Data Lists

Bidtheatre offers the possibility to target a campaign on data derived from the IP-address that makes the request. Currently we support campaign targeting based on the organization the IP-address belongs to and the postal code the IP-address is originating from. User-agent and IP-address targeting make use of the same base data lists. 

Data Provider

We use Digital Element as the provider of IP data and geolocation information. Read more about their capabilities at http://www.digitalelement.com/

How to use

You assign lists that contains the data you wish to match in the Audience tab. These lists is nothing more than text files that on each row contain a desired organization or postal code you wish to match. You dont need to worry about upper-/lowercase since we handle that internally. To support some extra flexibility when creating these lists Bidtheatre supports the use of regular expressions (following the Java implementation). You could also type small comments in the text files to help explain things, just prefix the row with a number sign (#) and it will be excluded from matching.

IP Targeting

IP addresses can be targeted in a few different forms;

(1) Just plan IP

(2) CIDR notation. Example: 192.168.1.1/24

(3) Intervals to define range. Example: IP1-IP2

Some SSP's cloak the last part of the user iP. These users can be targeted by targeting the IP with .255 in the end.

Examples

To target users originating from the ISPs Com Hem or Bahnhof you would create a text file with the following content

#ComHem.
com hem ab
#Bahnhof. 
bahnhof internet ab

To target the postal code area of Odenplan in the centre of Stockholm the following text file could be created. 

# postal code for Odenplan in Stockholm, note the space character.
113 22

Using regular expressions

Regular expressions are string patterns built into most programming languages and can be used to describe a string of text. 

For a introduction to regular expressions in Java, see http://ocpsoft.org/opensource/guide-to-regular-expressions-in-java-part-1/ or any other resource available online. 

In Java when creating regular expression you normally need to “double escape” backslashes, that is not needed when creating these text files. 

As an example, postal codes in the Stockholm metropolitan area all starts with the digit one follow by two other digits, a space character and then another set of two digits. This is something that could be expressed in regular expressions like this. 

# postal code stockholm
^1\d{2}\s{1}\d{2}$

The regular expression above consist of the following parts. 

^ = meta character matching the beginning of a line
1 = Match the digit 1
\d = character class describing any digit
{2} = quantifier saying we want to match two digits
\s = character class describing a white space character
{1} = quantifier saying we want to match the white space character one time
$ = meta character matching the end of a line

As another example, the Bahnhof ISP mentioned above could appear as somewhat different organization names for different IP ranges, but lets assume the common denominator is that the text "bahnhof" is mentioned in all of them. 

# All bahnhof organization names
^.*bahnhof.*$

The regular expression above consist of the following parts

^ = meta character matching the beginning of a line
. = meta charachter that matches any character
* = quantifier saying we want to match any character zero or more times.
bahnhof = the text string we require to match
$ = meta character matching the end of a line

In the same manner you could create complex regular expressions matching your intended target audience.