U.S. patent application number 14/502468 was filed with the patent office on 2015-10-29 for systems and methods for determining a likelihood of user termination of services.
The applicant listed for this patent is Rovi Guides, Inc.. Invention is credited to Matthew Emans, John Hoctor.
Application Number | 20150312605 14/502468 |
Document ID | / |
Family ID | 54336018 |
Filed Date | 2015-10-29 |
United States Patent
Application |
20150312605 |
Kind Code |
A1 |
Hoctor; John ; et
al. |
October 29, 2015 |
SYSTEMS AND METHODS FOR DETERMINING A LIKELIHOOD OF USER
TERMINATION OF SERVICES
Abstract
Systems and methods are described herein for determining a
likelihood that a user will change a service. A media guidance
application may identify a first service to which a user is
subscribed. The media guidance application may receive information
from a third-party data source corresponding to the user and
identify, based on the information from the third-party data
source, data indicating a negative interest in the first service.
Based on the identified data, the media guidance application may
calculate a likelihood that the user will change the first
service.
Inventors: |
Hoctor; John; (Newton,
MA) ; Emans; Matthew; (Boston, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Rovi Guides, Inc. |
Santa Clara |
CA |
US |
|
|
Family ID: |
54336018 |
Appl. No.: |
14/502468 |
Filed: |
September 30, 2014 |
Related U.S. Patent Documents
|
|
|
|
|
|
Application
Number |
Filing Date |
Patent Number |
|
|
61985149 |
Apr 28, 2014 |
|
|
|
Current U.S.
Class: |
725/14 |
Current CPC
Class: |
H04N 21/2543 20130101;
H04N 21/251 20130101; H04N 21/44213 20130101; H04N 21/4667
20130101; H04N 21/482 20130101; H04N 21/812 20130101; H04N 21/44218
20130101; H04N 21/25435 20130101; H04N 21/44222 20130101; G06Q
30/02 20130101; G06Q 30/0631 20130101; H04N 21/2668 20130101; H04N
21/462 20130101; H04N 21/40 20130101; H04N 21/4821 20130101; H04N
21/42201 20130101; H04N 21/25891 20130101; H04N 21/8133
20130101 |
International
Class: |
H04N 21/25 20060101
H04N021/25; H04N 21/442 20060101 H04N021/442; H04N 21/81 20060101
H04N021/81; H04N 21/258 20060101 H04N021/258 |
Claims
1. A method for determining a likelihood that a user will change a
service, the method comprising: identifying a first service to
which a user is subscribed; receiving information from a
third-party data source corresponding to the user; identifying,
based on the information from the third-party data source, data
indicating a negative interest in the first service; and
calculating a likelihood that the user will change the first
service based on the identified data.
2. The method of claim 1, wherein identifying, based on the
information from the third-party data source, data indicating a
negative interest in the first service comprises identifying, from
the information from the third-party data source, negative feedback
of the first service made by the user.
3. The method of claim 1, wherein identifying, based on the
information from the third-party data source, data indicating a
negative interest in the first service comprises: identifying, from
the information from the third-party data source, comments made by
the user that include the first service; determining a first time
period based on the identified comments; calculating a first
frequency of the identified comments during the first time period;
identifying, from the information from the third-party data source,
comments made by the user in a second time period subsequent to the
first time period; calculating a second frequency of the identified
comments made by the user in the second time period; and
determining that the second frequency is less than the first
frequency.
4. The method of claim 1, wherein the third-party data source is a
social media data source.
5. The method of claim 4, wherein identifying, based on the
information from the third-party data source, data indicating a
negative interest in the first service comprises: identifying an
individual connected to the user through a social network
maintained by the third-party data source; and identifying, from
the information from the third-party data source, negative feedback
of the first service made by the individual.
6. The method of claim 4, wherein identifying, based on the
information from the third-party data source, data indicating a
negative interest in the first service comprises: identifying an
individual connected to the user through a social network
maintained by the third-party data source; identifying, from the
information from the third-party data source, comments made by the
individual that include the first service; determining a first time
period based on the identified comments; calculating a first
frequency of the identified comments during the first time period;
identifying, from the information from the third-party data source,
comments made by the individual in a second time period subsequent
to the first time period; calculating a second frequency of the
identified comments made by the individual in the second time
period; and determining that the second frequency is less than the
first frequency.
7. The method of claim 1, further comprising transmitting the
likelihood that the user will change the first service to a service
provider of the first service.
8. The method of claim 1, further comprising, transmitting to the
user at least one of an advertisement for the first service or an
offer for a discount for the first service.
9. The method of claim 8, wherein transmitting to the user at least
one of the advertisement for the first service or the offer for the
discount for the first service is performed in response to
calculating the likelihood that the user will change the first
service.
10. The method of claim 1, further comprising: identifying a second
service to which the user is not subscribed; identifying, based on
the information from the third-party data source, data indicating a
positive interest in the second service; and updating the
likelihood that the user will change the first service based on the
identified data indicating a positive interest in the second
service.
11. A system for determining a likelihood that a user will change a
service, the system comprising: control circuitry configured to:
identify a first service to which a user is subscribed; receive
information from a third-party data source corresponding to the
user; identify, based on the information from the third-party data
source, data indicating a negative interest in the first service;
and calculate a likelihood that the user will change the first
service based on the identified data.
12. The system of claim 11, wherein the control circuitry is
configured to identify, based on the information from the
third-party data source, data indicating a negative interest in the
first service by identifying, from the information from the
third-party data source, negative feedback of the first service
made by the user.
13. The system of claim 11, wherein the control circuitry is
configured to identify, based on the information from the
third-party data source, data indicating a negative interest in the
first service by: identifying, from the information from the
third-party data source, comments made by the user that include the
first service; determining a first time period based on the
identified comments; calculating a first frequency of the
identified comments during the first time period; identifying, from
the information from the third-party data source, comments made by
the user in a second time period subsequent to the first time
period; calculating a second frequency of the identified comments
made by the user in the second time period; and determining that
the second frequency is less than the first frequency.
14. The system of claim 11, wherein the third-party data source is
a social media data source.
15. The system of claim 14, wherein the control circuitry is
configured to identify, based on the information from the
third-party data source, data indicating a negative interest in the
first service by: identifying an individual connected to the user
through a social network maintained by the third-party data source;
and identifying, from the information from the third-party data
source, negative feedback of the first service made by the
individual.
16. The system of claim 14, wherein the control circuitry is
configured to identify, based on the information from the
third-party data source, data indicating a negative interest in the
first service by: identifying an individual connected to the user
through a social network maintained by the third-party data source;
identifying, from the information from the third-party data source,
comments made by the individual that include the first service;
determining a first time period based on the identified comments;
calculating a first frequency of the identified comments during the
first time period; identifying, from the information from the
third-party data source, comments made by the individual in a
second time period subsequent to the first time period; calculating
a second frequency of the identified comments made by the
individual in the second time period; and determining that the
second frequency is less than the first frequency.
17. The system of claim 11, wherein the control circuitry is
further configured to transmit the likelihood that the user will
change the first service to a service provider of the first
service.
18. The system of claim 11, wherein the control circuitry is
further configured to transmit to the user at least one of an
advertisement for the first service or an offer for a discount for
the first service.
19. The system of claim 18, wherein the control circuitry is
configured to transmit to the user at least one of the
advertisement for the first service or the offer for the discount
for the first service in response to calculating the likelihood
that the user will change the first service.
20. The system of claim 11, wherein the control circuitry is
further configured to: identify a second service to which the user
is not subscribed; identify, based on the information from the
third-party data source, data indicating a positive interest in the
second service; and update the likelihood that the user will change
the first service based on the identified data indicating a
positive interest in the second service.
21-50. (canceled)
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application claims priority benefit under 35 U.S.C.
.sctn.119(e) from U.S. provisional application No. 61/985,149,
filed on Apr. 28, 2014. The aforementioned, earlier-filed
application is hereby incorporated by reference herein in its
entirety.
BACKGROUND
[0002] Users have access to content from a variety of sources
(e.g., various cable providers, various satellite providers,
various Internet sources, etc.). Some of these sources offer a
variety of services (e.g., premium services such as on-demand
content purchasing, premium channels, higher speed Internet access,
telephone services, etc.). Because of the variety of services
available and the availability of content from various sources,
users are often disconnecting or switching sources and/or services.
Traditional systems lack a way to determine the likelihood a user
is about to disconnect or switch sources/services to try to prevent
the user from doing so (e.g., by providing discounts and/or
advertisements).
SUMMARY
[0003] Viewer data (e.g., subscriber analytics) helps service
providers attract and retain customers by identifying those who may
have a propensity to add products and services or who may churn
based on viewing behaviors and subscription information. The media
guidance application may match viewership data with subscriber
billing records to model and evaluate the likely behavior of
subscribers and assign a propensity score. These scores are useful
for identifying cross-sell and up-sell opportunities as well as
focusing marketing activities on the most high-value
subscribers.
[0004] Accordingly, systems and methods are described herein for
determining a likelihood that a user will change a service. In some
aspects, a media guidance application may perform a method for
determining a likelihood that a user will change a service. The
media guidance application may identify a first service to which a
user is subscribed. In some embodiments, the media guidance
application may identify the first service by accessing user
subscription data or a user profile. The media guidance application
may receive information from a third-party data source
corresponding to the user. In some embodiments, the third-party
data source may be a social media data source, such as a social
media website, and the information from the third-party data source
corresponding to the user may comprise data from the user's social
media profile. The media guidance application may identify, based
on the information from the third-party data source, data
indicating a negative interest in the first service, and based on
the identified data, the media guidance application may calculate a
likelihood that the user will change the first service.
[0005] In some embodiments, the media guidance application may
identify negative interest in the first service by identifying
negative feedback of the first service made by the user. For
example, the user may post a negative review on a social media
website or provide negative comments to a market survey. The media
guidance application may also identify negative interest in the
first service by identifying a relative lack of comments about the
first service. For example, the media guidance application may
identify, from the information from the third-party data source,
comments made by the user that include the first service, determine
a first time period based on the identified comments, and calculate
a first frequency of the identified comments during the first time
period. The media guidance application may then identify, from the
information from the third-party data source, comments made by the
user in a second time period subsequent to the first time period,
calculate a second frequency of the identified comments made by the
user in the second time period, and determine that the second
frequency is less than the first frequency. Thus, the media
guidance application may detect whether a user stops commenting
about the service or posts comments less frequently than
before.
[0006] In some embodiments, the media guidance application may
identify negative interest in the first service through individuals
connected to the user through a social network maintained by the
third-party data source (e.g., Facebook friends). The media
guidance application may identify an individual connected to the
user through a social network maintained by the third-party data
source and identify, from the information from the third-party data
source, negative feedback of the first service made by the
individual. The media guidance application may also identify a
relative lack of comments by the individual connected to the user
through the social network. For example, the media guidance
application may identify an individual connected to the user
through a social network maintained by the third-party data source,
identify, from the information from the third-party data source,
comments made by the individual that include the first service,
determine a first time period based on the identified comments, and
calculate a first frequency of the identified comments during the
first time period. The media guidance application may further
identify, from the information from the third-party data source,
comments made by the individual in a second time period subsequent
to the first time period, calculate a second frequency of the
identified comments made by the individual in the second time
period, and determine that the second frequency is less than the
first frequency. In this manner, the media guidance application may
detect whether individuals in the user's social circle have stopped
commenting or are commenting less frequently about the service.
[0007] In some embodiments, the media guidance application may
transmit the likelihood that the user will change the first service
to a service provider of the first service. The media guidance
application and/or the service provider may determine whether the
user has a relative high likelihood of changing or terminating the
first service. For example, the media guidance application or the
service provider may determine whether the calculated likelihood
exceeds a threshold, indicating that the user will likely change or
terminate the service in the near future. The service provider
and/or the media guidance application may transmit to the user at
least one of an advertisement for the first service or an offer for
a discount for the first service. The advertisement or offer may be
transmitted and/or presented in response to calculating the
likelihood that the user will change the first service.
[0008] In some embodiments, the media guidance application may
further identify a second service to which the user is not
subscribed, identify, based on the information from the third-party
data source, data indicating a positive interest in the second
service, and update the likelihood that the user will change the
first service based on the identified data indicating a positive
interest in the second service. For example, the media guidance
application may determine that interest in the second service is
rising, and may determine that the user has a higher likelihood of
changing or terminating the first service.
[0009] In another aspect, systems and methods are described herein
for generating a model to determine a likelihood that a user will
change a service. A media guidance application may identify a first
service to which a plurality of users are subscribed, receive
information from a third-party data source for each of the
plurality of users, identify, based on the respective information
from the third-party data source, a user action performed by each
of the plurality of users in relation to the first service, and
identify for at least one of the plurality of users, based on the
respective information from the third-party data source, a request
to change the first service. Based on the identified user action
and the identified request to change the first service, the media
guidance application may generate a model to determine a likelihood
that a user will change the first service.
[0010] In some embodiments, the media guidance application may
generate the model by calculating a probability that the identified
user action is followed by the identified request to change the
first service. In some embodiments, the request to change the first
service may follow the identified user action after a
user-identified amount of time. As an illustrative example, the
media guidance application may identify a plurality of users who
posted negative comments about a service. At least one user of the
plurality of users requested to terminate the service. Based on
this data, the media guidance application may calculate a
probability that an action of posting negative comments about a
service is followed by a request to terminate the service.
[0011] In some embodiments, the media guidance application may
identify, based on the respective information from the third-party
data source, a second user action performed by each of the
plurality of users in relation to the first service, determine a
pattern of action based on the first user action and the second
user action, and calculate a probability that the determined
pattern of action is followed by the identified request to change
the first service. Continuing the illustrative example from above,
the plurality of users may each exhibit a pattern of posting
negative comments/feedback about the service. Based on this
information, the media guidance application may calculate the
probability that several negative comments are followed by a
request to terminate the first service. In some embodiments, the
user action is one of a playback action, negative feedback for the
first service, a negative comment made about the first service, or
a lack of user action for a period of time.
[0012] In some embodiments, the media guidance application may use
the model to determine the likelihood that a user will change a
service. The media guidance application may receive information
from the third-party data source for the user, identify, based on
the information from the third-party data source for the user, a
user action performed by the user in relation to the first service,
and compare the user action performed by the user to the user
action performed by each of the plurality of users. The media
guidance application may calculate, based on the comparison, a
correlation factor that indicates a similarity between the user and
one of the plurality of users. The media guidance application may
determine, based on the correlation factor, a probability that the
user will request to change the first service. For example, the
media guidance application may determine that the user and the one
of the plurality of users have executed one or more similar actions
in a similar timeframe, and thus are likely to request similar
changes to the service in the near future. In some embodiments, the
media guidance application may transmit the correlation factor to a
service provider of the first service.
[0013] It should be noted that the systems and/or methods described
above may be applied to, or used in accordance with, other systems,
methods and/or apparatuses.
BRIEF DESCRIPTION OF THE DRAWINGS
[0014] The above and other objects and advantages of the disclosure
will be apparent upon consideration of the following detailed
description, taken in conjunction with the accompanying drawings,
in which like reference characters refer to like parts throughout,
and in which:
[0015] FIG. 1 shows an illustrative example of a display screen for
use in accessing media content in accordance with some embodiments
of the disclosure;
[0016] FIG. 2 shows another illustrative example of a display
screen used access media content in accordance with some
embodiments of the disclosure;
[0017] FIG. 3 is a block diagram of an illustrative user equipment
device in accordance with some embodiments of the disclosure;
[0018] FIG. 4 is a block diagram of an illustrative media system in
accordance with some embodiments of the disclosure;
[0019] FIG. 5 is an illustrative system 500 for generating an
indicator of the likelihood that a user will terminate access to a
service or source;
[0020] FIG. 6 is a flowchart of illustrative steps for determining
a likelihood that a user will change a service in accordance with
some embodiments of the disclosure;
[0021] FIG. 7 is a flowchart of another set of illustrative steps
for determining a likelihood that a user will change a service in
accordance with some embodiments of the disclosure;
[0022] FIG. 8 is a flowchart of illustrative steps for generating a
model to determine a likelihood that a user will change a service
in accordance with some embodiments of the disclosure; and
[0023] FIG. 9 is a flowchart of another set of illustrative steps
for generating a model to determine a likelihood that a user will
change a service in accordance with some embodiments of the
disclosure.
DETAILED DESCRIPTION OF THE DRAWINGS
[0024] The amount of content available to users in any given
content delivery system can be substantial. Consequently, many
users desire a form of media guidance through an interface that
allows users to efficiently navigate content selections and easily
identify content that they may desire. An application that provides
such guidance is referred to herein as an interactive media
guidance application or, sometimes, a media guidance application or
a guidance application.
[0025] Systems and methods are described herein for determining a
likelihood that a user will change a service. In some aspects, a
media guidance application may perform a method for determining a
likelihood that a user will change a service. The media guidance
application may identify a first service to which a user is
subscribed. In some embodiments, the media guidance application may
identify the first service by accessing user subscription data or a
user profile. The media guidance application may receive
information from a third-party data source corresponding to the
user. In some embodiments, the third-party data source may be a
social media data source, such as a social media website, and the
information from the third-party data source corresponding to the
user may comprise data from the user's social media profile. The
media guidance application may identify, based on the information
from the third-party data source, data indicating a negative
interest in the first service, and based on the identified data,
the media guidance application may calculate a likelihood that the
user will change the first service.
[0026] Interactive media guidance applications may take various
forms depending on the content for which they provide guidance. One
typical type of media guidance application is an interactive
television program guide. Interactive television program guides
(sometimes referred to as electronic program guides) are well-known
guidance applications that, among other things, allow users to
navigate among and locate many types of content or media assets.
Interactive media guidance applications may generate graphical user
interface screens that enable a user to navigate among, locate and
select content. As referred to herein, the terms "media asset" and
"content" should be understood to mean an electronically consumable
user asset, such as television programming, as well as pay-per-view
programs, on-demand programs (as in video-on-demand (VOD) systems),
Internet content (e.g., streaming content, downloadable content,
Webcasts, etc.), video clips, audio, content information, pictures,
rotating images, text documents, playlists, websites, articles,
books, electronic books, blogs, advertisements, chat sessions,
social media, applications, games, and/or any other media or
multimedia and/or combination of the same. Guidance applications
also allow users to navigate among and locate content. As referred
to herein, the term "multimedia" should be understood to mean
content that utilizes at least two different content forms
described above, for example, text, audio, images, video, or
interactivity content forms. Content may be recorded, played,
displayed or accessed by user equipment devices, but can also be
part of a live performance.
[0027] The media guidance application and/or any instructions for
performing any of the embodiments discussed herein may be encoded
on computer readable media. Computer readable media includes any
media capable of storing data. The computer readable media may be
transitory, including, but not limited to, propagating electrical
or electromagnetic signals, or may be non-transitory including, but
not limited to, volatile and non-volatile computer memory or
storage devices such as a hard disk, floppy disk, USB drive, DVD,
CD, media cards, register memory, processor caches, Random Access
Memory ("RAM"), etc.
[0028] With the advent of the Internet, mobile computing, and
high-speed wireless networks, users are accessing media on user
equipment devices on which they traditionally did not. As referred
to herein, the phrase "user equipment device," "user equipment,"
"user device," "electronic device," "electronic equipment," "media
equipment device," or "media device" should be understood to mean
any device for accessing the content described above, such as a
television, a Smart TV, a set-top box, an integrated receiver
decoder (IRD) for handling satellite television, a digital storage
device, a digital media receiver (DMR), a digital media adapter
(DMA), a streaming media device, a DVD player, a DVD recorder, a
connected DVD, a local media server, a BLU-RAY player, a BLU-RAY
recorder, a personal computer (PC), a laptop computer, a tablet
computer, a WebTV box, a personal computer television (PC/TV), a PC
media server, a PC media center, a hand-held computer, a stationary
telephone, a personal digital assistant (PDA), a mobile telephone,
a portable video player, a portable music player, a portable gaming
machine, a smart phone, or any other television equipment,
computing equipment, or wireless device, and/or combination of the
same. In some embodiments, the user equipment device may have a
front facing screen and a rear facing screen, multiple front
screens, or multiple angled screens. In some embodiments, the user
equipment device may have a front facing camera and/or a rear
facing camera. On these user equipment devices, users may be able
to navigate among and locate the same content available through a
television. Consequently, media guidance may be available on these
devices, as well. The guidance provided may be for content
available only through a television, for content available only
through one or more of other types of user equipment devices, or
for content available both through a television and one or more of
the other types of user equipment devices. The media guidance
applications may be provided as on-line applications (i.e.,
provided on a web-site), or as stand-alone applications or clients
on user equipment devices. Various devices and platforms that may
implement media guidance applications are described in more detail
below.
[0029] One of the functions of the media guidance application is to
provide media guidance data to users. As referred to herein, the
phrase "media guidance data" or "guidance data" should be
understood to mean any data related to content or data used in
operating the guidance application. For example, the guidance data
may include program information, guidance application settings,
user preferences, user profile information, media listings,
media-related information (e.g., broadcast times, broadcast
channels, titles, descriptions, ratings information (e.g., parental
control ratings, critic's ratings, etc.), genre or category
information, actor information, logo data for broadcasters' or
providers' logos, etc.), media format (e.g., standard definition,
high definition, 3D, etc.), advertisement information (e.g., text,
images, media clips, etc.), on-demand information, blogs, websites,
and any other type of guidance data that is helpful for a user to
navigate among and locate desired content selections.
[0030] FIGS. 1-2 show illustrative display screens that may be used
to provide media guidance data and media assets. The display
screens shown in FIGS. 1-2 may be implemented on any suitable user
equipment device or platform. While the displays of FIGS. 1-2 are
illustrated as full screen displays, they may also be fully or
partially overlaid over content being displayed. A user may
indicate a desire to access content information by selecting a
selectable option provided in a display screen (e.g., a menu
option, a listings option, an icon, a hyperlink, etc.) or pressing
a dedicated button (e.g., a GUIDE button) on a remote control or
other user input interface or device. In response to the user's
indication, the media guidance application may provide a display
screen with media guidance data organized in one of several ways,
such as by time and channel in a grid, by time, by channel, by
source, by content type, by category (e.g., movies, sports, news,
children, or other categories of programming), or other predefined,
user-defined, or other organization criterion.
[0031] FIG. 1 shows illustrative grid program listings display 100
arranged by time and channel that also enables access to different
types of content in a single display. Display 100 may include grid
102 with: (1) a column of channel/content type identifiers 104,
where each channel/content type identifier (which is a cell in the
column) identifies a different channel or content type available;
and (2) a row of time identifiers 106, where each time identifier
(which is a cell in the row) identifies a time block of
programming. Grid 102 also includes cells of program listings, such
as program listing 108, where each listing provides the title of
the program provided on the listing's associated channel and time.
With a user input device, a user can select program listings by
moving highlight region 110. Information relating to the program
listing selected by highlight region 110 may be provided in program
information region 112. Region 112 may include, for example, the
program title, the program description, the time the program is
provided (if applicable), the channel the program is on (if
applicable), the program's rating, and other desired
information.
[0032] In addition to providing access to linear programming (e.g.,
content that is scheduled to be transmitted to a plurality of user
equipment devices at a predetermined time and is provided according
to a schedule), the media guidance application also provides access
to non-linear programming (e.g., content accessible to a user
equipment device at any time and is not provided according to a
schedule). Non-linear programming may include content from
different content sources including on-demand content (e.g., VOD),
Internet content (e.g., streaming media, downloadable media, etc.),
locally stored content (e.g., content stored on any user equipment
device described above or other storage device), or other
time-independent content. On-demand content may include movies or
any other content provided by a particular content provider (e.g.,
HBO On Demand providing "The Sopranos" and "Curb Your Enthusiasm").
HBO ON DEMAND is a service mark owned by Time Warner Company L.P.
et al. and THE SOPRANOS and CURB YOUR ENTHUSIASM are trademarks
owned by the Home Box Office, Inc. Internet content may include web
events, such as a chat session or Webcast, or content available
on-demand as streaming content or downloadable content through an
Internet web site or other Internet access (e.g. FTP).
[0033] Grid 102 may provide media guidance data for non-linear
programming including on-demand listing 114, recorded content
listing 116, and Internet content listing 118. A display combining
media guidance data for content from different types of content
sources is sometimes referred to as a "mixed-media" display.
Various permutations of the types of media guidance data that may
be displayed that are different than display 100 may be based on
user selection or guidance application definition (e.g., a display
of only recorded and broadcast listings, only on-demand and
broadcast listings, etc.). As illustrated, listings 114, 116, and
118 are shown as spanning the entire time block displayed in grid
102 to indicate that selection of these listings may provide access
to a display dedicated to on-demand listings, recorded listings, or
Internet listings, respectively. In some embodiments, listings for
these content types may be included directly in grid 102.
Additional media guidance data may be displayed in response to the
user selecting one of the navigational icons 120. (Pressing an
arrow key on a user input device may affect the display in a
similar manner as selecting navigational icons 120.)
[0034] Display 100 may also include video region 122, advertisement
124, and options region 126. Video region 122 may allow the user to
view and/or preview programs that are currently available, will be
available, or were available to the user. The content of video
region 122 may correspond to, or be independent from, one of the
listings displayed in grid 102. Grid displays including a video
region are sometimes referred to as picture-in-guide (PIG)
displays. PIG displays and their functionalities are described in
greater detail in Satterfield et al. U.S. Pat. No. 6,564,378,
issued May 13, 2003 and Yuen et al. U.S. Pat. No. 6,239,794, issued
May 29, 2001, which are hereby incorporated by reference herein in
their entireties. PIG displays may be included in other media
guidance application display screens of the embodiments described
herein.
[0035] Advertisement 124 may provide an advertisement for content
that, depending on a viewer's access rights (e.g., for subscription
programming), is currently available for viewing, will be available
for viewing in the future, or may never become available for
viewing, and may correspond to or be unrelated to one or more of
the content listings in grid 102. Advertisement 124 may also be for
products or services related or unrelated to the content displayed
in grid 102. Advertisement 124 may be selectable and provide
further information about content, provide information about a
product or a service, enable purchasing of content, a product, or a
service, provide content relating to the advertisement, etc.
Advertisement 124 may be targeted based on a user's
profile/preferences, monitored user activity, the type of display
provided, or on other suitable targeted advertisement bases.
[0036] While advertisement 124 is shown as rectangular or banner
shaped, advertisements may be provided in any suitable size, shape,
and location in a guidance application display. For example,
advertisement 124 may be provided as a rectangular shape that is
horizontally adjacent to grid 102. This is sometimes referred to as
a panel advertisement. In addition, advertisements may be overlaid
over content or a guidance application display or embedded within a
display. Advertisements may also include text, images, rotating
images, video clips, or other types of content described above.
Advertisements may be stored in a user equipment device having a
guidance application, in a database connected to the user
equipment, in a remote location (including streaming media
servers), or on other storage means, or a combination of these
locations. Providing advertisements in a media guidance application
is discussed in greater detail in, for example, Knudson et al.,
U.S. Patent Application Publication No. 2003/0110499, filed Jan.
17, 2003; Ward, III et al. U.S. Pat. No. 6,756,997, issued Jun. 29,
2004; and Schein et al. U.S. Pat. No. 6,388,714, issued May 14,
2002, which are hereby incorporated by reference herein in their
entireties. It will be appreciated that advertisements may be
included in other media guidance application display screens of the
embodiments described herein.
[0037] Options region 126 may allow the user to access different
types of content, media guidance application displays, and/or media
guidance application features. Options region 126 may be part of
display 100 (and other display screens described herein), or may be
invoked by a user by selecting an on-screen option or pressing a
dedicated or assignable button on a user input device. The
selectable options within options region 126 may concern features
related to program listings in grid 102 or may include options
available from a main menu display. Features related to program
listings may include searching for other air times or ways of
receiving a program, recording a program, enabling series recording
of a program, setting program and/or channel as a favorite,
purchasing a program, or other features. Options available from a
main menu display may include search options, VOD options, parental
control options, Internet options, cloud-based options, device
synchronization options, second screen device options, options to
access various types of media guidance data displays, options to
subscribe to a premium service, options to edit a user's profile,
options to access a browse overlay, or other options.
[0038] The media guidance application may be personalized based on
a user's preferences. A personalized media guidance application
allows a user to customize displays and features to create a
personalized "experience" with the media guidance application. This
personalized experience may be created by allowing a user to input
these customizations and/or by the media guidance application
monitoring user activity to determine various user preferences.
Users may access their personalized guidance application by logging
in or otherwise identifying themselves to the guidance application.
Customization of the media guidance application may be made in
accordance with a user profile. The customizations may include
varying presentation schemes (e.g., color scheme of displays, font
size of text, etc.), aspects of content listings displayed (e.g.,
only HDTV or only 3D programming, user-specified broadcast channels
based on favorite channel selections, re-ordering the display of
channels, recommended content, etc.), desired recording features
(e.g., recording or series recordings for particular users,
recording quality, etc.), parental control settings, customized
presentation of Internet content (e.g., presentation of social
media content, e-mail, electronically delivered articles, etc.) and
other desired customizations.
[0039] The media guidance application may allow a user to provide
user profile information or may automatically compile user profile
information. The media guidance application may, for example,
monitor the content the user accesses and/or other interactions the
user may have with the guidance application. Additionally, the
media guidance application may obtain all or part of other user
profiles that are related to a particular user (e.g., from other
web sites on the Internet the user accesses, such as
www.allrovi.com, from other media guidance applications the user
accesses, from other interactive applications the user accesses,
from another user equipment device of the user, etc.), and/or
obtain information about the user from other sources that the media
guidance application may access. As a result, a user can be
provided with a unified guidance application experience across the
user's different user equipment devices. This type of user
experience is described in greater detail below in connection with
FIG. 4. Additional personalized media guidance application features
are described in greater detail in Ellis et al., U.S. Patent
Application Publication No. 2005/0251827, filed Jul. 11, 2005,
Boyer et al., U.S. Pat. No. 7,165,098, issued Jan. 16, 2007, and
Ellis et al., U.S. Patent Application Publication No. 2002/0174430,
filed Feb. 21, 2002, which are hereby incorporated by reference
herein in their entireties.
[0040] Another display arrangement for providing media guidance is
shown in FIG. 2. Video mosaic display 200 includes selectable
options 202 for content information organized based on content
type, genre, and/or other organization criterion. In display 200,
television listings option 204 is selected, thus providing listings
206, 208, 210, and 212 as broadcast program listings. In display
200 the listings may provide graphical images including cover art,
still images from the content, video clip previews, live video from
the content, or other types of content that indicate to a user the
content being described by the media guidance data in the listing.
Each of the graphical listings may also be accompanied by text to
provide further information about the content associated with the
listing. For example, listing 208 may include more than one
portion, including media portion 214 and text portion 216. Media
portion 214 and/or text portion 216 may be selectable to view
content in full-screen or to view information related to the
content displayed in media portion 214 (e.g., to view listings for
the channel that the video is displayed on).
[0041] The listings in display 200 are of different sizes (i.e.,
listing 206 is larger than listings 208, 210, and 212), but if
desired, all the listings may be the same size. Listings may be of
different sizes or graphically accentuated to indicate degrees of
interest to the user or to emphasize certain content, as desired by
the content provider or based on user preferences. Various systems
and methods for graphically accentuating content listings are
discussed in, for example, Yates, U.S. Patent Application
Publication No. 2010/0153885, filed Dec. 29, 2005, which is hereby
incorporated by reference herein in its entirety.
[0042] Users may access content and the media guidance application
(and its display screens described above and below) from one or
more of their user equipment devices. FIG. 3 shows a generalized
embodiment of illustrative user equipment device 300. More specific
implementations of user equipment devices are discussed below in
connection with FIG. 4. User equipment device 300 may receive
content and data via input/output (hereinafter "I/O") path 302. I/O
path 302 may provide content (e.g., broadcast programming,
on-demand programming, Internet content, content available over a
local area network (LAN) or wide area network (WAN), and/or other
content) and data to control circuitry 304, which includes
processing circuitry 306 and storage 308. Control circuitry 304 may
be used to send and receive commands, requests, and other suitable
data using I/O path 302. I/O path 302 may connect control circuitry
304 (and specifically processing circuitry 306) to one or more
communications paths (described below). I/O functions may be
provided by one or more of these communications paths, but are
shown as a single path in FIG. 3 to avoid overcomplicating the
drawing.
[0043] Control circuitry 304 may be based on any suitable
processing circuitry such as processing circuitry 306. As referred
to herein, processing circuitry should be understood to mean
circuitry based on one or more microprocessors, microcontrollers,
digital signal processors, programmable logic devices,
field-programmable gate arrays (FPGAs), application-specific
integrated circuits (ASICs), etc., and may include a multi-core
processor (e.g., dual-core, quad-core, hexa-core, or any suitable
number of cores) or supercomputer. In some embodiments, processing
circuitry may be distributed across multiple separate processors or
processing units, for example, multiple of the same type of
processing units (e.g., two Intel Core i7 processors) or multiple
different processors (e.g., an Intel Core i5 processor and an Intel
Core i7 processor). In some embodiments, control circuitry 304
executes instructions for a media guidance application stored in
memory (i.e., storage 308). Specifically, control circuitry 304 may
be instructed by the media guidance application to perform the
functions discussed above and below. For example, the media
guidance application may provide instructions to control circuitry
304 to generate the media guidance displays. In some
implementations, any action performed by control circuitry 304 may
be based on instructions received from the media guidance
application.
[0044] In client-server based embodiments, control circuitry 304
may include communications circuitry suitable for communicating
with a guidance application server or other networks or servers.
The instructions for carrying out the above mentioned functionality
may be stored on the guidance application server. Communications
circuitry may include a cable modem, an integrated services digital
network (ISDN) modem, a digital subscriber line (DSL) modem, a
telephone modem, Ethernet card, or a wireless modem for
communications with other equipment, or any other suitable
communications circuitry. Such communications may involve the
Internet or any other suitable communications networks or paths
(which is described in more detail in connection with FIG. 4). In
addition, communications circuitry may include circuitry that
enables peer-to-peer communication of user equipment devices, or
communication of user equipment devices in locations remote from
each other (described in more detail below).
[0045] Memory may be an electronic storage device provided as
storage 308 that is part of control circuitry 304. As referred to
herein, the phrase "electronic storage device" or "storage device"
should be understood to mean any device for storing electronic
data, computer software, or firmware, such as random-access memory,
read-only memory, hard drives, optical drives, digital video disc
(DVD) recorders, compact disc (CD) recorders, BLU-RAY disc (BD)
recorders, BLU-RAY 3D disc recorders, digital video recorders (DVR,
sometimes called a personal video recorder, or PVR), solid state
devices, quantum storage devices, gaming consoles, gaming media, or
any other suitable fixed or removable storage devices, and/or any
combination of the same. Storage 308 may be used to store various
types of content described herein as well as media guidance data
described above. Nonvolatile memory may also be used (e.g., to
launch a boot-up routine and other instructions). Cloud-based
storage, described in relation to FIG. 4, may be used to supplement
storage 308 or instead of storage 308. Storage 308 may include a
logger which stores one or more user actions and/or a timestamp
corresponding to each action. Control circuitry 304 may use
communication circuitry to periodically transmit this data using
I/O path 302. For example, control circuitry 304 may transmit logs
of user actions to media content source 416 or media guidance data
source 418, discussed further below in relation to FIG. 4.
[0046] Control circuitry 304 may include video generating circuitry
and tuning circuitry, such as one or more analog tuners, one or
more MPEG-2 decoders or other digital decoding circuitry,
high-definition tuners, or any other suitable tuning or video
circuits or combinations of such circuits. Encoding circuitry
(e.g., for converting over-the-air, analog, or digital signals to
MPEG signals for storage) may also be provided. Control circuitry
304 may also include scaler circuitry for upconverting and
downconverting content into the preferred output format of the user
equipment 300. Circuitry 304 may also include digital-to-analog
converter circuitry and analog-to-digital converter circuitry for
converting between digital and analog signals. The tuning and
encoding circuitry may be used by the user equipment device to
receive and to display, to play, or to record content. The tuning
and encoding circuitry may also be used to receive guidance data.
The circuitry described herein, including for example, the tuning,
video generating, encoding, decoding, encrypting, decrypting,
scaler, and analog/digital circuitry, may be implemented using
software running on one or more general purpose or specialized
processors. Multiple tuners may be provided to handle simultaneous
tuning functions (e.g., watch and record functions,
picture-in-picture (PIP) functions, multiple-tuner recording,
etc.). If storage 308 is provided as a separate device from user
equipment 300, the tuning and encoding circuitry (including
multiple tuners) may be associated with storage 308.
[0047] A user may send instructions to control circuitry 304 using
user input interface 310. User input interface 310 may be any
suitable user interface, such as a remote control, mouse,
trackball, keypad, keyboard, touch screen, touchpad, stylus input,
joystick, voice recognition interface, or other user input
interfaces. Display 312 may be provided as a stand-alone device or
integrated with other elements of user equipment device 300. For
example, display 312 may be a touchscreen or touch-sensitive
display. In such circumstances, user input interface 312 may be
integrated with or combined with display 312. Display 312 may be
one or more of a monitor, a television, a liquid crystal display
(LCD) for a mobile device, amorphous silicon display, low
temperature poly silicon display, electronic ink display,
electrophoretic display, active matrix display, electro-wetting
display, electrofluidic display, cathode ray tube display,
light-emitting diode display, electroluminescent display, plasma
display panel, high-performance addressing display, thin-film
transistor display, organic light-emitting diode display,
surface-conduction electron-emitter display (SED), laser
television, carbon nanotubes, quantum dot display, interferometric
modulator display, or any other suitable equipment for displaying
visual images. In some embodiments, display 312 may be
HDTV-capable. In some embodiments, display 312 may be a 3D display,
and the interactive media guidance application and any suitable
content may be displayed in 3D. A video card or graphics card may
generate the output to the display 312. The video card may offer
various functions such as accelerated rendering of 3D scenes and 2D
graphics, MPEG-2/MPEG-4 decoding, TV output, or the ability to
connect multiple monitors. The video card may be any processing
circuitry described above in relation to control circuitry 304. The
video card may be integrated with the control circuitry 304.
Speakers 314 may be provided as integrated with other elements of
user equipment device 300 or may be stand-alone units. The audio
component of videos and other content displayed on display 312 may
be played through speakers 314. In some embodiments, the audio may
be distributed to a receiver (not shown), which processes and
outputs the audio via speakers 314.
[0048] The guidance application may be implemented using any
suitable architecture. For example, it may be a stand-alone
application wholly implemented on user equipment device 300. In
such an approach, instructions of the application are stored
locally (e.g., in storage 308), and data for use by the application
is downloaded on a periodic basis (e.g., from an out-of-band feed,
from an Internet resource, or using another suitable approach).
Control circuitry 304 may retrieve instructions of the application
from storage 308 and process the instructions to generate any of
the displays discussed herein. Based on the processed instructions,
control circuitry 304 may determine what action to perform when
input is received from input interface 310. For example, movement
of a cursor on a display up/down may be indicated by the processed
instructions when input interface 310 indicates that an up/down
button was selected.
[0049] In some embodiments, the media guidance application is a
client-server based application. Data for use by a thick or thin
client implemented on user equipment device 300 is retrieved
on-demand by issuing requests to a server remote to the user
equipment device 300. In one example of a client-server based
guidance application, control circuitry 304 runs a web browser that
interprets web pages provided by a remote server. For example, the
remote server may store the instructions for the application in a
storage device. The remote server may process the stored
instructions using circuitry (e.g., control circuitry 304) and
generate the displays discussed above and below. The client device
may receive the displays generated by the remote server and may
display the content of the displays locally on equipment device
300. This way, the processing of the instructions is performed
remotely by the server while the resulting displays are provided
locally on equipment device 300. Equipment device 300 may receive
inputs from the user via input interface 310 and transmit those
inputs to the remote server for processing and generating the
corresponding displays. For example, equipment device 300 may
transmit a communication to the remote server indicating that an
up/down button was selected via input interface 310. The remote
server may process instructions in accordance with that input and
generate a display of the application corresponding to the input
(e.g., a display that moves a cursor up/down). The generated
display is then transmitted to equipment device 300 for
presentation to the user.
[0050] In some embodiments, the media guidance application is
downloaded and interpreted or otherwise run by an interpreter or
virtual machine (run by control circuitry 304). In some
embodiments, the guidance application may be encoded in the ETV
Binary Interchange Format (EBIF), received by control circuitry 304
as part of a suitable feed, and interpreted by a user agent running
on control circuitry 304. For example, the guidance application may
be an EBIF application. In some embodiments, the guidance
application may be defined by a series of JAVA-based files that are
received and run by a local virtual machine or other suitable
middleware executed by control circuitry 304. In some of such
embodiments (e.g., those employing MPEG-2 or other digital media
encoding schemes), the guidance application may be, for example,
encoded and transmitted in an MPEG-2 object carousel with the MPEG
audio and video packets of a program.
[0051] User equipment device 300 of FIG. 3 can be implemented in
system 400 of FIG. 4 as user television equipment 402, user
computer equipment 404, wireless user communications device 406, or
any other type of user equipment suitable for accessing content,
such as a non-portable gaming machine. For simplicity, these
devices may be referred to herein collectively as user equipment or
user equipment devices, and may be substantially similar to user
equipment devices described above. User equipment devices, on which
a media guidance application may be implemented, may function as a
standalone device or may be part of a network of devices. Various
network configurations of devices may be implemented and are
discussed in more detail below.
[0052] A user equipment device utilizing at least some of the
system features described above in connection with FIG. 3 may not
be classified solely as user television equipment 402, user
computer equipment 404, or a wireless user communications device
406. For example, user television equipment 402 may, like some user
computer equipment 404, be Internet-enabled allowing for access to
Internet content, while user computer equipment 404 may, like some
television equipment 402, include a tuner allowing for access to
television programming. The media guidance application may have the
same layout on various different types of user equipment or may be
tailored to the display capabilities of the user equipment. For
example, on user computer equipment 404, the guidance application
may be provided as a web site accessed by a web browser. In another
example, the guidance application may be scaled down for wireless
user communications devices 406.
[0053] In system 400, there is typically more than one of each type
of user equipment device but only one of each is shown in FIG. 4 to
avoid overcomplicating the drawing. In addition, each user may
utilize more than one type of user equipment device and also more
than one of each type of user equipment device.
[0054] In some embodiments, a user equipment device (e.g., user
television equipment 402, user computer equipment 404, wireless
user communications device 406) may be referred to as a "second
screen device." For example, a second screen device may supplement
content presented on a first user equipment device. The content
presented on the second screen device may be any suitable content
that supplements the content presented on the first device. In some
embodiments, the second screen device provides an interface for
adjusting settings and display preferences of the first device. In
some embodiments, the second screen device is configured for
interacting with other second screen devices or for interacting
with a social network. The second screen device can be located in
the same room as the first device, a different room from the first
device but in the same house or building, or in a different
building from the first device.
[0055] The user may also set various settings to maintain
consistent media guidance application settings across in-home
devices and remote devices. Settings include those described
herein, as well as channel and program favorites, programming
preferences that the guidance application utilizes to make
programming recommendations, display preferences, and other
desirable guidance settings. For example, if a user sets a channel
as a favorite on, for example, the web site www.allrovi.com on
their personal computer at their office, the same channel would
appear as a favorite on the user's in-home devices (e.g., user
television equipment and user computer equipment) as well as the
user's mobile devices, if desired. Therefore, changes made on one
user equipment device can change the guidance experience on another
user equipment device, regardless of whether they are the same or a
different type of user equipment device. In addition, the changes
made may be based on settings input by a user, as well as user
activity monitored by the guidance application.
[0056] The user equipment devices may be coupled to communications
network 414. Namely, user television equipment 402, user computer
equipment 404, and wireless user communications device 406 are
coupled to communications network 414 via communications paths 408,
410, and 412, respectively. Communications network 414 may be one
or more networks including the Internet, a mobile phone network,
mobile voice or data network (e.g., a 4G or LTE network), cable
network, public switched telephone network, or other types of
communications network or combinations of communications networks.
Paths 408, 410, and 412 may separately or together include one or
more communications paths, such as, a satellite path, a fiber-optic
path, a cable path, a path that supports Internet communications
(e.g., IPTV), free-space connections (e.g., for broadcast or other
wireless signals), or any other suitable wired or wireless
communications path or combination of such paths. Path 412 is drawn
with dotted lines to indicate that in the exemplary embodiment
shown in FIG. 4 it is a wireless path and paths 408 and 410 are
drawn as solid lines to indicate they are wired paths (although
these paths may be wireless paths, if desired). Communications with
the user equipment devices may be provided by one or more of these
communications paths, but are shown as a single path in FIG. 4 to
avoid overcomplicating the drawing.
[0057] Although communications paths are not drawn between user
equipment devices, these devices may communicate directly with each
other via communication paths, such as those described above in
connection with paths 408, 410, and 412, as well as other
short-range point-to-point communication paths, such as USB cables,
IEEE 1394 cables, wireless paths (e.g., Bluetooth, infrared, IEEE
802-11x, etc.), or other short-range communication via wired or
wireless paths. BLUETOOTH is a certification mark owned by
Bluetooth SIG, INC. The user equipment devices may also communicate
with each other directly through an indirect path via
communications network 414.
[0058] System 400 includes content source 416 and media guidance
data source 418 coupled to communications network 414 via
communication paths 420 and 422, respectively. Paths 420 and 422
may include any of the communication paths described above in
connection with paths 408, 410, and 412. Communications with the
content source 416 and media guidance data source 418 may be
exchanged over one or more communications paths, but are shown as a
single path in FIG. 4 to avoid overcomplicating the drawing. In
addition, there may be more than one of each of content source 416
and media guidance data source 418, but only one of each is shown
in FIG. 4 to avoid overcomplicating the drawing. (The different
types of each of these sources are discussed below.) If desired,
content source 416 and media guidance data source 418 may be
integrated as one source device. Although communications between
sources 416 and 418 with user equipment devices 402, 404, and 406
are shown as through communications network 414, in some
embodiments, sources 416 and 418 may communicate directly with user
equipment devices 402, 404, and 406 via communication paths (not
shown) such as those described above in connection with paths 408,
410, and 412.
[0059] Content source 416 may include one or more types of content
distribution equipment including a television distribution
facility, cable system headend, satellite distribution facility,
programming sources (e.g., television broadcasters, such as NBC,
ABC, HBO, etc.), intermediate distribution facilities and/or
servers, Internet providers, on-demand media servers, and other
content providers. NBC is a trademark owned by the National
Broadcasting Company, Inc., ABC is a trademark owned by the
American Broadcasting Company, Inc., and HBO is a trademark owned
by the Home Box Office, Inc. Content source 416 may be the
originator of content (e.g., a television broadcaster, a Webcast
provider, etc.) or may not be the originator of content (e.g., an
on-demand content provider, an Internet provider of content of
broadcast programs for downloading, etc.). Content source 416 may
include cable sources, satellite providers, on-demand providers,
Internet providers, over-the-top content providers, or other
providers of content. Content source 416 may also include a remote
media server used to store different types of content (including
video content selected by a user), in a location remote from any of
the user equipment devices. Systems and methods for remote storage
of content, and providing remotely stored content to user equipment
are discussed in greater detail in connection with Ellis et al.,
U.S. Pat. No. 7,761,892, issued Jul. 20, 2010, which is hereby
incorporated by reference herein in its entirety.
[0060] Media guidance data source 418 may provide media guidance
data, such as the media guidance data described above. Media
guidance data may be provided to the user equipment devices using
any suitable approach. In some embodiments, the guidance
application may be a stand-alone interactive television program
guide that receives program guide data via a data feed (e.g., a
continuous feed or trickle feed). Program schedule data and other
guidance data may be provided to the user equipment on a television
channel sideband, using an in-band digital signal, using an
out-of-band digital signal, or by any other suitable data
transmission technique. Program schedule data and other media
guidance data may be provided to user equipment on multiple analog
or digital television channels. In some embodiments, media guidance
data source 418 may be a social media data source that maintains a
social network. The social media data source may maintain profiles
of each of a plurality of users and may allow the users to post
comments, indicate status updates, or post any other activity.
[0061] In some embodiments, guidance data from media guidance data
source 418 may be provided to users' equipment using a
client-server approach. For example, a user equipment device may
pull media guidance data from a server, or a server may push media
guidance data to a user equipment device. In some embodiments, a
guidance application client residing on the user's equipment may
initiate sessions with source 418 to obtain guidance data when
needed, e.g., when the guidance data is out of date or when the
user equipment device receives a request from the user to receive
data. Media guidance may be provided to the user equipment with any
suitable frequency (e.g., continuously, daily, a user-specified
period of time, a system-specified period of time, in response to a
request from user equipment, etc.). Media guidance data source 418
may provide user equipment devices 402, 404, and 406 the media
guidance application itself or software updates for the media
guidance application.
[0062] In some embodiments, the media guidance data may include
viewer data. For example, the viewer data may include current
and/or historical user activity information (e.g., what content the
user typically watches, what times of day the user watches content,
whether the user interacts with a social network, at what times the
user interacts with a social network to post information, what
types of content the user typically watches (e.g., pay TV or free
TV), mood, brain activity information, etc.). The media guidance
data may also include subscription data. For example, the
subscription data may identify to which sources or services a given
user subscribes and/or to which sources or services the given user
has previously subscribed but later terminated access (e.g.,
whether the user subscribes to premium channels, whether the user
has added a premium level of services, whether the user has
increased Internet speed). In some embodiments, the viewer data
and/or the subscription data may identify patterns of a given user
for a period of more than one year. The media guidance data may
include a model (e.g., a survivor model) used for generating a
score that indicates a likelihood a given user will terminate
access to a service/source. For example, the media guidance
application may process the viewer data with the subscription data
using the model to generate a value or score that indicates a
likelihood of whether the given user will terminate access to a
particular service or source. In particular, a higher score may
indicate a higher level of confidence that the user will terminate
access to a particular service or source. Based on the score, the
media guidance application may generate promotions and
advertisements that entice the user to keep the particular service
or source indicated by the score as one to which the user will
likely terminate access.
[0063] Media guidance applications may be, for example, stand-alone
applications implemented on user equipment devices. For example,
the media guidance application may be implemented as software or a
set of executable instructions which may be stored in storage 308,
and executed by control circuitry 304 of a user equipment device
300. In some embodiments, media guidance applications may be
client-server applications where only a client application resides
on the user equipment device, and server application resides on a
remote server. For example, media guidance applications may be
implemented partially as a client application on control circuitry
304 of user equipment device 300 and partially on a remote server
as a server application (e.g., media guidance data source 418)
running on control circuitry of the remote server. When executed by
control circuitry of the remote server (such as media guidance data
source 418), the media guidance application may instruct the
control circuitry to generate the guidance application displays and
transmit the generated displays to the user equipment devices. The
server application may instruct the control circuitry of the media
guidance data source 418 to transmit data for storage on the user
equipment. The client application may instruct control circuitry of
the receiving user equipment to generate the guidance application
displays.
[0064] Content and/or media guidance data delivered to user
equipment devices 402, 404, and 406 may be over-the-top (OTT)
content. OTT content delivery allows Internet-enabled user devices,
including any user equipment device described above, to receive
content that is transferred over the Internet, including any
content described above, in addition to content received over cable
or satellite connections. OTT content is delivered via an Internet
connection provided by an Internet service provider (ISP), but a
third party distributes the content. The ISP may not be responsible
for the viewing abilities, copyrights, or redistribution of the
content, and may only transfer IP packets provided by the OTT
content provider. Examples of OTT content providers include
YOUTUBE, NETFLIX, and HULU, which provide audio and video via IP
packets. Youtube is a trademark owned by Google Inc., Netflix is a
trademark owned by Netflix Inc., and Hulu is a trademark owned by
Hulu, LLC. OTT content providers may additionally or alternatively
provide media guidance data described above. In addition to content
and/or media guidance data, providers of OTT content can distribute
media guidance applications (e.g., web-based applications or
cloud-based applications), or the content can be displayed by media
guidance applications stored on the user equipment device.
[0065] Media guidance system 400 is intended to illustrate a number
of approaches, or network configurations, by which user equipment
devices and sources of content and guidance data may communicate
with each other for the purpose of accessing content and providing
media guidance. The embodiments described herein may be applied in
any one or a subset of these approaches, or in a system employing
other approaches for delivering content and providing media
guidance. The following four approaches provide specific
illustrations of the generalized example of FIG. 4.
[0066] In one approach, user equipment devices may communicate with
each other within a home network. User equipment devices can
communicate with each other directly via short-range point-to-point
communication schemes described above, via indirect paths through a
hub or other similar device provided on a home network, or via
communications network 414. Each of the multiple individuals in a
single home may operate different user equipment devices on the
home network. As a result, it may be desirable for various media
guidance information or settings to be communicated between the
different user equipment devices. For example, it may be desirable
for users to maintain consistent media guidance application
settings on different user equipment devices within a home network,
as described in greater detail in Ellis et al., U.S. patent
application Ser. No. 11/179,410, filed Jul. 11, 2005. Different
types of user equipment devices in a home network may also
communicate with each other to transmit content. For example, a
user may transmit content from user computer equipment to a
portable video player or portable music player.
[0067] In a second approach, users may have multiple types of user
equipment by which they access content and obtain media guidance.
For example, some users may have home networks that are accessed by
in-home and mobile devices. Users may control in-home devices via a
media guidance application implemented on a remote device. For
example, users may access an online media guidance application on a
website via a personal computer at their office, or a mobile device
such as a PDA or web-enabled mobile telephone. The user may set
various settings (e.g., recordings, reminders, or other settings)
on the online guidance application to control the user's in-home
equipment. The online guide may control the user's equipment
directly, or by communicating with a media guidance application on
the user's in-home equipment. Various systems and methods for user
equipment devices communicating, where the user equipment devices
are in locations remote from each other, is discussed in, for
example, Ellis et al., U.S. Pat. No. 8,046,801, issued Oct. 25,
2011, which is hereby incorporated by reference herein in its
entirety.
[0068] In a third approach, users of user equipment devices inside
and outside a home can use their media guidance application to
communicate directly with content source 416 to access content.
Specifically, within a home, users of user television equipment 402
and user computer equipment 404 may access the media guidance
application to navigate among and locate desirable content. Users
may also access the media guidance application outside of the home
using wireless user communications devices 406 to navigate among
and locate desirable content.
[0069] In a fourth approach, user equipment devices may operate in
a cloud computing environment to access cloud services. In a cloud
computing environment, various types of computing services for
content sharing, storage or distribution (e.g., video sharing sites
or social networking sites) are provided by a collection of
network-accessible computing and storage resources, referred to as
"the cloud." For example, the cloud can include a collection of
server computing devices, which may be located centrally or at
distributed locations, that provide cloud-based services to various
types of users and devices connected via a network such as the
Internet via communications network 414. These cloud resources may
include one or more content sources 416 and one or more media
guidance data sources 418. In addition or in the alternative, the
remote computing sites may include other user equipment devices,
such as user television equipment 402, user computer equipment 404,
and wireless user communications device 406. For example, the other
user equipment devices may provide access to a stored copy of a
video or a streamed video. In such embodiments, user equipment
devices may operate in a peer-to-peer manner without communicating
with a central server.
[0070] The cloud provides access to services, such as content
storage, content sharing, or social networking services, among
other examples, as well as access to any content described above,
for user equipment devices. Services can be provided in the cloud
through cloud computing service providers, or through other
providers of online services. For example, the cloud-based services
can include a content storage service, a content sharing site, a
social networking site, or other services via which user-sourced
content is distributed for viewing by others on connected devices.
These cloud-based services may allow a user equipment device to
store content to the cloud and to receive content from the cloud
rather than storing content locally and accessing locally-stored
content.
[0071] A user may use various content capture devices, such as
camcorders, digital cameras with video mode, audio recorders,
mobile phones, and handheld computing devices, to record content.
The user can upload content to a content storage service on the
cloud either directly, for example, from user computer equipment
404 or wireless user communications device 406 having content
capture feature. Alternatively, the user can first transfer the
content to a user equipment device, such as user computer equipment
404. The user equipment device storing the content uploads the
content to the cloud using a data transmission service on
communications network 414. In some embodiments, the user equipment
device itself is a cloud resource, and other user equipment devices
can access the content directly from the user equipment device on
which the user stored the content.
[0072] Cloud resources may be accessed by a user equipment device
using, for example, a web browser, a media guidance application, a
desktop application, a mobile application, and/or any combination
of access applications of the same. The user equipment device may
be a cloud client that relies on cloud computing for application
delivery, or the user equipment device may have some functionality
without access to cloud resources. For example, some applications
running on the user equipment device may be cloud applications,
i.e., applications delivered as a service over the Internet, while
other applications may be stored and run on the user equipment
device. In some embodiments, a user device may receive content from
multiple cloud resources simultaneously. For example, a user device
can stream audio from one cloud resource while downloading content
from a second cloud resource. Or a user device can download content
from multiple cloud resources for more efficient downloading. In
some embodiments, user equipment devices can use cloud resources
for processing operations such as the processing operations
performed by processing circuitry described in relation to FIG.
3.
[0073] FIG. 5 is an illustrative system 500 for generating an
indicator of the likelihood that a user will terminate access to a
service or source. The components and operation of system 500 may
be implemented by circuitry or by software (e.g., the media
guidance application). System 500 includes a predictive attributes
engine 520, a history of billing data memory 530, a learning model
engine 540, and a trained model engine 550. Predictive attributes
engine 520 receives data (e.g., content attributes data 510, user
equipment viewer data 512 which includes indications about what
live and recorded content a user watches, on-demand data 514,
online activity data 516, social network activity 518, current user
attributes 526, and data from memory 530). On-demand data 514 may
indicate which non-linear content the user has previously consumed
or purchased. Online activity data 516 indicates what content the
user consumed online (e.g., from a streaming source).
[0074] Predictive attributes engine 520 processes one or more of
the data it receives to generate attributes that represent a
population of users with similar activity. The generated attributes
522 are output to learning model engine 540. Learning model engine
540 receives historical outcomes 524 from history billing data
memory 530. Historical outcomes 524 indicate what sources or
services the user has previously subscribed to and to which sources
or services the user has previous terminated access a period of
time after subscribing to them. Learning model engine 540 may
correlate historical attributes 522 of various users with
historical outcomes 524 of those users to determine patterns that
resulted in termination of access to sources or services.
Historical outcomes 524 may be stored as a database for various
users. The database may indicate for each user what sources or
services the user has previously subscribed to and to which sources
or services the user has previous terminated access a period of
time after subscribing to them.
[0075] For example, learning model engine 540 may process
historical outcomes 524 of a first user to identify a point at
which the first user has terminated access to a source or service
(e.g., unsubscribed from a premium channel). In some embodiments,
the first user may be a former subscriber to a source or service
(e.g., a user who completely disconnected service from a particular
source, such as a former cable subscriber that switched to
satellite). In such circumstances, learning model engine 540 may
analyze behavior of the former subscriber corresponding to the
viewing activity and subscription activity the former subscriber
had before becoming the former subscriber. In particular, leaning
model engine 540 may process the viewing activity and subscription
activity of a former cable subscriber to determine what cable
services the former subscriber subscribed to and/or terminated
service from before disconnecting from cable and switching to
satellite.
[0076] Learning model engine 540 may retrieve historical attributes
522 for that first user for a period of time before the user
terminated access and/or a period of time after the user terminated
access to detect a change in viewing activity that may have
resulted in the user terminating access to the source or service.
Learning model engine 540 may perform the same analysis for each
other user for which data is available (e.g., in a database for
historical outcomes 524) and who terminated access to the same
source or service. After processing the data for each user who
terminated access to the particular source or service, learning
model engine 540 may identify similarities in attributes 522 of
those users during the period preceding and/or following each
respective user's termination of access to the source or service.
Learning model 540 may store a correlation factor between the
similar attributes and the particular source or service. The
correction factor indicates when a subsequent user who is a
subscriber to the same source or service exhibits at least some of
the similar attributes, the user will likely terminate access to
the source or service. The greater the number of similar attributes
that the user exhibits, the larger the score that results from the
correlation factor indicating a greater likelihood that the user
will terminate access to the source or service. Learning model
engine 540 may generate a different correlation factor for each
source or service to which a set of users terminated access.
[0077] In some embodiments, learning model engine 540 may be
trained on an on-going, continuous basis. In particular, learning
model engine 540 may continuously process information (e.g., user
activity, historical outcomes 524, and subscription information)
for each subscriber or user and adapt or change the correlation
factor for a given service. The updated correlation factor may be
then provided to trained model engine 550. In some implementations,
learning model engine 540 may update a previously determined
correlation factor each time a given user or set of users terminate
access to a particular source or service. For example, each time
new information is stored to a database of historical outcomes 524
(e.g., each time a given user unsubscribes or disconnects from a
given source or service), a signal identifying the source or
service associated with the new information may be transmitted to
learning model engine 540 indicating a need to re-compute or update
a correlation factor corresponding to the identified source or
service.
[0078] As referred to herein, the phrase "terminate access" or
"termination of access" means that the source or service was
disconnected by the user or requested by the user to be removed
from the user's subscription plan. After terminating access to a
given source or service a user has to re-subscribe (repay) for the
source or service to resume access.
[0079] After a predetermined amount of time and/or after a data
from a predetermined number of users has been processed by learning
model engine 540, the model may be provided to trained model engine
550. Trained model engine 550 may process current attributes 526 of
a given user with each of the correlation factors provided by
learning model engine 540 that is associated with a source or
service to which the user is a subscriber. Trained model engine 550
may output a score that represents how closely correlated the
current user's attributes are with the correlation factor. The
score output by trained model engine 550 may be source/service
specific. A larger score indicates a greater likelihood that the
user will terminate access to the source or service.
[0080] The media guidance application may process the score for a
given user to target advertisements and promotions. For example, in
response to determining that the score of a given user exceeds a
first threshold, the media guidance application may identify the
source or service associated with the score. The media guidance
application may provide a promotion to the user for the source or
service (e.g., allow the user to keep the subscription to the
source or service at a discounted price). Alternatively, the media
guidance application may provide an advertisement for content
available on the source or service to the user. In some
implementations, in response to determining that the score of a
given user exceeds a second threshold higher than the first
threshold, the media guidance application may provide a different
set of promotions and/or advertisements. If the score is below a
threshold, the media guidance application may avoid presenting
promotions or advertisements for the source or service.
[0081] In some embodiments, in response to determining that the
score of a given user is below a threshold, the media guidance
application may instruct a subscriber management system to initiate
a process for retaining the given user. In some embodiments, in
response to determining that the score of a given user is below a
threshold, the media guidance application may provide a visual
alert to an operator of source or service associated with the
score. The visual alert may include information that identifies the
user, the source or service, and/or the score. For example, the
subscriber management system may, based on the instruction from the
media guidance application and the score, contact the given user
(e.g., place a phone call, send a text message or email) to offer a
new offer, discount on other services (e.g., packages of
programming), or reduction in price of current services. The offer
may be specific to the source or service for which the score is
below the threshold or generic. In particular, if the score
indicates that the user is likely to terminate access to a premium
channel, the subscriber management system may contact the given
user offering any combination of: a reduction in the current price
the given user is paying for the premium channel, a discount on a
new service (e.g., phone service for a cable subscriber), or a
discount on a new premium channel not currently subscribed to by
the given user. In some implementations, the subscriber management
system may apply different offers to different users who have the
same scores. The subscriber management system may determine what
level of offer to a given user not only based on the score of the
user but also based on information stored in historical outcomes
524 for the user and/or currently subscribed to services. For
example, if first and second users have the same score for a
particular service (e.g., cable) but the first user is not a
subscriber to premium channels, the subscriber management system
may offer the premium channels (or a set of premium channels that
meet a user profile for the first user) at a discount. The second
user may already be a subscriber to the premium channels and
accordingly the subscriber management system may offer alternate
services to the second user at a discount (e.g., phone services if
the second user does not currently have phone service).
[0082] In some embodiments, trained model engine 550 may receive
subscription information for a given user and user activity
information. The subscription information may indicate that the
user is a subscriber to a premium channel on the source (e.g., HBO
on cable) and the user activity information may indicate that the
given user has not viewed content from the premium channel in more
than a threshold period of time (e.g., more than 2 weeks). In
response, trained model engine 550 may identify a correlation
factor associated with the premium channel and generate a score
indicating that the user is likely to terminate access to the
premium channel. The value of the score may be higher or lower
based on other user activity and subscription information. For
example, if the user watches content from an affiliate of the
premium channel (e.g., Cinemax) which is tied to the subscription
of the primary channel (e.g., HBO), then the score may be
reduced.
[0083] In some embodiments, the subscription information may
indicate that the user is a subscriber to a premium channel on the
source (e.g., HBO on cable) and the user activity information may
indicate that the given user has increased the speed of their
Internet connection. In response, trained model engine 550 may
identify a correlation factor associated with the premium channel
and generate a score indicating that the user is likely to
terminate access to the premium channel. In particular, the user
may have increased Internet speed because they intend to access
more content online and may not need the premium channel anymore.
The score may be further increased if the above determination is
made that the user has not viewed content from the premium source
in more than a threshold period of time (e.g., more than 2
weeks).
[0084] In some embodiments, the subscription information may
indicate that the user has purchased a predetermined number of
movies from a source (e.g., a certain cable provider) and the
activity information may indicate that the user watches non-premium
content sources (e.g., free TV). In response, the score output by
trained model engine 550 may be reduced as the user is less likely
to terminate access to the source (e.g., disconnect service from
the cable provider). In some implementations, the subscription
information may indicate that the user is a subscriber to a cable
provider and the user activity information may indicate that the
given user watches new releases on-demand from the cable provider.
In response, the score corresponding to the cable provider output
by trained model engine 550 may be decreased as the user is
unlikely to terminate access to the cable provider as there may not
be an alternate source from which the user can obtain access to the
new releases. In some implementations, the subscription information
may indicate that the user is a subscriber to a cable provider and
the user activity information may indicate that the given user does
not watch many live events (e.g., linear content) and has increased
the Internet speed. In response, the score corresponding to the
cable provider output by trained model engine 550 may be increased
as the user is likely to terminate access to the cable provider as
the user may be looking to stream more content from an online
source. In some implementations, the subscription information may
indicate that the user is a subscriber to a cable provider and the
user activity information may indicate that the given user watches
many live events (e.g., linear content) and comments on a social
network about the live events. In response, the score corresponding
to the cable provider output by trained model engine 550 may be
decreased as the user is unlikely to terminate access to the cable
provider. In some implementations, the subscription information may
indicate that the user is a subscriber to a cable provider and the
user activity information may indicate that the given user watches
a variety of content. In response, the score corresponding to the
cable provider output by trained model engine 550 may be decreased
as the user is unlikely to terminate access to the cable
provider.
[0085] In some implementations, the subscription information may
indicate that the user is a subscriber to a premium channel on the
source (e.g., HBO on cable) and the user activity information may
indicate that the given user has subscribed to a different premium
channel (e.g., Showtime on cable). In response, the score
corresponding to the HBO premium channel output by trained model
engine 550 may be increased as the user is likely to terminate
access to the HBO premium channel given that the user will consume
content from the other premium channel. In some implementations,
the subscription information may indicate that the user is a
subscriber to a premium channel on the source (e.g., HBO on cable)
and the user activity information may indicate that the given user
only watches a certain show on the premium channel that has
recently ended (e.g., the season of the show has finished). In
response, the score corresponding to the HBO premium channel output
by trained model engine 550 may be increased as the user is likely
to terminate access to the HBO premium channel given that the user
will no longer have content to consume from the premium
channel.
[0086] FIG. 6 is a flowchart of illustrative steps for determining
a likelihood that a user will change a service in accordance with
some embodiments of the disclosure. Process 600 includes
identifying a first service to which a user is subscribed at step
602, receiving information from a third-party data source
corresponding to the user at step 604, identifying, based on the
information from the third-party data source, data indicating a
negative interest in the first service at step 606, and calculating
a likelihood that the user will change the first service based on
the identified data at step 608.
[0087] At step 602, a media guidance application may identify
(e.g., via control circuitry 304 (FIG. 3)) a first service to which
a user is subscribed. The first service may be any subscription
service, including, but not limited to television services, media
delivery services, premium services such as on-demand content
purchasing or premium channels, Internet access, or telephone
services. The media guidance application may identify a user's
subscription status using any suitable method. For example, the
media guidance application may store or access information
associated with a user, such as a user profile, which includes
information on services to which the user is subscribed. The media
guidance application may also query a remote server to determine
whether a user is subscribed to the first service. As discussed
above in relation to FIG. 5, a user's subscription information may
be stored in a memory such as history billing data memory 530,
which sends the subscription information to learning model engine
540.
[0088] At step 604, the media guidance application may receive
(e.g., through communication network 414 (FIG. 4) using control
circuitry 304 (FIG. 3)) information from a third-party data source
corresponding to the user. The third-party data source may be any
suitable data source for storing information corresponding to the
user. For example, the third-party data source may be a media
guidance data source, such as media guidance data source 418
depicted in FIG. 4, that stores a user profile. The third-party
data source may also be a social network data source that maintains
a social networking application for connecting the user to other
individuals in the social network. The social network data source
may provide a user profile associated with the user, comments or
posts that the user has uploaded onto the social network, profiles
associated with individuals connected to the user via the social
network, comments or posts that those associated individuals have
uploaded onto the social network, or any other information
associated with the user.
[0089] At step 606, the media guidance application may identify
(e.g., via control circuitry 304 (FIG. 3)), based on the
information from the third-party data source, data indicating a
negative interest in the first service. The media guidance
application may identify negative interest in any number of ways.
For example, the media guidance application may identify negative
feedback or comments made about the service. As an illustrative
example, the media guidance application may search a user's social
media comments and posts for keywords associated with the first
service, such as the name or type of the first service. The media
guidance application may cross-reference these words with words
associated with negative feedback (e.g., "bad," "horrible," "never
again," etc.). The media guidance may identify negative interest in
the service by identifying one or more of the words associated with
negative feedback. The media guidance application may maintain
statistics on the frequency of each of the keywords and words
associated with negative feedback. The media guidance application
may also determine the proximity of the keywords associated with
the first service and the words associated with negative feedback.
The media guidance application may determine whether the words
associated with negative feedback occur with a frequency greater
than a frequency threshold, or if the words associated with
negative feedback occur within a predetermined number of words of
the keywords associated with the first service. The media guidance
application may identify negative interest based on either
determination.
[0090] The media guidance application may also identify negative
interest in the first service by identifying a relative lack of
comments or feedback about a first service during a period of time.
For example, the media guidance application may search a user's
comments or posts for occurrences of keywords associated with the
first service (e.g., the name of the service, the type of service,
posts about the service, etc.) within a first time period. The
media guidance application may determine a first frequency of
occurrence of the keywords during the first period of time. The
media guidance application may then search a user's comments or
posts for keywords associated with the first service during a
second time period and calculate a corresponding frequency of
occurrence for the second time period. A second frequency which is
less than the first frequency indicates that the user is mentioning
the first service with decreasing frequency. As an illustrative
example, the user may comment feverishly about a new cable service
that they have just subscribed to, but gradually become less
enthralled with the service. This loss of interest may be indicated
by a decrease in the number of comments about the new service as
time moves on.
[0091] At step 608, the media guidance application may calculate
(e.g., via control circuitry 304 (FIG. 3)) a likelihood that the
user will change the first service based on the identified data
indicating a negative interest in the first service. The media
guidance application may calculate the likelihood based on a type
of the negative interest. For example, the media guidance
application may initialize the likelihood that the user will change
the first service to zero and increment the likelihood based on
identifying occurrences of words associated with negative feedback,
as discussed above in relation to step 606. Some types of negative
feedback may be more or less heavily weighted when calculating the
likelihood. For example, an overt statement, such as "I should
probably cancel HBO" may receive a heavier weighting and thus
increase the likelihood by a greater amount than a more subtle
statement, such as "HBO is boring." The media guidance application
may determine the severity of a negative statement by
cross-referencing keywords with a database of pre-determined words
and phrases. For example, as discussed above in relation with FIG.
5, historical outcomes database 524 may store the historical
actions and patterns of several users that result in the
termination of services for those users. The media guidance
application may compare the actions and/or statement of the user to
the historical data in historical outcomes database 524 to
determine that likelihood that the user's actions will result in a
change in the first service. In some embodiments, the likelihood
that the user will change the first service may be in relation to a
time period. For instance, the likelihood that the user will change
the first service may be provided as a percentage likelihood of
termination in the next six months.
[0092] FIG. 7 is a flowchart of another set of illustrative steps
for determining a likelihood that a user will change a service in
accordance with some embodiments of the disclosure. Process 700
includes initializing the likelihood that the user will change a
service to zero at step 702, receiving information from a
third-party data source corresponding to the user at step 704, and
identifying individuals connected to the user through a social
network maintained by the third-party data source at step 706. One
of the identified individuals is selected at step 708, and a
determination is made whether negative feedback or comments have
been received from the selected individual at step 710. If negative
feedback or comments have been received from the selected
individual, then the likelihood that the user will change the
service is increased at step 712 and the process 700 continues to
step 714. If negative feedback or comments have been received from
the selected individual, then the process 700 continues directly to
step 714. The process 700 further comprises determining a first
frequency of comments during a first period and a second frequency
of comments during a second period at step 714 and determining
whether the second frequency is less than the first frequency at
step 716. If the second frequency is less than the first frequency,
then the likelihood that the user will change the service is
increased at step 718. If the second frequency is not less than the
first frequency, then the process 700 continues directly to step
720. The process 700 further includes determining whether
unselected individuals remain, and if they do, then selecting
another user of the identified individuals connected to the user
through a social network maintained by the third-party data source
at step 708. The process 700 further includes determining whether
the likelihood that the user will change the service exceeds a
threshold at step 722. If the likelihood exceeds the threshold,
then at least one of an advertisement or an offer for a discount
for the service may be transmitted to the user at step 724. If the
likelihood does not exceed the threshold, then the process 700 ends
at step 726.
[0093] At step 702, the media guidance application may initialize
(e.g., via control circuitry 304 (FIG. 3)) a likelihood that the
user will change a service to zero, and at step 704, the media
guidance application may receive (e.g., via control circuitry 304
(FIG. 3)) information from a third-party data source corresponding
to the user. Step 704 may be substantially similar to step 604
discussed above in relation to FIG. 6. At step 706, the media
guidance application may identify (e.g., via control circuitry 304
(FIG. 3)) individuals connected to the user through a social
network maintained by the third-party data source. For instance,
the media guidance application may identify "friends" of the user
connected through the social network. The media guidance
application may identify individuals connected through the user
through any number of links (e.g., "friends of friends") or within
a pre-determined number of links. At step 708, the media guidance
application may select (e.g., via control circuitry 304 (FIG. 3))
either the user or one of the identified individuals connected to
the user through the social network. At step 710, the media
guidance application determines (e.g., via control circuitry 304
(FIG. 3)) whether negative feedback or comments have been received
from the selected individual. Step 710 may be substantially similar
to step 606 discussed above in relation to FIG. 6. For example, the
media guidance application may identify comments, posts, or
activity that indicate negative interest in the first service. The
media guidance application may also identify a relative lack of
comments or a decrease in the frequency of commenting about a first
service. If such negative feedback or comments is detected, then
the media guidance may increase the likelihood that the user will
change the service at step 712. If negative feedback is not
detected, then the media guidance application may determine a first
frequency of comments during a first period and a second frequency
of comments during a second period at step 714. The media guidance
application compares the second frequency to the first frequency at
step 716, and if the second frequency is less than the first
frequency, then the media guidance application increases the
likelihood that the user will change the service at step 718. If
the second frequency is not less than the first frequency, then the
media guidance application continues to step 720, where it
determines (e.g., via control circuitry 304 (FIG. 3)) whether
unselected individuals remain. If unselected individuals remain,
then the media guidance application selects another individual at
step 708.
[0094] If all individuals connected to the user have been analyzed,
then the media guidance application determines whether the
likelihood that the user will change the first service exceeds a
threshold at step 720 (e.g., via control circuitry 304 (FIG. 3)).
The threshold may be a pre-determined threshold set by a service
provider of the first service. If the likelihood that the user will
change the first service is greater than this threshold, then the
media guidance application may transmit (e.g., via control
circuitry 304 (FIG. 3) over communications network 414 (FIG. 4)) to
the user at least one of an advertisement or an offer for a
discount for the service. If the likelihood does not exceed the
threshold, then the process 700 ends at step 726.
[0095] FIG. 8 is a flowchart of illustrative steps for generating a
model to determine a likelihood that a user will change a service
in accordance with some embodiments of the disclosure. Process 800
includes identifying a service to which a plurality of users are
subscribed at step 802, receiving information from a third-party
data source for each of the plurality of users at step 804,
identifying, based on the information from the third-party data
source, a user action performed by each of the plurality of users
in relation to the service at step 806, identifying for at least
one of the plurality of users, based on the respective information
from the third-party data source, a request to change the first
service at step 808, and generating a model to determine a
likelihood that a user will change the first service based on the
identified user action and the identified request to change the
first service at step 810.
[0096] At step 802, a media guidance application may identify
(e.g., via control circuitry 304 (FIG. 3)) a service to which a
plurality of users are subscribed. The media guidance application
may identify the service in step 802 in substantially the same way
as in step 602 described above in relation to FIG. 6. At step 804,
the media guidance application may receive (e.g., via control
circuitry 304 (FIG. 3)) information from a third-party data source
for each of the plurality of users at step 804. The media guidance
application may receive the information from any suitable data
source for storing information corresponding to the plurality of
users. For example, the third-party data source may be a media
guidance data source, such as media guidance data source 418
depicted in FIG. 4, that stores user profiles. The third-party data
source may also be a social network data source that maintains a
social networking application for connecting users to one another
in the social network. The social network data source may provide
user profiles associated with the users, comments or posts that the
users have uploaded onto the social network, profiles associated
with individuals connected to the users via the social network,
comments or posts that those associated individuals have uploaded
onto the social network, or any other information associated with
the users.
[0097] At step 806, the media guidance application may identify
(e.g., via control circuitry 304 (FIG. 3)), based on the
information from the third-party data source, a user action
performed by each of the plurality of users in relation to the
service. For example, each of the plurality of users may have
posted a bad review of the service to their social media profile.
The user action may be any user action performed in relation to the
service, including, but not limited to, using the service,
providing feedback for the service, providing a comment about the
service, upgrading a service, or terminating a service. At step
808, the media guidance application may identify (e.g., via control
circuitry 304 (FIG. 3) for at least one of the plurality of users,
based on the respective information from the third-party data
source, a request to change the first service. The request to
change the first service may comprise any change regarding the
first service, including, but not limited to, subscribing to the
first service, upgrading the first service, downgrading the first
service, or terminating the first service. In this manner, the
media guidance application may identify a plurality of users, each
of which has performed a particular user action in relation to a
service, and wherein at least one of the plurality of users (but
perhaps not all) has requested a change to the service.
[0098] At step 808, the media guidance application may generate
(e.g., via control circuitry 304 (FIG. 3)) a model to determine a
likelihood that a user will change the first service based on the
identified user action and the identified request to change the
first service. The media guidance application may generate the
model by calculating the probability that the identified user
action is followed by a request to change the service. As an
illustrative example, suppose 100 users posted a bad review of HBO,
and of those 100 users, 50 of them terminated HBO within the next
three months. The media guidance application, based on this data,
may calculate that for a 101.sup.st user that posts a bad review of
HBO, the probability of that 101.sup.st user terminating HBO within
the next three months is 50%. In this manner, the media guidance
application may maintain statistics and a database of user actions
and historic subscription activity (e.g., new subscriptions,
upgrades, downgrades, terminations, etc.) and analyze the historic
subscription activity to determine correlations between user
actions and historic subscription activity.
[0099] FIG. 9 is a flowchart of another set of illustrative steps
for generating a model to determine a likelihood that a user will
change a service in accordance with some embodiments of the
disclosure. Process 900 includes receiving information from a
third-party data source for each of a plurality of users at step
902, identifying actions performed by each of the plurality of
users in relation to a service at step 904, determining a pattern
of action based on the identified actions at step 906, identifying
a request to change the service for at least one of the plurality
of users at step 908, and generating a model to determine a
likelihood that an action or a pattern of action is followed by a
request to change the service at step 910. The process 900 further
includes selecting one of the plurality of users at step 912,
comparing actions performed by a current user to the actions
performed by the selected user at step 914, based on the
comparison, calculating a correlation factor that indicates a
similarity between the current user and the selected user at step
916, and determining whether the correlation factor exceeds a
threshold at step 918. If the correlation factor exceeds the
threshold, then the process 900 includes using the model,
determining a likelihood that the user will request to change the
service at step 920 and transmitting the likelihood that the user
will request to change the service to a service provider at step
922. The process 900 further includes determining whether
unselected users remain, and if they do remain, selecting another
user of the plurality of users at step 926. If unselected users do
not remain, the process 900 ends at step 928.
[0100] At step 902, the media guidance application may receive
(e.g., via control circuitry 304 (FIG. 3)) information from a
third-party data source for each of a plurality of users. The step
902 may be substantially similar to the step 804 described above in
relation to FIG. 8. At step 904, the media guidance application may
identify actions performed by each of the plurality of users in
relation to a service. The media guidance application may identify
actions in step 904 in substantially the same manner as the
identification in step 806 described above in relation to FIG. 8.
At step 906, the media guidance application may determine (e.g.,
via control circuitry 304 (FIG. 3)) a pattern of action based on
the identified actions at step 906. The pattern of action may be
any group of two or more user actions that the plurality of users
have performed. The two or more user actions may be performed in
sequence or out of sequence. At step 908, the media guidance
application may identify (e.g., via control circuitry 304 (FIG. 3))
a request to change the service for at least one of the plurality
of users. The step 908 may be substantially similar to step 808
described above in relation to FIG. 8. As an illustrative example,
a several users may exhibit a pattern of posting a series of
negative comments about a service, then terminating the service.
The media guidance application, based on this data, may determine
that the series of negative comments constitutes a pattern of
action that leads to a higher probability of terminating the
service.
[0101] At step 910, the media guidance application may generate
(e.g., via control circuitry 304 (FIG. 3)) a model to determine a
likelihood that an action or a pattern of action is followed by a
request to change the service. The step 910 may be substantially
similar to the step 810 described above in relation to FIG. 8. In
steps 912-916, the media guidance application may analyze a new
user based on the data used to generate the model. The media
guidance application may compare the actions of the new user to the
actions of the plurality of users to determine a user of the
plurality of users that closely matches the new user. At step 912,
the media guidance application may select (e.g., via control
circuitry 304 (FIG. 3)) one of the plurality of users. At step 914,
the media guidance application may compare (e.g., via control
circuitry 304 (FIG. 3)) actions performed by a current user to the
actions performed by the selected user. For example, the historic
actions of the current user (i.e., new user, user being analyzed)
in relation to the service may be stored by historic billing data
memory 530. The historic billing data memory 530 and/or the
generated model may also store historic actions of the selected
user of the plurality of users. Both sets of actions may be
compared to determine any similar actions or pattern of actions. At
step 916, the media guidance application may, based on the
comparison, calculate (e.g., via control circuitry 304 (FIG. 3)) a
correlation factor that indicates a similarity between the current
user and the selected user. The correlation factor may be
calculated in any suitable manner to provide a normalized value
indicating the similarity between the current user and the selected
user of the plurality of users. For example, the correlation factor
may calculate a percentage of the number of total actions performed
that were common to both the current user and the selected user of
the plurality of users. The correlation factor may be calculated by
weighting different user actions differently. For example, a bad
review of the service may be weighted more heavily than a negative
comment of the service.
[0102] At step 918, the media guidance application may determine
(e.g., via control circuitry 304 (FIG. 3)) whether the correlation
factor exceeds a threshold. The threshold may be a pre-determine
threshold set by a service provider of the service. If the
correlation factor exceeds the threshold, then the process media
guidance application may determine (e.g., via control circuitry 304
(FIG. 3)) using the model, a likelihood that the user will request
to change the service. The media guidance may determine the
likelihood that the current user will request to change the service
based at least in part on whether the selected user of the
plurality of users changed the service and the correlation factor.
In some embodiments, the media guidance application determine
whether the selected user requested a change to the service, and if
the selected user did request a change to the service, then the
media guidance application may apply the correlation factor as the
likelihood that the current user will change the service. For
example, if a first user exhibits similar behavior (evidenced by
common actions or pattern of actions) as a second user, resulting
in a relatively high correlation factor, and the second user
terminated the service, then the first user has a relatively high
likelihood of also terminating the service. In some embodiments,
the media guidance application may combine the correlation factors
of the plurality of users, either as a weighted or unweighted
average, to compute the likelihood that the user will request to
change the service. At step 922, the media guidance application may
transmit (e.g., via control circuitry 304 (FIG. 3) through network
414 (FIG. 4)) the likelihood that the user will request to change
the service to a service provider. The service provider may user
this information to determine users at high-risk of terminating or
downgrading the service, and may respond by sending advertisements
or discount offers to the these users. At step 924, the media
guidance application may determine (e.g., via control circuitry 304
(FIG. 3)) whether unselected users remain. If unselected users
remain, then the media guidance application may select another user
of the plurality of users at step 926 and loop back to step 914. If
no unselected users remain, then the process 900 ends at step
928.
[0103] The above-described embodiments of the present disclosure
are presented for purposes of illustration and not of limitation,
and the present disclosure is limited only by the claims that
follow. Furthermore, it should be noted that the features and
limitations described in any one embodiment may be applied to any
other embodiment herein, and flowcharts or examples relating to one
embodiment may be combined with any other embodiment in a suitable
manner, done in different orders, or done in parallel. In addition,
the systems and methods described herein may be performed in real
time. It should also be noted that the systems and/or methods
described above may be applied to, or used in accordance with,
other systems and/or methods.
* * * * *
References