Patent Application
20190236621
This disclosure relates generally to systems and methods for optimizing content variations including a plurality of content item options.
The optimization of content provided in communications such as email is increasingly important in retail environments, to engage persons receiving the communications with the end goal of eliciting a response. However, effective engagement of persons can depend on picking the content items such as subject lines and content modules that are most likely to be interesting and attractive to such persons. Because it can be difficult to assess in advance how responsive persons will be, such messages may be sent with a few different content variations, in the hopes that at least some of the content variations will be effective in eliciting a response. However, as some of the content variations may be less efficient in eliciting a response than others, such a process may not be optimal in obtaining responses from all persons receiving the communications.
To facilitate further description of the embodiments, the following drawings are provided in which:
For simplicity and clarity of illustration, the drawing figures illustrate the general manner of construction, and descriptions and details of well-known features and techniques may be omitted to avoid unnecessarily obscuring the present disclosure. Additionally, elements in the drawing figures are not necessarily drawn to scale. For example, the dimensions of some of the elements in the figures may be exaggerated relative to other elements to help improve understanding of embodiments of the present disclosure. The same reference numerals in different figures denote the same elements.
The terms “first,” “second,” “third,” “fourth,” and the like in the description and in the claims, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments described herein are, for example, capable of operation in sequences other than those illustrated or otherwise described herein. Furthermore, the terms “include,” and “have,” and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, device, or apparatus that comprises a list of elements is not necessarily limited to those elements, but may include other elements not expressly listed or inherent to such process, method, system, article, device, or apparatus.
The terms “left,” “right,” “front,” “back,” “top,” “bottom,” “over,” “under,” and the like in the description and in the claims, if any, are used for descriptive purposes and not necessarily for describing permanent relative positions. It is to be understood that the terms so used are interchangeable under appropriate circumstances such that the embodiments of the apparatus, methods, and/or articles of manufacture described herein are, for example, capable of operation in other orientations than those illustrated or otherwise described herein.
The terms “couple,” “coupled,” “couples,” “coupling,” and the like should be broadly understood and refer to connecting two or more elements mechanically and/or otherwise. Two or more electrical elements may be electrically coupled together, but not be mechanically or otherwise coupled together. Coupling may be for any length of time, e.g., permanent or semi-permanent or only for an instant. “Electrical coupling” and the like should be broadly understood and include electrical coupling of all types. The absence of the word “removably,” “removable,” and the like near the word “coupled,” and the like does not mean that the coupling, etc. in question is or is not removable.
As defined herein, two or more elements are “integral” if they are comprised of the same piece of material. As defined herein, two or more elements are “non-integral” if each is comprised of a different piece of material.
As defined herein, “real-time” can, in some embodiments, be defined with respect to operations carried out as soon as practically possible upon occurrence of a triggering event. A triggering event can include receipt of data necessary to execute a task or to otherwise process information. Because of delays inherent in transmission and/or in computing speeds, the term “real time” encompasses operations that occur in “near” real time or somewhat delayed from a triggering event. In a number of embodiments, “real time” can mean real time less a time delay for processing (e.g., determining) and/or transmitting data. The particular time delay can vary depending on the type and/or amount of the data, the processing speeds of the hardware, the transmission capability of the communication hardware, the transmission distance, etc. However, in many embodiments, the time delay can be less than approximately one second, two seconds, five seconds, or ten seconds.
As defined herein, “approximately” can, in some embodiments, mean within plus or minus ten percent of the stated value. In other embodiments, “approximately” can mean within plus or minus five percent of the stated value. In further embodiments, “approximately” can mean within plus or minus three percent of the stated value. In yet other embodiments, “approximately” can mean within plus or minus one percent of the stated value.
A number of embodiments can include a system. The system can include one or more processors, and one or more non-transitory computer-readable media storing computing instructions configured to run on the one or more processors. The one or more non-transitory computer-readable media can be configured to run on the one or more processors and perform acts of creating content variations for including in initial communications to initial targets, the content variations each comprising one or more content items selected from content item options, setting weightings for the content item options included in the content variations, the weightings corresponding to first relative fractions of the initial communications in which each of the content item options are included in a content variation; transmitting the initial communications comprising the content variations to the initial targets, with the first relative fractions of the initial communications in which each of the content item options are included in a content variation of the content variations being set according to the weightings for each of the content item options, receiving initial response information in relation to initial responses of the initial targets to the initial communications, determining, in relation to the initial response information, whether a minimum level of statistically significant difference is achieved between responses to a first portion of the initial communications having a first one of the content variations with a first one of the content item options as compared to a second portion of the initial communications having a second one of the content variations with a second one of the content item options, when the minimum level of statistically significant difference is achieved, determining updated weightings of the first and second ones of the content item options in relation to the initial response information, for a portion of the initial response information received in a first predetermined period of time, and transmitting updated communications comprising the content variations to subsequent targets, with second relative fractions of the updated communications in which the first and second ones of the content item options are included in a content variation being set according to the updated weightings for each of the first and second content item options.
Various embodiments include a method. The method can be implemented via execution of computing instructions configured to run at one or more processors and configured to be stored at non-transitory computer-readable media. The method can include creating content variations for including in communications to targets, the content variations each comprising one or more content items selected from content item options. The method can also include setting weightings for the content item options included in the content variations, the weightings corresponding to relative fractions of the communications in which each of the content item options are included in a content variation. The method can also include transmitting initial communications comprising the content variations to the targets, with the relative fractions of the communications in which each of the content item options are included in a content variation being set according to the weightings for each of the content item options. The method can also include receiving response information in relation to responses of the targets to the initial communications. The method can also include determining, in relation to the response information, whether a minimum level of statistically significant difference is achieved between responses to initial communications having a first content variation having a first content item option as compared to initial communications having a second content variation having a second content item option. The method can also include, if the minimum level of statistically significant difference is achieved, determining updated weightings of the first and second content items options in relation to the response information, for response information received in a predetermined period of time. The method can also include transmitting updated communications comprising the content variations to subsequent targets, with the relative fractions of the updated communications in which the first and second content item options are included in a content variation being set according to the updated weightings for each of the first and second content item options.
Various embodiments include a method. The method can be implemented via execution of computing instructions configured to run at one or more processors and configured to be stored at non-transitory computer-readable media. The method can include creating content variations for including in communications to targets in response to a trigger event, the content variations each comprising one or more content items selected from content item options. The method can also include setting weightings for the content item options included in the content variations, the weightings corresponding to relative fractions of the communications in which each of the content item options are included in a content variation. The method can also include receiving response information in relation to responses by the targets to communications transmitted to the targets in response to the trigger event, the communications comprising the content variations, with the relative fractions of the communications in which each of the content item options are included in a content variation being set according to the weightings for each of the content item options. The method can also include determining, in relation to the response information, whether a minimum level of statistically significant difference is achieved between responses to communications having a first content variation having a first content item option as compared to communications having a second content variation having a second content item option. The method can also include, if the minimum level of statistically significant difference is achieved, determining updated weightings of the first and second content items options in relation to the response information, for response information received in a predetermined period of time.
Email communications have been an increasingly important and effective marketing channel for communicating with current and potential customers of retailers. To efficiently engage customers using email campaigns, it can be important for marketing engineers to pick the best variations in content items including the email subject line and content modules.
Email campaigns can be roughly divided into at least two types: one-time batch campaigns and recurring trigger campaigns. For batch campaigns, emails are sent at a specific time to a specific set of customers only once. Batch campaigns are usually associated with a large size of recipients. The process of sending all the batch emails in the sending application often takes several hours. According to one embodiment, the relatively long time span of the sending process can offer opportunities for optimizing subject line and content modules in real time. That is, in certain embodiments, a given initial batch of emails can be sent evenly across different variations (e.g., subject line and/or content module). According to certain aspects, as response data is collected (e.g., open, click, etc.) in real time, the feedback data can be evaluated to influence the allocation of email variations sent out later.
Compared to batch campaigns, the scheduling of recurring trigger campaigns can be more complicated. In certain embodiments, trigger campaigns are scheduled once or multiple times daily, based on trigger events such as abandoning a shopping cart, a price drop of an item, expiration of a time window post-browsing, etc. Due to the relative sparsity of trigger events, each batch of trigger campaign emails is typically relatively small and does not take much time to send, as compared to a batch campaign. The total number of trigger emails sent typically depends on the number of trigger events, and thus typically is not predefined. Furthermore, within one send period, the difference in response data can be disproportionately affected by random noise, rather than reflecting any true underlying difference among the variations in terms of response. As a result, in certain embodiments, the same real-time subject line and content module optimization approach for batch email campaigns is not directly applicable to recurring trigger campaigns.
According to one embodiment, a near real-time robust optimization (RO) approach can be provided for optimizing content items such as subject lines and content modules in recurring trigger email campaigns. According to certain embodiments, the RO approach leverages statistical hypothesis testing over accumulated response data from multiple batches. According to certain aspects, although each batch of sends for trigger campaigns is small, a nice feature of trigger campaign is that it is recurring and may be running for several months. Accordingly, in certain embodiments, the RO approach can start from an even distribution of email variations, and as response data is collected for the same type of triggers across several days, statistical hypothesis testing can be run to see if the difference in responses across different variations is statistically significant. If the difference is significant, then according to certain aspects the accumulated response data generated up to that point is used to optimize the allocation of email variations for the next small batch. Furthermore, in some embodiments, to ensure that the response data is up to date, a sliding time window is used for collecting response data. Even further, according to certain embodiments, whenever there are changes in the content such as the subject line or content modules, the entire optimization process is re-initialized. Finally, the accumulated impact across multiple days can be used to report response lift against the evenly distribution baseline to ensure performance stability.
According to one embodiment, compared to the baseline scenario of distributing all email variations evenly, this near real-time robust optimization approach is capable of converging to the best email variation and can lead to 10% to 20% response lift. Because it is automatically adaptive to any changes in content such as subject line and content modules, it significantly reduces time and effort for marketing engineers to perform AB testing to find the best email variation.
Details of methodology and implementation of this approach, according to certain embodiments, is discussed below.
According to one embodiment, the following robust optimization problem is formulated to generate the optimal allocation of traffic across p email variations of a recurring trigger campaign.
Let r be the reward vector (e.g., click rate or open rate) to represent the metrics with the objective function E[rewards]=rjNj+ . . . +rpNp. The decision variables vector wi represents the ratio of email sends that is allocated for variation i, i.e., wi=Ni/Σi=1pNi.
The optimization formulation according to one embodiment is as follows:
where U={r|∥r−
p>0 is a scalar describing the size of perturbation;
Ni is the number of emails sent with variation i and weight wi;
Σi=1pNi is the total number of emails sent; and
p is the total number of variations.
According to one embodiment, at a given time t, the metrics r are obtained, and the optimal solution w* to the above robust optimization problem is obtained. The weights can be updated as new metrics come in.
To decide when to let the optimization kick in, according to certain embodiments, statistical hypothesis testing can be used to compare the metrics. For example, taking rates of opening email messages as an example, it can be assumed among all the variations that the highest and lowest open rates have O1, O2 opens and N1, N2 sends, respectively. A two-sample proportion test can be used to compare the difference with a test statistic:
According to one embodiment, the updating of the weights starts only after a statistically significant difference is found between the variations. In certain embodiments, to overcome the day-of-week bias, a rolling 7-day window is used to calculate the metrics.
Further aspects of embodiments of the implementation are described. In one embodiment, an example of a recurring trigger email campaign can have 3 candidate subject lines (denoted as s1, s2, s3 in the following description) and 2 email content modules (denoted as m1, m2). In this example, the campaign has been scheduled daily and will run for several months. In the process of this campaign, customers' response data is collected, and testing traffic is robustly allocated to winners.
In this example, the number of email sends for different subject lines and content module combinations are evenly distributed, and customers' open/click data is collected for optimization. For example, ⅓ is assigned as the weight to s1, s2, s3 individually, and ½ is assigned as the weight for m1, m2. Accordingly, in total there are 3*2 combinations of subject lines and content modules (s1m1, s2m1, s3m1, s1m2, s2m2, s3m2), and each of them will have ⅙ of the total number of sends.
An exemplary flow chart illustrating steps according to an embodiment is shown in
According to one embodiment, because the campaign will last for a range of days and optimization is run based on the accumulated sliding window's data, click lift calculation of only one day is not appropriate for our optimization performance. Furthermore, in certain embodiments, after the campaign is optimized, some variations might have only a very small number of sends, such as several hundreds or even less than 100. However, the total number of sends for the entire campaign on a current date, or for several days, might be several hundred thousand. The click rate based on such a small number of sends might not be representative, and thus, the click rate based on only the current batch for current date is not enough in some embodiments. Accordingly, in one embodiment, the accumulated data from the sliding window prior to the current date is reported.
According to one embodiment, the average click rate of the accumulated 7-day sliding window is calculated for each variation, and compared with the total average click rate. Then, the click lift for each variation can be calculated, along with the click lift of the total campaign.
Further discussion of aspects of the model, as well as embodiments of systems and methods that can incorporate the model or at least a portion thereof, are described below.
Turning to the drawings,
Continuing with
In various examples, portions of the memory storage module(s) of the various embodiments disclosed herein (e.g., portions of the non-volatile memory storage module(s)) can be encoded with a boot code sequence suitable for restoring computer system 100 (
As used herein, “processor” and/or “processing module” means any type of computational circuit, such as but not limited to a microprocessor, a microcontroller, a controller, a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a graphics processor, a digital signal processor, or any other type of processor or processing circuit capable of performing the desired functions. In some examples, the one or more processing modules of the various embodiments disclosed herein can comprise CPU 210.
Alternatively, or in addition to, the systems and procedures described herein can be implemented in hardware, or a combination of hardware, software, and/or firmware. For example, one or more application specific integrated circuits (ASICs) can be programmed to carry out one or more of the systems and procedures described herein. For example, one or more of the programs and/or executable program components described herein can be implemented in one or more ASICs. In many embodiments, an application specific integrated circuit (ASIC) can comprise one or more processors or microprocessors and/or memory blocks or memory storage.
In the depicted embodiment of
Network adapter 220 can be suitable to connect computer system 100 (
Returning now to
Meanwhile, when computer system 100 is running, program instructions (e.g., computer instructions) stored on one or more of the memory storage module(s) of the various embodiments disclosed herein can be executed by CPU 210 (
Further, although computer system 100 is illustrated as a desktop computer in
Turning ahead in the drawings,
Generally, therefore, system 300 can be implemented with hardware and/or software, as described herein. In some embodiments, part or all of the hardware and/or software can be conventional, while in these or other embodiments, part or all of the hardware and/or software can be customized (e.g., optimized) for implementing part or all of the functionality of system 300 described herein.
In some embodiments, system 300 can include a communications control system 310, a web server 320 (or front end server), a display system 360, a content variation optimization system 370, a content variation creation system 390, and/or communications database 380. Communications control system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 can each be a computer system, such as computer system 100 (
In many embodiments, system 300 also can comprise user computers 340, 341. User computers 340, 341 can comprise any of the elements described in relation to computer system 100. In some embodiments, user computers 340, 341 can be mobile devices. A mobile electronic device can refer to a portable electronic device (e.g., an electronic device easily conveyable by hand by a person of average size) with the capability to present audio and/or visual data (e.g., text, images, videos, music, etc.). For example, a mobile electronic device can comprise at least one of a digital media player, a cellular telephone (e.g., a smartphone), a personal digital assistant, a handheld digital computer device (e.g., a tablet personal computer device), a laptop computer device (e.g., a notebook computer device, a netbook computer device), a wearable user computer device, or another portable computer device with the capability to present audio and/or visual data (e.g., images, videos, music, etc.). Thus, in many examples, a mobile electronic device can comprise a volume and/or weight sufficiently small as to permit the mobile electronic device to be easily conveyable by hand. For examples, in some embodiments, a mobile electronic device can occupy a volume of less than or equal to approximately 1790 cubic centimeters, 2434 cubic centimeters, 2876 cubic centimeters, 4056 cubic centimeters, and/or 5752 cubic centimeters. Further, in these embodiments, a mobile electronic device can weigh less than or equal to 15.6 Newtons, 17.8 Newtons, 22.3 Newtons, 31.2 Newtons, and/or 44.5 Newtons.
Exemplary mobile electronic devices can comprise (i) an iPod®, iPhone®, iTouch®, iPad®, MacBook® or similar product by Apple Inc. of Cupertino, Calif., United States of America, (ii) a Blackberry® or similar product by Research in Motion (RIM) of Waterloo, Ontario, Canada, (iii) a Lumia® or similar product by the Nokia Corporation of Keilaniemi, Espoo, Finland, and/or (iv) a Galaxy™ or similar product by the Samsung Group of Samsung Town, Seoul, South Korea. Further, in the same or different embodiments, a mobile electronic device can comprise an electronic device configured to implement one or more of (i) the iPhone® operating system by Apple Inc. of Cupertino, Calif., United States of America, (ii) the Blackberry® operating system by Research In Motion (RIM) of Waterloo, Ontario, Canada, (iii) the Palm® operating system by Palm, Inc. of Sunnyvale, Calif., United States, (iv) the Android™ operating system developed by the Open Handset Alliance, (v) the Windows Mobile™ operating system by Microsoft Corp. of Redmond, Wash., United States of America, or (vi) the Symbian™ operating system by Nokia Corp. of Keilaniemi, Espoo, Finland.
Further still, the term “wearable user computer device” as used herein can refer to an electronic device with the capability to present audio and/or visual data (e.g., text, images, videos, music, etc.) that is configured to be worn by a user and/or mountable (e.g., fixed) on the user of the wearable user computer device (e.g., sometimes under or over clothing; and/or sometimes integrated with and/or as clothing and/or another accessory, such as, for example, a hat, eyeglasses, a wrist watch, shoes, etc.). In many examples, a wearable user computer device can comprise a mobile electronic device, and vice versa. However, a wearable user computer device does not necessarily comprise a mobile electronic device, and vice versa.
In specific examples, a wearable user computer device can comprise a head mountable wearable user computer device (e.g., one or more head mountable displays, one or more eyeglasses, one or more contact lenses, one or more retinal displays, etc.) or a limb mountable wearable user computer device (e.g., a smart watch). In these examples, a head mountable wearable user computer device can be mountable in close proximity to one or both eyes of a user of the head mountable wearable user computer device and/or vectored in alignment with a field of view of the user.
In more specific examples, a head mountable wearable user computer device can comprise (i) Google Glass™ product or a similar product by Google Inc. of Menlo Park, Calif., United States of America; (ii) the Eye Tap™ product, the Laser Eye Tap™ product, or a similar product by ePI Lab of Toronto, Ontario, Canada, and/or (iii) the Raptyr™ product, the STAR 1200™ product, the Vuzix Smart Glasses M100™ product, or a similar product by Vuzix Corporation of Rochester, N.Y., United States of America. In other specific examples, a head mountable wearable user computer device can comprise the Virtual Retinal Display™ product, or similar product by the University of Washington of Seattle, Wash., United States of America. Meanwhile, in further specific examples, a limb mountable wearable user computer device can comprise the iWatch™ product, or similar product by Apple Inc. of Cupertino, Calif., United States of America, the Galaxy Gear or similar product of Samsung Group of Samsung Town, Seoul, South Korea, the Moto 360 product or similar product of Motorola of Schaumburg, Ill., United States of America, and/or the Zip™ product, One™ product, Flex™ product, Charge™ product, Surge™ product, or similar product by Fitbit Inc. of San Francisco, Calif., United States of America.
In some embodiments, web server 320 can be in data communication through Internet 330 with user computers (e.g., 340, 341). In certain embodiments, user computers 340-341 can be desktop computers, laptop computers, smart phones, tablet devices, and/or other endpoint devices. Web server 320 can host one or more websites and/or can provide services as an email server. For example, web server 320 can host a website that allows users to browse and/or search for products, to add products to an electronic shopping cart, and/or to purchase products, in addition to other suitable activities. Web server also can serve as an email server to send and receive email messages via the internet 330 to user computers (e.g., 340, 341).
In many embodiments, communication control system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 can each comprise one or more input devices (e.g., one or more keyboards, one or more keypads, one or more pointing devices such as a computer mouse or computer mice, one or more touchscreen displays, a microphone, etc.), and/or can each comprise one or more display devices (e.g., one or more monitors, one or more touch screen displays, projectors, etc.). In these or other embodiments, one or more of the input device(s) can be similar or identical to keyboard 104 (
In many embodiments, communications system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 can be configured to communicate with one or more user computers 340 and 341. In some embodiments, user computers 340 and 341 also can be referred to as customer computers and/or target computers. In some embodiments, communications system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 can communicate or interface (e.g., interact) with one or more customer computers and/or target computers (such as user computers 340 and 341) through a network or internet 330. Internet 330 can be an intranet that is not open to the public. Accordingly, in many embodiments, communications system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 (and/or the software used by such systems) can refer to a back end of system 300 operated by an operator and/or administrator of system 300, and user computers 340 and 341 (and/or the software used by such systems) can refer to a front end of system 300 used by one or more users 350 and 351, respectively. In some embodiments, users 350 and 351 also can be referred to as customers, viewers and/or targets, in which case, user computers 340 and 341 can be referred to as customer computers, viewer computers, and/or target computers. In these or other embodiments, the operator and/or administrator of system 300 can manage system 300, the processing module(s) of system 300, and/or the memory storage module(s) of system 300 using the input device(s) and/or display device(s) of system 300.
Meanwhile, in many embodiments, communications system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 also can be configured to communicate with one or more databases or electronic file management systems. The one or more databases can comprise a product database that contains information about products, items, or SKUs (stock keeping units) sold by a retailer. The one or more databases can be stored on one or more memory storage modules (e.g., non-transitory memory storage module(s)), which can be similar or identical to the one or more memory storage module(s) (e.g., non-transitory memory storage module(s)) described above with respect to computer system 100 (
The one or more databases or electronic file management systems can each comprise a structured (e.g., indexed) collection of data and can be managed by any suitable database management systems configured to define, create, query, organize, update, and manage database(s). Exemplary database management systems can include MySQL (Structured Query Language) Database, PostgreSQL Database, Microsoft SQL Server Database, Oracle Database, SAP (Systems, Applications, & Products) Database, and IBM DB2 Database.
Meanwhile, communication between communications control system 310, web server 320, display system 360, content variation optimization system 370, content variation creation system 390, and/or communications database 380 and/or the one or more databases or electronic file management systems can be implemented using any suitable manner of wired and/or wireless communication. Accordingly, system 300 can comprise any software and/or hardware components configured to implement the wired and/or wireless communication. Further, the wired and/or wireless communication can be implemented using any one or any combination of wired and/or wireless communication network topologies (e.g., ring, line, tree, bus, mesh, star, daisy chain, hybrid, etc.) and/or protocols (e.g., personal area network (PAN) protocol(s), local area network (LAN) protocol(s), wide area network (WAN) protocol(s), cellular network protocol(s), powerline network protocol(s), etc.). Exemplary PAN protocol(s) can comprise Bluetooth, Zigbee, Wireless Universal Serial Bus (USB), Z-Wave, etc.; exemplary LAN and/or WAN protocol(s) can comprise Institute of Electrical and Electronic Engineers (IEEE) 802.3 (also known as Ethernet), IEEE 802.11 (also known as WiFi), etc.; and exemplary wireless cellular network protocol(s) can comprise Global System for Mobile Communications (GSM), General Packet Radio Service (GPRS), Code Division Multiple Access (CDMA), Evolution-Data Optimized (EV-DO), Enhanced Data Rates for GSM Evolution (EDGE), Universal Mobile Telecommunications System (UMTS), Digital Enhanced Cordless Telecommunications (DECT), Digital AMPS (IS-136/Time Division Multiple Access (TDMA)), Integrated Digital Enhanced Network (iDEN), Evolved High-Speed Packet Access (HSPA+), Long-Term Evolution (LTE), WiMAX, etc. The specific communication software and/or hardware implemented can depend on the network topologies and/or protocols implemented, and vice versa. In many embodiments, exemplary communication hardware can comprise wired communication hardware including, for example, one or more data buses, such as, for example, universal serial bus(es), one or more networking cables, such as, for example, coaxial cable(s), optical fiber cable(s), and/or twisted pair cable(s), any other suitable data cable, etc. Further exemplary communication hardware can comprise wireless communication hardware including, for example, one or more radio transceivers, one or more infrared transceivers, etc. Additional exemplary communication hardware can comprise one or more networking components (e.g., modulator-demodulator components, gateway components, etc.).
Turning ahead in the drawings,
In many embodiments, method 400 can comprise an activity 405 of creating content variations for including in initial communications to initial targets, where the content variations each comprise one or more content items selected from content item options. In some embodiments, activity 405 can comprise creating, at a first processor, such as but not limited to the content variation creation system 390 (
The targets can correspond to users 350, 351 (
In one embodiment, the activity 405 comprises creating the content variations for including in the initial communications to the initial targets, by creating content variations that each comprise content categories, where each content category of the content categories comprises the one or more content items that can be selected from the content item options for each respective category of the content categories, and where the content item options comprise one or more first category item options for a first category of the content categories, and one of more second category item options for a second category of the content categories. That is, according to one embodiment, the content variation creation system 390 (
In one embodiment, the content categories in the content variations include one or more different fields of the communications to the targets, such subjects fields for subjects of the communications, and body fields for bodies of the communications, and where the content item options include subject item options for the subjects of the communications and body module item options for the bodies of the communications. That is, in some embodiments, the communications database 380 (
In many embodiments, method 400 can comprise an activity 410 of setting weightings for the content item options included in the content variations, the weightings corresponding to first relative fractions of the initial communications in which each of the content item options are included in a content variation. That is, in some embodiments, activity 410 can comprise, at a first processor, such as but not limited to the content variation creation system 390 (
In several embodiments, method 400 can comprise an activity 415 of transmitting the initial communications comprising the content variations to the initial targets, with the first relative fractions of the initial communications in which each of the content item options are included in a content variation of the content variations being set according to the weightings for each of the content item options. That is, according to one embodiment, the activity 415 can comprise receiving, at a first processor, such as but not limited to the communications control system 310 (
In certain embodiments, the activity 415 comprises controlling the fraction of communications that contain each content variation in relation to the weightings set for each content item option, such as via the communications control system 310 (
In several embodiments, method 400 can comprise an activity 420 of receiving initial response information in relation to initial responses of the initial targets to the initial communications. That is, according to one embodiment, the activity 420 can comprise receiving, at a first processor, such as but not limited to the web server 320, the initial response information corresponding to the initial target responses. In certain embodiments, activity 420 can comprise receiving the initial response information in relation to one or more of a rate at which the initial targets have opened and/or viewed the initial communications, and a rate at which the initial targets execute actions in response to receiving the initial communications. For example, the response information can include information that indicates, for each content variation, how many communications sent with the content variation were opened and/or viewed by the targets. The response information can also include information that indicates, for example, for each content variation, how many communications elicited a response from their targets such as opening a link included in the communication, visiting an online site referred to in the communication, target inquiries regarding information in the communication, etc.
In various embodiments, method 400 can comprise an activity 425 of determining, in relation to the initial response information, whether a minimum level of statistically significant difference is achieved between responses to a first portion of the initial communications having a first one of the content variations with a first one of the content item options as compared to a second portion of the initial communications having a second one of the content variations with a second one of the content item options. That is, the activity 425 can comprise determining whether a statistically significant difference is achieved between different content variations having different content item options, for the initial communications. According to one embodiment, the activity 425 can comprise receiving at a first processor, such as but not limited to the content variation optimization system 370 (
In certain embodiments, the activity 425 comprises determining, in relation to the initial response information, whether the minimum level of statistically significant difference is achieved between responses to the first portion of the initial communications having the first one of the content variations with the first one of the content item options as compared to the second portion of the initial communications having the second one of the content variations with the second one of the content item options, by determining a statistical difference according to a two-sample proportion test:
N2 represents a number of the initial communications sent to the initial targets having the second one of the content variations with the second one of the content item options,
and after determining the statistical difference, comparing Z to a baseline level to determine whether the minimum level is achieved.
Furthermore, in certain embodiments, when the minimum level of statistically significant difference is determined by performing activity 425 to not have been achieved, then method 400 returns to activity 420, which is continued to be performed for continuing to receive the initial response information in relation to the initial responses of the initial targets to the initial communications, until it is determined by performing activity 425 that the minimum level of statistically significant difference is achieved.
In several embodiments, when the minimum level of statistically significant difference is achieved as determined by activity 425, the method 400 can comprise the activity 430 of determining updated weightings of the first and second ones of the content item options in relation to the initial response information, for a portion of the initial response information received in a first predetermined period of time. According to one embodiment, the activity 430 can comprise at a first processor, such as but not limited to the content variation optimization system 370 (
According to some embodiments, the activity 430 comprises determining the updated weightings of the first and second ones of the content item options in relation to the initial response information, for the portion of the initial response information received in the first predetermined period of time, where determining the updated weightings can be accomplished by obtaining a solution w* to an optimization formula:
In several embodiments, the method 400 can comprise the activity 435 of transmitting updated communications comprising the content variations to subsequent targets, with second relative fractions of the updated communications in which the first and second ones of the content item options are included in a content variation being set according to the updated weightings for each of the first and second content item options. That is, in certain embodiments, the updated weightings determined in activity 430 can be used to set the relative fractions of content item options in subsequently sent communications, such that content options that elicited increased response rates can be emphasized over content item options that did not elicit as strong a response. For example, for content item options having an increased response, the number of communications sent with content variations including the content item options, can make up a larger fraction of the total number of communications sent as compared to the number of communications sent with content variations including content item options that exhibited a lesser response. Accordingly, in certain aspects, the updated communications are optimized as compared to the initial communications, in that the content being provided in the messages is weighted towards that content that elicited an increased response. According to one embodiment, the activity 430 can comprise receiving, at a first processor, such as but not limited to the communications control system 310 (
In yet another embodiment, the method 400 can further comprise performing activities of receiving subsequent response information in relation to subsequent responses of the subsequent targets to the updated communications, determining updated weightings of the first and second ones of the content item options in relation to the subsequent response information received from the subsequent targets to the updated communications, for a portion of the subsequent response information received in a second predetermined period of time, and transmitting further updated communications according to the updated weightings to further targets. In one embodiment, the further targets comprise one or more of the updated targets and initial targets, such as all of the updated and initial targets. In yet another embodiment, the further targets comprise targets other than the updated and initial targets. That is, the targets for the further updated communications can be the same as the original targets and/or updated targets, and/or can comprise different targets than those receiving the initial communications and/or the first updated communications. According to one embodiment, the receiving of the subsequent response information, determining the updated weightings, and transmitting the further updated communications can correspond to repeating the activities 420, 430, and 435, using the subsequent response information instead of the initial response information for 420 and 430, and transmitting the further updated communications in 435 using the updated weighting as determined using this subsequent response information.
In yet another embodiment, the method 400 can further comprise performing activities of changing one or more of the content item options to an updated content item option, in response to the updated weightings, and in response to changing to the updated content item option, setting further updated weightings for the content item options, transmitting further communications comprising the content variations including the updated content item option to further targets, receiving further response information in relation to further responses of the further targets to the further communications, determining whether the minimum level of statistically significant difference is achieved for the further responses to the further communications, when the minimum level of statistically significant difference is achieved for the further responses to the further communications, determining additionally updated weightings for the one or more content items comprising the updated content item option, and transmitting additional communications comprising the content variations including the updated content item to additional targets, wherein the additional communications are based at least in part on the additionally updated weightings for the one or more content items. That is, in certain embodiments, the weightings determined for the content items can indicate that a particle one of the content item options is performing poorly compared to others. In such a situation, in certain embodiment, a decision can be made to manually or otherwise replace the content item option with a new content item option that has not yet been transmitted as a part of a content variation (or has been transmitted as a different category in a content variation). That is, the method 400 can comprise performing activity 405, but where the content variations are being created with at least one updated content item, for sending in further communications to further targets. In one embodiment, the further targets comprise one or more of the initial targets and subsequent targets, and in another embodiment the further targets comprise new targets that are other than the initial and subsequent targets. Once the content item option is changed, some embodiments involve repeating the activities 410, 420, 430, and 435, using the updated content items and variations created therewith, including setting further updated weightings (which in certain embodiments can involve setting evenly distributed weightings to establish a baseline), transmitting further communications with the updated content item, receiving further response information in relation to the updated content items, determining whether statistical significance is achieved, determining additionally updated weightings, and transmitting additional communications with the updated content item having the additionally updated weighting, wherein the additional communications are based at least in part on the additionally updated weightings. That is, once a new content item is introduced into the content variations, the method 400 can be repeated to determine the weighting optimizations for the new content variations with the updated content item.
In many embodiments, communications control system 310 can comprise non-transitory memory storage module 512. Memory storage module 512 can be referred to as communications control module 512. In many embodiments, communications control module 512 can store computing instructions configured to run on one or more processing modules and perform one or more acts of method 400 (
In many embodiments, web server 320 can comprise non-transitory memory storage module 522. Memory storage module 522 can be referred to as web server module 522. In many embodiments, web server module 522 can store computing instructions configured to run on one or more processing modules and perform one or more acts of method 400 (
In many embodiments, display system 360 can comprise non-transitory memory storage module 562. Memory storage module 562 can be referred to as display module 562. In many embodiments, display module 562 can store computing instructions configured to run on one or more processing modules and perform one or more acts of method 400 (
In many embodiments, content variation optimization system 370 can comprise non-transitory memory storage module 572. Memory storage module 572 can be referred to as content variation optimization module 572. In many embodiments, content variation optimization module 572 can store computing instructions configured to run on one or more processing modules and perform one or more acts of method 400 (
In many embodiments, content variation creation system 390 can comprise non-transitory memory storage module 572. Memory storage module 572 can be referred to as content variation creation module 592. In many embodiments, content variation creation module 572 can store computing instructions configured to run on one or more processing modules and perform one or more acts of method 400 (
In many embodiments, communications database 380 can store computing instructions configured to run on one or more processing modules and perform one or more acts of method 400 (
Although systems and methods for optimizing content variations for communications to targets have been described with reference to specific embodiments, it will be understood by those skilled in the art that various changes may be made without departing from the spirit or scope of the disclosure. Accordingly, the disclosure of embodiments is intended to be illustrative of the scope of the disclosure and is not intended to be limiting. It is intended that the scope of the disclosure shall be limited only to the extent required by the appended claims. For example, to one of ordinary skill in the art, it will be readily apparent that any element of
All elements claimed in any particular claim are essential to the embodiment claimed in that particular claim. Consequently, replacement of one or more claimed elements constitutes reconstruction and not repair. Additionally, benefits, other advantages, and solutions to problems have been described with regard to specific embodiments. The benefits, advantages, solutions to problems, and any element or elements that may cause any benefit, advantage, or solution to occur or become more pronounced, however, are not to be construed as critical, required, or essential features or elements of any or all of the claims, unless such benefits, advantages, solutions, or elements are stated in such claim.
Moreover, embodiments and limitations disclosed herein are not dedicated to the public under the doctrine of dedication if the embodiments and/or limitations: (1) are not expressly claimed in the claims; and (2) are or are potentially equivalents of express elements and/or limitations in the claims under the doctrine of equivalents.
