This application claims priority to U.S. patent application Ser. No. 11/557,939, filed Nov. 8, 2006, entitled “Behavioral Analysis Engine for Profiling Wireless Subscribers,” by James Barnes, et al., which is incorporated by reference in its entirety.
Mobile communication devices, such as cellular telephones, communicate through networks provided by a carrier. Through carrier networks, the mobile communications devices are able to obtain products in the form of content from various content providers. For example, users of cellular telephones can download audio clips (e.g., songs) to be played through the phone as a ringer. Other content can be similarly obtained, including games, software utilities, and images that serve as a background on the telephone's display. Various services can also be accessed, including text messaging, email services, news alerts, etc., and such services may also be viewed as products of the carrier.
Products, such as content or services described above, may be managed and marketed much like products traditionally marketed and sold in stores or on the internet. Maintaining an inventory of such products creates numerous issues including a need for efficient management of resources and marketing efforts to maximize the value.
Methods and systems are disclosed for carrier data based inventory management and marketing. An illustrative method is provided that includes receiving a product transaction record relating to a product from a carrier data source. The method also includes determining a present phase in a life cycle for the product based on a product history for the product and the product transaction record. The method further includes adjusting a product management plan for the product based on the present phase in the life cycle.
The present disclosure also describes a carrier system for carrier data based inventory management and marketing. The carrier system includes a plurality of data sources that provide product transaction records relating to a plurality of products, wherein each product data record is generated by a mobile device activity of a subscriber. The carrier system also includes a data store that stores a product history for each product of the plurality of products. The carrier system further includes a product life cycle management engine and a marketing engine. The product life cycle management engine determines a present phase in a life cycle for each product of the plurality of products based on the product history for each product and the product transaction record for each product. The marketing engine adjusts a product management plan for each product based on the present phase in the life cycle determined by the product life cycle management engine.
These and other features and advantages will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings and claims.
For a more complete understanding of the present disclosure and the advantages thereof, reference is now made to the following brief description, taken in connection with the accompanying drawings and detailed description, wherein like reference numerals represent like parts.
It should be understood at the outset that although an illustrative implementation of one embodiment of the present invention is illustrated below, the present system may be implemented using any number of techniques, whether currently known or in existence. The present disclosure should in no way be limited to the implementations, drawings, and techniques illustrated below, but may be modified as desired and as would be understood by one of ordinary skill in the art.
A carrier that provides network services to mobile communication devices is in a unique position to gather vast quantities of information pertaining to its subscribers, the devices used by the subscribers, and any products purchased with and used by such devices. Specifically, carriers have unique access to demographic and behavioral information pertaining to subscribers at a detailed level, providing insight into, for example, which products a subscriber purchases using her mobile communication device, how she uses the products, and even how often she uses the products.
The carrier based data product inventory management engine and marketing engine of the present disclosure focus on making use of vast amounts of information available about which products are purchased by whom and how they are used in order to improve inventory management and marketing for such products. By determining where a product is in its life cycle and by determining a category and segments in which a product is successfully being marketed, a product's management and marketing may be adjusted in order to extend and prolong the profitable phases in its life cycle, thereby maximizing return on investment. Adjustments may be made in the management and marketing of specific products successful with a particular demographic or segment, or may also be made with respect to the management and marketing of specific categories of products. Furthermore, with the vast quantity of information available to a carrier, a product's life cycle phase (and success) may be linked with particular segments, and prioritized or deprioritized over its life cycle marketing to such segments in customized presentations (i.e. online stores, etc.) For example, marketing of a product to a subscriber segment with whom the product has been historically successful could include reducing the marketing during a decline phase, or changing priority of marketing for the product earlier on in order to put off the decline phase.
Referring to
The life cycle 100 continues with the market introduction phase (block 104). During the market introduction phase (block 104), costs may be high with initial marketing strategies, and sales volume starts low. In the market introduction phase (block 104), there may be little to no competition, as competing enterprises watch for acceptance of the product and segment growth. Losses may be evident as the enterprise launches the new product in the market introduction phase (block 104).
The life cycle 100 continues with the growth phase (block 106). During the growth phase (block 106), the costs of producing and selling the product decrease due to economies of scale, and sales volume increases. The enterprise may begin to make profits. As the product grows in the market, public awareness of the product may increase due to marketing efforts, and competitors may begin to join the enterprise in the field of the product with competing products.
The life cycle 100 continues with the maturity phase (block 108). During the maturity phase (block 108), costs for marketing decrease as the product becomes well established in the market and the need for publicity is less. The sales volume for the product peaks. Offerings of competitive products increase, and therefore prices begin to drop. The maturity phase (block 108) is the most profitable phase of the life cycle 100.
The life cycle 100 concludes with the decline or stability phase (block 110) in which the product either stabilizes for the long term, or declines to the completion of its life. In the decline or stability phase (block 110), costs may become counter-optimal, and prices, and therefore profit, may drop off.
In each phase of the life cycle 100, marketing and management for a product may be optimized so as to minimize time spent with a product in the costly or low profit phases, and maximize and prolong the profitable phases. Different product types may have different typical lengths in, or aftermarket patterns of, such phases.
Referring to
The data sources 200 include data about how subscribers use their mobile devices, specifics about individual subscribers, and reference data. Specifically, the data service usage data source 201 includes data records pertaining to how subscribers use their mobile devices. The data service usage data source 201 may include records generated by activities undertaken by the subscriber either on the mobile device or in some cases the Internet. The activities may be, for example, content data usage 202 (e.g., the amount of network resources consumed in delivering content to a customer including time elapsed, KB of bandwidth used, etc.), mobile TV viewing 204 done on the mobile device, on demand 206 (e.g., a customized “newsreader” application with user-selected types and/or sources of news), text messaging 208, picture mail 210, video mail 212, music store usage 214 where electronic versions of music may be purchased, streaming audio 216 of music or talk shows, browsing the carrier's web page from a personal computer by logging in, push to talk 220, and/or WAP requests 222 from the mobile device.
Specifically, the data service and content purchases data source 240 includes data records pertaining to purchases made by subscribers from their mobile device. The data service and content purchases data source 240 may include records generated by purchases made by the subscriber either on the mobile device, or in some cases the Internet. The activities may be, for example, the purchase of applications 242, call tones 244, games 246, music files from a music store 248, ringers 250, screen savers 252, themes 254, and/or wallpapers 256, any of which may be used by the subscriber's mobile device.
Specifically, the reference data source 224 includes data records that are used to define associations and categories used in categorization by the behavioral engine as disclosed herein. For example, for the various types of premium content purchases, a catalog may list the items that may be purchased, an item identifier for each item, and the categories associated for each item. The reference data sources 224 may additionally define a hierarchy within the catalogs. For example, a ringer may be comprised of a song that is a fight song for a university team. In the catalog of ringers, that particular ringer may fall into a hierarchy where Music is the highest level, the next level is Theme Songs, and the next level is Sports Teams, and the lowest level is University Sports. At each level, a category may be associated with the ringer, such that when a subscriber purchases the ringer, the category for all of the levels, some of the levels, or just the lowest level may be associated with the subscriber's profile.
The reference data source 224 may include, for example, a premium services content catalog 226, a music store catalog 228, a call tone catalog 230, a themes catalog 232, a mobile TV channel and program data catalog 234, and a WAP domains & page definitions catalog 236. Each of the catalogs maps the items in the catalog to the same categories used when categorizing other types of behaviors, such as mobile web requests.
Specifically, the subscriber reference data source 258 includes data records that maintain carrier data pertaining to subscribers other than the behavioral data processed by the behavioral engine. The subscriber reference data source 258 includes data records such as basic account and subscriber information 260, subscriber plan details 262 (e.g. number of minutes per month, etc.), marketing profile 264 (e.g. subscriber provided demographics used for marketing), demographics 266 (i.e., an individual's traits), firmographics 268 (i.e., a company's traits such as size, industry focus, # of employees, location, etc.), and subscriber preferences 270.
Specifically, the subscriber profile data source 272 includes data records that define categories and rules for use by the behavioral engine as disclosed herein. The subscriber profile data source 272 may include behavioral categories 274 based on usage records, premium content categories 276, web keywords and categories 278 used for mobile web requests, category activation rules 280, and third party vendor profiles 282. Third party vendor profiles may consist of pre-mapped categories associated with premium content that is available from the third party vendor; such third party vendor profiles enable the categories of the present disclosure to be aligned with the categorization of items that has already been done by the third party vendors.
Referring to
The data store of rules for categorization and segmentation 302 is a repository that stores various categories into which specific products (services or content purchases) may be categorized. The data store of rules for categorization and segmentation 302 is also a repository that stores various segments to which products may be associated according to demographic or behavioral traits exhibited by users that purchase such products (i.e., by subscribing to a service or by purchasing premium content). For example, according to the rules a premium content ringtone that sounds a university fight song may be categorized as “sports” and a category for the particular university, and may be linked with the segment (demographically speaking) for college aged men that live near the university.
The segmentation engine 304 applies the rules from the data store of rules for categorization and segmentation 302 in order to process the vast amount of incoming raw data from the raw data sources 200, such that products are categorized according to the categories, and analyzed for whether to associate a given product with a segment of subscribers. By segmenting products according to the rules, the segments may, for example, be utilized for adjusting marketing of the products to successfully place the products to reach the subscribers in each segment. By categorizing products according to the same rules, marketing of similar products may, for example, be accomplished.
The data store of product history 306 is a repository that maintains a product history for each product in a product profile 308, including for example, when the product was introduced, sales since introduction, and segments of subscribers in which sales have been made. The product history provides the information about the product since its launch from the carrier's information, and the product profile 308 includes the information about a product since it's launch based on the various data sources once segmented and categorized by the segmentation engine 304. From the product profile 308, including the latest segmented and categorized data from the segmentation engine 304, it is possible to determine the present phase of the life cycle for a particular product. The product life cycle management engine 310 accesses the data store of product history 306 and determines, based on the most up-to-date categorized, segmented data along with the product's historical data, the present phase of the life cycle for a particular product. The present phase of the life cycle is added to the product profile 308, and may be updated as additional data for the product is delivered from the data sources 200. Additionally, the product life cycle management engine 310 may associate the present phase of the life cycle for a particular product with a particular market segment, as products may be in different phases for different market segments.
For example, the product life cycle management engine 310 may access the data store of product history 306 for Product A (ex. a downloadable song), and find that Product A was introduced 6 weeks ago, and has been selling wildly to the market of teenaged girls, which may be used to determine that Product A is in the Growth phase 106 of its life cycle. After six months, when Product A is featured in a blockbuster movie and sales increase dramatically across the market segments, the product life cycle management engine 310 may determine that Product A is in the Maturity phase 108 of its life cycle. After two years, when sales have dropped below a threshold of the peak in sales, the product life cycle management engine 310 may determine that Product A is in the decline phase 110 of its life cycle.
The marketing engine 314 uses the product profile 308, including the present phase of the life cycle, in order to adjust the management of inventory for the product and/or marketing of the product. Specifically, a product may be placed in a customized presentation (i.e., in a customized online store, or the like) based on a subscriber's identity, if the product is associated with one or more segments into which the subscriber falls, thereby targeting the product to subscribers that are more likely to purchase the product. Additionally, known marketing approaches may be taken to prolong certain phases of the life cycle, such as the growth, maturity, and stability phases, based on the known present phase for a product. Likewise, the inventory of a product may be decreased (such as no longer offering unpopular services, or archiving downloadable products that are seasonal or losing popularity), once the decline phase is indicated for the product. The marketing engine 314 makes such adjustments to inventory management and marketing based on various rules stored in data stores in the system. For example, the data store of rules for product placement 316 includes various business rules for product placement and managing levels of inventory based on the present phase of the life cycle for a given product. One example of a rule for product placement is that a product that is seasonal is advertised prominently and prominently placed in an online store or downloads page for a predetermined period of time before the appropriate holiday begins. Another rule for product placement is that levels of inventory may be automatically reduced when the product life cycle management engine 310 determines that a product is in the decline phase 110, or that the product is moved to archives instead of being advertised or placed prominently in a store or download area.
Another data store is the data store of rules for extending product life 318 that includes various business rules, based on traditional or newly conceived marketing techniques, to extend the profitable phases of a product's life cycle by effectively targeting subscribers based on interest in like products, or strategic placement of the product such that subscribers most likely to purchase the product will be exposed to the product. One example of a rule for extending product life is re-releasing the product as a special edition or otherwise changing the product's presentation (i.e., image, marketing, promotional materials, actual appearance), thereby renewing interest among subscribers. Another rule for extending product life is targeting the same product to a different segment, such as targeting a product previously popular among a certain age group in one region of the country to target a similar age group in another region of the country, based on similar other interests. The present disclosure may be applied as a test of inferred similarities in interests between market segments, such that a product expected to be successful in one segment expected to have similarities with another may be shifted in priority for the new segment, and if the shift is successful, further effort (i.e. prioritization) may be devoted to marketing the product in the new segment based on success in that segment as well as in the similar other segment. Yet another rule for extending product life is improving or modifying the product interface in such a way as to render the product more attractive to the current market segment or a new market segment.
The inventory delivery engine 320 is the feature of the system 300 whereby subscribers purchase the products. For example, the inventory delivery engine 320 may include a web site for downloading premium content such as applications, games, screen savers, ring tones, music, and more. The inventory delivery engine 320 may also include a web site for registering for premium services. Alternatively, the inventory delivery engine 320 may include a traditional store that sells the mobile communications devices for the carriers network, where a subscriber may purchase certain content or services along with the purchase of a mobile communications device. Alternatively, the inventory delivery engine 320 may include the mechanism to “push” product to the mobile communications device based on preferences of the subscriber or as part of a sales and advertising campaign. In such an embodiment, the subscriber is enabled to purchase the product pushed to his device by responding to the pushed communication.
Referring to
The data processed in blocks 404 and 406 as well as product history is used by the product life cycle management engine 310 to determine the present phase of the life cycle for each product (block 408). The present phase of the life cycle and the segmented, categorized data are added to a product profile 308 and stored (block 410). The marketing engine 314 applies rules for product placement and rules for extending product life to adjust marketing of each product based on the product's product profile (block 412). The method iterates to block 402 to readily improve the inventory management and marketing for products purchased through, used by, or used in conjunction with mobile communication devices.
Illustrative use cases further exhibit the practical advantages of the present disclosure. In one example, the product transaction records may be used in life cycle management of cross-linked products. Cross-linked products may refer to products that are related to one another by topic (e.g., mobile TV showing of a Saturday Night Live episode and a screen saver of the cast of Saturday Night Live), or related to each other by success within various market segments. The related products may be an explicit link or may be a mere inference of relation. By implementing the present disclosure, knowing the history and present life cycle phase of a first product may result in altering the marketing of a cross-linked product to test for whether a similar trend in life cycle applies, and to test of any inferred relationship between the products. If the trend for the life cycle of the first product does not prove to be true for the cross-linked product, based on feedback, the marketing may be dropped off, while if the trend for the life cycle of the first product is also true for the cross-linked product, the marketing efforts may be duplicated or increased for the cross-linked product. In various embodiments, such a test of the relationship and life cycles may be performed within a single market segment, for example.
In another example, knowledge of the life cycles of products, even as the life cycles vary from one segment to another (i.e. one product may be holding steady for a first segment while declining for a second segment), may be used to personalize the market place in which the products are sold. For example, various products may be purchased through a download site, and thus the appearance and marketing of the site may be tailored, either to the specific user or to specific market segments, based on the knowledge of the product life cycles.
The present disclosure may be implemented, at least partially, on a server or on any general-purpose computer(s) with sufficient processing power, memory resources, and network throughput capability to handle the necessary workload placed upon it.
The secondary storage 84 is typically comprised of one or more disk drives or tape drives and is used for non-volatile storage of data and as an over-flow data storage device if RAM 88 is not large enough to hold all working data. Secondary storage 84 may be used to store programs which are loaded into RAM 88 when such programs are selected for execution. The ROM 86 is used to store instructions and perhaps data which are reads during program execution. ROM 86 is a non-volatile memory device which typically has a small memory capacity relative to the larger memory capacity of secondary storage. The RAM 88 is used to store volatile data and perhaps to store instructions. Access to both ROM 86 and RAM 88 is typically faster than to secondary storage 84.
I/O 90 devices may include printers, video monitors, liquid crystal displays (LCDs), touch screen displays, keyboards, keypads, switches, dials, mice, track balls, voice recognizers, card readers, paper tape readers, or other well-known input devices. The network connectivity devices 92 may take the form of modems, modem banks, ethernet cards, universal serial bus (USB) interface cards, serial interfaces, token ring cards, fiber distributed data interface (FDDI) cards, wireless local area network (WLAN) cards, radio transceiver cards such as code division multiple access (CDMA) and/or global system for mobile communications (GSM) radio transceiver cards, and other well-known network devices. These network connectivity 92 devices may enable the processor 82 to communicate with an Internet or one or more intranets. With such a network connection, it is contemplated that the processor 82 might receive information from the network, or might output information to the network in the course of performing the above-described method steps. Such information, which is often represented as a sequence of instructions to be executed using processor 82, may be received from and outputted to the network, for example, in the form of a computer data signal embodied in a carrier wave.
Such information, which may include data or instructions to be executed using processor 82 for example, may be received from and outputted to the network, for example, in the form of a computer data baseband signal or signal embodied in a carrier wave. The baseband signal or signal embodied in the carrier wave generated by the network connectivity 92 devices may propagate in or on the surface of electrical conductors, in coaxial cables, in waveguides, in optical media, for example optical fiber, or in the air or free space. The information contained in the baseband signal or signal embedded in the carrier wave may be ordered according to different sequences, as may be desirable for either processing or generating the information or transmitting or receiving the information. The baseband signal or signal embedded in the carrier wave, or other types of signals currently used or hereafter developed, referred to herein as the transmission medium, may be generated according to several methods well known to one skilled in the art.
The processor 82 executes instructions, codes, computer programs, scripts which it accesses from hard disk, floppy disk, optical disk (these various disk based systems may all be considered secondary storage 84), ROM 86, RAM 88, or the network connectivity devices 92.
While several embodiments have been provided in the present disclosure, the disclosed systems and methods may be embodied in many other specific forms without departing from the spirit or scope of the present disclosure. The present examples are to be considered as illustrative and not restrictive, and the intention is not to be limited to the details given herein, but may be modified within the scope of the appended claims along with their full scope of equivalents. For example, the various elements or components may be combined or integrated in another system or certain features may be omitted, or not implemented.
Also, techniques, systems, subsystems and methods described and illustrated in the various embodiments as discrete or separate may be combined or integrated with other systems, modules, techniques, or methods without departing from the scope of the present disclosure. Other items shown or discussed as directly coupled or communicating with each other may be coupled through some interface or device, such that the items may no longer be considered directly coupled to each other but may still be indirectly coupled and in communication, whether electrically, mechanically, or otherwise with one another. Other examples of changes, substitutions, and alterations are ascertainable by one skilled in the art and could be made without departing from the spirit and scope disclosed herein.
Although the present invention and its advantages have been described in detail, various changes, substitutions and alterations may be made herein without departing from the spirit and scope of the invention as defined by the appended claims.
Number | Name | Date | Kind |
---|---|---|---|
5636346 | Saxe | Jun 1997 | A |
5761648 | Golden et al. | Jun 1998 | A |
5848396 | Gerace | Dec 1998 | A |
5848397 | Marsh et al. | Dec 1998 | A |
5918014 | Robinson | Jun 1999 | A |
5918041 | Berstis | Jun 1999 | A |
5933811 | Angles et al. | Aug 1999 | A |
5937392 | Alberts | Aug 1999 | A |
5974398 | Hanson et al. | Oct 1999 | A |
6202023 | Hancock et al. | Mar 2001 | B1 |
6233566 | Levine et al. | May 2001 | B1 |
6266649 | Linden et al. | Jul 2001 | B1 |
6286005 | Cannon | Sep 2001 | B1 |
6317722 | Jacobi et al. | Nov 2001 | B1 |
6321983 | Katayanagi et al. | Nov 2001 | B1 |
6332127 | Bandera et al. | Dec 2001 | B1 |
6826575 | Waclawski | Nov 2004 | B1 |
6834266 | Kumar et al. | Dec 2004 | B2 |
6839680 | Liu et al. | Jan 2005 | B1 |
6853982 | Smith et al. | Feb 2005 | B2 |
6910017 | Woo et al. | Jun 2005 | B1 |
6963867 | Ford et al. | Nov 2005 | B2 |
6966536 | Enomoto et al. | Nov 2005 | B2 |
6990462 | Wilcox et al. | Jan 2006 | B1 |
7022905 | Hinman et al. | Apr 2006 | B1 |
7065532 | Elder et al. | Jun 2006 | B2 |
7096194 | Johnson | Aug 2006 | B2 |
7127313 | Neri | Oct 2006 | B2 |
7143143 | Thompson | Nov 2006 | B1 |
7251615 | Woo | Jul 2007 | B2 |
7284033 | Jhanji | Oct 2007 | B2 |
7353267 | Cunningham et al. | Apr 2008 | B1 |
7406436 | Reisman | Jul 2008 | B1 |
7437308 | Kumar et al. | Oct 2008 | B2 |
7481367 | Fees et al. | Jan 2009 | B2 |
7647258 | William et al. | Jan 2010 | B2 |
7676394 | Ramer et al. | Mar 2010 | B2 |
7840498 | Frank et al. | Nov 2010 | B2 |
7958005 | Dangaltchev | Jun 2011 | B2 |
7974616 | Urbanek | Jul 2011 | B1 |
20010039500 | Johnson | Nov 2001 | A1 |
20010044743 | McKinley et al. | Nov 2001 | A1 |
20010047294 | Rothschild | Nov 2001 | A1 |
20020010627 | Lerat | Jan 2002 | A1 |
20020013727 | Lee | Jan 2002 | A1 |
20020026355 | Mitsuoka et al. | Feb 2002 | A1 |
20020026361 | Blom | Feb 2002 | A1 |
20020030100 | Katayanagi et al. | Mar 2002 | A1 |
20020032771 | Gledje | Mar 2002 | A1 |
20020035474 | Alpdemir | Mar 2002 | A1 |
20020059387 | Wolfe | May 2002 | A1 |
20020060246 | Gobburu et al. | May 2002 | A1 |
20020065713 | Awada et al. | May 2002 | A1 |
20020091569 | Kitaura et al. | Jul 2002 | A1 |
20020091571 | Thomas et al. | Jul 2002 | A1 |
20020095333 | Jokinen et al. | Jul 2002 | A1 |
20020107027 | O'Neil | Aug 2002 | A1 |
20020128904 | Carruthers et al. | Sep 2002 | A1 |
20020128908 | Levin et al. | Sep 2002 | A1 |
20020143630 | Steinman et al. | Oct 2002 | A1 |
20020152133 | King et al. | Oct 2002 | A1 |
20020184080 | Murad et al. | Dec 2002 | A1 |
20030004802 | Callegari | Jan 2003 | A1 |
20030004808 | Elhaoussine et al. | Jan 2003 | A1 |
20030018516 | Ayala et al. | Jan 2003 | A1 |
20030018558 | Heffner et al. | Jan 2003 | A1 |
20030028451 | Ananian | Feb 2003 | A1 |
20030050863 | Radwin | Mar 2003 | A1 |
20030074251 | Kumar et al. | Apr 2003 | A1 |
20030074259 | Slyman, Jr. et al. | Apr 2003 | A1 |
20030101024 | Adar et al. | May 2003 | A1 |
20030101449 | Bentolila et al. | May 2003 | A1 |
20030126250 | Jhanji | Jul 2003 | A1 |
20030171962 | Hirth et al. | Sep 2003 | A1 |
20030172007 | Helmolt et al. | Sep 2003 | A1 |
20030229502 | Woo | Dec 2003 | A1 |
20040019540 | William et al. | Jan 2004 | A1 |
20040019541 | William et al. | Jan 2004 | A1 |
20040111315 | Sharma et al. | Jun 2004 | A1 |
20050021403 | Ozer et al. | Jan 2005 | A1 |
20050028188 | Latona et al. | Feb 2005 | A1 |
20050101332 | Kotzin | May 2005 | A1 |
20050102272 | Kumar et al. | May 2005 | A1 |
20050114829 | Robin et al. | May 2005 | A1 |
20050177419 | Choi et al. | Aug 2005 | A1 |
20050194431 | Fees et al. | Sep 2005 | A1 |
20050197887 | Zuerl et al. | Sep 2005 | A1 |
20050197918 | Wittmer et al. | Sep 2005 | A1 |
20050215238 | Macaluso | Sep 2005 | A1 |
20050228754 | Pezzaniti et al. | Oct 2005 | A1 |
20050246394 | Neri | Nov 2005 | A1 |
20050256759 | Acharya et al. | Nov 2005 | A1 |
20050278296 | Bostwick | Dec 2005 | A1 |
20060080135 | Frank et al. | Apr 2006 | A1 |
20060080171 | Jardins et al. | Apr 2006 | A1 |
20060085253 | Mengerink et al. | Apr 2006 | A1 |
20060085517 | Kaurila | Apr 2006 | A1 |
20060224437 | Gupta et al. | Oct 2006 | A1 |
20070005647 | Cugi et al. | Jan 2007 | A1 |
20070026871 | Wager | Feb 2007 | A1 |
20070061229 | Ramer et al. | Mar 2007 | A1 |
20070100963 | Ban et al. | May 2007 | A1 |
20070106520 | Akkiraju et al. | May 2007 | A1 |
20070130005 | Jaschke | Jun 2007 | A1 |
20070192715 | Kataria et al. | Aug 2007 | A1 |
20070198339 | Shen et al. | Aug 2007 | A1 |
20070208619 | Branam et al. | Sep 2007 | A1 |
20070239518 | Chung et al. | Oct 2007 | A1 |
20080004884 | Flake et al. | Jan 2008 | A1 |
20080082412 | Tallyn et al. | Apr 2008 | A1 |
20080126515 | Chambers et al. | May 2008 | A1 |
20080147478 | Mall et al. | Jun 2008 | A1 |
20080228583 | MacDonald et al. | Sep 2008 | A1 |
20090222329 | Ramer et al. | Sep 2009 | A1 |
20110131109 | Pappas et al. | Jun 2011 | A1 |