A transaction management method for a real estate sales system

Abstract

The application provides a transaction management method for a house selling system. A transaction management method for a house selling system comprises the following steps: screening house resources based on a house purchase request to obtain a first house resource set; determining whether the number of house resources in the first house resource set is greater than a preset number; if yes, showing the first house resource set to a user; otherwise, screening a second house resource set and showing the second house resource set to the user; receiving target house resource information, querying environmental information around the target house resource, and sending the environmental information to the user; receiving house purchase pre-application information, and generating transaction information based on the house purchase pre-application information. The application screens house resources based on a house purchase request of a user, obtains house resources meeting the user's intention, and recommends the house resources to the user. According to the target house resource selected by the user, corresponding geographical position information is screened out for the user to refer to, and a suitable detail query list is recommended to the user to view the detail information of the house resource, so that the recommendation efficiency is improved, and the transaction is smoothly promoted.

Description

Technical Field

[0001] This invention relates to the field of sales management technology, and in particular to a transaction management method for a sales system. Background Technology

[0002] When buying a house, people usually consider many factors, such as price, location, lighting, and transportation. Therefore, they need to spend a considerable amount of time selecting a property. For sales offices, sales staff typically provide customers with various materials to help them gain a deeper understanding of the properties for sale.

[0003] During the sales process, after learning about various data and information, customers usually choose to visit the property in person to understand the details of the house. In this process, the photos provided by the sales staff may differ from the actual property, leading to customer dissatisfaction and ultimately preventing the transaction from being completed. This wastes a lot of time for both parties. Summary of the Invention

[0004] This invention provides a transaction management method for a real estate sales system, aiming to solve at least one of the technical problems mentioned in the background art above.

[0005] The technical solution of this invention is: a transaction management method for a real estate sales system, comprising:

[0006] Receive a home purchase request from a user, extract expected conditions from the home purchase request, and filter the housing resources according to the expected conditions and the first screening conditions to obtain a first set of housing resources;

[0007] Determine whether the number of properties in the first property set is greater than the preset number. If the number of properties in the first property set is greater than the preset number, then the first property set is displayed to the user. Otherwise, the properties are filtered according to the expected conditions and the second filtering conditions to obtain the second property set, and the second property set is displayed to the user.

[0008] Receive target property information sent by the user, extract geographical location information from the target property information, query the environmental information around the target property based on the geographical location information, and send the environmental information around the target property to the user;

[0009] Receive pre-purchase application information from users and generate transaction information based on the pre-purchase application information.

[0010] Furthermore, the step of filtering the housing resources according to the expected conditions and the first screening conditions to obtain the first set of housing resources includes:

[0011] The properties are filtered by each element in the expected conditions to obtain a property list corresponding to each element. Properties that exist in the property list corresponding to each element are filtered out to construct the first property set.

[0012] The step of filtering the properties according to the expected conditions and the second screening conditions to obtain the second set of properties includes:

[0013] The expected conditions are expanded according to the preset expansion scheme to obtain the expanded expected conditions. The properties corresponding to the first property set are removed from the property list to obtain the target properties. The target properties are then filtered using the expanded expected conditions to obtain the second property set.

[0014] Furthermore, it also includes:

[0015] Based on the target property information, a detailed query list of target properties is determined and sent to the user. In response to the user's detailed query request, the detailed query list of target properties is sorted according to the expected conditions, and the sorted detailed query list of target properties is displayed to the user.

[0016] Furthermore, sorting the target property details query list according to the expected conditions includes:

[0017] Sort all elements in the expected conditions according to the selection time of each element in the expected conditions, establish a mapping relationship between each element in the expected conditions and each query item in the target property details query list, map all elements in the sorted expected conditions according to the mapping relationship between each element in the expected conditions and each query item in the target property details query list to obtain a mapping query list, and use the mapping query list as the sorted target property details query list.

[0018] Furthermore, it also includes:

[0019] The system acquires user browsing data for target properties, including the start and end times of browsing each query item in the target property details query list. Based on the browsing data, the system calculates an expected value, sorts the target properties according to the expected value, and recommends the sorted target properties to the user.

[0020] Furthermore, calculating the expected value based on the browsing data includes:

[0021] The browsing time of each query item in the target property details query list is calculated based on the user's browsing start time and browsing end time.

[0022] The search terms in the target property details search list are sorted based on the user's browsing start time for each search term. The expected value is then calculated using the following formula:

[0023] E = α1t1 + α2t2 + ... + αntn;

[0024] In the formula, E represents the expected value, t1, t2, ..., tn are the browsing durations corresponding to the first to nth query items after sorting, and α1, α2, ..., αn are the weight parameters corresponding to the first to nth query items, where α1 < α2 < ... < αn.

[0025] Furthermore, it also includes:

[0026] Receive user requests to view the target property in person, query the record of such requests, determine if other users are viewing the target property, and if so, issue a duplicate notification.

[0027] The system processes on-site inspection requests based on user feedback regarding repeated reminders to the target. If the on-site inspection request is approved, the system records the user's location information in real time.

[0028] The beneficial effects of this invention are as follows:

[0029] This invention filters housing listings based on users' home purchase requests, obtains listings that match users' preferences, and recommends these listings to users. It also filters the corresponding geographical location information of the target housings selected by users for their reference and recommends a suitable detailed query list so that users can view the detailed information of the housings, thereby improving recommendation efficiency and facilitating smooth transactions. Attached Figure Description

[0030] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0031] Figure 1 This is a flowchart illustrating a transaction management method for a sales system in an embodiment of the present invention. Detailed Implementation

[0032] To make the objectives, technical solutions, and advantages of this application clearer, some embodiments of this application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. However, those skilled in the art will understand that many technical details have been provided in the various embodiments of this application to facilitate a better understanding of the application. However, the technical solutions claimed in this application can be implemented even without these technical details and various variations and modifications based on the following embodiments.

[0033] Example 1

[0034] See Figure 1 Embodiment 1 of the present invention provides a transaction management method for a sales system, which is applied to a sales system. Specifically, the sales system is a system used by a developer's sales office to query information on various housing units. In this embodiment, it can be understood as product sales software. Through the sales system, basic information and status information of housing units can be queried. Specifically, it includes the following steps:

[0035] S1. Receive a home purchase request from a user and extract the expected conditions from the home purchase request;

[0036] It should be noted that users can make a purchase request through the device provided by the sales office that is equipped with the sales system software, or through their own smart device, such as a smartphone. In this embodiment, no specific restrictions are imposed. Furthermore, the purchase request made by the user can also be understood as a purchase request generated in accordance with the user's wishes. The purchase request can also be made by the sales staff based on the user's wishes by operating the sales system software, and it is not limited to the customer making the operation.

[0037] The purchase request includes conditions selected by the user, such as price, floor height, property size, property model, and other information related to purchasing a property. Expected conditions can be extracted from the purchase request.

[0038] S2. Filter the properties according to the expected conditions and the first screening conditions to obtain a first set of properties;

[0039] It should be added that the first screening criterion follows the principle of complete compliance, meaning that the selected properties completely meet every element of the expected criteria. Specifically, this includes the following screening steps:

[0040] The properties are filtered by each element in the expected conditions to obtain a property list corresponding to each element. Properties that exist in the property list corresponding to each element are filtered out to construct the first property set.

[0041] It should be noted that, for example, the expected conditions include expected floor, expected area, expected price, etc., and properties that meet the corresponding floor, property area, and price below the expected price are selected to construct the first property set.

[0042] S3. Determine whether the number of properties in the first property set is greater than the preset number. If yes, proceed to step S4; otherwise, proceed to step S5.

[0043] It should be added that the purpose of setting a preset number is to avoid having too few listings that match the user's preferences, resulting in a limited selection and a poor user experience.

[0044] S4. Display the first collection of properties to users;

[0045] S5. Filter the properties according to the expected conditions and the second filtering conditions to obtain a second property set, and display the second property set to the user;

[0046] It should be noted that the second screening criterion has a broader scope than the first screening criterion, and specifically includes the following screening steps:

[0047] The expected conditions are expanded according to the preset expansion scheme to obtain the expanded expected conditions. The properties corresponding to the first property set are removed from the property list to obtain the target properties. The target properties are then filtered using the expanded expected conditions to obtain the second property set.

[0048] It should be noted that the preset expansion plan is a pre-determined plan, which includes a plan for each element. For example, regarding the expected floor, if the user expects the 6th and 7th floors, the preset expansion plan can also include the 5th and 8th floors in the expected conditions. Taking price as another example, if the user expects a price not exceeding 20,000, the preset expansion plan can also include a price not exceeding 21,000 in the expected conditions. After expanding the expected conditions, the properties are then filtered based on the expanded expected conditions to provide users with more choices.

[0049] S6. Receive target property information sent by the user, and extract geographical location information from the target property information;

[0050] It should be noted that after sending the user the property listings that match their preferences, the user can browse them using relevant devices such as smartphones and tablets, and select the property they want. The sales system receives the user's target property information and extracts the corresponding geographical location information. As you can imagine, the number of properties in the target property information can be one or more, and the target property information will include the geographical location information of each property.

[0051] S7. Query the environmental information around the target property based on the geographical location information and send the environmental information around the target property to the user;

[0052] It should be noted that the surrounding environment information of the target property can be queried based on the geographical location information of the target property, such as the surrounding transportation routes, such as subway stations, bus stations and other related information, and the types of surrounding areas, such as whether they include educational, medical, ecological park and other related buildings. In this step, the information about the surrounding area of ​​the target property is extracted and sent to the user so that the user can have a better understanding of the target property.

[0053] S8. Receive the pre-purchase application information sent by the user, and generate transaction information based on the pre-purchase application information.

[0054] It should be noted that after users have a detailed understanding of the target property, they can choose whether to purchase it based on their actual situation. If they are interested in purchasing, they can submit their purchase request, and the system will generate corresponding transaction details based on the user's request to facilitate the relevant home purchase transaction.

[0055] In one optional implementation, the process by which users learn about property information also includes:

[0056] Based on the target property information, a detailed search list of target properties is determined and sent to the user.

[0057] It should be noted that once a user has a target property, a detailed search list of the target property can be generated based on that property. This detailed search list includes detailed images, videos, and other information captured on the property, such as detailed information about the corresponding locations of the target property, including the lobby, kitchen, bathroom, rooms, and balcony. Keywords can be extracted for each area as an index to create a detailed search list of the target property and send it to the user.

[0058] In response to a user's detailed query request, the target property details query list is sorted according to the expected conditions, and the sorted target property details query list is displayed to the user.

[0059] It should be noted that users can learn more about the target property through the detailed property search list. When a user wants to search for detailed information about a property, the system can respond to the user's detailed search request and display all the detailed information to the user for easy searching.

[0060] To improve efficiency, users can search for detailed information about target properties based on their desired criteria, allowing them to quickly find the information they need. This includes the following:

[0061] Sort all elements in the expected conditions according to the selection time of each element in the expected conditions;

[0062] It should be noted that the elements in the expected conditions can be sorted according to the order of time, with the elements that the customer cares about first. For example, if the user has high requirements for the balcony's lighting and was selected earlier, then the elements related to the balcony can be sorted first.

[0063] Establish a mapping relationship between each element in the expected conditions and each query item in the target property details query list. Based on the mapping relationship between each element in the expected conditions and each query item in the target property details query list, map all elements in the sorted expected conditions to obtain a mapping query list. Use the mapping query list as the sorted target property details query list.

[0064] It should be noted that the expected conditions include multiple pieces of information. The target property details query list includes some details about the interior of the property and some details about its surroundings. A mapping relationship can be established between the two. For example, if the expected conditions include content about lighting, a mapping relationship can be established between the elements in the expected conditions related to lighting and the index terms related to windows, balconies, etc. in the target property details query list. After all the elements in the expected conditions are sorted, the sorted elements are mapped to obtain the index terms corresponding to each element. The index terms are sorted according to the sorting method of the elements to obtain a sorted target property details query list. Users can more easily understand the details about the property they want to know.

[0065] In one optional implementation, the process of a user browsing a target property also includes:

[0066] Obtain user browsing data for target properties;

[0067] It should be noted that the browsing data includes at least the start and end times of the user's browsing of each query item in the target property details query list.

[0068] The expected value is calculated based on the browsing data, the target properties are sorted according to the expected value, and the sorted target properties are recommended to the user.

[0069] It should be noted that the system can analyze users' browsing data of target properties to determine their preference for each property within the target properties list. By calculating users' expectations for each property in the target properties list, the properties can be sorted according to these expectations, and properties with high expectations can be further recommended to users.

[0070] In one optional implementation, calculating the expected value based on the browsing data includes:

[0071] The browsing time of each query item in the target property details query list is calculated based on the user's browsing start time and browsing end time.

[0072] The search terms in the target property details search list are sorted based on the user's browsing start time for each search term. Specifically, earlier browsing start times result in higher ranking. For each sorted search term, the expected value is calculated based on the browsing duration of each search term using the following formula:

[0073] E = α1t1 + α2t2 + ... + αntn;

[0074] In the formula, E represents the expected value, t1, t2, ..., tn are the browsing durations corresponding to the first to nth query items after sorting, and α1, α2, ..., αn are the weight parameters corresponding to the first to nth query items, where α1 < α2 < ... < αn.

[0075] It should be noted that α1, α2, ..., αn are the weight parameters corresponding to the first to nth query items in the sorted order, respectively. The values ​​of α1, α2, ..., αn are fixed and not specific to any particular property. For any property query item, after the query items for that property are sorted, the weight parameter corresponding to the first query item in the sorted order is α1, the weight parameter corresponding to the second query item in the sorted order is α2, and so on, with the weight parameter corresponding to the last query item in the sorted order being αn. Furthermore, during the browsing process, the further along the browsing order, the greater the proportion of browsing time it occupies.

[0076] In one optional implementation, it also includes:

[0077] Receive user requests to view the target property in person, query the record of such requests, determine if other users are viewing the target property, and if so, issue a duplicate notification.

[0078] It should be noted that when users are selecting properties, after learning about various information about the target property, they may want to visit it in person. In this case, the system first retrieves the corresponding visit request records for the target property to determine if other users are currently viewing it. If other users are viewing it without the current user's knowledge, it may affect the user's mood and prevent the transaction from proceeding smoothly. Therefore, if other users are viewing the target property, a duplicate notification is sent to the user.

[0079] The system processes on-site inspection requests based on user feedback regarding repeated reminders to the target. If the on-site inspection request is approved, the system records the user's location information in real time.

[0080] It should be noted that after receiving repeated reminders about the target, users may choose not to go to the site or continue to go to the site. The site visit request can be processed according to the user's actual choice to improve the user experience.

[0081] It should be understood that those skilled in the art can make improvements or modifications based on the above description, and all such improvements and modifications should fall within the protection scope of the appended claims. Parts not described in detail in this specification are prior art known to those skilled in the art.

Claims

1. A transaction management method for a real estate sales system, characterized in that, include: Receive a home purchase request from a user, extract expected conditions from the home purchase request, and filter the housing resources according to the expected conditions and the first screening conditions to obtain a first set of housing resources; Determine whether the number of properties in the first property set is greater than the preset number. If the number of properties in the first property set is greater than the preset number, then the first property set is displayed to the user. Otherwise, the properties are filtered according to the expected conditions and the second filtering conditions to obtain the second property set, and the second property set is displayed to the user. Receive target property information sent by the user, extract geographical location information from the target property information, query the environmental information around the target property based on the geographical location information, and send the environmental information around the target property to the user; Receive pre-purchase application information from users and generate transaction information based on the pre-purchase application information; The step of filtering the housing resources according to the expected conditions and the first screening conditions to obtain the first set of housing resources includes: The properties are filtered by each element in the expected conditions to obtain a property list corresponding to each element. Properties that exist in the property list corresponding to each element are filtered out to construct the first property set. The step of filtering the properties according to the expected conditions and the second screening conditions to obtain the second set of properties includes: The expected conditions are expanded according to the preset expansion scheme to obtain the expanded expected conditions. The properties corresponding to the first property set are removed from the property list to obtain the target property list. The target property list is then filtered using the expanded expected conditions to obtain the second property set. Also includes: Based on the target property information, a detailed query list of target properties is determined and sent to the user. In response to the user's detailed query request, the detailed query list of target properties is sorted according to the expected conditions, and the sorted detailed query list of target properties is displayed to the user. The sorting of the target property details query list according to the expected conditions includes: Sort all elements in the expected conditions according to the selection time of each element in the expected conditions, establish a mapping relationship between each element in the expected conditions and each query item in the target property details query list, map all elements in the sorted expected conditions according to the mapping relationship between each element in the expected conditions and each query item in the target property details query list to obtain a mapping query list, and use the mapping query list as the sorted target property details query list. Also includes: The system acquires user browsing data for target properties, including the start and end times of browsing each query item in the target property details query list. Based on the browsing data, the system calculates the expected value, sorts the target properties according to the expected value, and recommends the sorted target properties to the user. The step of calculating the expected value based on the browsing data includes: The browsing time of each query item in the target property details query list is calculated based on the user's browsing start time and browsing end time. The search terms in the target property details search list are sorted based on the user's browsing start time for each search term. The expected value is then calculated using the following formula: E = α1t1 + α2t2 + … + αntn; In the formula, E represents the expected value, t1, t2, ..., tn are the browsing time corresponding to the first to nth query items after sorting, and α1, α2, ..., αn are the weight parameters corresponding to the first to nth query items, where α1 < α2 < ... < αn; Also includes: Receive user requests to view the target property in person, query the record of such requests, determine if other users are viewing the target property, and if so, issue a duplicate notification. The system processes on-site inspection requests based on user feedback regarding repeated reminders to the target. If the on-site inspection request is approved, the system records the user's location information in real time.

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