Geotargeting (Ofer Abarbanel online library)

Geotargeting in geomarketing and internet marketing is the method of determining the geolocation of a website visitor and delivering different content to that visitor based on their location. This includes country, region/state, city, metro code/zip code, organization, IP address, ISP or other criteria.[1]

A common usage of geo targeting is found in online advertising, as well as internet television with sites such as iPlayer and Hulu. In these circumstances, content is often restricted to users geolocated in specific countries; this approach serves as a means of implementing digital rights management. Use of proxy servers and virtual private networks may give a false location.[2]

Geographical information provided by the visitor

In geotargeting with geolocation software, the geolocation is based on geographical and other personal information that is provided by the visitor or others.

Different content by choice

Typical examples for different content by choice in geotargeting are the FedEx and UPS websites where users have the choice to select their country location first and are then presented with different site or article content depending on their selection.

Automated different content

In internet marketing and geomarketing, the delivery of different content based on the geographical geolocation and other personal information is automated.[3] A good example is the Ace Hardware website at The company utilizes geolocation software to power the “My Local Ace” section of its website. Based on a site visitor’s location, the website’s online locator service can show the visitor how many stores are in their area, as well as a city-level locator map to help the customer find the store closest to their address.[4]

IP spidering

The automated discovery of user person/organisation/city-level geolocation information based on IP addresses by traceroute, pings, and a combination of other tools and methods is far more advanced.[5]

It is dependent on the pre-analysis of the entire IP address space. There are more than 4 billion possible IPv4 addresses, and detailed analysis of each of them is a Herculean task, especially in light of the fact that IP addresses are constantly being assigned, allocated, reallocated, moved and changed due to routers being moved,[6] enterprises being assigned IP addresses or moving, and networks being built or changed. In order to keep up with these changes, complex algorithms, bandwidth measurement and mapping technology, and finely tuned delivery mechanisms are necessary.[7] Once all of the IP space is analyzed, each address must be periodically updated to reflect changes in the IP address information, without invading a user’s privacy. This process is similar in scale to the task of Web spidering.

IP delivery in SEO

IP delivery for search engine optimization (SEO) is the method of delivering different content to search engine spiders (also known as robots and crawlers) then to human visitors. The IP address determines if a visitor is a known search engine spider. SEOs compare the visitor’s IP address with their list of IP addresses, which are known to be servers that are owned by a search engine and used to run their crawler applications (spiders). The delivery of different content to search engine spiders than to human visitors is called cloaking and is against most search engines’ webmaster guidelines.[8][9][10]

Although the search engine guidelines seem to imply that any type of cloaking is bad, there are cases where cloaking might be legitimate. The subject is very controversial and SEO experts continue to debate about when cloaking might be acceptable and when not.[11]

“Cloaking” via IP delivery works differently from cloaking via “user agent”. While IP address spoofing is harder than user-agent spoofing and more reliable, it is also harder to keep the list of IP addresses used by search engines for their crawlers up-to-date. An outdated list with active crawler IP addresses missing enables the search engines to detect the cloaking and may result in a removal of the site from the search engine’s index.

Common uses

  • Content Localization:[12]Webmasters who want to serve local content on a global domain[13][14][15]
  • Copyright owners and delivery networks restrict streams based on the geographical information.
  • Pay per click advertisement to have ads appear only to users who live in selected locations.
  • Display advertisement where banner or other multimedia ads are selected to be displayed based on the visitor’s location.[16]
  • The use of connection speed data correlated to IP address to tailor content.
  • Online analytics identify live the correlation of city-level geography, connection speed data and certain demographic data to IP addresses.
  • Enhanced performance networks provide superior customer targeting to advertisers.
  • Fraud prevention identifies suspicious payment transactions live by correlations between IP address and additional information (billing records, email header).[17][18]
  • City advertising[19]by advertising on web sites with extensive content related to particular cities. Such web sites can connect large city audiences with products/services for sale in those cities. Surfers searching for information about particular cities find adverts at such web sites as a result of city name related searches rather than product/service keyword searches. In this way businesses, e.g. shops, restaurants, can advertise and reach out to consumers located in the real-world localities of their product/service offerings.
  • Content based on local time using IP geolocation.[20]
  • Use of a content distribution network to serve data from a nearby server.
  • Website Personalization where website content is changed and replaced based on visitor location.
  • One-to-one or household IP targeting surfaces display advertisements to individual buildings or homes.
  • Content / Ad verification – changing IPs for content compliance or ad verification.[21]


  1. ^Michael Freedman, Mythili Vutukuru, Nick Feamster and Hari Balakrishnan, Geographic Locality of IP Prefixes, Internet Measurement Conference (IMC), 2005
  2. ^STEPHANIE CLIFFORD (March 15, 2009). “Many See Privacy on Web as Big Issue, Survey Says”. Retrieved 12 February 2014.
  3. ^Wall Street Journal, “On the Web’s Cutting Edge, Anonymity in Name Only”, August 4, 2010
  4. ^Chain Store Age, “Making it Personal”, November, 2008
  5. ^“Digital Element Finding Demand for Granular IP targeting”. 2009-08-20. Retrieved 2010-04-28. Discussing automated spidering technology
  6. ^SAUL HANSELL (February 22, 2008). “Google Says I.P. Addresses Aren’t Personal”. Retrieved 12 February 2014.
  7. ^KATE MURPHY (May 2, 2012). “How to Muddy Your Tracks on the Internet”. Retrieved 12 February 2014.
  8. ^Google webmaster guidelines
  9. ^Yahoo! search content quality guidelines
  10. ^MS Search guidelines for successful indexing Archived2006-08-19 at the Wayback Machine
  11. ^Chris Sherman (July 18, 2001), Search Engine Cloaking: The Controversy Continues Archived 2007-11-13 at the Wayback Machine, Search Engine Watch, retrieved on December 9, 2007
  12. ^ClientSideNews, Nov/Dec 2010 issue, Page 6 “You Can Really Do That? – The Power of Geolocation Technology”
  13. ^Internet World Map 2007 Study showing the geographic distribution of the Internet across the entire world.
  14. ^Internet IP Address Allocation by Country 2008 ReportArchived 2008-01-31 at the Wayback Machine Study showing the IP address distribution of the Internet in 2007
  15. ^Internet IP Address Allocation by Country 2009 ReportArchived 2009-03-17 at the Wayback Machine Study showing the IP address distribution of the Internet in 2008
  16. ^Brand Republic, February 10, 2011 “Thetrainline brings Digital Element on board for localised ad task”
  17. ^IPInfoDB (2010-04-18). “E-Commerce fraud detection”. IPInfoDB. Retrieved 2009-08-25.
  18. ^Credit Card Fraud Prevention Tips Archived July 16, 2011, at the Wayback Machine Top 10 Tips to Prevent Online Credit Card Fraud for Merchants
  19. ^Search Engine Optimization for Dummies, 3rd Edition, 2008, by Peter Kent, Chapter 10 ‘Finding Traffic via Geo-Targeting’
  20. ^IPInfoDB (2010-04-18). “IP location XML API”. IPInfoDB. Archived from the original on 2013-05-16. Retrieved 2010-04-18.
  21. ^“Ad verification residential IPs”. Retrieved 9 October2017.

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Ofer Abarbanel online library

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Ofer Abarbanel online library

Ofer Abarbanel online library