Vehicle reservation process optimization method and system based on maximization of user rights and interests

Abstract

The invention provides a user right maximization-based vehicle booking process optimization method and system, and the method comprises the steps: collecting and analyzing behavior data, order data, log data, channel information data and industry data of a user in a vehicle booking process, and obtaining a preferential maximization result; according to the preferential maximization result, pushing corresponding discount coupon information, and adding and displaying a total order price in a vehicle model lease period and a second-level page display of expense details corresponding to the total order price on a vehicle model list page; and after the user confirms the order placing data, the coupon with the maximum denomination which can be used by the user in the coupon list is checked by default on an order confirmation page. The user experience is improved, and the rights and interests of the user are guaranteed to the maximum extent.

Description

Technical Field

[0001] The present invention belongs to the technical field of vehicle rental, and in particular relates to a method and system for optimizing a vehicle reservation process based on maximizing user rights and interests. Background Art

[0002] With the development of Internet technology, online car rental services are becoming more and more popular. However, the recommendation strategies of existing car rental services cannot meet the needs of users, resulting in a certain loss of customers on the car rental platform. The main reason for this phenomenon is the uncertainty of user behavior. The user's booking behavior may be affected by many factors, including personal preferences, budget, time, etc., so it is difficult to accurately predict and meet the needs of each user.

[0003] According to existing user data, most users are still sensitive to price and hope to use the coupon with the largest denomination in the booking process. However, there are still users who want to use the coupon that is about to expire first, rather than giving priority to the coupon with the largest denomination. Therefore, there is an urgent need for an optimization method and system for the vehicle booking process that can maximize user rights. Summary of the invention

[0004] The purpose of the present invention is to overcome the above-mentioned shortcomings and to provide a method and system for optimizing the vehicle reservation process based on maximizing user rights and interests, so as to ensure that users can enjoy more convenient, efficient, transparent and personalized services throughout the entire reservation process, thereby maximizing the protection of user rights and interests.

[0005] To achieve the above-mentioned purpose, the present invention provides a method for optimizing a vehicle booking process based on maximizing user rights and interests, which comprises: collecting and analyzing the user's behavior data, order data, log data, channel information data and industry data in the process of booking a vehicle to obtain a discount maximization result; according to the discount maximization result, pushing corresponding coupon information, and adding a secondary page display showing the total order price within the vehicle model rental period and the fee details corresponding to the order total price on the vehicle model list page; when the user confirms the order data, on the order confirmation page, the coupon with the largest denomination that the user can use in the coupon list is checked by default.

[0006] Optionally, the behavior data includes user click data, page browsing data, page dwell time data and user behavior path data; the order data includes the order's scheduled pick-up time, scheduled return time, car model name, pick-up city, return city, pick-up store, return store, order discount amount and order total amount.

[0007] Optionally, the push time of the corresponding coupon information based on the discount maximization result is: when the number of car models browsed by the user on the car model list page is greater than or equal to N models, the available coupon information is pushed; and / or when the number of times the user browses the order confirmation page is greater than or equal to J times, the available coupon information is pushed; wherein N≥4, J≥3, and N and J are both integers.

[0008] Optionally, when a user browses the vehicle model list page, order confirmation page and / or vehicle details page more than M times, a vehicle model configuration quick screening entry is added to the vehicle model list page, allowing the user to quickly screen the vehicle model that meets his or her booking expectations; where M≥5 and is an integer.

[0009] Optionally, the vehicle model configuration quick screening includes the following steps: S1, merging the vehicle models with the same model name in the vehicle model list page; S2, the user further filters according to additional conditions; the additional conditions include license plate type and whether self-service pick-up is available.

[0010] Optionally, the model list page increases the total order price during the model rental period, which includes the rental fee, basic insurance fee, handling fee and the total cost after deducting the coupon with the largest face value.

[0011] Optionally, a first notification mark of fee details is added on the order confirmation page; and / or a second notification mark of a small question mark rule explanation is added on the order confirmation page to explain the fees that users have many doubts about; and / or a third notification mark of car rental instructions is added at the bottom of the order confirmation page; the car rental instructions include: cancellation rules before picking up the car, order change rules during rental, car pick-up voucher, deposit payment, and invoice information.

[0012] Optionally, a specific booking entrance is added to the homepage of vehicle booking; the specific entrance includes a 24-hour booking entrance and a long-rental booking entrance; the store list page is entered through the 24-hour booking entrance, and the business hours of the stores in the store list page are all 24 hours; the default rental period of all vehicles in the vehicle model list page entered through the long-rental booking entrance is 30 days.

[0013] Optionally, for coupons in the coupon list with a validity period of less than or equal to 7 days, a reminder label "Expires in K days" is added to the coupon; where K = expiration date of the coupon - current date; when the user has membership benefits that can be deducted for delayed return of the vehicle or worry-free return of the vehicle, a membership label "Deduction for membership benefits" is added to the order confirmation page.

[0014] Another aspect of the present invention also provides an optimization system for a vehicle reservation process based on maximizing user benefits, which includes a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the optimization method as described above.

[0015] In summary, compared with the prior art, the vehicle reservation process optimization method and system provided by the present invention based on maximizing user rights and interests has the following beneficial effects:

[0016] (1) Improve user experience by adjusting the style of the car model list page, adding a secondary page displaying the total order price during the car model rental period and the fee details corresponding to the total order price, thereby reducing the complexity of user operations and waiting time, improving the efficiency and success rate of booking, and enabling users to quickly complete bookings and obtain a better service experience;

[0017] (2) Enhance user trust by adding a first notice of fee details, a second notice of question mark rules, and a third notice of car rental instructions on the order confirmation page, thereby providing clear and transparent booking information such as price, refund and change policies, service standards, etc., and protecting user data security and privacy, thereby increasing users' trust in the booking platform and services;

[0018] (3) Optimize resource allocation. By setting the push time of coupon information and the value-added service recommendation module, accurate demand forecasting and efficient order processing mechanism can be achieved, and resource allocation and utilization efficiency can be optimized to ensure that suppliers can meet user needs while reducing resource waste;

[0019] (4) Promoting sustainable development: Optimization methods based on maximizing user benefits can help improve user satisfaction and loyalty, thereby promoting the sustainable development and growth of the booking platform. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a flowchart of a method for optimizing a vehicle reservation process based on maximizing user rights and interests provided by an embodiment of the present invention;

[0021] Figure 2 It is a schematic diagram of steps for obtaining a preferential maximization result in a method for optimizing a vehicle reservation process based on maximizing user rights and interests provided by an embodiment of the present invention;

[0022] Figure 3 It is a module schematic diagram of a cashier management system provided by an embodiment of the present invention;

[0023] Figure 4It is a schematic diagram of the execution steps of a cashier system after a user submits an order and initiates payment in a method for optimizing a vehicle reservation process based on maximizing user rights and interests provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the attached embodiment of the present invention Figure 1 ~Attached Figure 3 , the technical solutions, structural features, objectives achieved and effects in the embodiments of the present invention are described in detail.

[0025] It should be noted that the drawings are in a very simplified form and use non-precise proportions. They are only used to conveniently and clearly assist in explaining the embodiments of the present invention, and are not used to limit the conditions for the implementation of the present invention. Therefore, they have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical content disclosed by the present invention.

[0026] It should be noted that, in the present invention, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only the elements explicitly listed, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0027] like Figure 1 As shown, this embodiment provides an optimization method for a vehicle booking process based on maximizing user rights and interests, which includes: S101, collecting and analyzing the user's behavior data, order data, log data, channel information data and industry data in the process of booking a vehicle, and obtaining the result of maximizing the discount; S102, according to the result of maximizing the discount, pushing the corresponding coupon information, and adding the total order price within the rental period of the vehicle model on the vehicle model list page, and setting the fee details corresponding to the total order price on the secondary page for display; S103, when the user confirms the order data, on the order confirmation page, the coupon with the largest denomination that the user can use in the coupon list is checked by default. In this embodiment, by adjusting the layout of the vehicle model list page, adding the display of the total order price within the rental period of the vehicle model, and the secondary page display of the fee details corresponding to the total order price, the order total price information of the coupon with the largest denomination checked is presented to the user first, so that the user can quickly place an order, and at the same time reduce the scenario where the user cancels the order because of forgetting to select the coupon.

[0028] Further, if Figure 2 As shown, the steps of obtaining the preferential maximization result include:

[0029] S111, data collection, in this embodiment, the sensor data analysis SDK is used to collect the behavior data, order data, log data, channel information data and industry data;

[0030] Among them, the behavior data includes the user's click data, browsing page data, page dwell time data, and user behavior path data; for example, user A stays on the car model list page (browsing page data) for 10 seconds (page dwell time data), views 3 car models (click data), then selects the last car, enters the order confirmation page, and finally submits the order. The order data includes the order's scheduled pick-up time, scheduled return time, car model name, car pick-up city, car return city, car pick-up store, car return store, order discount amount, and order total amount. The log data includes order placement operation records and order modification operation records. The order content includes: user ID, car model ID, order ID, operator ID, etc. The channel information includes: channel number, channel source, user order pick-up time, car return time, car model information, order amount, channel discount amount, etc. The industry data includes: industry rental information, competing company car model categories, daily rental fees of competing companies' cars of the same level, and value-added service information of competing companies' car rental processes.

[0031] S112, pre-processing the collected data; specifically, combining the behavior data and business data generated by the user when booking a vehicle, and associating them through the user ID, to find out the behavior path of the user before submitting the order, first from individual cases, then to the crowd, to divide similar groups, find the special commonalities of the groups, and form different types of user groups; such as high-end car user groups, experienced driver groups, and self-driving tour groups, etc. The vehicle booking includes selecting the time to use the vehicle, the store to use the vehicle, and the model.

[0032] S113. Build a preferential network for different types of user groups; for example, for high-end car user groups, give priority to recommending high-end car models on the car model list page, and arrange the high-end car models in a higher order; secondly, on the order confirmation page, recommend high-end protection options, such as "worry-free throughout the journey" protection.

[0033] S114, determining the search path, specifically including: S1141, checking the types and quantities of coupons included in the user's account; S1142, checking the number of times the user browses the model list page and the number of times the user views the vehicle details; S1143, searching for the user's frequently used models in history; determining the user's reservation expectation data through steps S1141 to S1143;

[0034] S115. Get the result of maximizing discounts based on the user's booking expectation data; for example, for economically affordable people, recommend relatively cheaper models, and on the model list page and order confirmation page, check the coupon with the largest denomination in the user's account by default; in addition, on the order confirmation page, when the user submits the order, if the user has not purchased the value-added service, the user will be retained and reminded to purchase the value-added service to reduce travel risks. Further, in the value-added service recommendation module, the user will be recommended to purchase based on the user's purchase behavior of historical orders and the protection purchased by similar users when traveling; for example, if the user purchased premium protection last time, the premium protection area will be marked with a label of "last purchase" on the order confirmation page; for another example, for high-end car users, high-end car users have higher requirements for travel quality, so the "worry-free" value-added service will be marked with a label of "super value selection".

[0035] Among them, since the promotional activities usually include various restrictions, when the coupon with the largest denomination in the user's account is checked by default, it is necessary to filter out the coupon with the largest denomination that best suits the user according to the restrictions through the benefit maximization strategy algorithm. In some embodiments, the restrictions on the coupons include: the coupons cannot be used on holidays and the day before holidays, the coupons cannot be used at the same time as some member benefits; the coupons for some car models cannot be used; the coupons with some rental period restrictions cannot be used, etc.

[0036] Among them, the push time of pushing the corresponding coupon information according to the discount maximization result described in step S102 is: when the number of models browsed by the user on the model list page is greater than or equal to N models, the available coupon information is pushed; and / or when the number of times the user browses the order confirmation page is greater than or equal to J times, the available coupon information is pushed; wherein, N≥4, J≥3, and N and J are both integers. This is because the research found that when the user browses 4 models on the model list page or the user browses the order confirmation page 3 times, the willingness to place an order is higher. Therefore, when the user browses the third model, a coupon dialog box can be popped up to push and inform the user which coupons are currently waiting to be used, thereby increasing the effective exposure rate of coupons, using coupons to guide users to place orders, and facilitating users to place orders.

[0037] Furthermore, when a user browses the model list page, order confirmation page and / or vehicle details page for more than M times, a model configuration quick screening entry is added to the model list page, so that the user can quickly screen the model that meets his or her booking expectations; where M≥5 and is an integer. This is because research has found that when a user browses the model list page, order confirmation page and / or vehicle details page for more than 5 times, it means that the user is more entangled in the choice of model. Therefore, by adding a model configuration quick screening entry to the model list page, users can quickly find their favorite model, thereby improving the order conversion rate.

[0038] The vehicle model configuration quick screening includes the following steps: S1, merging the vehicle models with the same vehicle model name in the vehicle model list page; S2, the user further screens according to additional conditions; the additional conditions include license plate type, whether self-service pick-up and return are available, etc. By merging the vehicle models with the same vehicle model name in step S1, the user is asked to select the vehicle model first, and then screen the additional conditions on the selected vehicle model, which reduces repeated options for the user, thereby helping the user reduce the entangled options and is more conducive to the generation of orders.

[0039] Since the total cost of a car rental order also includes basic security fees and handling fees, there may be a situation where the user sees a relatively cheap price for each car on the car model list page, but the price is relatively high when the user reaches the order confirmation page. For example, the user sees that the price of model A on the car model list page is 90 yuan / day, but the price of model A on the order confirmation page is 230 yuan / day, which leads to the phenomenon of abandoning the platform due to large price differences. Therefore, in this embodiment, the car model list page adds the total price of the order during the rental period of the car model, which includes the total cost after deducting the maximum denomination of the coupon, so that the car rental price seen by the user on the car model list page is consistent with the price seen on the order confirmation page, reducing the phenomenon of abandoning the platform due to large price differences and improving the success rate of user order submission.

[0040] Furthermore, in order to improve price transparency and increase users' trust in the booking platform and services, the strike-through price, total price, and current price information of the estimated daily rental price after using the coupon are added to each car model on the car model list page; at the same time, a first notification mark of fee details is added to the order confirmation page; and / or a second notification mark of a small question mark rule explanation is added to the order confirmation page to explain the fees that users question most; and / or a third notification mark of car rental instructions is added to the bottom of the order confirmation page; the car rental instructions include: cancellation rules before picking up the car, order change rules during rental, car pick-up voucher, deposit payment, invoice information, etc.

[0041] Furthermore, based on the user data analysis results, a variety of booking methods are provided, and a specific booking entrance is added to the homepage of vehicle booking; the specific entrance includes a 24-hour booking entrance and a long-rental booking entrance; through the 24-hour booking entrance, the store list page is entered, and the store business hours in the store list page are all 24 hours, so that the store information can more accurately meet user needs; the default rental period of all vehicles in the vehicle model list page entered through the long-rental booking entrance is 30 days, and the models that meet the long-rental discounts are automatically screened out to accurately meet user needs.

[0042] In other embodiments, the user wants to use the expiring coupons first, rather than using the coupons with the largest denomination first. Therefore, for the coupons in the coupon list with a validity period of less than or equal to 7 days, a reminder label "Expires in K days" is added to the coupon; where K = coupon expiration date - current date, which can help users quickly select expiring coupons and improve the user experience. Furthermore, when the user has membership rights that can be deducted for delayed or worry-free car returns, a member label "Member rights can be deducted" is added to the order confirmation page. For example, the subsequent refueling service fee and 2 hours of overtime fee can be deducted through rights, allowing users to book with confidence, improving the efficiency and success rate of booking, and enabling users to complete bookings quickly.

[0043] As the scale of enterprises expands and the business becomes more complicated, the traditional cashier management system can no longer meet the needs of vehicle reservations. Therefore, this embodiment also provides a cashier management system 200, such as Figure 3 As shown, it includes: a payment method management module 201, which is used to manage the increase and decrease of payment channels, and the payment channels include WeChat payment, Alipay payment, UnionPay payment, etc.; a payment method icon management module 202, which is used to update and maintain the validity of each payment method icon; a payment method activity management module 203, which is used to manage the trigger mechanism and activity start / end time of preferential activities; a cashier sorting management module 204, which is used to adjust the position of the payment method icon on the user display end, and the icon position adjustment can be arranged according to the user's frequent use or activity discounts or low channel costs; through the adjustment of each management module in the cashier management system 200, a cashier system for order payment can be formed.

[0044] After the user submits the order and initiates payment, Figure 4As shown, the order payment process entering the cashier system specifically includes the following steps: S31, initiating a payment request, the user submits the order to the cashier system; S32, payment channel selection, the user selects his own payment channel (such as WeChat, Alipay, JD Baitiao, etc.); S33, payment channel verification, the cashier system needs to verify whether the payment channel is normal and whether it is in the configuration information of the cashier system; S34, payment information encryption and transmission, the cashier system encrypts the payment information and transmits it to the payment channel; S35 the payment channel processes the payment information; S36, payment result notification, the payment channel informs the cashier system of the payment result, that is, whether the user payment is successful or failed; S37, payment records and reports, the cashier system records the information returned by the payment channel to facilitate subsequent data statistics; S38, risk management, because order payment involves the transmission of currency, there is risk management and encryption processing in every step of the entire process of order payment to ensure the security of user accounts.

[0045] On the other hand, this embodiment also provides an optimization system for a vehicle booking process based on maximizing user rights and interests, which includes a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the optimization method as described above, thereby optimizing the vehicle booking process, improving user experience and protecting user rights and interests.

[0046] Wherein, in some embodiments, the computer-readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (e.g., SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the processor can be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip. The processor is generally used to control the overall operation of a computer device. In this embodiment, the processor is used to run computer executable instructions stored in a computer-readable storage medium, such as running a program code of an optimization method for a vehicle reservation process based on maximizing user benefits.

[0047] In summary, the vehicle reservation process optimization method and system provided by the present invention based on maximizing user rights and interests, by adjusting the style of the vehicle model list page, adding a secondary page display showing the total order price within the vehicle model rental period and the fee details corresponding to the total order price on the vehicle model list page, reduces the complexity and waiting time of user operations, improves the efficiency and success rate of reservation, enables users to quickly complete reservations, and obtain better service experience;

[0048] Secondly, by adding a first notification mark of fee details, a second notification mark of question mark rule explanation, and a third notification mark of car rental instructions on the order confirmation page, we can provide clear and transparent booking information, such as price, refund and change policy, service standards, etc., and protect user data security and privacy, so as to increase users' trust in the booking platform and services;

[0049] Furthermore, by setting the push time of coupon information and the value-added service recommendation module, accurate demand forecasting and efficient order processing mechanism can be achieved, the allocation and utilization efficiency of resources can be optimized, ensuring that suppliers can meet user needs while reducing resource waste; at the same time, the optimization method based on maximizing user rights and interests can help improve user satisfaction and loyalty, thereby promoting the sustainable development and growth of the booking platform.

[0050] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A method for optimizing a vehicle reservation process based on maximizing user rights and interests, characterized in that: include: Collect and analyze user behavior data, order data, log data, channel information data, and industry data during the vehicle booking process to maximize discounts; According to the discount maximization result, the corresponding coupon information is pushed, and a secondary page display showing the total order price during the rental period of the model and the fee details corresponding to the total order price is added to the model list page; When the user confirms the order data, on the order confirmation page, the coupon with the largest denomination that the user can use in the coupon list is checked by default.

2. The optimization method according to claim 1, characterized in that: The behavior data includes user click data, page browsing data, page dwell time data and user behavior path data; the order data includes the order's scheduled pick-up time, scheduled return time, car model name, pick-up city, return city, pick-up store, return store, order discount amount and order total amount.

3. The optimization method according to claim 2, characterized in that: The push time of the corresponding coupon information according to the discount maximization result is: when the number of models browsed by the user on the model list page is greater than or equal to N models, the available coupon information is pushed; and / or when the number of times the user browses the order confirmation page is greater than or equal to J times, the available coupon information is pushed; wherein N≥4, J≥3, and N and J are both integers.

4. The optimization method according to claim 2, characterized in that: When a user browses the vehicle model list page, order confirmation page and / or vehicle details page more than M times, a vehicle model configuration quick screening entry is added to the vehicle model list page, allowing the user to quickly screen the vehicle model that meets his or her booking expectations; where M≥5 and is an integer.

5. The optimization method according to claim 4, characterized in that: The vehicle model configuration quick screening includes the following steps: S1. Merge the models with the same model name in the model list page; S2. The user further screens according to additional conditions; the additional conditions include the type of license plate and whether self-service pick-up is possible.

6. The optimization method according to claim 1, characterized in that: The total order price during the rental period of the model added to the model list page includes the total cost after deducting the maximum denomination coupon, car rental fee, basic insurance fee, handling fee and the maximum denomination coupon.

7. The optimization method according to claim 1, characterized in that: On the order confirmation page, a first notification mark of fee details is added; and / or a second notification mark of a small question mark rule explanation is added on the order confirmation page to explain the fees that users have many doubts about; And / or add a third notification mark of car rental instructions at the bottom of the order confirmation page; the car rental instructions include: cancellation rules before picking up the car, order change rules during rental, car pick-up voucher, deposit payment, and invoice information.

8. The optimization method according to claim 1, characterized in that: Add a specific booking entrance on the home page of vehicle booking; the specific entrance includes a 24-hour booking entrance and a long-term rental booking entrance; enter the store list page through the 24-hour booking entrance, and the store business hours on the store list page are all 24 hours; The default rental period for all vehicles on the vehicle model list page entered through the long-term rental booking portal is 30 days.

9. The optimization method according to claim 1, characterized in that: For coupons in the coupon list with a validity period of less than or equal to 7 days, a reminder label "Expires in K days" is added to the coupon; where K = coupon expiration date - current date; when a user has membership benefits that can be deducted for delayed or worry-free car returns, a member label "Member benefits can be deducted" is added to the order confirmation page.

10. A vehicle booking process optimization system based on maximizing user rights and interests, characterized in that: It comprises a processor and a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions that can be executed by the processor, and the processor executes the computer-executable instructions to implement the optimization method as described in any one of claims 1 to 9.

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