Clickstream analysis methods and systems
View Patent ↗Methods and systems are provided herein for the analysis of clickstream data of online users. The analysis methods and systems allow for the creation of new offline business methods based on online consumer behavior.
1. A method, comprising:
obtaining, by a processor, an input data set reflecting online actions of a plurality of online users, wherein the plurality of online users are selected according to a panel selection process based on a statistical process of analyzing demographic characteristics of the online users, wherein the input data set includes a plurality of timestamps associated with the clickstream activity;
analyzing, by the processor, the data set to identify characteristics of cross-shopping behavior of the users between different brands of products; and
modifying an off-line marketing promotion that includes an offline incentive for buying a particular brand of product based on the identified characteristics, wherein the offline promotion include a process for offline presentation of a media item, and wherein the statistical process comprises:
conducting a survey of user demographics in an initial panel of users,
determining a current statistic related to the user demographics in the initial panel of users,
comparing the current statistic to a statistic corresponding to a historical panel of users for updating the current statistic, and
selecting the plurality of online users in the current panel of users from the initial panel of users based on the updated current statistic and the user demographics.
2. A method of claim 1 , wherein the input data set includes data related to price sensitivity of the plurality of online users, and the method comprises modifying an offline pricing process for an offline item.
3. A method of claim 1 , wherein the input data set includes data related to an ordering of items for online user viewing, and the method comprises modifying an offline process related to product placement.
4. A method of claim 1 , wherein the input data set includes data related to user buying behavior, and the method comprises modifying an offline process related to forecasting offline demand for a product.
5. A method of claim 1 , wherein the input data set includes data related to actions of the plurality of users with respect to online content choices, and the method comprises modifying an offline process related to presenting media content offline.
6. A method, comprising:
obtaining, by a processor, an input data set reflecting clickstream activity of a plurality of online users, including data reflecting actions of the users with respect to online content choices, wherein the plurality of online users are selected according to a panel selection process based on a statistical process of analyzing demographic characteristics of the online users, and wherein the input data set includes a plurality of timestamps associated with the clickstream activity;
analyzing, by the processor, user behavior reflected by the clickstream activity;
drawing, by the processor, one or more inferences based on the user behavior; and
modifying one or more offline processes based on the inferences, wherein the offline processes include a process for offline presentation of a media item, wherein the statistical process comprises:
conducting a survey of user demographics in an initial panel of users,
determining a current statistic related to the user demographics in the initial panel of users,
comparing the current statistic to a statistic corresponding to a historical panel of users for updating the current statistic, and
selecting the plurality of online users in the current panel of users from the initial panel of users based on the updated current statistic and the user demographics.
7. The method of claim 6 , wherein the offline item is one of:
an offline media product offering chosen based on the online content choices, and
an item having offline media content.
8. The method of claim 7 , wherein the input data set includes data related to user buying behavior, and the offline processes include a process for forecasting offline demand for a product.
9. The method of claim 6 , wherein the offline item is a catalog customized to reflect at least one demographic characteristic of the plurality of online users determined based on the online content choices of the users.
10. The method of claim 6 , wherein the offline item is a media merchandise offered based on user online choices related to movie content.
11. A method, comprising:
obtaining, by a processor, an input data set reflecting clickstream activity of a plurality of online users, including data related to price sensitivity of the users determined from an online site of a first vendor, wherein the plurality of online users are selected according to a panel selection process based on a statistical process of analyzing demographic characteristics of the online users, and wherein the input data set includes a plurality of timestamps associated with the clickstream activity;
analyzing, by the processor, user behavior reflected by the clickstream activity;
drawing, by the processor, one or more inferences based on the user behavior; and
modifying one or more offline processes based on the inferences, wherein the offline processes include a pricing process for an offline item of a second vendor, wherein the offline processes include a process for offline presentation of a media item, and wherein the first vendor is different from the second vendor, wherein the statistical process comprises:
conducting a survey of user demographics in an initial panel of users,
determining a current statistic related to the user demographics in the initial panel of users,
comparing the current statistic to a statistic corresponding to a historical panel of users for updating the current statistic, and
selecting the plurality of online users in the current panel of users from the initial panel of users based on the updated current statistic and the user demographics.
12. The method of claim 11 , wherein the price sensitivity relates to actions of the plurality of online users in response to a change in a pricing process of an online item.
13. A method, comprising:
obtaining, by a processor, an input data set reflecting clickstream activity of a plurality of online users, where the data set includes a plurality of timestamps associated with the clickstream activity, wherein the plurality of online users are selected according to a panel selection process based on a statistical process of analyzing demographic characteristics of the online users;
analyzing, by the processor, user behavior reflected by the clickstream activity;
drawing, by the processor, one or more inferences based on the user behavior; and
modifying one or more offline processes based on the inferences, wherein the offline processes include a process for offline presentation of a media item, wherein the statistical process comprises:
conducting a survey of user demographics in an initial panel of users,
determining a current statistic related to the user demographics in the initial panel of users,
comparing the current statistic to a statistic corresponding to a historical panel of users for updating the current statistic, and
selecting the plurality of online users in the current panel of users from the initial panel of users based on the updated current statistic and the user demographics.
14. The method of claim 13 , wherein the clickstream activity includes a plurality of HTTP transactions and the timestamps include times of the respective HTTP transactions.
15. The method of claim 13 , wherein at least one of the inferences relates to cross-shopping behavior of the plurality of users between different goods, and the offline processes include a process for marketing promotion.
16. The method of claim 15 , wherein the marketing promotion is an offline incentive for buying a product, and the inference relates to cross-shopping behavior of the plurality of users between different brands of the product based on the offline incentive.
17. The method of claim 16 , wherein the product comprises a brand of automobile, and the marketing promotion comprises an incentive for buying the brand of automobile.
18. The method of claim 13 , wherein the input data set includes data related to price sensitivity of the plurality of online users, and the offline processes include a pricing process for an offline item.
19. The method of claim 18 , wherein the price sensitivity of the online users is determined from an online site of a first vendor and relates to a pricing process for an offline item of a second vendor.
20. The method of claim 13 , wherein the input data set includes data related to an ordering of items for online user viewing, and the offline processes include a process for product placement.
21. The method of claim 13 , wherein the input data set includes data related to actions of the plurality of online users with respect to online content choices, and the offline processes include a process for presenting offline media content.
22. A method, comprising:
selecting, by a processor, a plurality of online users for a current panel of users according to a panel selection process, wherein the panel selection process selects the current panel of users based on a statistical process of analyzing demographic characteristics of the plurality of online users;
obtaining, by the processor, an input data set reflecting clickstream activity of the plurality of online users, wherein the input data set includes a plurality of timestamps associated with the clickstream activity;
analyzing, by the processor, user behavior reflected by the clickstream activity;
drawing, by the processor, one or more inferences based on the user behavior; and
modifying one or more offline processes based on the inferences, wherein the offline processes include a process for offline presentation of a media item, and wherein the statistical process comprises:
conducting a survey of user demographics in an initial panel of users,
determining a current statistic related to the user demographics in the initial panel of users,
comparing the current statistic to a statistic corresponding to a historical panel of users for updating the current statistic, and
selecting the plurality of online users in the current panel of users from the initial panel of users based on the updated current statistic and the user demographics.
23. The method of claim 22 , wherein the panel selection process comprises selecting the plurality of online users from a larger set of online users in an initial panel of users.
24. The method of claim 22 , wherein at least one of the inferences relates to cross-shopping behavior of the plurality of users between different goods, and the offline processes include a process for marketing promotion.
25. The method of claim 22 , wherein the input data set includes data related to price sensitivity of the plurality of users in the user panel, and the offline processes include a pricing process for an item offline.
26. The method of claim 22 , wherein the input data set includes data relates to an ordering of items for online user viewing, and the offline processes include a process for product placement.
27. The method of claim 22 , wherein the input data set includes data related to user buying behavior, and the offline processes include a process for forecasting offline demand for a product.
28. The method of claim 22 , wherein the input data set includes data related to actions of the plurality of users in the user panel with respect to online content choices, and the offline processes include a process for presenting media content offline.