktop, but how do you address fraud on mobile?
Fraud is an area that we’ve looked at closely and taken a lot of steps to address. As a company, we take a lot of steps internally to balance fraud traffic. We see the incoming request, a quick analysis happens and we bounce it. We don’t even consider it beyond that. We worked with Forensiq, a leader in the space — they evaluated, post-bouncing, what the percentage of fraudulent traffic was. It was three percent, obviously we want it to be zero. That extends to mobile as well. The same system is bouncing all of these mobile requests.
When you think about all of the data available to marketers, what can location data provide that others cannot?
The value is most evident in places where it’s measurable. With location, we can show that it works. Customers sign up and then they renew, they love it and they can’t get enough. The next level is showing those real-world insights, or taking that real-world behavior and showing that it can drive performance — outside of just driving foot traffic, it drives performance in other ways.
There are online signals, to find people who shop for certain types of goods. Or, I can look at real-world location behavior and find people who frequently are going to gyms, yoga studios, visiting stores like REI. So now, instead of targeting somebody who bought a pair of shoes for a friend or someone who never goes to the gym, I’m finding people who actually go there frequently. That type of understanding the consumer can only be found at scale with this type of location data. That’s really the power of what it brings.
Annie Melton is a contributor to Street Fight.