The present disclosure relates to methods, systems and apparatus for monitoring, gathering and processing information relating to media across different mediums and platforms.
Content providers and advertisers have a considerable interest in determining the amounts and types of users/panelists that are exposed to particular content. In the case of Internet content, websites and advertisers have long relied on “cookies” and other related technology for monitoring and tracking web pages and content being accessed by users. In the case of broadcast media, companies like Arbitron have relied on embedded audio codes (e.g., Critical Band Encoding Technology (CBET)) as well as audio signature-matching and pattern-matching technology to monitor and track exposure of panelists to broadcast media (e.g., radio, television). In other types of media, such as billboard, signage, publication, and/or product exposure, various techniques have been implemented using proximity-based sensors to determine what users are being exposed to in commercial establishments.
One of the issues facing content providers and advertisers is that monitoring panelist content exposure across different platforms is relatively inefficient and, at times, unreliable. As more content becomes integrated across different platforms, it will become increasingly important to measure, determine, and verify content exposure among these platforms. Accordingly, there is a need to develop systems and methods for cross-platform monitoring and matching.
Systems, apparatuses and method are disclosed allowing content providers and advertisers to accurately measure exposure to A/V media content. One portion of the system measures data pertaining to a computer network, while another portion measures data relating to audio signals of the A/V media content. As the network and audio data is accumulated, each portion of the system creates respective content sequences, indicating a sequence in which media was played for a specific user. The respective sequences are then processed in a resolution processor to compare the sequences to verify the content sequence and confirm the presence of a user. Additional processing may be utilized to adjust the comparison process and increase/decrease the sensitivity of the system.
Various embodiments of the present invention will be described herein below with reference to the accompanying drawings. In the following description, well-known functions or constructions are not described in detail since they would obscure the invention with unnecessary detail.
Turning to
The one or more servers (150A-C) providing network content 150 are arranged so that content 115 can be served to users directly, or through one or more of a plurality of software applications 125, such as Facebook™, Myspace™, YouTube™ or Hulu™. Software applications 125 may be accessed from network content 150, or can alternately reside locally on individual user devices (151-153).
In the exemplary embodiment of
When users access content 115 from their devices, it is preferable that their on-line activities (also referred to as “clickstream data”) be collected and analyzed at count server 155. This can be accomplished for smaller amounts of content using logfile analysis via web server logs and optional cookie information. For larger amounts of content, it is preferable to employ the use of embedded references to web beacons (also referred to as “Clear GIFs,” “Web Bugs,” or “Pixel Tags”). Web beacons are preferably in the form of a very small graphic image (e.g., 1 pixel by 1 pixel in size) which is typically clear or transparent. Depending on how the web beacon reference is encoded in the web page definition, and depending on the user's actions when viewing a web page, or viewing or listening to A/V content, a request message will be issued from the user's device to retrieve the file containing the web beacon. Because of its small size and transparency, the web beacon that is rendered on the user's display is relatively unobtrusive. Often, the web beacon uses executable code written in JavaScript (or other suitable language) to report on the content of the respective web page by sending a message with information about the particular page within which the web beacon was requested. The HTTP request header which requests delivery of the web beacon also supplies certain types of information about the client, such as the user agent (i.e. browser) in use at the time, what types of encoding the user agent supports, as well as other information. When using web beacon in this manner, the user's browser sends clickstream data directly to a site analysis application preferably stored on count server 155. Additionally, a web beacon may include software script that is carried with text or A/V content that already includes or actively gathers data about the content, the content's origin and travel path (e.g. referral page), the device, the network (e.g., IP address and network travel path, ISP) and content usage (e.g., duration, rewind), and reports this data to count server 155.
Whenever a web page, with our without beacons, is downloaded, the server holding the page knows and can store the IP address of the device requesting the page. This information can also be retrieved from the server log files. Preferably, web beacons are used when user monitoring is done by a server that is different from the one holding the web page(s). This can be advantageous for example when the web pages are served by different servers, or when monitoring is done by a third party. When web beacons are requested, they typically send the server their URL, as well as the URL of the page containing them. The URL of the page containing the beacon allows the server (count server 155) to determine which particular web page the user has accessed. The URL of the beacon can be appended with an arbitrary string in various ways while still identifying the same object. This extra information can be used to better identify the conditions under which the beacon was loaded, and can be added while sending the page or by JavaScripts after the download.
Turning to
The acoustic signals in
When audio data is received by the portable device, which in certain embodiments comprises one or more processors, the portable device forms signature data characterizing the audio data. Suitable techniques for extracting signatures from audio data are disclosed in U.S. Pat. No. 6,996,237 to Jensen et al, U.S. Pat. No. 6,871,180 to Neuhauser et al., U.S. Pat. No. 5,612,729 to Ellis, et al. and in U.S. Pat. No. 4,739,398 to Thomas, et al., each of which is assigned to the assignee of the present invention and each of which are incorporated by reference in their entirety herein.
When using techniques utilizing “signature” extraction and/or pattern matching, a reference signature database is formed containing a reference signature for each program in the media data for which exposure is to be measured. The reference signatures are created by measuring or extracting certain features of the respective programs before broadcast. Upon reception of the media data, signature extraction is again performed, and the extracted signatures are compared to the reference signatures to find matches.
Still other suitable techniques are the subject of U.S. Pat. No. 2,662,168 to Scherbatskoy, U.S. Pat. No. 3,919,479 to Moon, et al., U.S. Pat. No. 4,697,209 to Kiewit, et al., U.S. Pat. No. 4,677,466 to Lert, et al., U.S. Pat. No. 5,512,933 to Wheatley, et al, U.S. Pat. No. 4,955,070 to Welsh, et al., U.S. Pat. No. 4,918,730 to Schulze, U.S. Pat. No. 4,843,562 to Kenyon, et al., U.S. Pat. No. 4,450,531 to Kenyon, et al., U.S. Pat. No. 4,230,990 to Lert, et al., U.S. Pat. No. 5,594,934 to Lu, et al., and PCT publication WO91/11062 to Young, et al., all of which are incorporated by reference in their entirety herein.
Portable user device 163 is further comprised of storage 196 coupled with processor 190 and operative to store data as needed. In certain embodiments, storage 196 comprises a single storage device, while in others it comprises multiple storage devices. In certain embodiments, a single device implements certain functions of both processor 190 and storage 196.
In addition, portable user device 163 includes a microphone 195 coupled with processor 190 to transduce audio to an electrical signal, which it supplies to processor 190, and speaker and/or earphone 192 coupled with processor 190 to transduce received audio from processor 190 to an acoustic output to be heard by the user. Portable user device 163 may also include user input 194 coupled with processor 190, such as a keypad, to enter telephone numbers and other control data, as well as display 193 coupled with processor 190 to provide data visually to the user under the control of processor 190.
In certain embodiments, portable user device may provide additional functions and/or comprises additional elements. In certain examples of such embodiments, portable user device provides e-mail, text messaging and/or web access through its wireless communications capabilities, providing access to media and other content. For example, Internet access by portable user device enables access to video and/or audio content that can be reproduced by the cellular telephone for the user, such as songs, video on demand, video clips and streaming media. In certain embodiments, storage 196 stores software providing audio and/or video downloading and reproducing functionality, such as iPod™ software, enabling the user to reproduce audio and/or video content downloaded from a source, such as a personal computer via communications 191 or through direct Internet access via communications 191.
To enable a portable user device to produce research data, research software is installed in storage 196 to control processor 190 to gather such data and communicate it via communications 191 to a centralized server system such as audio matching server 165. In certain embodiments, research software controls processor 190 to decode ancillary codes in the transduced audio from microphone 195 using one or more of the techniques identified hereinabove, and then to store and/or communicate the decoded data for use as research data indicating encoded audio to which the user was exposed. In certain embodiments, research software controls processor 190 to extract signatures from the transduced audio from microphone 195 using one or more of the techniques identified hereinabove, and then to store and/or communicate the extracted signature data for use as research data to be matched with reference signatures representing known audio to detect the audio to which the user was exposed. In certain embodiments, the research software both decodes ancillary codes in the transduced audio and extracts signatures therefrom for identifying the audio to which the user was exposed. In certain embodiments, the research software controls processor 190 to store samples of the transduced audio, either in compressed or uncompressed form for subsequent processing either to decode ancillary codes therein or to extract signatures therefrom. In certain examples of these embodiments, compressed or uncompressed audio is communicated to a remote processor for decoding and/or signature extraction.
Referring back to
Content1 (110) was accessed using Application1 (120) at Time1;
Content2 (111) was accessed using Application1 (120) at Time2;
Content3 (112) was accessed using Application2 (121) at Time3;
Content4 (113) was accessed using Application1 (120) at Time4; and
Content5 (114) was accessed using Application1 (120) at Time5.
A second sequence 201 for another user's device shows that:
Content1 (111) was accessed using Application3 (122) at Time1;
Content3 (112) was accessed using Application3 (122) at Time2;
Content4 (113) was accessed using Application2 (121) at Time3;
Content1 (110) was accessed using Application2 (121) at Time4; and
Content5 (114) was accessed using Application1 (120) at Time5.
Thus, the count server can establish for example that a user viewed a music video using Facebook™at 12:15PM, then viewed a movie preview using Facebook™at 12:20PM, then listened to a streaming audio program using Shoutcast™at 12:30PM. It is important to note that the clickstream data can contain additional information, such as originating source data, to obtain further information. In such a case, and following the preceding example, the count server can establish that a user viewed a music video from VH1 using Facebook™at 12:15PM, then viewed a movie preview from NBC using Facebook™ at 12:20PM, then listened to a streaming audio program from WABC using Shoutcast™ at 12:30PM.
Turning to
Content1 (110) was heard at Time1;
Content2 (111) was heard at Time2;
Content3 (112) was heard at Time3;
Content4 (113) was heard at Time4; and
Content5 (114) was heard at Time5.
The second audio matching sequence 301 for another user's device shows that:
Content2 (111) was heard at Time1;
Content3 (112) was heard at Time2;
Content4 (113) was heard at Time3;
Content1 (110) was heard at Time4; and
Content5 (114) was heard at Time5.
Thus, the audio matching server can establish for example that a user heard a music video at 12:15PM, then heard a movie preview at 12:20PM, then listened to a streaming audio program at 12:30PM.
In the embodiment of
Turning to
It is appreciated that content sequences from count server 155 and audio matching server 165 will not always have a direct one-to-one alignment for verification. Accordingly, it is preferred that the resolution software in resolution processor 180 is able to process various data points from the clickstream/audio match data and correlate the data points to a timestamp. As an example,
The audio match data content sequence 300 in
Continuing with
The above example illustrates the additional flexibility provided to content providers and advertisers in measuring content exposure. In an alternate embodiment, the resolution software may be programmed to provide “weights” to content sequence measurements to improve accuracy. For example, if nine out of ten sequences match between a content sequence and audio matching sequence, the non-matching sequence may be given a weighted value to determine a probability that the non-matching sequence was an anomaly, and should be included. Similarly, non-matching sequences at the end of a sequence may be weighted to exclude the data, as it is more likely that the user became disengaged with the content at that time. Also, as mentioned above, the length of time in which content was played could be used to further supplement the weight factors. Content having a shorter audio matching exposure time should be given preference, as the shortened exposure would indicate that the user was not near the computer throughout the duration of the content.
The differences in time when content is first registered in the count server 155 and audio matching server 165 may be adjusted (e.g., 0.05 sec-2 sec) to take into account hardware and network latencies (as well as audio signal propagation) that may exist. This way, content may still be accurately registered in resolution processor 180, even though the timestamps are not identical. Moreover, the time difference adjustments may be dynamically linked to the sequence “weights” described above to capture more data accurately; as the number of sequence matches increase, the time difference may be increased in proportion.
Information from the content sequences and audio match sequences may be used to supplement one another's data. In
In an alternate embodiment,
It can be seen from the embodiments discussed above that the system provides a powerful new tool for content providers and advertisers to accurately measure and interpret content exposure. Although various embodiments of the present invention have been described with reference to a particular arrangement of parts, features and the like, these are not intended to exhaust all possible arrangements or features, and indeed many other embodiments, modifications and variations will be ascertainable to those of skill in the art.
As an example, location-based data could also be incorporated to improve the functionality of the system. If a portable user device and laptop are connected to the same Wi-Fi hotspot, this would indicate a high statistical probability that the user is near the content during playback. Wi-Fi signal strengths could further be compared to determine relative distances of portable user devices to the computer. GPS data could also be used to determine locations of users.
The Abstract of the Disclosure is provided to comply with 37 C.F.R. § 1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.