Ad-based geotargeting sucks. At a broad level–national or regional–it can be useful for brand advertisers, but for the truly small business, geotargeting fails. It’s fantasy. Advertisers don’t like to talk about this but it’s a fact that local ad inventory does not exist in any scale. Yet. This will change over time when the ability to have meaningful geotargeting is developed (more on this from UMI in the coming weeks). This will drive usage, which drives awareness, then advertisers.
Geographical targeting of advertising can happen by geo-intelligence on the serving platform or by a user profile/explicit communication of the desired search area (ie, Cambridge, 02138, user profiles, etc.). Within paid search, Google’s AdWords, Yahoo’s Panama, and MSN’s adCenter represent the primary means of delivering text-based advertising. Since more than 75% of the web’s search traffic is carried by Google and Yahoo!, they are significant players. Contextual and rich media ads represent a smaller but more rapidly growing segment and includes is driven by Google’s AdSense, DoubleClick, smaller publishing networks and a vast ecosystem of ad networks, agencies and other intermediaries.
Geotargeting within the ad serving platform is generally limited to its embedded geo-intelligence. Internet Protocol-based geotargeting seeks to convert a computer’s IP to a real-world location. In theory this is an intuitive and valuable approach; assuming the user is searching in this area, advertisements could be geographically targeted to a very local level. In practice, this rarely happens. Internet service providers commonly use load-balancing equipment to distribute traffic across their network. The experience of all AOL subscribers’ IP addresses showing up Dulles, Virginia, is the most widely-known example of this happening. The end result is geo-IP lookup that provides consistent results for the city or metropolitan area. At times, increased granularity (ZIP code) can be achieved, but this is by no means guaranteed.
In addition to a website determining the user’s location based on IP lookup, users can directly provide information about their desired location to perform a search. Because user profiles (such as My Yahoo!, Google Accounts, etc..) are predetermined, they require no additional effort for the user. However, if a user is searching outside the area contained in her profile, results will be bogus. The vast majority of the time, this is the scenario–it is up to the searcher to define the geographic proximity, and that is where the system breaks down. ‘Formal geography’– cities, addresses, postal codes and others are recognized by search engines, but the informal geography–proximity to schools, parks, neighborhood locations, key landmarks, etc…, are recognized in a keyword, not spatial, method. This is critical and is the difference between (say) coffee shops located in Tribeca, Manhattan and the Tribeca Coffee shop in Krakow, Poland or Durban, South Africa.
