6targetingTargeting means displaying advertising to an audience selected and segmented according to predefined criteria. The goal is to deliver advertising to the right target group and make digital advertising more effective, and ensure that users are offered relevant products.


In technical targeting the user will see ads, which are optimized for the user’s own software and hardware environment, also including bandwidth, geographic data and browser information.

Bandwidth – segmenting user groups according to the internet speeds they have available, so also avoiding unnecessarily long loading times.

Geographic / Regional Targeting – displaying advertising to user groups segmented according to IP ranges, i.e. specific target regions.

Frequency Capping (FC) - restricting (capping) the number of times (frequency) a specific visitor to a site is shown a particular advertisement. This restriction is applied to all websites that serve ads from the same advertising network.

Provider – segmenting user groups according to the internet provider they use.

Browser – segmenting by browsers used.

Time – segmenting by time of day, e.g. 6 to 10 p.m.

Screen Resolution – ensuring that large scale flash ads or video ads are only displayed on appropriate screens.

Operating System – e.g. sending ads for apple software to users of MAC OS.

Wi-Fi – selecting users of Wi-Fi.

Mobile Carrier – segmenting users according to mobile carrier used.

Device vendor – targeting users of specific device brands, e.g. Samsung users.

Device Type – targeting according to device type, e.g. desktop, notebook, tablet, mobile etc.


Keyword Targeting - displays appropriate ads to users who enter a related keyword in a search engine.

Contextual Targeting – the content of an ad will be in direct correlation to the content of the web page the user is viewing.

Semantic Targeting - aims to match the specific context of content on page within a website to an available advertising campaign. The key difference to contextual targeting is that a semantic system examines all the words and identifies the senses of those words, instead of scanning a page for bided keywords.


Behavioral Targeting utilizes data generated by website and landing page visitors. When done without the knowledge of users, it may be considered a breach of browser security and may be illegal in some countries.

Onsite Behavioral Targeting – uses web analytics to break-down the range of all page visitors into a number of discrete channels. Each channel is then analyzed and a virtual profile is created to deal with each channel. These profiles can be based around “personas” that gives the website operators a starting point in terms of deciding what content, navigation and layout to show to each of the different personas.

Network Behavioral Targeting – advertising networks use behavioral targeting in a different way than individual sites. Since they serve many advertisements across many different sites, they are able to build up a picture of the likely demographic makeup of internet users. An example would be a user seen on football sites, business sites and male fashion sites. A reasonable guess would be to assume the user is male. Demographic analyses of individual sites, and internally (user surveys) or externally collected data, allow the networks to sell audiences rather than sites.

Predictive Behavioral Targeting - learns from user behavior combined with surveys or other third party data in real time. Machine-learning algorithms are put to work in order to provide ad servers with precise profile information for the whole inventory. The technology used is the same as in research on artificial intelligence and robotics.


Personalized retargeting is used to recapture consumers who visit a retailer’s site and leave without making a purchase. It utilizes basic information, pulled from cookies that are placed on a user’s web browser, to serve display advertisements. The products that appear in each user’s display ad are unique to each user and reflect products that the user previously viewed on a retailer’s website.


This very precise technique makes use of information users themselves declared, e.g. by signing in to a newsletter. It also makes use of user-declared data and log-in data collected from web sites and social media platforms. (Sources: bvdw.de / Wikipedia)

By Anjum Siddiqi