Systems and methods for detecting data leakage of online content

1 . A method for detecting data leakage of online content, comprising:

generating a plurality of synthetic-user profiles including a first group and a second group;

exposing only the first group of the synthetic-user profiles to a predetermined website, provided by a first content provider operating in a first category;

providing first party data associated with the exposure of the first group to one or more intermediaries;

after providing the first party data to the one or more intermediaries, exposing the synthetic-user profiles to third-party websites such that dynamic content of the third-party websites are received by the first and second groups of the synthetic-user profiles, wherein the dynamic content of the third-party websites received by the first group comprises first dynamic content and wherein the dynamic content of the third-party websites received by the second group comprises second dynamic content;

retrieving data corresponding to the dynamic content of the third-party websites; and

based on the retrieved data, determining whether data leakage occurred via at least one of the one or more intermediaries at least in part by,

determining, from among the first dynamic content, a first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category, including competitors of the first content provider,

determining, from among the second dynamic content, a second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category, including competitors of the first content provider, and

determining a difference between the second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category and the first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category.

2 . The method of claim 1 , further comprising:

in response to determining that the first percentage or the second percentage exceeds a predetermined threshold, generating an indication that data leakage via at least one of the one or more intermediaries occurred.

3 . The method of claim 1 , wherein determining whether data leakage occurred comprises comparing the first dynamic content to the second dynamic content.

4 . The method of claim 3 , further comprising:

generating a report based on a comparison of the first and second dynamic content; and

displaying the report to a user via a display unit.

5 . The method of claim 1 , wherein determining whether data leakage occurred comprises:

determining whether the first dynamic content is in the first category;

determining whether the second dynamic content is in the first category;

if (a) the first dynamic content is in the first category and (b) the second dynamic content is not in the first category, then generating an indication that data leakage via at least one of the one or more intermediaries occurred.

6 . The method of claim 1 , wherein the synthetic-user profiles have profile characteristics, and wherein the first and second groups have similar or identical profile characteristics except for exposing the first group of the synthetic-user profiles to the predetermined website.

7 . The method of claim 1 , further comprising not exposing the second group to the predetermined website.

8 . The method of claim 1 , wherein the first category is one of a plurality of content categories, the method further comprising:

characterizing the dynamic content of the third-party websites to be within one of the plurality of content categories, wherein the plurality of content categories include at least two of auto, travel, healthcare, hospitality, insurance, telecommunications, online retail or financial services.

9 . The method of claim 1 , wherein the one or more intermediaries comprises a content agency, content server, content exchange, content network, data exchange, data management platform, customer data platform, supply side platform and/or demand side partner (DSP).

10 . The method of claim 1 , wherein exposing the synthetic-user profiles includes repeatedly exposing the first and second groups to third-party websites not characterized to be within the first category for a duration of at least 12 hours at a predetermined frequency.

11 . The method of claim 1 , wherein:

the third-party websites include internal content hosted by a first web server, and

the first and second dynamic content of the third-party websites are hosted by a second web server different than the first web server.

12 . The method of claim 1 , wherein the first category is the retail category, wherein the first content provider owns the first party data, wherein determining the first percentage comprises determining, from among the first dynamic content, a percentage of dynamic content corresponding to content providers, other than the first content provider, that operate in the retail category, and wherein determining the second percentage comprises determining, from among the second dynamic content, a percentage of dynamic content corresponding to content providers, other than the first content provider, that operate in the retail category.

13 . A tangible, non-transitory computer-readable medium storing instructions that, when executed by one or more processors of a computing system cause the system to perform a method comprising:

generating a plurality of synthetic-user profiles including a first group and a second group;

exposing only the first group of the synthetic-user profiles to a predetermined website provided by a first content provider operating in a first category;

providing first party data associated with the exposure of the first group to one or more intermediaries;

after providing the first party data to the one or more intermediaries, exposing the synthetic-user profiles to third-party websites such that dynamic content of the third-party websites are received by the first and second groups of the synthetic-user profiles, wherein the dynamic content of the third-party websites received by the first group comprises first dynamic content and wherein the dynamic content of the third-party websites received by the second group comprises second dynamic content;

retrieving data corresponding to the dynamic content of the third-party websites; and

based on the retrieved data, determining whether data leakage occurred via at least one of the one or more intermediaries at least in part by,

determining, from among the first dynamic content, a first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category, including competitors of the first content provider,

determining, from among the second dynamic content, a second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category, including competitors of the first content provider, and

determining a difference between the second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category and the first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category.

14 . The computer-readable medium of claim 13 , further comprising:

generating an indication that data leakage via at least one of the one or more intermediaries occurred.

15 . The computer-readable medium of claim 13 , wherein determining whether data leakage occurred comprises comparing the first dynamic content to the second dynamic content.

16 . The computer-readable medium of claim 15 , further comprising:

generating a report based on a comparison of the first and second dynamic content; and

displaying the report to a user via a display unit.

17 . The computer-readable medium of claim 13 , wherein determining whether data leakage occurred comprises:

determining whether the first dynamic content is in the first category;

determining whether the second dynamic content is in the first category;

if (a) the first dynamic content is in the first category and (b) the second dynamic content is not in the first category, then generating an indication that data leakage via at least one of the one or more intermediaries occurred.

18 . The computer-readable medium of claim 13 , wherein the synthetic-user profiles have profile characteristics, and wherein the first and second groups have similar or identical profile characteristics prior to exposing the first group of the synthetic-user profiles to the predetermined website.

19 . The computer-readable medium of claim 13 , the method further comprising not exposing the second group to the predetermined website.

20 . The computer-readable medium of claim 13 , wherein the determined difference comprises a percentage change from the second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category to the first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category.

21 . A computing system for detecting data leakage of online content, the computing system comprising:

one or more processors;

one or more memories;

a first component, comprising computer-executable instructions stored in the one or more memories for execution by the computing system, configured to generate a plurality of synthetic-user profiles including a first group and a second group;

a second component, comprising computer-executable instructions stored in the one or more memories for execution by the computing system, configured to expose only the first group of the synthetic-user profiles to a predetermined website provided by a first content provider operating in a first category;

a third component, comprising computer-executable instructions stored in the one or more memories for execution by the computing system, configured to provide first party data associated with the exposure of the first group to one or more intermediaries;

a fourth component, comprising computer-executable instructions stored in the one or more memories for execution by the computing system, configured to expose the synthetic-user profiles to third-party websites such that dynamic content of the third-party websites are received by the first and second groups of the synthetic-user profiles, wherein the dynamic content of the third-party websites received by the first group comprises first dynamic content and wherein the dynamic content of the third-party websites received by the second group comprises second dynamic content;

a fifth component, comprising computer-executable instructions stored in the one or more memories for execution by the computing system, configured to retrieve data corresponding to the dynamic content of the third-party websites; and

a sixth component, comprising computer-executable instructions stored in the one or more memories for execution by the computing system, configured to determine whether data leakage occurred via at least one of the one or more intermediaries at least in part by,

determining, from among the first dynamic content, a first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category, including competitors of the first content provider,

determining, from among the second dynamic content, a second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category, including competitors of the first content provider, and

determining a difference between the second percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category and the first percentage of dynamic content corresponding to content providers that do not own the first party data and that operate in the first category.

22 . The computing system of claim 21 , further comprising:

in response to determining that the first percentage exceeds a predetermined threshold, generating an indication that data leakage via at least one of the one or more intermediaries occurred.