Thinknear GM: Why the Shift to Programmatic Will Benefit Local
Among technology folks, mobile and local are considered two peas in a pod. Location, they argue, is the smartphone’s distinctive capability, opening the door for marketers, developers and consumers to engage with media and information in new, dynamic ways. Location made its mark first as a user feature, helping developers standout in a fleeting mobile app market; but over the past year, it’s also become a money maker.
Part of what’s driving this change is a willingness among advertisers to pay a premium for mobile inventory that includes data on a user’s location, with some networks seeing a 3-5X premium for hyperlocal inventory. Meanwhile, data from Advertisers Perceptions, a research firm that surveys advertising executives, suggests that marketers plan to increase spending on location advertising next year. According to the July 2013 study, 55% of respondents said that they currently use location-based ad formats, and 45% identified location-based ad products as the most important format for the smartphone a year from now.
Eli Portnoy, GM of Thinknear at Telenav, the navigation and mapping company that pushed into mobile advertising with the 2012 acquisition, says demand for location ad tech is “white hot.” The company is one of a number of mobile-local advertising networks and exchanges competing to help brand marketers plan, target and execute hyperlocal campaigns on mobile.
In the lead up to Street Fight’s Local Data Summit in Denver on February 25th, we’re taking a deep dive into the world of local information, speaking with some of the sharpest minds in the industry about using the data to make businesses more efficient, and to make experiences richer for consumer. Street Fight caught up with Portnoy recently to talk about why the industry needs to distance itself from its Internet counterpart; what the rise of programmatic means for hyperlocal targeting; and the dirty secret(s) marketers need to know before jumping in.
There’s been a lot of activity among technology folks to create the targeting parameters made for the web work for mobile. But it’s seemed like trying to fit square pegs in round holes. What’s unique about mobile, and how do marketers need to think differently?
Part of it is that certain categories work better on mobile, and so it just changes the dynamic of how you think about the entire industry. On a PC, I’m very comfortable trying to create a buying impulse. I’m trying to get someone to actually make a purchase right there and then, because e-commerce works so well. So, if I’m Amazon or if I’m Macy’s, I’m happy to spend a ton of money driving that. The way I think about that campaign is very different, whereas on mobile e-commerce works — but it doesn’t work nearly as well.
It’s much harder to get people to actually buy stuff on a mobile phone. What you’re trying to do is either touch them at the exact right moment, because that’s when they’re thinking about it — and therefore you influence the decision when they actually go and buy — or you’re trying to get them to take an action that will lead to a purchase later on, or you’re trying to get them to go into a store. What you’re trying to do, it’s a little bit more nuanced. So, the way you have to think about the whole medium changes.
Does our understanding of audience need to change when we think about mobile?
I feel that the advertising world has always been very focused on audience. “Who you are” is very important, but it’s not everything. There are certain categories where it actually doesn’t matter. Everyone eats fast food — knowing who you are just doesn’t matter if I’m McDonald’s because everyone eats my food. What really does matter is making sure that McDonald’s reaches me at a time when McDonald’s is relevant to me and interesting. So, the simplest way that we, as an advertising industry, figure this out is by time.
However, it expands so far beyond that. There are just so many opportunities to be nuanced about context on mobile, and to think about different products and how they relate to us in different times and different periods of our lives. Being able to uncover that is really, really important. I think as an industry, we’ve been touching on this by accident, but we never really pushed hard to fully grasp it..
How does location data fit into the quest for context, so to speak?
Location data is most interesting when you use it as starting point to create a situational awareness, if you will. The idea that if a consumer is carrying their phone with them 16 hours a day, everywhere they go, they’re basically going through a whole bunch of different situations throughout the day.
As an advertiser, being able to understand those situations and context is really interesting. For instance, if I’m walking outside and it starts to rain, probably what’s top of mind for me is an umbrella. If I’m in Atlanta and it’s 12 degrees below zero — that’s probably top of mind. If I’m in a car dealership, probably a car’s top of mind. So, understanding that place, activity and context is just really interesting, and the way you do that is by first understanding in a very precise way, where is that person, then you overlay POI data to figure out, okay, what activity are they actually doing?
Programmatic advertising grew leaps and bounds last year. What does this growth mean for hyperlocal targeting on mobile?
Real-time bidding has evolved in a very, very big way in the last year and a half for mobile. Whereas a year and a half ago, there were one, maybe two exchanges out there. At this point, there are probably 15 [exchanges] that offer decent value of mobile ad impression. Pretty much every ad network at this point has opened up an RTB exchange on the back end. But the emergence of location-based mobile ads coincided almost perfectly with the emergence of RTB and mobile. And it did so for a reason.
For one, RTB or programmatic exchanges have created scale in a way that didn’t exist before — and scale is of paramount importance when it comes to location buying, because by definition, what you’re saying when you’re doing location buying is, “I want to filter out 99% of the traffic, and only focus on that one percent that falls in the location that I care about.” The inventory is going to be limited, and so, massive reach is really important to be able to do location-based buying. So, RTB has enabled that by creating scale across all these different sorts of an inventory.
The second way that it’s really helped and made it possible is that you can actually go out and make a bid/no-bid decision on an impression-by-impression basis. So, you’re not pre-committing to buying a whole slop of traffic or slop of inventory and having a huge amount of it that you can’t do anything with because the location is not relevant to what you’re trying to do. So, this idea that you’ve got all this scale, plus you’ve got the ability to go by individual impressions, only by the impressions that matter to you, is of paramount importance to be able to do location-based buying.
Amid the success, what’s the biggest limitations for advertisers looking to invest in taking advantage of location data on mobile?
It’s the accuracy of it. The dirty little secret in our industry is that the location data that gets passed in often not reliable, and it’s just very, very dirty. To the ad network or the exchange or wherever they’re passing that information, it all looks the same, because they have to transform it into an actual lat/long coordinate.
Whether app A gets my location through GPS or it gets it from registration data or some other way, they’re converting the data into a latitude-longitude and sending it through the ad network. So, the ad network just gets a ton of lat/long inventory, but it has no idea what the source of the data is and how accurate it is. That’s the biggest problem that we face, and where we’re spending the majority of our resources. That’s foundational to any of the other stuff we’re working on.
Demand for hyperlocal inventory jumped last year. What impact does this have on the amount of inaccurate data in the marketplace?
It’s caused a massive jump. More and more and more publishers are passing it. That’s made the problem bigger because there hasn’t been a material increase in the amount of publishers that are actually asking for GPS global data. So everyone’s realized that you get a premium for passing location, and so, everyone is trying to pass location. But the actual good location data hasn’t been increased nearly as exponentially. So, there’s just a lot more bad data out there.
Steven Jacobs is Street Fight’s deputy editor.
Find out more about how big data can be used in local context at Street Fight’s Local Data Summit, taking place on February 25th, in Denver. Learn from and network with some of the top local data experts in the country. Tickets just $399 until January 23rd. Buy now!