Dynamic timing and pricing for online retail platforms

Abstract

A method for dynamically adjusting one or more factors associated with an electronic transaction includes initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform. The listing may be associated with a time period and an offer increase amount. The method also includes receiving an offer for the item from a remote buyer. The method further includes adjusting the time period and / or the offer increase amount based on receiving the offer and the one or more adjustment factors. The method further includes repeating the adjustment of the time period and / or the offer increase amount until the time period expires. The method also includes terminating the listing based on the expiration of the time period.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001]

[0001] This application claims priority to U.S. patent application Ser. No. 18 / 114,727, filed February 27, 2023, entitled "DYNAMIC TIMING AND PRICING FOR ONLINE RETAIL PLATFORM," the disclosure of which is expressly incorporated by reference in its entirety. [Technical Field]

[0002] FIELD OF THE DISCLOSURE

[0002] The present disclosure relates generally to online retail platforms, and more particularly to dynamically adjusting one or more characteristics associated with the sale of items via the online platform. [Background technology]

[0003]

[0003] Retail platforms match buyers and sellers in transacting the sale of goods. In some traditional face-to-face retail platforms, potential buyers (e.g., bidders) physically gather together, and a salesperson at the retail platform solicits offers for items, one item at a time. The item may be sold to the buyer with the highest offer when a time period associated with the sale of the item expires. To enhance the convenience of such retail platforms, some retail platforms allow potential buyers to submit offers remotely (e.g., by telephone or internet). In some cases, sellers can use online retail platforms (e.g., internet-based retail platforms) to post descriptions and photos of items they intend to sell. In such cases, buyers browse the posted items and submit offers electronically. In most online retail platforms, buyers can submit offers as soon as a seller lists an item. The time period for receiving offers may be limited, and the item may be sold when the time period expires. Buyers can submit offers up to a specified end time, and the winning offer may be the highest offer at the end time. Summary of the Invention

[0004] In one aspect of the present disclosure, a method for dynamically adjusting one or more factors associated with electronic transactions includes initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, the listing being associated with a time period and an offer increment. The method further includes receiving offers for the item from remote buyers. The method further includes adjusting the time period and / or the offer increment based on receiving the offers and one or more adjustment factors. The method also includes repeating the adjustment of the time period and / or the offer increment until the time period expires. The method further includes terminating the listing based on the expiration of the time period.

[0005] Another aspect of the present disclosure is directed to an apparatus including means for initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, the listing being associated with a time period and an offer increment amount. The apparatus further includes means for receiving offers for the item from remote buyers. The apparatus further includes means for adjusting the time period and / or the offer increment amount based on receiving the offers and one or more adjustment factors. The apparatus also includes means for repeating the adjustment of the time period and / or the offer increment amount until the time period expires. The apparatus further includes means for terminating the listing based on expiration of the time period.

[0006] In another aspect of the present disclosure, a non-transitory computer-readable medium having non-transitory program code recorded thereon is disclosed. The program code, when executed by a processor, includes program code for initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, where the listing is associated with a time period and an offer increase amount. The program code further includes program code for receiving offers for the item from remote buyers. The program code further includes program code for adjusting the time period and / or the offer increase amount based on receiving the offers and one or more adjustment factors. The program code also includes program code for repeating the adjustment of the time period and / or the offer increase amount until the time period expires. The program code further includes program code for terminating the listing based on expiration of the time period.

[0007] Another aspect of the present disclosure is directed to an apparatus having a processor and a memory coupled to the processor, the memory storing instructions operable, when executed by the processor, to cause the apparatus to initiate a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, the listing being associated with the time period and an offer increment amount. Execution of the instructions also causes the apparatus to receive offers for the item from remote buyers. Execution of the instructions further causes the apparatus to adjust the time period and / or the offer increment amount based on receiving the offers and one or more adjustment factors. Execution of the instructions still further causes the apparatus to repeat adjusting the time period and / or the offer increment amount until the time period expires. Execution of the instructions also causes the apparatus to terminate the listing based on the expiration of the time period.

[0008]

[0008] Aspects generally include methods, apparatus, systems, computer program products, non-transitory computer-readable media, user equipment, base stations, wireless communication devices, and processing systems, as substantially described with reference to and exemplified by the accompanying drawings and specification.

[0009]

[0009] The foregoing has outlined rather broadly the features and technical advantages of examples of the present disclosure in order that the detailed description that follows may be better understood. Additional features and advantages will now be described. The concepts and specific examples disclosed may be readily utilized as a basis for modifying or designing other structures for carrying out the same purposes of the present disclosure. Such equivalent constructions do not depart from the scope of the appended claims. The features of the disclosed concepts, both their organization and method of operation, and associated advantages, will be better understood from the following description when considered in conjunction with the accompanying figures. Each of these figures is provided for the purpose of illustration and description, and not as a definition of the limits of the claims.

[0010]

[0010] To enable the features of the present disclosure to be understood in detail, a specific description can be made by referring to embodiments, some of which are illustrated in the accompanying drawings. However, it should be noted that the accompanying drawings illustrate only certain embodiments of the present disclosure, and therefore should not be considered as limiting its scope, since the description may admit of other equally effective embodiments. The same reference numbers in different drawings may identify the same or similar elements. [Brief explanation of the drawings]

[0011] [Figure 1]

[0011] A block diagram illustrating an example of a system for an online retail platform according to various aspects of the present disclosure. [Figure 2]

[0012] FIG. 1 illustrates an example hardware implementation of a system according to various aspects of the present disclosure. [Figure 3]

[0013] FIG. 1 is a flow diagram illustrating a process for selling multiple items on a retail platform according to various aspects of the present disclosure. [Figure 4]

[0014] FIG. 1 is a flow diagram illustrating a process for increasing the price of an item according to various aspects of the present disclosure. [Figure 5]

[0015] FIG. 1 is a flow diagram illustrating an example process performed, for example, by a device, according to various aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0012]

[0016] Various aspects of the present disclosure are described more fully below with reference to the accompanying drawings. However, the present disclosure may be embodied in many different forms and should not be construed as limited to any specific structure or function presented throughout this disclosure. Rather, these aspects are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. Based on the present teachings, those skilled in the art should recognize that the scope of the present disclosure is intended to cover any aspect of the present disclosure, whether implemented independently of or in combination with any other aspect of the disclosure. For example, an apparatus may be implemented or a method may be practiced using any number of the described aspects. In addition, the scope of the present disclosure is intended to cover an apparatus or method implemented using other structure, functionality, or structure and functionality in addition to or other than the various aspects of the disclosure described. It should be understood that any aspect of the present disclosure disclosed may be embodied by one or more elements of a claim.

[0013]

[0017] Certain aspects of the auction system will now be presented with reference to various apparatus and techniques. These apparatus and techniques are described in the following detailed description and illustrated in the accompanying drawings by various blocks, modules, components, circuits, steps, processes, algorithms, and the like (collectively referred to as "elements"). These elements may be implemented using hardware, software, or a combination thereof. Whether such elements are implemented as hardware or software depends on the particular application and design constraints imposed on the overall system.

[0014]

[0018] As described above, retail platforms, such as physical stores, bring together buyers and sellers to transact the sale of goods. In some traditional face-to-face retail platforms, such as auctions, potential buyers (e.g., bidders) come together, and a salesperson (e.g., an auctioneer) at the retail platform solicits offers (e.g., bids) for items, one item at a time. When there are no more bids and the salesperson decides to end the auction, the item may be sold to the buyer with the highest offer. For face-to-face retail platforms, the end time may be random and up to the auctioneer. Traditional face-to-face retail platforms are time-consuming and inefficient because buyers cannot make offers for multiple items simultaneously. To be precise, salespersons at retail platforms sell one item at a time because it is impossible for one person to keep track of multiple offers being made simultaneously for different items. Furthermore, even if a retail platform uses multiple sellers, each selling different items at different physical locations on the in-person retail platform (e.g., an auction house), it is physically impossible for an individual buyer to make offers for multiple items simultaneously, because a buyer cannot be simultaneously present in different locations and make multiple in-person offers. Furthermore, participating in an in-person retail platform can be time-consuming and expensive, as each buyer may need to pay for travel expenses. As a result, fewer buyers may participate in the in-person retail platform. Therefore, the true market price of the items may not be achieved.

[0015]

[0019] In some cases, retail platforms allow potential buyers to submit offers remotely (e.g., by telephone or internet). In some cases, sellers can use online retail platforms (e.g., internet-based retail platforms) to post descriptions and photos of items. In such cases, buyers browse the posted items and submit offers electronically. In most online retail platforms, buyers can submit offers (e.g., make offers) for items once the seller posts them, with a time period for submitting offers ending at a predetermined time. Buyers can submit offers before the expiration of the time period, and the winning offer may be the highest offer at the end of the time period.

[0016]

[0020] Online retail platforms may allow buyers to make offers on groups of items. Furthermore, online retail platforms allow sellers to sell groups of items. Each item in a group of items may have a start time and an end time that are the same or different from the other items in the group of items. In such traditional online retail platforms, the time period for selling each item may be fixed. Furthermore, while buyers can make offers on multiple items, buyers cannot simultaneously make offers on multiple items in a group of items. Rather, buyers are limited to making offers sequentially on each item in a group of items. That is, a buyer can make an offer on a first item, then navigate to an online page for a second item and make another offer, and so on.

[0017]

[0021] Various aspects of the present disclosure are directed to a dynamic online retail platform in which the time period for each item sale may be dynamically adjusted based on one or more factors. In some examples, the time period may be dynamically increased when one or more factors are met. For example, the time period may be increased when the number of people viewing the item sale is greater than a viewer threshold. The number of people viewing the item sale may be determined based on the number of unique connections to a page (e.g., a web page) associated with the item sale. The unique connections may be determined based on IP addresses, device identifiers, and / or other identifiers. As another example, the time period may be increased when the time period between successive bids from the same or different buyers is less than an offer time period threshold. In such cases, dynamically increasing the time period can increase the sale price of the item by giving buyers more time to make offers on the item. Because traditional face-to-face retail platforms are not associated with time periods, such dynamically increasing a time period (e.g., a live offer period) may not be possible in face-to-face retail platforms. That is, in traditional in-person retail platforms, a listing for an item ends when no other offers are received from in-person or remote participants. Furthermore, even if traditional in-person retail platforms are associated with a time period, it is not feasible for a human to calculate such a time adjustment while the auction's time period is about to expire. For example, given the number of factors used in determining a time adjustment, the auction may end by the time a human can calculate the time increase for the listing (e.g., auction).

[0018]

[0022] Additionally or alternatively, in some examples, the price increment for each item may be dynamically adjusted based on one or more conditions. The price increment refers to a set value between successive offers. For example, the price increment may be set to $10, so that if the first offer for the item is $20, the next offer must be at least $30. In some examples, the price increment may be dynamically adjusted based on the time remaining to sell the item and / or the current price of the item. In such cases, dynamically increasing the price increment may increase the selling price of the item. In other such cases, decreasing the price increment may encourage buyers to make larger offers for the item, thereby increasing the selling price of the item.

[0019]

[0023] Furthermore, in some examples, a buyer may make offers for multiple items simultaneously. In such examples, the ability to make offers for multiple items simultaneously may increase the efficiency of the online retail platform by reducing the overall amount of network traffic. For example, network traffic may be reduced when a buyer makes one offer or a set of offers for multiple items via one data transmission compared to when a buyer makes multiple consecutive offers for multiple items via sequential data transmissions. Furthermore, the ability to make offers for multiple items simultaneously may also increase the selling price of the items by allowing more buyers to make offers for each item.

[0020]

[0024] FIG. 1 is a block diagram illustrating an example of a system 100 for an online retail platform. As shown in the example of FIG. 1, the system 100 may include one or more user devices 110 and one or more servers 120. For ease of explanation, only one server 120 is shown in the example of FIG. 1. Each user device 110 may be connected to a network 104 via one or more communication links 102. The communication links 102 may be wired and / or wireless communication links. The server 120 may also be connected to the network 104 via the communication links 102.

[0021]

[0025] Network 104 may be an example of the Internet. Additionally or alternatively, network 104 may include any suitable computer network, such as an intranet, a wide area network (WAN), a local area network (LAN), a wireless network, a digital subscriber line (DSL) network, a frame relay network, an asynchronous transfer mode (ATM) network, and / or a virtual private network (VPN). Communication link 102 may be any type of communication link that may be suitable for communicating data between user device 110 and server 120. For example, communication link 102 may include one or more of a network link, a dial-up link, a wireless link (e.g., a Wi-Fi link, a satellite link, or a cellular communication link), or a hardwired link.

[0022]

[0026] Server 120 may be a computing device such as a server, processor, computer, cloud computing device, cellular phone (e.g., smartphone), personal digital assistant (PDA), wireless modem, wireless communication device, handheld device, laptop computer, cordless phone, wireless local loop (WLL) station, tablet, camera, gaming device, netbook, smartbook, ultrabook, medical device or equipment, biometric sensor / device, wearable device (smart watch, smart clothing, smart glasses, smart wristband, smart jewelry (e.g., smart ring, smart bracelet)), entertainment device (e.g., music or video device, or satellite radio), vehicle component or sensor, smart meter / sensor, industrial manufacturing equipment, global positioning system device, or any other suitable device configured to host an auction site and communicate via a wireless or wired medium. In some examples, server 120 may host the auction site. In some such examples, one or more servers 120 may cooperate to host the auction site. Specifically, server 120 may implement functionality and / or computer code to execute the auction process via the auction site. An auction site refers to an online retail platform house that sells one or more items online via a network 104 .

[0023]

[0027] Each user device 110 may be an example of a personal computing device, a cellular phone (e.g., a smartphone), a personal digital assistant (PDA), a wireless modem, a wireless communication device, a handheld device, a laptop computer, a cordless phone, a wireless local loop (WLL) station, a tablet, a camera, a gaming device, a netbook, a smartbook, an ultrabook, a medical device or equipment, a biometric sensor / device, a wearable device (smartwatch, smart clothing, smart glasses, smart wristband, smart jewelry (e.g., a smart ring, smart bracelet)), an entertainment device (e.g., a music or video device, or satellite radio), a vehicle component or sensor, a smart meter / sensor, industrial production equipment, a global positioning system device, or any other suitable device configured to communicate via a wireless or wired medium. User device 110 may be used by a seller to sell one or more items via an auction site. Additionally or alternatively, user device 110 may be used by a buyer to make an offer for one or more items via an auction site. 1 may be used by a different buyer, such that multiple buyers may make offers for one or more items via an auction site hosted on server 120. Each user device 110 and server 120 may be stationary or mobile.

[0024]

[0028] In some examples, each user device 110 may be included within a housing that houses components of the user device 110, such as one or more processors 116 and memory 118. The housing may also include or be connected to a display 112 and input devices 114, which may be interconnected with other components of the user device 110. For ease of explanation, only one processor 116 is shown for each user device 110. In some examples, the one or more processors 116, display 112, input devices 114, and memory 118 may be interconnected via a bus architecture. The memory 118 may include one or more different types of memory, such as random access memory (RAM), static RAM (SRAM), dynamic RAM (DRAM), and / or another type of memory. Each user device 110 may also include a storage device (not shown in the example of FIG. 1 ), such as a hard disk (e.g., a non-transitory computer-readable medium). In some examples, the memory 118 and / or storage device(s) include program code (e.g., instructions) that may be executed by the processor 116 to control one or more functions of the user device 110. The input device 114 may be used by buyers to navigate to an auction site, browse the auction site, submit offers for desired items, and / or perform other tasks. In some examples, the input device 114 may be used by sellers to navigate to an auction site, browse the auction site, post items intended for sale, and / or perform other tasks. In conjunction with one or more components of the user device 110, the processor 116 may receive product and sales information regarding items being auctioned and control the display 112 to output auction information, such as, for example, the current best offer, the minimum allowable initial offer, the offer increment amount, the auction start time, and / or the amount of time remaining in the auction for one or more items. The display 112 may output (e.g., display) information received by the processor 116.In some examples, the processor 116 of the user device 110 is configured to perform operations and implement one or more elements associated with one or more processes, such as processes 300, 400, and 500, respectively, described with respect to Figures 3-5.

[0025]

[0029] In some examples, the auction host and / or an entity associated with the auction host may maintain the server 120. The server 120 may be contained within a housing that houses components of the server 120, such as one or more processors 116 and memory 118. The housing may also include or be connected to a display 112 and input devices 114, which may be interconnected with other components of the user device 110. For ease of explanation, only one processor 116 is shown for the server 120. In some examples, the one or more processors 116, the display 112, the input devices 114, and the memory 118 may be interconnected via a bus architecture. The memory 118 may include one or more different types of memory, such as RAM, SRAM, DRAM, and / or another type of memory. The server 120 may also include a storage device (not shown in the example of FIG. 1 ), such as a hard disk (e.g., a non-transitory computer-readable medium). In some examples, the memory 118 and / or the storage device include program code (e.g., instructions) that may be executed by the processor 116 to control one or more functions of the server 120. For example, processor 116 may execute instructions to establish an auction for a particular item, enable participants to join the auction, filter and accept offers for the item, submit offers on behalf of potential buyers, and control other aspects of the online retail platform. In some examples, processor 116 of server 120 is configured to perform actions and implement one or more elements associated with one or more processes, such as processes 300, 400, and 500, respectively, described with respect to FIGS.

[0026]

[0030] FIG. 2 illustrates an example hardware implementation of a system 200 according to various aspects of the present disclosure. The system 200 may be a component of a device 250. The device 250 may be an example of the user device 110 or the server 120 described with reference to FIG. 1. As shown in the example of FIG. 2, the device 250 may include a display 112 and an input device 114 (e.g., a keyboard). In some examples, the system 200 is configured to perform operations and implement one or more elements associated with one or more processes, such as processes 300, 400, and 500, described with reference to FIGS. 3-5, respectively.

[0027]

[0031] System 200 may be implemented using a bus architecture, represented broadly by bus 206. Bus 206 may include any number of interconnected buses and bridges, depending on the particular application and overall design constraints of system 200. Bus 206 links together various circuits, including one or more processors and / or hardware modules, represented by processor 116 and communications module 202. Bus 206 may also link various other circuits, such as timing sources, peripherals, voltage regulators, and power management circuits, which are well known in the art and will not be described further.

[0028]

[0032] The system 200 includes a transceiver 208 coupled to the processor 116, a communications module 202, and a computer-readable medium 204. The transceiver 208 is coupled to an antenna 210. The transceiver 208 communicates with various other devices over a transmission medium, such as the communications link 102 described with reference to FIG. 1. For example, the transceiver 208 may receive commands via transmissions from a user or a remote device.

[0029]

[0033] As shown in the example of FIG. 2 , system 200 may include an offer model 260 that can be trained to perform one or more tasks associated with an online retail platform. For example, offer model 260 may be trained to adjust a live offer period and / or adjust an offer increment amount to attract more buyers, increase the final offer value, and / or increase the probability of meeting the reserve price. Additionally or alternatively, offer model 260 may be trained to autonomously issue offers and / or incremental offers for items associated with a reserve price to attract more buyers, increase the final offer value, and / or increase the probability of meeting the reserve price. Offer model 260 may include artificial intelligence or computational intelligence elements, such as neural networks, fuzzy logic, or other machine learning algorithms. In one or more arrangements, one or more of the other modules 116, 118, 202, 204, 208 may also include artificial intelligence or computational intelligence elements, such as neural networks, fuzzy logic, or other machine learning algorithms. Additionally, in one or more arrangements, one or more of the modules 116, 118, 202, 204, 208 may be distributed among multiple modules 116, 118, 202, 204, 208, 260 described herein. In one or more arrangements, two or more of the modules 116, 118, 202, 204, 208, 260 of the system 200 may be combined into a single module.

[0030]

[0034] System 200 includes processor 116 coupled to computer-readable medium 204. Processor 116 performs processes, including executing software stored on computer-readable medium 204, that provide functionality according to the present disclosure. When executed by processor 116, the software causes system 200 to perform various functions described for particular devices, such as any of modules 116, 118, 202, 204, 208, and 260. For example, when executed by processor 116, the software causes system 200 and / or offer model 260 to implement one or more elements associated with one or more processes, such as processes 300, 400, and 500, respectively, described with respect to FIGS. 3-5. Computer-readable medium 204 may also be used to store data manipulated by processor 116 when executing the software. For example, in conjunction with one or more of the other modules, modules 116, 118, 202, 204, and 208, offer model 260 may initiate a time period for receiving live offers via an online interface for an item associated with a listing on the online retail platform. The listing may be associated with a time period and an offer increment amount. Offer model 260 may also receive offers for the item from remote buyers. Offer model 260 may further adjust the time period and / or the offer increment amount based on receiving the offers and one or more adjustment factors. Offer model 260 may also repeat adjusting the time period and / or the offer increment amount until the time period expires. Offer model 260 may terminate the listing based on the expiration of the time period.

[0031]

[0035] As noted above, Figures 1 and 2 are provided as examples. Other examples may differ from those described with respect to Figures 1 and 2.

[0032]

[0036] As mentioned above, various aspects of the present disclosure are directed to an online retail platform. In some examples, multiple items may be offered for sale simultaneously via an online retail platform (e.g., an online auction). In some such examples, a group of items may be associated with the same category, and each item in the group of items may be offered for sale simultaneously. Furthermore, a buyer may simultaneously place offers (e.g., bids) on two or more items in the group of items. In some examples, the respective time periods for selling each listed item and the respective price increment amounts for each listed item may be dynamically adjusted based on one or more factors. Furthermore, in some such examples, a seller may monitor activity, such as offers, for one or more items and interact within the live online retail platform environment. For example, a seller may manually adjust one or more parameters associated with the sale of an item; these parameters may include, for example, an end time, a minimum bid price, and / or a price increment amount.

[0033]

[0037] As described above, in some examples, a buyer can use the online retail platform to simultaneously place offers on two or more items of a group of items. In some such examples, each item may be offered for sale at the same time. Each item may be associated with a minimum bid price or may be based on an absolute price. In some examples, a buyer can place one or more advance offers on an item, which can result in the online retail platform placing advance offers on the items as soon as the sale time period associated with the item is activated. In some examples, a buyer can use a token to extend the sale time period associated with the item. The token may be referred to as an auction extension token or an electronic token. The token may use proprietary technology associated with the retail platform or may be associated with established technology such as an electronic coin or a blockchain coin. The sale time period refers to the amount of time an item can receive offers. In some examples, a seller can accept offers below the set minimum bid price.

[0034]

[0038] As described above, in traditional retail platforms, such as online or in-person retail platforms, each item may be associated with a predetermined sales time period. In such online retail platforms, the predetermined sales time period may be fixed and cannot be dynamically adjusted. Furthermore, in traditional online retail platforms, a buyer may make offers for multiple items sequentially. That is, the buyer makes an offer for each item in a group of items one after the other. However, such offers cannot be made for multiple items simultaneously. Thus, in the case of in-person offers, the process for making offers for multiple items is time-consuming. Also, a buyer may miss out on another item while making an offer for one item. As described above, it may be physically impossible for a buyer to make offers for two or more items in a group of offers simultaneously on in-person retail platforms.

[0035]

[0039] Various aspects of the present disclosure are directed to providing a buyer with the option to make offers on multiple items simultaneously. FIG. 3 is a flow diagram illustrating a process 300 for selling multiple items (multi-items) on a retail platform according to various aspects of the present disclosure. In the example of FIG. 3 , at block 302, a seller, an online retail platform, or a salesperson associated with the online retail platform may associate a group of items with a category. For example, a group of jewelry items may be associated with a jewelry category. In some examples, items may be manually associated with a category. In such examples, a plurality of predetermined categories may be provided to the seller, and the seller may associate an item with one of the predetermined categories.

[0036]

[0040] In some other examples, the online retail platform may categorize items based on one or more of keywords associated with the items, item descriptions, item images, or other item attributes. The keywords and descriptions may be manually entered by the seller or an auction host participant. Additionally or alternatively, the keywords and descriptions may be autonomously generated by the online retail platform based on a machine learning model or other computer-based functionality. Additionally or alternatively, a machine learning model may be used to associate items with categories based on item images and / or other item attributes. The machine learning model may be referred to as an offer model, such as offer model 260 described with reference to FIG. 2. Multiple items associated with the same category may be offered by one or more different sellers. For example, one seller may offer two items associated with a category, and another seller may offer one item associated with the category. As another example, the same seller may offer all items associated with a category.

[0037]

[0041] Each item in the group of items associated with a category may be offered for sale via an online retail platform. The listing of each item may be referred to as a micro-listing 350a, 350b, 350c. In this application, a listing may be an example of a micro-listing, such as one of micro-listings 350a, 350b, 350c. A listing refers to the offering of an item for sale on an online retail platform. As shown in the example of FIG. 3, the first micro-listing 350a may be a listing for a ring, the second micro-listing 350b may be a listing for a necklace, and the third micro-listing 350c may be a listing for a bracelet. The number of micro-listings associated with a category is not limited to three micro-listings, and any number of micro-listings may be associated with a category. In block 304, each micro-listing 350a, 350b, 350c may be activated. In some examples, the micro-listings 350a, 350b, 350c may be activated simultaneously. In some other examples, the start time of one or more micro listings 350a, 350b, 350c may be different from the micro listings 350a, 350b, 350c of other micro listings. A buyer may place an offer for the item once the micro listing is activated. In some examples, such an offer may be a pre-offer (e.g., a pre-bid). A pre-offer is an example of an offer placed for the item before the start of the live offer period of the micro listing. A pre-offer may be the maximum amount a buyer is willing to pay for the item. Furthermore, in block 304, once the micro listing is activated, seller activity for the micro listing may begin. Seller activity may include, but is not limited to, adjusting the reserve price and / or monitoring offers via a seller dashboard.

[0038]

[0042] At block 306, each micro listing 350a, 350b, 350c may begin a respective live offer period. A live offer period may also be referred to as a sales time period or an auction period. In some examples, the live offer period at block 306 may begin when the micro listing is activated at block 304. In some other examples, the start time of the live offer period for a micro listing 350a, 350b, 350c may be randomized based on one or more conditions, such as the number of prior offers placed for the item. Each micro listing 350a, 350b, 350c may be associated with a respective offer time period. The offer time period for each micro listing 350a, 350b, 350c may be the same or different. The offer time period is the time period for receiving offers for the item. The offer time period begins when the live offer period begins at block 306.

[0039]

[0043] In some examples, when a micro listing's live offer period begins, an initial offer amount may be preset by the seller or the online retail platform. The initial offer amount may be the minimum offer amount that can be initially placed for the item. For example, if the initial offer amount is $10, then the initial offer for the item must be $10 or greater. Buyers may place live offers for the item during the live offer period. Additionally, the online retail platform may place offers for the item based on each prior bid associated with each micro listing. Successive bids for each item may be subject to a price increase amount (also referred to as an offer increase amount or a bid increase amount). As described above, the price increase amount is the increase amount between successive offers. For example, the price increase amount may be set to $10, so if the initial offer for the item is $20, the next offer must be at least $30. Both live offers from buyers and offers placed based on prior offers are subject to the price increase amount. In some examples, during the live offer period, the price increase amount may be adjusted depending on the current offer price. For example, the price increase amount may increase as the current offer price increases.

[0040]

[0044] In some examples, while each micro listing 350a, 350b, 350c is live (e.g., before the expiration of each micro listing's 350a, 350b, 350c's respective live offer period or respective price increment amount), one or more of each micro listing 350a, 350b, 350c's respective live offer period or respective price increment amount may be adjusted based on one or more factors. In some examples, the live offer period of each micro listing 350a, 350b, 350c may be adjusted based on one or more of the following: the number of buyers actively viewing the item, the number of prior offers, the current offer price, the amount of time between offers from the same buyer, the amount of time between offers from different buyers, the number of offers, or other conditions. Additionally, the price increment amount may be adjusted based on one or more factors, such as the amount of time remaining in each micro listing or the current price of the item.

[0041]

[0045] At block 308, each micro listing 350a, 350b, 350c determines whether its respective live offer period has expired. If the live offer period has not expired, the live offer period at block 306 may continue, thereby allowing additional bids to be received. Additionally or alternatively, the live offer period and price increment amount may continue to be adjusted until the live offer period expires. As shown in the example of FIG. 3 , if the live offer period of each micro listing 350a, 350b, 350c expires at block 308, the online retail platform terminates the respective micro listing 350a, 350b, 350c at block 310. Once the micro listing 350a, 350b, 350c expires, no further offers may be accepted. Additionally, the item associated with the deactivated micro listing 350a, 350b, 350c may be sold to the buyer associated with the highest offer. At block 312, once each micro listing 350a, 350b, 350c has finished, the category associated with each of the micro listings 350a, 350b, 350c may be closed.

[0042]

[0046] In some examples, a buyer can use digital tokens to extend the live offer period associated with a micro listing. By using digital tokens to extend the live offer period, a buyer can increase the opportunity to place offers on multiple items and extend the time available to place a winning offer. In some examples, a buyer can earn digital tokens based on previous offers and / or purchasing activity. Additionally or alternatively, a buyer may purchase one or more digital tokens. In some examples, each digital token may be associated with an expiration date.

[0043]

[0047] Each digital token may be associated with a specific amount of time to extend the live offer period. In some examples, the time period for applying the digital token may be limited to when the amount of time remaining in the live offer period is below a threshold. As an example, the digital token may only be applied if the amount of time remaining is two minutes or less. In some examples, if two or more purchasers apply digital tokens to extend the live offer period, the time of the live offer period is extended based on the digital token with the longest extension period. For example, one digital token may extend the live offer period by one minute, and another digital token may extend the live offer period by two minutes. In such an example, if both digital tokens are applied during the live offer period, the live offer period may be extended by two minutes.

[0044]

[0048] As described above, a buyer can earn digital tokens based on their offer and / or purchasing activity. In one example, a buyer can earn digital tokens for making offers on a specific number of items. In one such example, a buyer can earn digital tokens for making offers on five items. In another example, a buyer can earn digital tokens for making several offers on one particular item. In one such example, a buyer can earn digital tokens after making ten offers on a single item. In another example, a buyer can earn digital tokens after purchasing a certain number of items.

[0045]

[0049] In some examples, the online retail platform may provide sellers with a dashboard for monitoring item activity during a live offer period associated with a listing, such as a microlisting. The dashboard may be referred to as a seller dashboard. Item activity may include a current best offer, offer history, and offer price. Furthermore, if an item is associated with a reserve price, the seller may modify the reserve price from the seller dashboard. As an example, a seller may lower the reserve price at any time via the seller dashboard. The reserve price cannot be modified to be less than the item's current price (e.g., the current best offer). In some examples, if an item is associated with a reserve price, the seller may accept offers below the reserve price via the seller dashboard during the live offer period. Accepting an offer does not end the live offer period; rather, accepting an offer below the reserve price may also lower the reserve price. Furthermore, buyers may continue to make offers during the live offer period if the seller lowers the reserve price and / or accepts an offer below the reserve price. Furthermore, if the seller accepts an offer below the reserve price, the item's status may be changed to "reserve met." Alternatively, the reserve price may be met if a buyer makes an offer equal to or greater than the reserve price. In traditional in-person retail platforms, such as auctions, the seller must be physically present at the in-person sale to lower the reserve price or accept offers below the reserve price. For example, an auction manager may be present with the seller to ensure the seller is aware of the current bids. The auction manager may attempt to get the seller to lower the reserve price or accept the current bid. If the seller agrees to accept the lower bid, a signal is sent to the live auctioneer to accept the current bid and / or additional bids. That is, the reserve price is removed, the item sells, but the auctioneer continues to seek more bids.Yet, in-person retail platforms do not allow sellers to lower reserve prices for multiple items simultaneously. In contrast, aspects of the present disclosure allow sellers to adjust reserve prices for multiple items simultaneously, thereby increasing seller efficiency. As described above, in some configurations, reserve prices for multiple items may be adjusted via a seller dashboard that may be accessed via an online interface, such as a website. By allowing sellers to simultaneously adjust reserve prices for multiple items through a single interface, rather than adjusting one item at a time, aspects of the present invention reduce overall network bandwidth because sellers are not forced to visit each individual auction website to adjust reserve prices.

[0046]

[0050] As described above, a live offer period for an item may begin after the item is activated to receive offers. In some examples, one or more buyers may place pre-offers on the item. In some other examples, no pre-offers are placed on the item. Furthermore, a price increase amount may be specified during the live offer period depending on the current best offer (e.g., the current item price). FIG. 4 is a flow diagram illustrating a process 400 for increasing the price of an item according to various aspects of the present disclosure. Process 400 may be implemented via a system such as system 200 described with respect to FIG. 2. For ease of explanation, process 400 is directed to one micro listing. However, aspects of the present disclosure are not limited to one micro listing, as described above, and multiple micro listings may be active simultaneously via an online retail platform. Furthermore, process 400 may be applied to one or more micro listings that are active simultaneously.

[0047]

[0051] As shown in the example of FIG. 4 , process 400 begins at block 402 by initiating a live offer period, such as the live offer period initiated at block 306 of FIG. 3 . In some examples, no prior offers may be placed for an item within a micro listing. In such examples, if no live offers are received for the item, process 400 continues by waiting until an offer is made or until the live offer period expires. If an offer is received while waiting at block 406, process 400 continues by adjusting the offer increase amount and / or adjusting the live offer period at block 404. In some examples, the offer increase amount and / or the live offer period may be adjusted by an offer model (e.g., a machine learning model) trained to solicit bids. The offer model may be an example of the offer model 260 described with reference to FIG. 2 . For example, the offer model may increase the live offer period to allow more time for offers from buyers with a history of purchasing items. Additionally or alternatively, the offer model may lower the offer increase amount to solicit additional bids from buyers viewing the micro listing.

[0048]

[0052] At block 404, if another bid is subsequently received within a certain time period from the previous bid, the process continues to adjust the offer increase amount and / or the live offer period at block 404. Alternatively, if at block 404 a subsequent bid is not received within a certain time period from the previous bid, process 400 returns to block 406 and waits for the offer or live offer period to expire. At block 406, the process continues to wait for the offer or live offer period to expire if no bids are received. In some examples, if no bids are received at block 406, process 400 may adjust the offer increase amount to solicit additional bids (not shown in FIG. 4 ). Further, if at block 406 the live offer period has expired, process 400 ends the auction at block 408.

[0049]

[0053] In some examples, an item in a micro listing may be associated with a reserve price. A reserve price listing is a type of listing in which a seller sets a minimum price (e.g., a reserve price) they are willing to accept for the item being sold. Thus, if no offers reach the reserve price, the item does not sell. Buyers typically do not know the reserve price, and the listing continues as with a traditional listing, with buyers making offers in specified increments until the live offers period ends. In some examples, buyers may be notified when the reserve price is met. If the final offer meets or exceeds the reserve price, the item is sold to the buyer associated with the highest bid. If the final offer is below the reserve price, the item remains unsold. Reserve price listings are a useful tool for sellers because they guarantee that they receive a minimum price for the item while allowing for the possibility of a higher price through competitive offers. In the example of FIG. 4, when the live offers period ends in block 408, the item may not be sold to the highest bidder if the highest offer is not at or above the reserve price. Additionally, as noted above, in some instances, a seller may lower the reserve price during the live offer period.

[0050]

[0054] In the example of FIG. 4 , if the item is associated with a reserve price, the offer model may autonomously bid to elicit action from other buyers. In some examples, offers made by the offer model may be made until the item price is within the reserve price. For example, the offer model may make offers until the highest offer is within a certain percentage of the reserve price. The offer model may be trained to make offers when one or more conditions are met. An offer may be made by the offer model when the process is waiting at block 406, within the time period of another offer at block 404, or upon starting a live offer period at block 402. The one or more conditions may include the wait time at block 406 being greater than or equal to a wait time threshold, the amount of offers being less than an offer threshold, the amount of viewers being greater than a viewer threshold, the amount of consecutive offers being greater than or less than a consecutive offer threshold, and / or other conditions. In some examples, the offer model may be trained to make autonomous offers (e.g., increase offer activity for the item) to create the impression that the item is popular. In such an example, a human buyer interacting with the online retail platform may not be aware that the offer model is making autonomous offers. Thus, the human buyer may believe that the item is popular, and thus, the human buyer may be motivated to make an offer on the item because of its popularity. In other words, the human buyer may fear missing out when they notice increased offer activity on the item.

[0051]

[0055] As described above, in some examples, one or more pre-offers may be placed for an item prior to the start of a live offer period. Each pre-offer may be for a different offer amount. If a buyer attempts to place a pre-offer for the same amount as another pre-offer, the online retail platform may notify the buyer that the pre-offer is invalid and request that the buyer place a higher pre-offer amount. In such examples, once one or more pre-offers have been placed for an item, process 400 may autonomously place an offer for the item, where the offer is an increment of each pre-offer amount. In some such examples, process 400 may autonomously place a respective offer from each of the one or more pre-offers to give the illusion of activity from live buyers.

[0052]

[0056] As an example, at block 402, the live offer period may begin with a two-minute period. The two-minute period may be associated with a countdown timer. In response to activating the live offer period, process 400 may issue an initial offer corresponding to one of one or more prior offers previously issued for the item. The offer corresponding to the prior offer may be an increase amount of the prior offer. As described above, the increase amount may be a percentage of the minimum price or an estimated price increase amount. The offer corresponding to the prior offer may be referred to as an increase offer. The increase offer may be issued when the live offer period is activated or at a randomized time after the live offer period becomes active. If an increase offer is issued during the live period, the process may adjust the offer increase amount and / or the live offer period at block 404. Furthermore, in some examples, after issuing the increase offer, process 400 may pause for a predetermined period of time and wait for live bids (e.g., bids from actual buyers). In such an example, if there are no live bids, process 400 may issue another increased offer corresponding to the same or another pre-offer with a value greater than the previous increased offer. Process 400 may repeatedly issue increased offers until there are no more live bids or until the highest pre-offer amount of one or more pre-offers is reached. After this point, the live offer period may expire and the auction ends.

[0053]

[0057] In another example, an item in a micro listing may have a reserve price of $20. The reserve price may be known to the device implementing process 400. In this example, the highest advance offer may be $15. At block 402, a live offer period begins with a two-minute live offer period, where the item (or each item associated with the category) may start at $1, and the offer increase amount may be $5. Process 400 may issue an increase offer of $5 (e.g., 25% of the reserve price) once the live offer period begins. Further, at block 404, based on the increase offer, process 400 may add 10 seconds to the live offer period. Process 400 may then repeat issuing increase offers, issuing a subsequent increase offer of $10 (e.g., $5 more than the previous increase offer to satisfy the offer increase amount value), thereby bringing the current offer to $10. Further, at block 404, based on the increased offer, process 400 may add another 10 seconds to the live offer period. After issuing the subsequent increased offer, process 400 may wait for a live offer before issuing another increased offer based on the prior offer at block 406. In this example, a live offer may be issued while process 400 is waiting at block 406. Because the offer increase amount is $5, the live offer should be greater than or equal to $15 because the current best offer is $10. In this example, the live offer may be $20, and therefore, a current best offer of $20 is issued. Because the current best offer of $20 is equal to the highest prior offer amount, process 400 does not issue any further increased offers. Further, at block 404, process 400 may adjust the offer increase amount to 25% of the current best bid for the live offer (e.g., $6.25). Process 400 may then wait for a further live offer or for the live offer period to expire at block 406. After a predetermined amount of time with no activity, the process 400 adjusts the offer increase amount to 10% of the current highest offer (eg, $2.50) to induce a new live offer.The live offer period may expire if no new live offers are received, resulting in the listing ending at block 408 .

[0054]

[0058] As described in the example of FIG. 4 , at block 404, process 400 can adjust the offer increase amount and / or adjust the live offer period (e.g., extend the live offer period) based on one or more factors. In some examples, an offer model (e.g., a machine learning model) can be trained to adjust the live offer period and adjust the offer increase amount to attract more buyers, increase the final offer value, and / or increase the probability of meeting the reserve price. Such adjustments are not possible for a human to calculate in real time for one or more listings. For example, by the time a human calculates one or more adjustments (e.g., adjusting the live offer period, adjusting only the offer increase amount to attract more buyers, increasing the final offer value, and / or increasing the probability of meeting the reserve price), a lot of time may have passed in each auction. Thus, the calculations would be meaningless because they should be performed in real time to accommodate the dynamic nature of the auction. In some examples, an offer model can be trained on a configured offer increase amount chart to determine the offer increase amount based on the current highest offer. Additionally or alternatively, the offer increase amount may be adjusted based on the amount of time remaining in the live offer period, the number of offers received, the minimum winning bid price, historical offer patterns for similar items, and / or other factors. Furthermore, an offer model may be trained to adjust the live offer period. In some examples, the offer model may increase the live offer period after an offer (e.g., a live offer or an increased offer corresponding to a prior offer) is made. In some other examples, the offer model may increase the live offer period after waiting for an offer for a period of time. The live offer period may be adjusted based on one or more factors, such as the number of buyers viewing the current micro listing, the number of prior offers made for the item, the current offer price, the time between successive offers, the number of offers made for the item, the buyer's rating, the seller's rating, and / or other factors.As an example, an offer model may determine the number of buyers viewing a current microlisting by determining the number of devices connected to an online retail platform, which may be filtered by device ID, IP address, or another type of identifier.

[0055]

[0059] In some examples, online auction platforms allow buyers to create a personalized view of one or more upcoming listings (e.g., micro-listings). For example, buyers can view all items for sale in one or more categories, pre-bid on one or more items, and select (e.g., browse or favorite) specific items. These selected items are then saved to the buyer's dashboard, where the buyer can further edit and arrange them in preparation for a live listing. Buyers can customize the size of the displayed item box, filter items, and preview their personalized view before a live listing. This allows buyers to optimize their experience and make more informed decisions during a live listing.

[0056]

[0060] FIG. 5 is a flow diagram illustrating an example process 500, performed by, for example, a device, according to various aspects of the present disclosure. The device may be an example of the device 250 described with reference to FIG. 2. The example process 500 is an example of dynamically adjusting one or more elements of an electronic transaction according to various aspects of the present disclosure. As shown in the example of FIG. 5, the process begins at block 502 by initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform. The listing may be associated with a time period and an offer increment amount. The online retail platform may be an example of an online auction site. Furthermore, the electronic transaction occurs through the online retail platform. In some examples, the listing for the item is one listing of a group of listings. For example, the listing may be for jewelry items, and each item in the group of listings may be a jewelry item or an item associated with jewelry. Furthermore, the group of listings and / or each item in the group of listings may be associated with one or more listing categories. For example, the group of listings may be associated with a jewelry category and another category, such as home goods or fashion items. In some examples, the listing may be associated with a minimum bid price. In some such examples, process 500 may issue (e.g., enter) one or more autonomous offers for the item via a machine learning model (e.g., an offer model). Each of the one or more autonomous offers may be less than the minimum bid price. Further, the one or more autonomous offers may simulate live offers from one or more remote buyers. In some examples, when the item is associated with a minimum bid price, process 500 may receive a message from a seller associated with the item requesting a reduction in the minimum bid price. In such examples, process 500 may reduce the minimum bid price based on receiving the message, where the seller is remotely located.

[0057]

[0061] At block 504, process 500 receives an offer for the item from a remote buyer. In some examples, the offer is one offer of a group of offers received from the remote buyer. Each offer in the group of offers may be associated with a group of listings and / or a respective listing in one or more other groups of listings. The groups of offers may be posted simultaneously for each listing.

[0058]

[0062] At block 506, process 500 adjusts the time period and / or the offer increase amount based on receiving the offers and one or more adjustment factors. The one or more adjustment factors include one or more of the following: the number of active connections from remote users to the online listing, the number of offers for the item associated with the online listing, the time between successive offers, the amount of time remaining in the time period, the current highest offer, the remote buyer's rating, the minimum winning bid price, or the number of prior offers. The number of active connections may be determined by monitoring network traffic, including wired and wireless connections to a server associated with the online listing. In some examples, the connections may be filtered by device ID (e.g., IP address, user ID) and / or one or more other types of filtering parameters to determine a number of unique active connections. In some examples, process 500 receives prior offers for the item from remote buyers before starting the time period. In such examples, process 500 may issue (e.g., input) one or more increased offers for the item based on the total value of the prior offers via a machine learning model (e.g., an offer model). The one or more increased offers may pose as live offers from one or more remote buyers. Further, the one or more increased offers may be made until the highest offer for the item is equal to or exceeds the total value of the prior offers.

[0059]

[0063] 5, in block 508, process 500 repeats adjusting the time period and / or the offer increase amount until the time period expires. Finally, in block 510, process 500 ends the listing based on the expiration of the time period. The item may be sold to the buyer with the highest offer after the listing expires, thereby completing the electronic transaction.

[0060]

[0064] The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the embodiments to the precise form disclosed. Modifications and variations may be made in light of the above disclosure or may be acquired from practice of the embodiments.

[0061]

[0065] When used, the term "component" is intended to be broadly interpreted as hardware, firmware, and / or a combination of hardware and software. When used, a processor is implemented in hardware, firmware, and / or a combination of hardware and software.

[0062]

[0066] Some aspects are described in relation to thresholds. When used, meeting a threshold may refer to a value being greater than the threshold, greater than or equal to the threshold, less than the threshold, less than or equal to the threshold, equal to the threshold, and / or not equal to the threshold, depending on the context.

[0063]

[0067] It will be apparent that the described systems and / or methods may be implemented in different forms of hardware, firmware, and / or combinations of hardware and software. The actual specific control hardware or software code used to implement these systems and / or methods is not a limiting aspect. Thus, the operation and behavior of the systems and / or methods are described without reference to specific software code, and it will be understood that software and hardware can be designed to implement the systems and / or methods based at least in part on the specification.

[0064]

[0068] Although particular combinations of features are recited in the claims and / or disclosed herein, these combinations are not intended to limit the disclosure of various aspects. Indeed, many of these features may be combined in ways not specifically recited in the claims and / or disclosed herein. Although each dependent claim listed below may depend directly on only one claim, the disclosure of various aspects includes each dependent claim in combination with all other claims in the claim set. Phrases referring to "at least one of" a list of items refer to any combination of those items, including single members. As an example, "at least one of a, b, or c" is intended to cover a, b, c, ab, ac, bc, and abc, as well as any combination with multiple similar elements (e.g., aa, aaa, aab, aac, abb, acc, bb, bbb, bbc, cc, and ccc, or any other permutation of a, b, and c).

[0065]

[0069] No element, act, or instruction used should be construed as critical or essential unless expressly described as such. Also, when used, the articles "a" and "an" are intended to include one or more items and may be used interchangeably with "one or more." Furthermore, when used, the terms "set" and "group" are intended to include one or more items (e.g., related items, unrelated items, combinations of related and unrelated items, and / or the like) and may be used interchangeably with "one or more." Where only one item is intended, the phrase "only one" or similar language is used. Also, when used, the terms "has," "have," "having," and / or the like are intended to be open-ended terms. Furthermore, the phrase "based on" is intended to mean "based at least in part on," unless expressly specified otherwise.

Claims

1. 1. A method for dynamically adjusting one or more elements associated with an electronic transaction, comprising: initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, wherein the listing is associated with the time period and an offer increment amount; receiving an offer for the item from a remote purchaser; adjusting the time period and / or the offer increase amount based on receiving the offer and one or more adjustment factors; repeating the adjustment of said time period and / or said offer increase amount until said time period expires; Terminating the listing upon expiration of the time period; A method comprising:

2. the listing for the item is one listing of a group of listings; the group of listings is associated with one or more listing categories; The method of claim 1.

3. 3. The method of claim 2, further comprising receiving a group of offers from the remote buyer, each offer in the group of offers being associated with a respective listing in the group of listings, and the group of offers being simultaneously posted for the respective listings in the group of listings.

4. 2. The method of claim 1, wherein the one or more adjustment factors include one or more of the following: the number of active connections from remote users to the online listing, the number of offers for the item associated with the online listing, the time between successive offers, the amount of time remaining in the time period, the current highest offer, the rating of the remote buyer, the minimum winning bid price, or the number of prior offers.

5. receiving a prior offer for the item prior to beginning the time period; making one or more increased offers for the item based on the total value of the prior offers via a machine learning model; Further provided with the one or more increased offers masquerading as live offers from one or more remote purchasers; the one or more increased offers are made until a highest offer for the item is equal to or greater than the total value of the prior offers. The method of claim 1.

6. The method of claim 1 , wherein the online listing is associated with a minimum bid price.

7. and generating one or more autonomous offers for the item via a machine learning model. each of the one or more autonomous offers is less than the reserve price; the one or more autonomous offers posing as live offers from one or more remote buyers; The method of claim 6.

8. receiving a message from a seller associated with the item requesting a reduction in the reserve price; reducing the reserve price based on receipt of the message; 7. The method of claim 6, further comprising: wherein the merchant is remotely located.

9. 1. An apparatus for dynamically adjusting one or more factors associated with an electronic transaction, comprising: a processor; a memory coupled to the processor; the memory, when executed by the processor, causes the device to initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, wherein the listing is associated with the time period and an offer increment amount; receiving an offer for the item from a remote purchaser; adjusting the time period and / or the offer increase amount based on receiving the offer and one or more adjustment factors; repeating the adjustment of said time period and / or said offer increase amount until said time period expires; Terminating the listing upon expiration of the time period; storing instructions operable to cause a device to perform the

10. the listing for the item is one listing of a group of listings; the group of listings is associated with one or more listing categories; 10. The apparatus of claim 9.

11. 11. The device of claim 10, wherein execution of the instructions further causes the device to receive a group of offers from the remote buyer, each offer in the group of offers being associated with a respective listing in the group of listings, and the group of offers being simultaneously posted for the respective listings in the group of listings.

12. 10. The device of claim 9, wherein the one or more adjustment factors include one or more of the number of active connections from remote users to the online listing, the number of offers for the item associated with the online listing, the time between successive offers, the amount of time remaining in the time period, the current highest offer, the rating of the remote buyer, the minimum winning bid price, or the number of prior offers.

13. Execution of the instructions causes the device to: receiving a prior offer for the item prior to beginning the time period; making one or more increased offers for the item based on the total value of the prior offers via a machine learning model; Further, the one or more increased offers masquerading as live offers from one or more remote purchasers; the one or more increased offers are made until a highest offer for the item is equal to or greater than the total value of the prior offers.

10. The apparatus of claim 9.

14. Execution of the instructions further causes the device to make one or more autonomous offers for the item via a machine learning model; the online listing is associated with a minimum bid price; each of the one or more autonomous offers is less than the reserve price; the one or more autonomous offers posing as live offers from one or more remote buyers; 10. The apparatus of claim 9.

15. Execution of the instructions causes the device to: receiving a message from a seller associated with the item requesting a reduction in the reserve price; reducing the reserve price based on receipt of the message; 15. The apparatus of claim 14, further comprising:

16. A non-transitory computer-readable medium having recorded thereon program code for dynamically adjusting one or more factors associated with an electronic transaction, the program code being executed by a processor; program code for initiating a time period for receiving live offers via an online interface for an item associated with a listing on an online retail platform, the listing being associated with the time period and an offer increase amount; program code for receiving offers for the item from remote purchasers; program code for adjusting the time period and / or the offer increase amount based on receiving the offer and one or more adjustment factors; program code for repeating adjustments to the time period and / or the offer increase amount until the time period expires; program code for terminating the listing based on expiration of the time period; 1. A non-transitory computer-readable medium comprising:

17. 17. The non-transitory computer-readable medium of claim 16, wherein the program code further comprises program code for receiving a group of offers from the remote buyer, each offer in the group of offers being associated with a respective listing in the group of listings, and the group of offers being simultaneously posted for the respective listings in the group of listings.

18. 17. The non-transitory computer-readable medium of claim 16, wherein the one or more adjustment factors include one or more of the number of active connections from remote users to the online listing, the number of offers for the item associated with the online listing, the time between successive offers, the amount of time remaining in the time period, the current highest offer, the rating of the remote buyer, the minimum winning bid price, or the number of prior offers.

19. The program code program code for receiving an advance offer for the item prior to beginning the time period; program code for making one or more increased offers for the item based on the total value of the prior offers via a machine learning model; Further provided with the one or more increased offers masquerading as live offers from one or more remote purchasers; the one or more increased offers are made until a highest offer for the item is equal to or greater than the total value of the prior offers.

17. The non-transitory computer-readable medium of claim 16.

20. the program code further comprising: program code for making one or more autonomous offers for the item via a machine learning model; the online listing is associated with a minimum bid price; each of the one or more autonomous offers is less than the reserve price; the one or more autonomous offers posing as live offers from one or more remote buyers; 17. The non-transitory computer-readable medium of claim 16.

Images