• by Phil Leggiere , December 17, 2008

In the user-centric and thus behaviorally driven world of contemporary marketing, the implicit assumption of most marketers is that more is always better, particularly when more means more data points about who's browsing a Web site, what they're doing there, and have done previously online. Sometimes, however, it can be more relevant to focus not on what consumers are doing -- but on where they're doing it from, as Kerry Langstaff, vice president of marketing at Quova, explains below.

 

Behavioral Insider: Quovo specializes, as I understand it, in dynamic geo-location. How does that work?

Kerry Langstaff: Basically we go and map the infrastructure of Web servers set up all over the world and map where IP Addresses have been allocated. We're talking about over two million addresses in the database. The data is constantly changing, because IP addresses are subject to enormous flux. Up to 10% of them can change every month and even more if a telecom company is acquired.

We identify where a user is connecting from through their IP address, not their email address or their name or their credit card information, and we don't employ cookies. From this information we get the country, state, city and can derive attributes including DMA, time zone and Zip code area, within up to a 25 to 50 mile radius. In addition to network characteristics, we can tell exactly what kind of connection they have whether it's DSL, cable or satellite.

BI: How does what you do relate to customized targeting of ads, content, landing pages?

Langstaff: Marketers increasingly want to make decisions based on where customers actually are, which, given the mobility of laptop users, has become a very flexible target. You could be physically in San Diego, for instance, but be logging in through a VPN in London, so it would appear that you are in London.

The interesting thing is that a single piece of non-personal data can be leveraged to dynamically customize content, be it an advertisement or a landing page. It's amazing how rich the simple knowledge of IP location can be.

BI: Can you give some examples of how a publisher or advertiser can custom-target consumers based on geo-location?

Langstaff: So, as an example, say a customer is searching for shoes. By using IP geo-location data to situate exactly where they are, a shoe retailer can localize its landing page for each incoming visitor. Another customer example is a newspaper which uses reader location to customize their news and ad content. If you log in from Massachusetts, you'll get the Red Sox score first -- not the Yankees score. And news, weather, and the store locations of advertisers can be localized based on where a particular person is logged in from.

This particular publisher has 60 DMAs they serve, from Boston to San Francisco. Not only can they geo-localize targeted content, but they are able to sell local advertising to national advertisers granularized by metro market.

We have an agency using geo-data to do promotional campaigns for a Lasik Eye Center that has multiple locations. Whenever someone comes to their Web site, they'll get information relevant to their location. They'll be referred to the centers nearest them for contact and also only see advertising that complies with the state laws applicable in their geographic location.

BI: Are there other types of targeting applications where the geo-locational piece can be deployed to enhance overall targeting efficiencies?

Langstaff: Another increasingly important application of dynamic geo-targeting is multichannel marketing. Any retailer that has both an online and offline presence, for instance, can better synchronize online with in-store promotions. There's a huge body of research which documents that a majority of online shoppers research purchases online but ultimately purchase in-store. So IP geolocation enables a marketer to much more closely integrate those two channels.

For instance, if a retailer, has excess inventory at its Pittsburgh stores they can leverage that 'back-end' data to customize promotions for that particular inventory to people who log in from the Pittsburgh area. Obviously this would also be useful to track the effectiveness of offline advertising more closely.

If you ran a print ad in Boston, you could track exactly how much online traffic you generated from the specific areas where the ad ran. With the economic slowdown it will become even more critical for marketers to leverage greater efficiencies between offline and online channels, and we see geo-location as a key to doing that.

BI: What refinements and new iterations are you looking at for geo-locational applications going forward?

Langstaff: Looking forward, another important area of application will be mapping Wi-Fi IP location by routing Wi-Fi hotspots and cell towers to triangulate precise location. This type of marketing would of course be permission-based. But as you can imagine, the potentials for customizing content based on the Starbucks location someone is connecting from can be enormously valuable not only to marketers but to consumers who get truly relevant information.