System for improving shape-based targeting by using interest level data
View Patent ↗A system for improving shape-based targeting by using interest level data is disclosed. According to one embodiment, a computer-implemented method includes creating one or more trade zones, wherein creating a trade zone includes grouping a set of parameters to deliver custom shapes, clustering the custom shapes according to offline data and geographic distribution of IP addresses, and mapping clusters of the custom shapes to IP addresses. Data indicating consumption of a content source is received by one or more trade zones at a calculated rate and the calculated rate is analyzed to determine an interest associated with each trade zone. Targeting is based on a selected trade zone, wherein the selected trade zone is selected based upon a desired interest representative of a desired audience. A targeting request is transmitted including instructions or information associated with a target action, and the target action is performed.
1. A computer-implemented method, comprising:
creating one or more trade zones, wherein creating a trade zone comprises
grouping a set of parameters to deliver custom shapes;
clustering the custom shapes according to offline data, online data, and geographic distribution of IP addresses; and
mapping clusters of the custom shapes to IP addresses;
receiving data indicating consumption of a content source by one or more trade zones at a calculated rate;
analyzing the calculated rate to determine an interest associated with each trade zone;
selecting the one or more trade zones based upon a desired interest representative of a desired audience;
transmitting a targeting request to the one or more selected trade zones including display instructions and information associated with a target action; and
performing the target action.
2. The computer-implemented method of claim 1 , wherein online data and offline data associated with the one or more trade zones are independent of cookies.
3. The computer-implemented method of claim 1 , wherein the custom shapes are independent of geographic location.
4. The computer-implemented method of claim 1 , wherein offline data comprises demographic data, point of sale data, and business information data.
5. The computer-implemented method of claim 1 , wherein online data comprises page content, user clicks, advertisement impressions, and pages visited.
6. The computer-implemented method of claim 1 , wherein offline data uses location information in the offline data to map to the custom shapes.
7. The computer-implemented method of claim 1 , wherein online data uses IP addresses to map to the custom shapes.
8. The computer-implemented method of claim 1 , wherein transmitting a targeting request to the one or more selected trade zones results in properly targeted actions, wherein properly targeted actions reach only the desired audience.
9. The computer-implemented method of claim 1 , wherein a trend of an interest for a trade zone is calculated, wherein the trend is one of upward or downward.
10. The computer-implemented method of claim 1 , wherein the content source is one of a webpage, a purchased server log, a mobile application, a television programming transcript, or an on-demand video selection.
11. The computer-implemented method of claim 1 , wherein consumption of the content source comprises:
organizing one or more keywords according to the one or more trade zones, wherein the one or more trade zones consume the one or more keywords at a calculated rate.
12. The computer-implemented method of claim 11 , wherein the calculated rate is determined by multiplying a first number of times that a content source was viewed by a second number of occurrences of a chosen keyword in the content source.
13. The computer-implemented method of claim 1 , wherein consumption of the content source at a calculated rate comprises:
using a data mining technique to produce an output, wherein the output is mapped into one or more phrases having one or more words; and
organizing the one or more phrases according to the one or more trade zones.
14. The computer-implemented method of claim 13 , wherein the calculated rate is determined by multiplying a first number of times a content source was viewed by a second number of occurrences of a chosen phrase in the content source.
15. The computer-implemented method of claim 13 , wherein data mining techniques comprise linear and nonlinear classification methods, supervised and unsupervised learning algorithms and neural networks.
16. The computer-implemented method of claim 1 , wherein creating a trade zone further comprises combining custom shapes that are too small to represent an IP range mapping based on consideration of one or more sets of parameters.
17. The computer-implemented method of claim 16 , wherein consideration of one or more sets of parameters comprises geographic areas that best conform to the probable distribution of the IP address range, demographic homogeneity, natural geographic boundaries and types of IP address ranges.
18. The computer-implemented method of claim 16 , wherein types of IP address ranges comprise business, residential and public locations.
19. The computer-implemented method of claim 1 , wherein selecting one or more trade zones is further based on using probability to find a range of interests that related to a desired interest of a desired audience.
20. The computer-implemented method of claim 1 , wherein transmitting a targeting request to the one or more selected trade zones further comprises transmitting simultaneously to similar trade zones based on one or more sets of parameters.
21. The computer-implemented method of claim 1 , transmitting a targeting request to the one or more selected trade zones further comprises using a selection process to select the best target action.
22. The computer-implemented method of claim 21 , wherein the selection process comprises weighted, random and sequential processes.
23. The computer-implemented method of claim 1 , further comprising optimizing the targeting request based upon performance metrics collected when performing the target action.
24. The computer-implemented method of claim 23 , wherein performance metrics comprise click-through rates, coupon downloads, impressions delivered, price per impression, lead submissions, landing page arrivals, product queries and product purchases.
25. The computer-implemented method of claim 1 , wherein information associated with a target action comprises a weighted score dynamically assigned to each content source based upon one or more desired interests.
26. The computer-implemented method of claim 1 , wherein creating a trade zone further comprises assigning one or more secondary custom shapes based on census tracts that are in close proximity to the clusters of custom shapes.
27. The computer-implemented method of claim 1 , wherein performing the target action occurs independent of keywords and a prior online presence of the desired audience.
28. The computer-implemented method of claim 1 , further comprising: determining whether multiple target items match the one or more selected trade zones; and
determining a best fit target item of the multiple target items.
29. The computer-implemented method of claim 9 , further comprising
mapping the trend to the one or more trade zones to use as a targeting configuration for campaigns.
30. The computer-implemented method of claim 9 , further comprising
discovering new search engine marketing keywords using the trend.
31. The computer-implemented method of claim 1 , further comprising
using keywords for interest discovery.
32. A system, comprising:
a server, hosting a first webpage, in communication with a network, wherein a client system accesses the first webpage via the network; and
a targeting system in communication with the network,
wherein the targeting system creates one or more trade zones by
grouping a set of parameters to deliver custom shapes;
clustering the custom shapes according to offline data, online data, and geographic distribution of IP addresses; and
mapping clusters of the custom shapes to IP addresses;
receives data indicating consumption of a content source by one or more trade zones at a calculated rate;
analyzes the calculated rate to determine an interest associated with each trade zone;
selects the one or more trade zones based upon a desired interest representative of a desired audience;
transmits a targeting request to the one or more selected trade zones including display instructions and information associated with a target action; and
performs the target action.
33. The system of claim 32 , wherein online data and offline data associated with the one or more trade zones are independent of cookies.
34. The system of claim 32 , wherein the custom shapes are independent of geographic location.
35. The system of claim 32 , wherein offline data comprises demographic data, point of sale data, and business information data.
36. The system of claim 32 , wherein online data comprises page content, user clicks, advertisement impressions, and pages visited.
37. The system of claim 32 , wherein offline data uses location information in the offline data to map to the custom shapes.
38. The system of claim 32 , wherein online data uses IP addresses to map to the custom shapes.
39. The system of claim 32 , wherein transmitting a targeting request to the one or more selected trade zones results in properly targeted advertisement impressions, wherein properly targeted advertisement impressions reach only the desired audience.
40. The system of claim 32 , wherein a trend of an interest for a trade zone is calculated, wherein the trend is one of upward or downward.
41. The system of claim 32 , wherein the content source is one of a second webpage, a purchased server log, a mobile application, a television programming transcript, or an on-demand video selection.
42. The system of claim 32 , wherein consumption of the content source comprises:
organizing one or more keywords according to the one or more trade zones, wherein the one or more trade zones consume the one or more keywords at a calculated rate.
43. The system of claim 42 , wherein the calculated rate is determined by multiplying a first number of times that a content source was viewed by a second number of occurrences of a chosen keyword in the content source.
44. The system of claim 32 , wherein
the targeting system uses a data mining technique to produce an output, maps the output into one or more phrases comprising one or more words; and organizes the one or more phrases according to the one or more trade zones.
45. The system of claim 44 , wherein the calculated rate is determined by the targeting system that multiplies a first number of times a content source was viewed by a second number of occurrences of a chosen phrase in the content source.
46. The system of claim 44 , wherein data mining techniques comprise linear and nonlinear classification methods, supervised and unsupervised learning algorithms and neural networks.
47. The system of claim 32 , wherein the targeting system further creates a trade zone by combining custom shapes that are too small to represent an IP range mapping based on consideration of one or more sets of parameters.
48. The system of claim 47 , wherein the one or more sets of parameters comprise geographic areas that best conform to the probable distribution of the IP address range, demographic homogeneity, natural geographic boundaries and types of IP address ranges.
49. The system of claim 48 , wherein types of IP address ranges comprise business, residential and public locations.
50. The system of claim 32 , wherein the targeting system selects one or more trade zones by using probability to find a range of interests that are similar to a desired interest of a desired audience.
51. The system of claim 32 , wherein the targeting system transmits a targeting request to the one or more selected trade zones and transmits the targeting request to similar trade zones based on one or more sets of parameters.
52. The system of claim 32 , wherein the targeting system transmits a targeting request to the one or more selected trade zones and uses a selection process to select the best target action.
53. The system of claim 52 , wherein the selection process comprises weighted, random and sequential processes.
54. The system of claim 32 , wherein the targeting system further comprises optimizing the targeting request based upon performance metrics collected when performing the target action.
55. The system of claim 54 , wherein performance metrics comprise click-through rates, coupon downloads, impressions delivered, price per impression, lead submissions, landing page arrivals, product queries and product purchases.
56. The system of claim 32 , wherein information associated with a target action comprises a weighted score dynamically assigned to each content source based upon one or more desired interests.
57. The system of claim 32 , wherein the targeting system assigns one or more secondary custom shapes based on census tracts that are in close proximity to the clusters of custom shapes.
58. The system of claim 32 , further comprising a real-time bidding system and a plurality of real-time bidders in communication with the network, wherein the targeting system acquires impressions from the real-time bidders for serving advertisements.
59. The system of claim 32 , further comprising a publisher site in communication with the network, wherein the publisher site uses the targeting system to perform target actions for the publisher site's audiences.
60. The system of claim 32 , wherein a target action is one of serving content, serving video, serving a page view, serving an advertisement, or serving a game.
61. The system of claim 32 , wherein the target action occurs independent of page keywords and a prior online presence of the desired audience.
62. The system of claim 32 , wherein the targeting system determines whether multiple target items match the one or more selected trade zones; determines a best fit target item of the multiple target items.
63. The system of claim 41 , wherein the targeting system maps the trend to the one or more trade zones to use as a targeting configuration for campaigns.
64. The system of claim 41 , wherein the targeting system discovers new search engine marketing keywords using the trend.
65. The system of claim 32 , wherein keywords are used for interest discovery.