- Number
- 10248960
- Published
- 2019-04-02
- Filed
- 2011-11-11
- Assignee
- Disney Enterprises, Inc.
- Inventors
- Anderson; John et al.
- CPC
- G06Q30/0244; G06Q30/02; G06Q30/0246
- Verdict
- Set aside data mining online user responses to broadcast messages, analytics
- Source
- Google Patents · FreePatentsOnline
Abstract
In a networked system, a method and apparatus for measuring advertising effectiveness involves broadcasting an advertisement at a broadcast time, monitoring at least one social network or other online forum following the broadcast time, filtering social network traffic to identify messages, search engine queries to identify queries, or other traffic entries, that appear to be responsive to the broadcast advertisement, determining a time of initiation for at least a plurality of entries that appear to be responsive to the broadcast advertisement, and determining at least one demographic for at least the plurality of the entries that appear to be responsive to the broadcast advertisement.
Background
FIELD(1) The present application relates to data mining of network activity in order to infer statistics about user responses and behaviors in general and in particular to using time-sensitive data sources to determine time-based responses to advertising messages in unrelated media and incidental activities.BACKGROUND(2) Effectiveness of television advertising can be measured, somewhat, by broadcasting (sometimes in a loud voice) the message to “call now” so that interested parties will immediately make a phone call. However, such responses would likely be limited to those with an immediate interest in what is being sold and exclude those who are undecided about the offering, do not have immediate access to a telephone, etc., but might nonetheless be influenced by the advertising.(3) With the advent of Internet-based advertising (here, the “Internet” is used as just one example of a network over which many people can participate in many roles), other techniques have been developed for determining effectiveness of Internet ads, such as through the use of banner ads wherein the URL that is requested when a viewer clicks on the ad is a URL that first calls to an ad tracking server and then is passed on to another URL that provides the view with additional information. When the system providing the ad is the same as the one measuring response, the measuring might be simple. However, it is more complicated when there is not a direct connection.(4) A well-known adage, which some at
Claims
1. In a system wherein computing devices are used by users at a plurality of nodes at least to initiate messages that flow between nodes of the plurality of nodes, a method of measuring advertising effectiveness, the method comprising: monitoring, by a processor, at least one aggregate activity stream following a broadcast time of a broadcast advertisement, wherein the at least one aggregate activity stream represents one or more messages sent by an aggregation of users that form a statistical group over which advertising effectiveness is to be measured, wherein each of the one or more messages representing the at least one aggregate activity stream do not include the broadcast advertisement; filtering, by the processor, the one or more messages representing the at least one aggregate activity stream to identify messages that appear to be responsive to the broadcast advertisement, wherein filtering the one or more messages includes determining which of the identified messages were sent before the broadcast time of the broadcast advertisement, and determining which of the identified messages are mechanically generated and which of the identified messages are not mechanically generated, wherein a mechanically generated message includes a message that was previously sent at a prior time and that is resent following the broadcast time, and wherein a non-mechanically generated message includes a message that is sent following the broadcast time and that is based on a human response from an observation of the broadcast advertisement; assigning, by the processor, a first weight value to the identified messages that are mechanically generated and assigning a second weight value to the identified messages that are non-mechanically generated, wherein the first weight value is less than the second weight value; classifying, by the processor, the identified messages into a plurality of groups, wherein the identified messages are classified into a group based at least in part on a word pattern or phrase associated with an author; determining, by the processor, a demographic for each of the plurality of groups; and for each demographic: determining, by the processor, a measure of favorability based on the identified messages in one or more groups corresponding to the demographic and the weight values assigned to the identified messages in the one or more groups.
5. An advertising management system, comprising: one or more processors; and memory coupled to the one or more processors, wherein the memory stores instructions configured to cause the one or more processors to perform a method comprising: filtering user messages following a broadcast time of a broadcast advertisement to identify the user messages that appear to be responsive to the broadcast advertisement, wherein each of the user messages do not include the broadcast advertisement, wherein filtering the user messages includes determining which of the identified user messages were sent before the broadcast time of the broadcast advertisement, and determining which of the identified user messages are mechanically generated and which of the identified user messages are not mechanically generated, wherein a mechanically generated message includes a message that was previously sent at a prior time and that is resent following the broadcast time, and wherein a non-mechanically generated message includes a message that is sent following the broadcast time and that is based on a human response from an observation of the broadcast advertisement; assigning a first weight value to the filtered messages that are mechanically generated and assigning a second weight value to the filtered messages that are non-mechanically generated, wherein the first weight value is less than the second weight value; and classifying the identified messages into a plurality of groups, wherein the identified messages are classified into a group based at least in part on a word pattern or phrase associated with an author; determining a demographic for each of the plurality of groups; and for each demographic: determining a measure of favorability based on the identified messages in one or more groups corresponding to the demographic and the weight values assigned to the identified messages in the one or more groups.
14. An advertising management system, comprising: a memory storage device to store extracted user activity that includes data about user messages; one or more processors; and memory coupled to the one or more processors, wherein the memory stores instructions configured to cause the one or more processors to perform a method comprising: filtering user messages following a broadcast time of a broadcast advertisement to identify user messages that appear to be responsive to the broadcast advertisement, wherein each of the user messages do not include the broadcast advertisement, wherein filtering the user messages includes determining which of the identified user messages were sent before the broadcast time of the broadcast advertisement, and determining which of the identified user messages are mechanically generated and which of the identified user messages are not mechanically generated, wherein a mechanically generated message includes a message that was previously sent at a prior time and that is resent following the broadcast time, and wherein a non-mechanically generated message includes a message that is sent following the broadcast time and that is based on a human response from an observation of the broadcast advertisement; assigning a first weight value to the filtered messages that are mechanically generated and assigning a second weight value to the filtered messages that are non-mechanically generated, wherein the first weight value is less than the second weight value; classifying the identified messages into a plurality of groups, wherein the identified messages are classified into a group based at least in part on a word pattern or phrase associated with an author; determining a demographic for each of the plurality of groups; and for each demographic: determining a measure of favorability based on the identified messages in one or more groups corresponding to the demographic and the weight values assigned to the identified messages in the one or more groups.
18. An advertising management system, comprising: one or more processors; and memory coupled to the one or more processors, wherein the memory stores instructions configured to cause the one or more processors to perform a method comprising: filtering user messages following a broadcast time of a broadcast advertisement to identify the user messages that appear to be responsive to the broadcast advertisement, wherein each of the user messages do not include the broadcast advertisement; wherein filtering the user messages includes determining which of the identified user messages were sent before the broadcast time of the broadcast advertisement, and determining which of the identified user messages are mechanically generated and which of the identified user messages are not mechanically generated, wherein a mechanically generated message includes a message that was previously sent at prior time and that is resent following the broadcast time, and wherein a non-mechanically generated message includes a message that is sent following the broadcast time and that is based on a human response from an observation of the broadcast advertisement; and adjusting content in the broadcast advertisement based at least in part on results of identified user messages responsive of a broadcast advertisement.