BidTheatre offers the possibility to target a campaign on data derived from the IP-address that makes the request. Currently we support data lists to target:

Organisational name, domain names and postal codes are derived from a lookup of the user IP address with our provider Digital Element.

Data Lists are simply text files where each row contains a target organization, postal code, or IP address you want to include. These text files can be added by navigating to Supply → Data Lists → New Data List. The exact steps may vary depending on the type of data list you wish to upload, and these will be described below. Once your data list is uploaded, it can then be included in a Custom Audience.
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Note: Remember to add a Fixed CPM in the order to ensure the cost is deducted from the campaign budget and not added as an additional cost.

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IP addresses can be targeted in a few different forms;

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.

Upload your text file containing IP addresses by navigating to Assets → Data Lists → New Data List. To create an audience using this data list, go to Supply → Audience → New Audience, select the type: User - Data List: IP, and then choose your data list under Value.

Note: Add a Fixed CPM in the order to ensure the cost is deducted from the campaign budget and not added as an additional cost.
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In Assets → Data Lists, a tool is provided to search for a given list of organisation pattern. The tool can be used to identify whether a given organisation has been previously seen, and hence could be available to target.

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To use the search tool, upload a text file (.txt) containing the pattern/company you wish to search for:

The tool will respond by outputting a text file containing each matched organisation per line. If the output file is empty, no match has been found.
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Example

To target users originating from the ISPs Com Hem or Bahnhof, your output file should look like this:

Double-check the output file and delete any unwanted matches; then click 'new data list' and upload the corrected output file here:
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Once the Data List is an available targeting asset, it can be used in an Audience. Go to Supply → Audience → New Audience, select the type: User - Data List: Organization, and then choose your data list under Value.

Note: Add a Fixed CPM in the order to ensure the cost is deducted from the campaign budget and not added as an additional cost.

The Domain Search Tool works in the same way as the Organization Search Tool, with the difference that you can search for specific domain names for the organizations you wish to target.

Refer to the same rules and guide as above. When you later create a target audience for this, select the type: User - Data List: Domain, and then choose your data list under Value.

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

Upload your text file containing postal codes by navigating to Assets → Data Lists → New Data List. To create an audience using this data list, go to Supply → Audience → New Audience, select the type: User - Data List: Postal code, and then choose your data list under Value.

Note: Add a Fixed CPM in the order to ensure the cost is deducted from the campaign budget and not added as an additional cost.

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.

The regular expression above consist of the following parts.

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.

The regular expression above consist of the following parts

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