CROSS-CHANNEL AUDIENCE SEGMENTATION

1 . A method comprising using at least one hardware processor for:

receiving first a set of keywords associated with a first advertising platform;

receiving second a set of keywords associated with a second advertising platform;

defining binary relations between the first and second sets of keywords;

applying formal concept analysis (FCA) to the binary relations, to produce a concept lattice; and

updating the concept lattice responsive to changes in the first or second sets of keywords.

2 . The method according to claim 1 , further comprising using said at least one hardware processor for:

extracting association rules from the concept lattice;

selecting extracted association rules by collaborative filtering; and

producing a cross-channel audience segmentation report.

3 . The method according to claim 2 , further comprising using said at least one hardware processor for effecting at least one action in at least one of said first and second advertising platforms, the at least one action selected from the group consisting of:

adding one or more keywords to an advertising campaign,

removing one or more keywords from an advertising campaign,

adding one or more negative keywords to an advertising campaign,

removing one or more negative keywords from an advertising campaign,

initiating a new advertising campaign,

stopping an advertising campaign, and

changing ad copy.

4 . The method according to claim 1 , wherein said updating of the concept lattice is incremental updating of the concept lattice.

5 . The method according to claim 1 , further comprising using said at least one hardware processor for combining similar keywords.

6 . The method according to claim 1 , wherein the defining of the binary relation comprises:

collecting anonymous cookie data from Internet users clicking on online advertisements; and

using the cookie data, cross-referencing activity associated with the first advertising platform and the second advertising platform.

7 . The method according to claim 6 , wherein the anonymous cookie data is devoid of a real identity of the Internet users.

8 . The method according to claim 6 , further comprising maintaining an ad-centric database which comprises the cross-referenced activity.

9 . The method according to claim 6 , wherein the cross-referencing comprises constructing anonymous demographic profiles of the Internet users.

10 . The method according to claim 9 , further comprising maintaining an ad-centric database which comprises the cross-referenced activity and the anonymous demographic profiles.

11 . A computer program product for cross-channel audience segmentation, the computer program product comprising a non-transitory computer-readable storage medium having program code embodied therewith, the program code executable by at least one hardware processor for:

receiving first a set of keywords associated with a first advertising platform;

receiving second a set of keywords associated with a second advertising platform;

defining a binary relation between the first and second sets of keywords;

applying formal concept analysis (FCA) to the binary relation, to produce a concept lattice; and

updating the concept lattice responsive to changes in the first or second sets of keywords.

12 . The computer program product according to claim 11 , wherein the program code is further executable by the at least one hardware processor for:

extracting association rules from the concept lattice;

selecting extracted association rules by collaborative filtering; and

producing a cross-channel audience segmentation report.

13 . The computer program product according to claim 12 , wherein the program code is further executable by the at least one hardware processor for effecting at least one action in at least one of said first and second advertising platforms, the at least one action selected from the group consisting of:

adding one or more keywords to an advertising campaign,

removing one or more keywords from an advertising campaign,

adding one or more negative keywords to an advertising campaign,

removing one or more negative keywords from an advertising campaign,

initiating a new advertising campaign,

stopping an advertising campaign, and

changing ad copy.

14 . The computer program product according to claim 11 , wherein said updating of the concept lattice is incremental updating of the concept lattice.

15 . The computer program product according to claim 11 , wherein the program code is further executable by the at least one hardware processor for combining similar keywords.

16 . The computer program product according to claim 11 , wherein the defining of the binary relation comprises:

collecting anonymous cookie data from Internet users clicking on online advertisements; and

using the cookie data, cross-referencing activity associated with the first advertising platform and the second advertising platform.

17 . The computer program product according to claim 16 , wherein the anonymous cookie data is devoid of a real identity of the Internet users.

18 . The computer program product according to claim 16 , wherein the program code is further executable by the at least one hardware processor for maintaining an ad-centric database which comprises the cross-referenced activity.

19 . The computer program product according to claim 16 , wherein the cross-referencing comprises constructing anonymous demographic profiles of the Internet users.

20 . The computer program product according to claim 19 , wherein the program code is further executable by the at least one hardware processor for maintaining an ad-centric database which comprises the cross-referenced activity and the anonymous demographic profiles.