Call-out recommendation method and device based on intelligent engine, and electronic equipment

Abstract

The invention discloses an outbound recommendation method and device based on an intelligent engine, and electronic equipment, and relates to the field of financial science and technology, the outbound recommendation method comprises the following steps: based on a customer group identifier carried by a recommendation request, obtaining a customer list associated with the customer group identifier from a preset database, and based on the preset database, obtaining the customer list associated with the customer group identifier; and determining outbound data associated with each customer identifier in the customer list, generating an outbound list based on the outbound data and a touch configuration rule, and controlling each outbound channel to perform outbound recommendation according to the outbound list. According to the method and the device, the technical problem that multiple times of outbound calls are possibly carried out on the same customer in a short time when outbound recommendation is carried out on the customer in related technologies is solved.

Description

Technical Field

[0001] The present invention relates to the field of financial technology, and in particular to an outbound call recommendation method based on an intelligent engine, a device thereof, and an electronic device. Background Art

[0002] With the rapid development of the financial market, financial institutions have adopted outbound telephone calls to recommend products and promote services in order to expand their business scale and improve customer satisfaction. As a direct and fast communication method, outbound telephone calls can help financial institutions establish connections with potential customers, understand customer needs, and provide personalized services.

[0003] However, when making outbound calls, financial institutions may face the problem of multi-channel coordination. Since the recommendation strategy for the same customer may be sent to different channels for independent outbound calls, there may be a situation where the same customer is called within a short period of time, which will cause the customer to be frequently disturbed and affect the brand image and customer loyalty of the financial institution.

[0004] In order to solve the above problems, there is an urgent need for an anti-disturbance method for outbound calls to monitor and analyze outbound call activities in real time, avoid repeatedly calling the same customer, and thus reduce disturbances to the customer.

[0005] To the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0006] The embodiment of the present invention provides an outbound call recommendation method based on an intelligent engine, a device thereof, and an electronic device, so as to at least solve the technical problem in the related art that when outbound call recommendations are made to customers, multiple outbound calls may be made to the same customer in a short period of time.

[0007] According to one aspect of an embodiment of the present invention, there is provided an outbound call recommendation method based on an intelligent engine, which is applied to an intelligent engine, and the intelligent engine is connected to multiple outbound call channels, including: based on the customer group identifier carried in the recommendation request, obtaining a customer list associated with the customer group identifier from a preset database, wherein the customer list includes at least: a customer identifier; based on the preset database, determining the outbound call data associated with each customer identifier in the customer list; based on the outbound call data and the contact configuration rules, generating an outbound call list, wherein the contact configuration rules are used to indicate the maximum number of contacts to contact the customer within a preset time length; controlling each outbound call channel to make outbound call recommendations based on the outbound call list.

[0008] In one embodiment of the present application, before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, it also includes: determining the customer group identifier based on the business needs of the business to be recommended, wherein the customer group indicated by the customer group identifier includes: multiple customer identifiers; for each customer identifier, filtering customer information associated with the customer identifier from a preset database; splicing the customer information associated with the customer identifier to obtain a customer record corresponding to the customer identifier; constructing a customer list based on the customer records corresponding to all customer identifiers, and associating the customer list with the customer group identifier.

[0009] In one implementation of the present application, before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, it also includes: generating a recommendation strategy based on the business needs of the business to be recommended; and generating a recommendation request based on the recommendation strategy and the customer group identifier.

[0010] In one embodiment of the present application, the outbound call recommendation method also includes: monitoring each outbound call channel; when the outbound call channel is monitored to make an outbound call recommendation to the customer's customer terminal, generating an outbound call record of the current outbound call recommendation, wherein the outbound call record includes at least: customer identification, outbound call channel identification, outbound call time, outbound call result; and storing the outbound call record in the outbound call data associated with the customer identification.

[0011] In one implementation of the present application, before generating an outbound call list based on outbound call data and reach configuration rules, it also includes: determining a recommendation cycle based on a recommendation strategy carried in a recommendation request; configuring reach configuration rules based on the recommendation cycle, wherein the reach configuration rules include: a reach times threshold.

[0012] In one embodiment of the present application, the step of generating an outbound call list based on outbound call data and reach configuration rules includes: based on the outbound call time corresponding to each outbound call record in the outbound call data, counting the number of outbound calls made to the customer terminal of the customer indicated by the customer identifier within the recommended period; determining the customer identifier whose outbound call number is less than the reach number threshold as the outbound customer identifier; and generating an outbound call list based on all outbound customer identifiers.

[0013] In one embodiment of the present application, the step of controlling each outbound channel to make outbound call recommendations based on the outbound call list includes: dividing all outbound customer identifiers in the outbound call list into outbound customer sets of the number of channels based on the channel number of the outbound channel, wherein the outbound customer set includes: multiple outbound customer identifiers; allocating the outbound customer set to each outbound channel, and sending the recommendation strategy carried by the recommendation request to each outbound channel, wherein the outbound channel makes outbound call recommendations to the customer terminal of the customer indicated by each outbound customer identifier in the outbound customer set based on the recommendation strategy.

[0014] According to another aspect of an embodiment of the present invention, there is also provided an outbound call recommendation device based on an intelligent engine, which is applied to the intelligent engine, and the intelligent engine is connected to multiple outbound call channels, including: an acquisition unit, which is used to acquire a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, wherein the customer list includes at least: a customer identifier; a determination unit, which is used to determine the outbound call data associated with each customer identifier in the customer list based on the preset database; a generation unit, which is used to generate an outbound call list based on the outbound call data and the contact configuration rules, wherein the contact configuration rules are used to indicate the maximum number of contacts to contact the customer within a preset time length; an outbound call unit, which is used to control each outbound call channel to make outbound call recommendations based on the outbound call list.

[0015] In one embodiment of the present application, the outbound call recommendation device also includes: a first determination module, which is used to determine the customer group identifier based on the business needs of the recommended business before obtaining the customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, wherein the customer group indicated by the customer group identifier includes: multiple customer identifiers; a first screening module, which is used to screen the customer information associated with the customer identifier from the preset database for each customer identifier; a first splicing module, which is used to splice the customer information associated with the customer identifier to obtain the customer record corresponding to the customer identifier; a first construction module, which is used to construct a customer list based on the customer records corresponding to all customer identifiers, and associate the customer list with the customer group identifier.

[0016] In one embodiment of the present application, the outbound call recommendation device also includes: a first generation module, which is used to generate a recommendation strategy based on the business needs of the recommended business before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request; and a second generation module, which is used to generate a recommendation request based on the recommendation strategy and the customer group identifier.

[0017] In one embodiment of the present application, the outbound call recommendation device also includes: a first monitoring module, used to monitor each outbound call channel; a third generating module, used to generate an outbound call record of the current outbound call recommendation when the outbound call channel is monitored to make an outbound call recommendation to the customer's customer terminal, wherein the outbound call record includes at least: customer identification, outbound call channel identification, outbound call time, outbound call result; a first storage module, used to store the outbound call record to the outbound call data associated with the customer identification.

[0018] In one embodiment of the present application, the outbound call recommendation device also includes: a second determination module, which is used to determine the recommendation period based on the recommendation strategy carried by the recommendation request before generating an outbound call list based on the outbound call data and the reach configuration rules; a first configuration module, which is used to configure the reach configuration rules based on the recommendation period, wherein the reach configuration rules include: a reach times threshold.

[0019] In one embodiment of the present application, the generation unit includes: a first statistical module, which is used to count the number of outbound calls made to the customer terminal of the customer indicated by the customer identifier within the recommended period based on the outbound call time corresponding to each outbound call record in the outbound call data; a third determination module, which is used to determine the customer identifier whose outbound call number is less than the reach number threshold as the outbound customer identifier; and a fourth generation module, which is used to generate an outbound call list based on all outbound customer identifiers.

[0020] In one embodiment of the present application, the outbound call unit includes: a first division module, used to divide all the outbound customer identifiers in the outbound call list into outbound customer sets of the number of channels according to the channel number of the outbound channels, wherein the outbound customer set includes: multiple outbound customer identifiers; a first allocation module, used to allocate the outbound customer set to each outbound channel, and send the recommendation strategy carried by the recommendation request to each outbound channel, wherein the outbound channel makes an outbound call recommendation to the customer terminal of the customer indicated by each outbound customer identifier in the outbound customer set based on the recommendation strategy.

[0021] According to another aspect of an embodiment of the present invention, a computer program product is also provided, including a non-volatile computer-readable storage medium, the non-volatile computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, any one of the above-mentioned outbound call recommendation methods based on the intelligent engine is implemented.

[0022] According to another aspect of an embodiment of the present invention, there is also provided an electronic device, comprising one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by one or more processors, the one or more processors implement any one of the above-mentioned outbound call recommendation methods based on the intelligent engine.

[0023] In the present invention, based on the customer group identifier carried in the recommendation request, a customer list associated with the customer group identifier is obtained from a preset database, and based on the preset database, the outbound call data associated with each customer identifier in the customer list is determined, and based on the outbound call data and the contact configuration rules, an outbound call list is generated, and each outbound call channel is controlled to make outbound call recommendations based on the outbound call list, thereby solving the technical problem in the related technology that when making outbound call recommendations to customers, there may be multiple outbound calls to the same customer in a short period of time.

[0024] In the present invention, through the unified scheduling of the intelligent engine, before outbound call recommendations are made to customers through different outbound call channels, the customer list can be screened according to the reach configuration rules to obtain the outbound call list used when each outbound call channel makes outbound call recommendations, thereby avoiding excessive reach of customers, improving customer experience, and achieving the technical effect of improving outbound call efficiency and business conversion rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The drawings described herein are used to provide a further understanding of the present invention and constitute a part of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0026] Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing an outbound call recommendation method based on an intelligent engine is shown;

[0027] Figure 2 is a flow chart of an outbound call recommendation method based on an intelligent engine according to Embodiment 1 of the present invention;

[0028] Figure 3 is a schematic diagram of an optional outbound call recommendation device based on an intelligent engine according to an embodiment of the present invention;

[0029] Figure 4 is a structural block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the scheme of the present invention, the technical scheme in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of the present invention.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] It should be noted that the outbound call recommendation method based on the intelligent engine and the device thereof in the present invention can be used in the field of financial technology when outbound call recommendations are performed based on the intelligent engine, and can also be used in any field other than the field of financial technology when outbound call recommendations are performed based on the intelligent engine. The present invention does not limit the application field of the outbound call recommendation method based on the intelligent engine and the device thereof.

[0033] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) collected and involved in the present invention are all information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of relevant data are in compliance with the relevant laws, regulations and standards of the relevant regions, necessary confidentiality measures are taken, and public order and good customs are not violated, and corresponding operation entrances are provided for users to choose to authorize or refuse. For example, an interface is set between the system and the relevant users or organizations. Before obtaining relevant information, it is necessary to send an acquisition request to the aforementioned user or organization through the interface, and obtain relevant information after receiving the consent information fed back by the aforementioned user or organization.

[0034] In the present invention, efficient management and optimized configuration of outbound call channels are achieved through the unified scheduling of the intelligent engine. Not only can the outbound call list be intelligently generated based on the customer's historical outbound call data and contact configuration rules, thus avoiding excessive contact with customers and improving customer experience, but customers can also be allocated according to the characteristics of the outbound call channels, thereby improving outbound call efficiency and business conversion rate.

[0035] The present invention is described in detail below in conjunction with various embodiments.

[0036] Example 1

[0037] According to an embodiment of the present application, an embodiment of an outbound call recommendation method based on an intelligent engine is also provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0038] The method embodiment provided in the first embodiment of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1 FIG. 1 shows a hardware structure block diagram of a computer terminal (or mobile device) for implementing an outbound call recommendation method based on an intelligent engine. Figure 1 As shown, the computer terminal 10 (or mobile device) may include one or more ( Figure 1102a, 102b, ..., 102n are used to illustrate) processor 102 (processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera, wherein the network interface may be connected to a wired and / or wireless network. A person of ordinary skill in the art will understand that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components as shown, or with Figure 1 Different configurations are shown.

[0039] It should be noted that the one or more processors 102 and / or other data processing circuits described above may generally be referred to herein as "data processing circuits". The data processing circuits may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computer terminal 10 (or mobile device). As described in the embodiments of the present application, the data processing circuit acts as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).

[0040] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the outbound call recommendation method based on the intelligent engine in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, the outbound call recommendation method based on the intelligent engine is realized. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0041] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0042] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 (or mobile device).

[0043] Under the above operating environment, this application provides Figure 2 The outbound call recommendation method based on the intelligent engine is shown. Figure 2 is a flow chart of an outbound call recommendation method based on an intelligent engine according to Embodiment 1 of the present invention. Figure 2 As shown, the method comprises the following steps:

[0044] Step S201, based on the customer group identifier carried in the recommendation request, a customer list associated with the customer group identifier is obtained from a preset database, wherein the customer list includes at least: the customer identifier.

[0045] In an embodiment of the present invention, an intelligent engine may be used to execute an outbound call recommendation method. The intelligent engine may be connected to multiple outbound call channels to control the outbound call channels to make outbound call recommendations to customers who meet the reach conditions.

[0046] In this embodiment, the reach condition refers to the condition that the maximum reach times are not reached within a preset time. Outbound call channels include but are not limited to: outbound calls by phone, outbound calls by SMS, outbound calls by various communication applications, and the like.

[0047] In an embodiment of the present invention, the intelligent engine may receive a recommendation request sent by a business system of a financial institution, where the recommendation request carries identification information of a specific customer group (ie, a customer group identification) to implement product recommendations or service promotions for this customer group.

[0048] In an embodiment of the present invention, the intelligent engine may obtain a customer list associated with a customer group identifier from a preset database, so as to make outbound call recommendations to customers indicated by the customer identifiers on the customer list.

[0049] Here, the preset database stores a customer list associated with a customer group identifier, and the customer list records a plurality of customer records associated with customer identifiers, and the customer records include customer names, attribute information, and the like.

[0050] Step S202: determining outbound call data associated with each customer identifier in the customer list based on a preset database.

[0051] In the embodiment of the present invention, the outbound call data of different outbound call channels to customers obtained by monitoring can be recorded in a preset database. When a recommendation request is received, the corresponding outbound call data can be determined according to the customer group identifier carried in the recommendation request.

[0052] In the embodiment of the present invention, the outbound call data includes but is not limited to: customer identification, outbound call time, outbound call channel, outbound call result (answered / unanswered), recommendation strategy performed during outbound call, etc.

[0053] Step S203, generating an outbound call list based on the outbound call data and the reach configuration rules, wherein the reach configuration rules are used to indicate the maximum number of times to reach the customer within a preset time period.

[0054] In an embodiment of the present invention, a reach configuration rule may be pre-configured, wherein the reach configuration rule indicates the maximum number of outbound calls to a customer within a preset time period.

[0055] In the embodiment of the present invention, the outbound call data corresponding to each customer ID on the customer list and the contact configuration rules can be used to screen out customers that meet the contact conditions and generate a new "outbound call list". The outbound call list excludes customers who have been called out the maximum number of times within the specified time, thereby avoiding repeated disturbances to customers.

[0056] Step S204, controlling each outbound call channel to make outbound call recommendations based on the outbound call list.

[0057] In an embodiment of the present invention, the intelligent engine distributes the generated outbound call list to various outbound call channels. The outbound call channels make outbound call recommendations to the customers on the outbound call list based on the information on the outbound call list. At the same time, the intelligent engine can also monitor the outbound call situation of each outbound call channel to avoid unnecessary disturbance to the customers, thereby realizing cross-channel collaborative recommendations and improving customer experience and recommendation efficiency.

[0058] In summary, through the unified scheduling of the intelligent engine, before outbound call recommendations are made to customers through different outbound call channels, the customer list can be screened according to the reach configuration rules to obtain the outbound call list used for outbound call recommendations through each outbound call channel, thereby avoiding excessive reach of customers, improving customer experience, and achieving the technical effect of improving outbound call efficiency and business conversion rate, thereby solving the technical problem in related technologies that when outbound call recommendations are made to customers, there may be multiple outbound calls to the same customer in a short period of time.

[0059] In order to improve the accuracy of constructing a customer list corresponding to the business to be recommended, in the outbound call recommendation method based on the intelligent engine provided in Example 1 of the present application, before obtaining the customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, the customer group identifier is determined based on the business needs of the business to be recommended, wherein the customer group indicated by the customer group identifier includes: multiple customer identifiers; for each customer identifier, filtering customer information associated with the customer identifier from the preset database; splicing the customer information associated with the customer identifier to obtain the customer record corresponding to the customer identifier; constructing a customer list based on the customer records corresponding to all customer identifiers, and associating the customer list with the customer group identifier.

[0060] In an embodiment of the present invention, the customer group identifier can be determined according to the specific business requirements of the recommended business (e.g., the consumer voucher recommendation business) (e.g., the consumer voucher needs to be recommended to customers aged 30). For example, if a financial institution wants to promote the latest credit card products, the business requirements may include characteristics such as age range, occupation type, credit score, etc., and then customers meeting these characteristics can be determined to obtain a customer group, and the customer group identifier corresponding to the customer group can be determined.

[0061] In an embodiment of the present invention, for each customer identifier in the customer group indicated by the customer group identifier, the intelligent engine can filter the customer information associated with the customer identifier from the preset database (including but not limited to: name, gender, age, occupation, credit score, historical transaction records, etc.). Then, the filtered customer information is spliced ​​to form a complete customer record corresponding to the customer identifier. The splicing operation ensures that all relevant information of the customer is integrated into one record, which is convenient for subsequent analysis and processing. Afterwards, based on the customer records corresponding to all customer identifiers, a customer list is constructed, and the customer list is associated with the predetermined customer group identifier.

[0062] In the embodiment of the present invention, the customer list is formed after screening and splicing operations, and contains the basic information of all target customers and recommendation-related data. In addition, the customer list is associated with the customer group identifier, so that the customer list can become a collection of target customer group data for a specific recommendation activity. In this way, the intelligent engine can quickly locate the customer group that needs to be intelligently called.

[0063] In this embodiment, the intelligent engine can accurately construct a customer list containing target customers based on the specific needs of the business to be recommended, which not only ensures that every customer on the customer list is highly relevant to the recommended activity, but also improves the customization and accuracy of the outbound call strategy by integrating customer information.

[0064] In order to improve the accuracy of generating recommendation requests, in the outbound call recommendation method based on the intelligent engine provided in Example 1 of the present application, before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, a recommendation strategy is generated based on the business needs of the business to be recommended; and a recommendation request is generated based on the recommendation strategy and the customer group identifier.

[0065] In the embodiment of the present invention, a recommendation strategy can be generated according to the business requirements of the recommended business (i.e., the specific goals that the financial institution hopes to achieve through outbound calling activities, such as promoting new products, improving customer satisfaction, increasing customer stickiness, etc.), for example, issuing consumption coupons to customers aged 30 and notifying these customers through outbound calling. Then, a recommendation request is generated according to the generated recommendation strategy and the determined customer group identifier.

[0066] Here, the recommendation request is an instruction containing specific outbound calling strategies and target customer group information, which is used to guide the outbound calling channel on how to make recommended outbound calls to customers in the customer group.

[0067] In order to accurately monitor the outbound call recommendations made by the outbound call channels, in the outbound call recommendation method based on the intelligent engine provided in Example 1 of the present application, each outbound call channel is monitored; when the outbound call channel is monitored to make an outbound call recommendation to the customer's customer terminal, an outbound call record of the current outbound call recommendation is generated, wherein the outbound call record includes at least: customer identification, outbound call channel identification, outbound call time, outbound call result; and the outbound call record is stored in the outbound call data associated with the customer identification.

[0068] In an embodiment of the present invention, the intelligent engine can establish a real-time communication connection with all outbound call channels to monitor each outbound call channel, thereby capturing all information about outbound calls to customers. When the intelligent engine monitors that a certain outbound call channel recommends an outbound call to a customer's client terminal, an outbound call record will be generated based on the captured outbound call information. The outbound call record includes at least key fields such as customer ID, outbound call channel ID, outbound call time, and outbound call result. The outbound call record is then stored in the outbound call data associated with the customer ID, so that detailed information about each outbound call made by the customer can be recorded, and a personal outbound call history record of the customer can be constructed.

[0069] In order to improve the accuracy of configuring the reach configuration rules, in the outbound call recommendation method based on the intelligent engine provided in Example 1 of the present application, before generating an outbound call list based on the outbound call data and the reach configuration rules, the recommendation cycle is determined based on the recommendation strategy carried by the recommendation request; based on the recommendation cycle, the reach configuration rules are configured, wherein the reach configuration rules include: a reach times threshold.

[0070] In an embodiment of the present invention, after receiving a recommendation request, the intelligent engine can determine the duration of the recommendation activity according to the recommendation period field in the recommendation strategy. Then, according to the duration of the recommendation period, the maximum number of outbound calls to the customer (i.e., the reach threshold) is determined to obtain the reach configuration rules for the current outbound call recommendation. For example, if the recommendation period is one week, the reach threshold can be set to three times, which means that within this week, the intelligent engine will make a maximum of three outbound call recommendations to each customer in the same customer group.

[0071] In this embodiment, the setting of the reach configuration rules comprehensively considers factors such as customer acceptance, recommendation activity goals, and resource efficiency, ensuring that the recommendation activities avoid frequent interruptions to customers while achieving business goals.

[0072] In this embodiment, the intelligent engine can manage outbound call recommendation activities in a more refined manner, and achieve a balance between recommendation efficiency and customer experience by setting recommendation cycles and contact configuration rules. The determination of the recommendation cycle provides a time frame for the recommendation activities, and the contact number threshold in the contact configuration rules effectively controls the frequency of recommendation activities, avoids repeated interruptions to customers, and maintains the brand image and customer loyalty of financial institutions. In addition, the dynamic configuration capability of the contact configuration rules enables the intelligent engine to flexibly adjust the recommendation strategy based on customer feedback, thereby improving the response speed and success rate of recommendation activities.

[0073] In order to improve the accuracy of generating outbound call lists, in the outbound call recommendation method based on the intelligent engine provided in Example 1 of the present application, based on the outbound call time corresponding to each outbound call record in the outbound call data, the number of outbound calls made to the customer terminal of the customer indicated by the customer identifier within the recommendation period is counted; the customer identifier whose outbound call number is less than the reach number threshold is determined as the outbound customer identifier; and based on all outbound customer identifiers, an outbound call list is generated.

[0074] In an embodiment of the present invention, through the statistical analysis of outbound call data by the intelligent engine, it is possible to determine the customer identifiers that meet the reach configuration rules within the recommendation period, and then generate an outbound call list. Specifically: first, according to the outbound call time corresponding to each outbound call record in the outbound call data, the number of outbound calls to the customer terminal corresponding to each customer identifier within the current recommendation period can be counted. After counting the number of outbound calls to the customer terminal within the recommendation period, the intelligent engine can filter these data and identify customer identifiers whose outbound call times are less than the reach times threshold as outbound customer identifiers. In this way, it can be determined which customers have not yet reached the reach upper limit of the recommendation strategy, and therefore can continue to be contacted by outbound calls to improve the coverage and effectiveness of the recommendation activity.

[0075] In the embodiment of the present invention, after determining the outbound customer identification, the intelligent engine will generate an outbound call list based on this identification set. The outbound call list contains all customer information that has not reached the threshold number of contacts within the recommended period, and is the direct basis for each outbound channel to conduct the next round of outbound call activities. By generating this list, the intelligent engine ensures the accuracy and efficiency of outbound call activities and avoids repeated disturbances to customers who have reached the anti-disturbance standard.

[0076] In this embodiment, the intelligent engine can intelligently screen out customer groups that have not reached the threshold number of contacts within the recommendation period through statistical analysis of outbound call data, and achieve accurate control and efficient execution of outbound call activities, which not only improves the contact accuracy of recommendation activities, but also effectively avoids over-recommendation to customers, improves customer experience and the overall effect of recommendation activities. At the same time, by generating an outbound call list, the intelligent engine provides a clear recommendation direction for the outbound call channel, reduces the waste of resources, and improves the return on investment of recommendation activities.

[0077] In order to avoid frequent disturbances to customers, in the outbound call recommendation method based on the intelligent engine provided in Example 1 of the present application, all outbound customer identifiers in the outbound call list are divided into outbound customer sets of the number of channels according to the channel number of the outbound channels, wherein the outbound customer set includes: multiple outbound customer identifiers; the outbound customer set is assigned to each outbound channel, and the recommendation strategy carried by the recommendation request is sent to each outbound channel, wherein the outbound channel makes an outbound call recommendation to the customer terminal of the customer indicated by each outbound customer identifier in the outbound customer set based on the recommendation strategy.

[0078] In an embodiment of the present invention, after the intelligent engine receives a recommendation request and generates an outbound call list, the outbound customer identifiers in the outbound call list can be reasonably divided according to the number of channels of the outbound call channel so as to be allocated to each outbound call channel. That is, according to the number of channels, all outbound customer identifiers in the outbound call list are equally divided or divided into the same number of outbound customer sets according to a certain strategy. Each set contains multiple outbound customer identifiers, so that each outbound channel can be ensured to have clear target customers when executing outbound call recommendations. At the same time, through reasonable allocation, excessive concentration of resources in a single channel is avoided, and the balance between channels is maintained.

[0079] Each outbound customer set can then be assigned to a specific outbound channel. For example, if there are four outbound channels, the outbound call list will be divided into four outbound customer sets, each set is assigned to a channel. At the same time, the intelligent engine sends the recommendation strategy carried in the recommendation request to each outbound channel. The recommendation strategy contains key elements such as the specific content and method of the outbound call, which is used to guide the outbound channel to make outbound call recommendations.

[0080] In an embodiment of the present invention, after the outbound call channel receives the allocated outbound customer set and recommendation strategy, it will make outbound call recommendations to the customer terminal of the customer indicated by each outbound customer identifier in the outbound customer set according to the guidance in the strategy. In this way, the standardization and consistency of outbound call activities are ensured, while also giving the outbound call channel sufficient autonomy to flexibly adapt to the characteristics of different customer groups.

[0081] In this embodiment, the intelligent engine achieves efficient coordination and precise execution of outbound activities by reasonably dividing the outbound customer set and allocating it to each outbound channel, while synchronizing the recommendation strategy to the channel. The division of the outbound customer set ensures the balanced allocation of outbound resources, avoiding competition and waste of resources between channels. The issuance of the recommendation strategy provides clear outbound guidance for the outbound channel, improving the customer acceptance and recommendation conversion rate of outbound activities.

[0082] The outbound call recommendation method based on the intelligent engine provided in the embodiment of the present application can, through the unified scheduling of the intelligent engine, filter the obtained customer list according to the contact configuration rules before making outbound call recommendations to customers through different outbound call channels, so as to obtain the outbound call list used for outbound call recommendations by each outbound call channel, thereby avoiding excessive contact with customers, improving customer experience, and achieving the technical effect of improving outbound call efficiency and business conversion rate, thereby solving the technical problem in the related technology that when making outbound call recommendations to customers, there may be multiple outbound calls to the same customer in a short period of time.

[0083] It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and that, although a logical order is shown in the flowcharts, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0084] Example 2

[0085] The embodiment of the present application also provides an outbound call recommendation device based on an intelligent engine. It should be noted that the outbound call recommendation device based on an intelligent engine in the embodiment of the present application can be used to execute the outbound call recommendation method based on an intelligent engine provided in the embodiment of the present application. The outbound call recommendation device based on an intelligent engine provided in the embodiment of the present application is introduced below.

[0086] According to an embodiment of the present application, a device for implementing the above-mentioned outbound call recommendation method based on an intelligent engine is also provided. Figure 3 is a schematic diagram of an optional outbound call recommendation device based on an intelligent engine according to an embodiment of the present invention. Figure 3 As shown, the outbound call recommendation device may include: an acquisition unit 30 , a determination unit 31 , a generation unit 32 , and an outbound call unit 33 .

[0087] The acquisition unit 30 is used to acquire a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, wherein the customer list includes at least: the customer identifier;

[0088] A determination unit 31, configured to determine outbound call data associated with each customer identifier in the customer list based on a preset database;

[0089] A generating unit 32, configured to generate an outbound call list based on the outbound call data and the reach configuration rule, wherein the reach configuration rule is used to indicate a maximum number of reach times for reaching a customer within a preset time period;

[0090] The outbound call unit 33 is used to control each outbound call channel to make outbound call recommendations based on the outbound call list.

[0091] Optionally, the outbound call recommendation device also includes: a first determination module, used to determine the customer group identifier based on the business needs of the recommended business before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, wherein the customer group indicated by the customer group identifier includes: multiple customer identifiers; a first screening module, used to screen customer information associated with the customer identifier from a preset database for each customer identifier; a first splicing module, used to splice the customer information associated with the customer identifier to obtain a customer record corresponding to the customer identifier; a first construction module, used to construct a customer list based on the customer records corresponding to all customer identifiers, and associate the customer list with the customer group identifier.

[0092] Optionally, the outbound call recommendation device also includes: a first generation module, which is used to generate a recommendation strategy based on the business needs of the business to be recommended before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request; and a second generation module, which is used to generate a recommendation request based on the recommendation strategy and the customer group identifier.

[0093] Optionally, the outbound call recommendation device also includes: a first monitoring module, used to monitor each outbound call channel; a third generating module, used to generate an outbound call record of the current outbound call recommendation when the outbound call channel is monitored to make an outbound call recommendation to the customer's customer terminal, wherein the outbound call record includes at least: customer identification, outbound call channel identification, outbound call time, outbound call result; a first storage module, used to store the outbound call record to the outbound call data associated with the customer identification.

[0094] Optionally, the outbound call recommendation device also includes: a second determination module, used to determine the recommendation period based on the recommendation strategy carried by the recommendation request before generating an outbound call list based on the outbound call data and the reach configuration rules; a first configuration module, used to configure the reach configuration rules based on the recommendation period, wherein the reach configuration rules include: a reach times threshold.

[0095] Optionally, the generation unit includes: a first statistical module, used to count the number of outbound calls made to the customer terminal of the customer indicated by the customer identifier within the recommended period based on the outbound call time corresponding to each outbound call record in the outbound call data; a third determination module, used to determine the customer identifier whose outbound call number is less than the reach number threshold as the outbound customer identifier; and a fourth generation module, used to generate an outbound call list based on all outbound customer identifiers.

[0096] Optionally, the outbound call unit includes: a first division module, used to divide all the outbound customer identifiers in the outbound call list into outbound customer sets of the number of channels according to the channel number of the outbound channels, wherein the outbound customer set includes: multiple outbound customer identifiers; a first allocation module, used to allocate the outbound customer set to each outbound channel, and send the recommendation strategy carried by the recommendation request to each outbound channel, wherein the outbound channel makes an outbound call recommendation to the customer terminal of the customer indicated by each outbound customer identifier in the outbound customer set based on the recommendation strategy.

[0097] The above-mentioned outbound call recommendation device may also include a processor and a memory. The above-mentioned acquisition unit 30, determination unit 31, generation unit 32, outbound call unit 33, etc. are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0098] The processor includes a kernel, and the kernel retrieves the corresponding program unit from the memory. One or more kernels can be set, and each outbound call channel can be controlled to make outbound call recommendations based on the outbound call list by adjusting kernel parameters.

[0099] The above-mentioned memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash memory (fl ash RAM), and the memory includes at least one storage chip.

[0100] It should be noted that the acquisition unit 30, the determination unit 31, the generation unit 32, and the outbound call unit 33 correspond to steps S201 to S204 in Example 1, and the examples and application scenarios implemented by the above units and the corresponding steps are the same, but are not limited to the contents disclosed in the above Example 1. It should be noted that the above units can be hardware components or software components stored in a memory (e.g., memory 104) and processed by one or more processors (e.g., processors 102a, 102b, ..., 102n), and the above units can also be run in the computer terminal 10 provided in Example 1 as part of the device.

[0101] Example 3

[0102] An embodiment of the present application may provide an electronic device, Figure 4 is a structural block diagram of an electronic device according to an embodiment of the present invention. Figure 4 As shown, the electronic device may include: one or more ( Figure 4 (only one is shown) processor 402, memory 404, storage controller, and peripheral interface, wherein the peripheral interface is connected to the radio frequency module, audio module and display.

[0103] Among them, the memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the outbound call recommendation method and device based on the intelligent engine in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, that is, realizing the above-mentioned outbound call recommendation method based on the intelligent engine. The memory may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include a memory remotely arranged relative to the processor, and these remote memories can be connected to the terminal via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0104] The processor can call the information and application stored in the memory through the transmission device to perform the following steps: based on the customer group identifier carried in the recommendation request, obtain a customer list associated with the customer group identifier from a preset database, wherein the customer list includes at least: a customer identifier; based on the preset database, determine the outbound call data associated with each customer identifier in the customer list; based on the outbound call data and the contact configuration rules, generate an outbound call list, wherein the contact configuration rules are used to indicate the maximum number of contacts to contact the customer within a preset time length; control each outbound call channel to make outbound call recommendations based on the outbound call list.

[0105] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: determine the customer group identifier based on the business needs of the business to be recommended, wherein the customer group indicated by the customer group identifier includes: multiple customer identifiers; for each customer identifier, filter the customer information associated with the customer identifier from a preset database; splice the customer information associated with the customer identifier to obtain the customer record corresponding to the customer identifier; based on the customer records corresponding to all customer identifiers, build a customer list, and associate the customer list with the customer group identifier.

[0106] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: generating a recommendation strategy based on the business requirements of the business to be recommended; and generating a recommendation request based on the recommendation strategy and the customer group identifier.

[0107] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: monitor each outbound call channel; when the outbound call channel is monitored to make an outbound call recommendation to the customer's customer terminal, generate an outbound call record of the current outbound call recommendation, wherein the outbound call record includes at least: customer identification, outbound call channel identification, outbound call time, outbound call result; store the outbound call record in the outbound call data associated with the customer identification.

[0108] The processor can also call the information and applications stored in the memory through the transmission device to perform the following steps: determine the recommendation cycle based on the recommendation strategy carried by the recommendation request; configure the reach configuration rules based on the recommendation cycle, wherein the reach configuration rules include: a reach times threshold.

[0109] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: based on the outbound call time corresponding to each outbound call record in the outbound call data, count the number of outbound calls made to the customer terminal of the customer indicated by the customer identifier within the recommended period; determine the customer identifier whose outbound call number is less than the reach number threshold as the outbound customer identifier; and generate an outbound call list based on all outbound customer identifiers.

[0110] The processor can also call the information and application programs stored in the memory through the transmission device to perform the following steps: according to the channel number of the outbound call channel, all the outbound customer identifiers in the outbound call list are divided into outbound customer sets of the channel number, wherein the outbound customer set includes: multiple outbound customer identifiers; the outbound customer set is assigned to each outbound call channel, and the recommendation strategy carried by the recommendation request is sent to each outbound call channel, wherein the outbound channel makes an outbound call recommendation to the customer terminal of the customer indicated by each outbound customer identifier in the outbound customer set based on the recommendation strategy.

[0111] By adopting the embodiment of the present application, a solution for outbound call recommendation based on an intelligent engine is provided. Through the unified scheduling of the intelligent engine, before outbound call recommendations are made to customers through different outbound call channels, the customer list can be screened according to the contact configuration rules to obtain the outbound call list used when each outbound call channel makes outbound call recommendations, thereby avoiding excessive contact with customers, improving customer experience, and achieving the technical effect of improving outbound call efficiency and business conversion rate, thereby solving the technical problem in the related technology that when outbound call recommendations are made to customers, there may be multiple outbound calls to the same customer in a short period of time.

[0112] It can be understood by those skilled in the art that Figure 4 The structure shown is for illustration only, and the electronic device may also be a terminal device such as a smart phone, a tablet computer, a PDA, and a Mobile Internet Device (MID). Figure 4The structure of the electronic device is not limited. Figure 4 More or fewer components (such as network interfaces, display devices, etc.) shown in, or having Figure 4 Different configurations are shown.

[0113] A person of ordinary skill in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing the hardware related to the terminal device through a program, and the program can be stored in a computer-readable storage medium, and the storage medium may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0114] Example 4

[0115] The embodiment of the present application further provides a storage medium. Optionally, in this embodiment, the storage medium can be used to store the program code executed by the outbound call recommendation method based on the intelligent engine provided in the first embodiment.

[0116] Optionally, in this embodiment, the above storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0117] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for executing the program steps of the outbound call recommendation method based on the intelligent engine.

[0118] The serial numbers of the above-mentioned embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.

[0119] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0120] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.

[0121] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0122] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0123] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or CD-ROM and other media that can store program codes.

[0124] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. An outbound call recommendation method based on an intelligent engine, characterized in that: Applied to an intelligent engine that is connected to multiple outbound channels, including: Based on the customer group identifier carried in the recommendation request, a customer list associated with the customer group identifier is obtained from a preset database, wherein the customer list includes at least: the customer identifier; Based on the preset database, determining outbound call data associated with each of the customer identifiers in the customer list; Generate an outbound call list based on the outbound call data and the reach configuration rule, wherein the reach configuration rule is used to indicate the maximum number of reach times to reach the customer within a preset time period; Control each of the outbound call channels to make outbound call recommendations based on the outbound call list.

2. The outbound call recommendation method according to claim 1, characterized in that: Before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, the method further includes: Determine the customer group identifier based on the business requirements of the business to be recommended, wherein the customer group indicated by the customer group identifier includes: a plurality of customer identifiers; For each of the customer identifiers, filtering customer information associated with the customer identifier from the preset database; splicing the customer information associated with the customer identifier to obtain a customer record corresponding to the customer identifier; The customer list is constructed based on the customer records corresponding to all the customer identifiers, and the customer list is associated with the customer group identifier.

3. The outbound call recommendation method according to claim 1, characterized in that: Before obtaining a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, the method further includes: Generate a recommendation strategy based on the business needs of the business to be recommended; The recommendation request is generated based on the recommendation strategy and the customer group identifier.

4. The outbound call recommendation method according to claim 1, characterized in that: The outbound call recommendation method further includes: Monitoring each of the outbound calling channels; In the case of monitoring that the outbound call channel makes an outbound call recommendation to the client terminal of the client, generating an outbound call record of the current outbound call recommendation, wherein the outbound call record at least includes: the client identifier, the outbound call channel identifier, the outbound call time, and the outbound call result; The outbound call record is stored in the outbound call data associated with the customer identifier.

5. The outbound call recommendation method according to claim 1, characterized in that: Before generating an outbound call list based on the outbound call data and the reach configuration rule, the method further includes: Determining a recommendation cycle based on the recommendation strategy carried in the recommendation request; Based on the recommendation period, the reach configuration rule is configured, wherein the reach configuration rule includes: The number of touches threshold.

6. The outbound call recommendation method according to claim 5, characterized in that: The step of generating an outbound call list based on the outbound call data and the reach configuration rule includes: Based on the outbound call time corresponding to each outbound call record in the outbound call data, counting the number of outbound calls to which the client terminal of the client indicated by the client identifier is called within the recommendation period; Determine the customer identifier whose outbound call number is less than the reach number threshold as the outbound customer identifier; The outbound call list is generated based on all the outbound call client identifiers.

7. The outbound call recommendation method according to claim 1, characterized in that: The step of controlling each of the outbound call channels to make outbound call recommendations according to the outbound call list comprises: According to the channel number of the outbound call channel, all the outbound call customer identifiers in the outbound call list are divided into outbound call customer sets of the channel number, wherein the outbound call customer set includes: a plurality of the outbound call customer identifiers; The outbound customer set is assigned to each of the outbound call channels, and the recommendation strategy carried in the recommendation request is sent to each of the outbound call channels, wherein the outbound call channel makes an outbound call recommendation to the customer terminal of each customer indicated by the outbound customer identifier in the outbound customer set based on the recommendation strategy.

8. An outbound call recommendation device based on an intelligent engine, characterized in that: Applied to an intelligent engine that is connected to multiple outbound channels, including: An acquisition unit is used to acquire a customer list associated with the customer group identifier from a preset database based on the customer group identifier carried in the recommendation request, wherein the customer list at least includes: a customer identifier; A determination unit, configured to determine, based on the preset database, outbound call data associated with each of the customer identifiers in the customer list; A generating unit, configured to generate an outbound call list based on the outbound call data and a reach configuration rule, wherein the reach configuration rule is used to indicate a maximum number of reach times for reaching a customer within a preset time period; The outbound call unit is used to control each of the outbound call channels to make outbound call recommendations based on the outbound call list.

9. A computer program product, characterized in that It comprises a non-volatile computer-readable storage medium, wherein the non-volatile computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the outbound call recommendation method based on the intelligent engine as described in any one of claims 1 to 7 is implemented.

10. An electronic device, characterized in that: It includes one or more processors and a memory, wherein the memory is used to store one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the outbound call recommendation method based on the intelligent engine as described in any one of claims 1 to 7.

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