Business opportunity information management method and system

Abstract

A business opportunity information management system comprises an information collection module used for collecting customer information and sending the customer information to an information extraction module; the information extraction module is used for segmenting customer information, filling the segmented customer information into information groups according to preset information groups, and sending the content of the information groups to the structuring module, and the information groups at least comprise time groups and customer name groups; the structuring module takes time and customer names as indexes, recombines the content of the information groups by using semantic analysis to obtain corresponding business opportunity information, and sends the business opportunity information to the storage module; according to the system, the customer information can be obtained, the customer information is extracted, the business opportunity information of the customer is generated, a salesman can quickly know the demand and preference of the customer through the business opportunity information, the extraction difficulty of the business opportunity information is greatly reduced, and the obtaining efficiency of the business opportunity information is improved.

Description

Technical Field

[0001] The present invention relates to the field of information processing technology, and in particular to a method and system for managing business opportunity information. Background Art

[0002] In today's fast-changing and highly competitive business environment, companies are exposed to massive amounts of customer information and complex business communication data every day. The scale and complexity of this data far exceeds any time in the past, bringing unprecedented opportunities and challenges to companies. Traditional business opportunity information management methods mostly rely on manual data sorting, screening and analysis. This method is not only inefficient and difficult to meet the needs of immediate decision-making, but also very easy to cause errors due to human factors, which in turn affects the accuracy and timeliness of corporate decision-making.

[0003] With the rapid progress in big data technology and artificial intelligence, enterprises have unprecedented technical means to meet this challenge. The use of big data technology enables enterprises to efficiently collect, store and process these huge data sets, while artificial intelligence technology, especially advanced algorithms such as machine learning, natural language processing (NLP) and deep learning, makes it possible to automatically analyze and mine valuable information from these data.

[0004] Therefore, how to combine information processing technology to process the business opportunity information of the enterprise and obtain useful value information has become a technical problem that needs to be solved urgently. Summary of the invention

[0005] In view of the above-mentioned defects, the purpose of the present invention is to propose a management system for business opportunity information to solve the problem that the existing business opportunity information mining is difficult and time-consuming.

[0006] To achieve this purpose, the present invention adopts the following technical solution: a management system for business opportunity information, comprising:

[0007] The information collection module is used to collect customer information and send the customer information to the information extraction module;

[0008] The information extraction module is used to segment the customer information, and fill the segmented customer information into the information group according to the preset information grouping, and send the content of the information grouping to the structuring module, wherein the information grouping includes at least a time grouping and a customer name grouping;

[0009] The structuring module uses time and customer name as indexes and uses semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information, and sends the business opportunity information to the storage module;

[0010] The storage module is used to search the database using the customer name, determine whether the customer is in the data to construct a corresponding storage document, if not, construct a storage document by adding the customer name to the generated ID, and store the business opportunity information in the storage document, if it exists, obtain the time in the business opportunity information, and sort the business opportunity information according to the time of different business opportunity information;

[0011] A reminder module, which is used to read the business opportunity information sorted at the front in the storage document, determine whether the current time reaches the scheduled time, and if so, send the business opportunity information to the corresponding business personnel and trigger the feedback module;

[0012] The feedback module is used to receive feedback information from the salesperson within a time threshold, and if the feedback information is received within the time threshold, a deletion instruction is sent to the reminder module; if the feedback information is not received within the time threshold, a resend instruction is sent to the reminder module;

[0013] After receiving the deletion instruction, the reminder module removes the business opportunity information sorted at the front in the storage document;

[0014] After receiving the resend instruction, the reminder module resends the business opportunity information to the corresponding business personnel and continues to trigger the feedback module.

[0015] Preferably, the customer information includes text content, voice content and picture content;

[0016] The information collection module includes a document information acquisition submodule, a voice information acquisition submodule and an image information acquisition submodule;

[0017] The document information acquisition submodule is used to generate a first program interface, and acquire text content in the specified chat software through the first program;

[0018] The voice information acquisition submodule is used to generate a second program interface, obtain the voice content in the specified chat software through the second program, or obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the salesperson;

[0019] The image information acquisition submodule is used to generate a third program interface and acquire the image content in the specified chat software through the third program.

[0020] Preferably, it also includes an official website information acquisition submodule, which is used to generate a fourth program interface, and the fourth program is used to connect to the customer's official website and perform targeted crawling of network information through web crawler technology to obtain text content and / or image content.

[0021] Preferably, the information extraction module includes a text processing submodule, a voice processing submodule and a picture processing submodule;

[0022] The text processing submodule is used to receive the text content, and perform semantic analysis on the text content through natural language processing technology, divide the text data according to the semantic analysis result, and extract key information therefrom;

[0023] The speech processing submodule is used to receive speech content, perform denoising and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into the deep learning model, map the extracted speech features to acoustic units of phonemes or subphonemes, generate a vocabulary sequence according to the acoustic unit sequence and the natural language model, normalize the identified vocabulary sequence, perform semantic analysis on the normalized vocabulary sequence through natural language processing technology, and obtain key information;

[0024] The image processing submodule is used to receive image content, call the OCR interface, extract text content in the image content through OCR technology, and perform semantic analysis on the text content through natural language processing technology to obtain key information.

[0025] Preferably, the information extraction module further includes an input submodule;

[0026] The input submodule is used to clean key information and remove redundant, erroneous or irrelevant data;

[0027] And map the cleaned key information into the defined information groups.

[0028] Preferably, the structuring module includes a sentence-making module, which is used to call the artificial intelligence language model interface to output each information group to the artificial intelligence language model in sequence, and the artificial intelligence language model reorganizes the content of the information group through semantic analysis to obtain a reorganized sentence;

[0029] Combine the restructured statements and customer information sources to obtain complete business opportunity information.

[0030] A business opportunity information management method, applied to the business opportunity information management system, comprises the following steps:

[0031] Step S1: Collect customer information;

[0032] Step S2: Segment the customer information and fill the segmented customer information into the information groups according to the preset information groups;

[0033] Step S3: using time and customer name as indexes and using semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information;

[0034] Step S4: Use the customer name to search the database to determine whether the customer is in the data to construct a corresponding storage document. If not, a storage document is constructed by adding the customer name to a randomly generated ID, and the business opportunity information is stored in the storage document. If it exists, the time in the business opportunity information is obtained, and the business opportunity information is sorted according to the time of different business opportunity information;

[0035] Step S5: Read the business opportunity information sorted at the front in the storage document, determine whether the current time reaches the scheduled time, and if so, send the business opportunity information to the corresponding business personnel;

[0036] Step S6, determining whether feedback information from the salesperson is received within the time threshold. If feedback information is received within the time threshold, the business opportunity information ranked at the front in the storage document is removed. If no feedback information is received, step S5 is re-executed.

[0037] Preferably, the step S1 specifically includes the following steps:

[0038] Generate a first program interface, and obtain text content in the specified chat software through the first program;

[0039] Generate a second program interface, obtain the voice content in the specified chat software through the second program, or obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the salesperson;

[0040] Generate a third-party program interface, obtain the image content in the specified chat software through the third-party program, or connect to the customer's official website, and use web crawler technology to crawl network information in a targeted manner to obtain the image content.

[0041] Preferably, the specific steps of step S2 are as follows:

[0042] Used to receive the text content, perform semantic analysis on the text content through natural language processing technology, divide the text data according to the semantic analysis results, and extract key information therefrom;

[0043] Receive speech content, perform denoising and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into the deep learning model, map the extracted speech features to acoustic units of phonemes or subphonemes, generate a vocabulary sequence based on the acoustic unit sequence and the natural language model, normalize the recognized vocabulary sequence, perform semantic analysis on the normalized vocabulary sequence through natural language processing technology, and obtain key information;

[0044] Receive the image content and call the OCR interface to extract the text content in the image content through OCR technology, perform semantic analysis on the text content through natural language processing technology to obtain key information;

[0045] Clean key information and remove redundant, erroneous or irrelevant data;

[0046] And map the cleaned key information into the defined information groups.

[0047] Preferably, the specific steps of step S3 are as follows:

[0048] Calling the artificial intelligence language model interface, outputting each information group to the artificial intelligence language model in sequence, and the artificial intelligence language model reorganizing the content of the information group through semantic analysis to obtain a reorganized sentence;

[0049] Combine the restructured statements and customer information sources to obtain complete business opportunity information.

[0050] One of the above technical solutions has the following advantages or beneficial effects: the system of the present invention can obtain customer information, extract customer information, generate business opportunity information of the customer, and enable the salesperson to quickly understand the customer's needs and preferences through the business opportunity information, thereby facilitating the completion of transactions. In addition, the system of the present invention can realize automatic acquisition of business opportunity information, greatly reducing the difficulty of extracting business opportunity information and improving the efficiency of acquiring business opportunity information. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 It is a schematic diagram of the structure of an embodiment of the system of the present invention.

[0052] Figure 2 is a flow chart of an embodiment of the method of the present invention. DETAILED DESCRIPTION

[0053] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals represent the same or similar elements or elements having the same or similar functions from beginning to end. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and cannot be understood as limiting the present invention.

[0054] In the description of the embodiments of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the embodiments of the present invention, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0055] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, the meaning of "plurality" is two or more. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0056] like Figures 1-2 As shown, a business opportunity information management system includes:

[0057] The information collection module is used to collect customer information and send the customer information to the information extraction module;

[0058] The information extraction module is used to segment the customer information, and fill the segmented customer information into the information group according to the preset information grouping, and send the content of the information grouping to the structuring module, wherein the information grouping includes at least a time grouping and a customer name grouping;

[0059] The structuring module uses time and customer name as indexes and uses semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information, and sends the business opportunity information to the storage module;

[0060] The storage module is used to search the database using the customer name, determine whether the customer is in the data to construct a corresponding storage document, if not, construct a storage document by adding the customer name to the generated ID, and store the business opportunity information in the storage document, if it exists, obtain the time in the business opportunity information, and sort the business opportunity information according to the time of different business opportunity information;

[0061] A reminder module, which is used to read the business opportunity information sorted at the front in the storage document, determine whether the current time reaches the scheduled time, and if so, send the business opportunity information to the corresponding business personnel and trigger the feedback module;

[0062] The feedback module is used to receive feedback information from the salesperson within a time threshold, and if the feedback information is received within the time threshold, a deletion instruction is sent to the reminder module; if the feedback information is not received within the time threshold, a resend instruction is sent to the reminder module;

[0063] After receiving the deletion instruction, the reminder module removes the business opportunity information sorted at the front in the storage document;

[0064] After receiving the resend instruction, the reminder module resends the business opportunity information to the corresponding business personnel and continues to trigger the feedback module.

[0065] In order to solve the problem of slow manual data screening and extraction of business opportunity information in the prior art, and the problem that business opportunity information cannot be technically utilized. In the present invention, an information collection module is provided, through which customer information can be collected. After collecting different customer information, the information extraction module will extract the content in the customer information. For example, the customer information is: a customer in a certain area needs to purchase a certain commodity within XX time, but because the customer information is sometimes not so complete, the customer information may be multiple groups of scattered text content, voice content and picture content. Therefore, the region, customer, time, commodity and quantity will be separated from the customer information at this time, and then filled in according to the above information in the preset information group. The setting of information grouping can be customized according to the importance of obtaining different information in different enterprises.

[0066] After the customer information is filled into the information group, the structured module will use the time and customer name as indexes to facilitate the subsequent storage and search for different information to speed up the information processing. At this time, since the customer information exists in different information groups, the existing natural language processing (NLP) can be used to reorganize the content in the information group to obtain a business opportunity information, which includes important information in the business and can help the salesperson to facilitate transactions. At this time, the storage module will store the business opportunity information. When storing, it will determine whether there is a storage document corresponding to the customer in the database. If it exists, a new storage document will not be created. When there is no corresponding storage document, a corresponding storage document will be created, and the corresponding business opportunity information will be stored through the storage document. It is worth mentioning that since some customers (individual customers) may have duplicate names, ID information will be generated at this time. The ID information can usually use the customer's social unified code, ID card or the last four digits of the mobile phone as ID information. If there are multiple business opportunity information in the storage document, they will be sorted according to time at this time, and the business opportunity information with an earlier time will be ranked first.

[0067] Since the business opportunity information has a corresponding time, for example, customer A needs to buy a product on November 6, and if the business opportunity information is sent to the salesperson in advance, the salesperson may forget. Therefore, it is necessary to check whether the current time has reached the scheduled time, where the scheduled time is the time in the business opportunity information minus the fixed time value. For example, the time in the business opportunity information is November 6, and the fixed time is 3 days (the fixed time can be set according to different business scenarios). At this time, the scheduled time is November 3, and the business opportunity information will be sent to the salesperson on November 3. The salesperson can also communicate with the customer in advance to get the business opportunity as soon as possible.

[0068] After sending the business opportunity information to the salesperson, the salesperson may not notice the business opportunity information. Therefore, a feedback module is provided in the present invention. When the salesperson receives the business opportunity information, he / she will confirm it. After confirmation, the feedback module will be fed back. Receiving the feedback information means that the salesperson has understood it. At this time, the business opportunity information stored in the storage document is no longer useful. Therefore, the business opportunity information ranked at the front in the storage document can be removed to reduce the content occupation. If the feedback information is not received within the time threshold, it means that the salesperson has not noticed the business opportunity information. Therefore, the business opportunity information needs to be sent to the salesperson again.

[0069] The system of the present invention can obtain customer information, extract customer information, and generate business opportunity information of the customer. The business opportunity information can enable the salesperson to quickly understand the customer's needs and preferences and promote the completion of the transaction. In addition, the system of the present invention can realize the automatic acquisition of business opportunity information, which greatly reduces the difficulty of extracting business opportunity information and improves the efficiency of acquiring business opportunity information.

[0070] Preferably, the customer information includes text content, voice content and picture content;

[0071] The information collection module includes a document information acquisition submodule, a voice information acquisition submodule and an image information acquisition submodule;

[0072] The document information acquisition submodule is used to generate a first program interface, and acquire text content in the specified chat software through the first program;

[0073] The voice information acquisition submodule is used to generate a second program interface, obtain the voice content in the specified chat software through the second program, or obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the salesperson;

[0074] The image information acquisition submodule is used to generate a third program interface and acquire the image content in the specified chat software through the third program.

[0075] Since the salesperson can use different methods to communicate with the customer, the customer information is also diverse. For this reason, the present invention is provided with a document information acquisition submodule, a voice information acquisition submodule and an image information acquisition submodule. The document information acquisition submodule generates a first program interface, through which the chat information of the specified chat program can be obtained, such as corporate WeChat, and when obtaining the text information of the chat window, it is usually in units of days, and the text content of the salesperson and the customer in the chat software is obtained every day.

[0076] The voice information acquisition submodule will generate a second program interface. Similarly, the second program will acquire the voice content of the salesperson and the customer in the chat software every day. Of course, the salesperson and the customer may communicate directly by phone. In order to avoid illegal monitoring of the salesperson's privacy, the second program will monitor the content of the telephone communication only after the salesperson issues a request instruction. Record the voice content of the salesperson and the customer.

[0077] The image information acquisition submodule generates a third program interface, and the third program is responsible for monitoring the image content in the chat information.

[0078] Through these three programs, you can monitor all aspects of the chat content, avoid missing customer information, and help extract business opportunity information.

[0079] Preferably, it also includes an official website information acquisition submodule, which is used to generate a fourth program interface, and the fourth program is used to connect to the customer's official website and perform targeted crawling of network information through web crawler technology to obtain text content and / or image content.

[0080] In order to further expand the scope of obtaining business opportunity information, an official website information acquisition submodule is also provided in the present invention, through which useful text content and / or picture content in the official website of the enterprise can be crawled to develop new customers.

[0081] Preferably, the information extraction module includes a text processing submodule, a voice processing submodule and a picture processing submodule;

[0082] The text processing submodule is used to receive the text content, and perform semantic analysis on the text content through natural language processing (NLP) technology, divide the text data according to the semantic analysis result, and extract key information therefrom;

[0083] For text content recognition, the existing and mature natural language processing (NLP) technology can be used to perform semantic analysis on the text content. The results of the analysis can be used to determine the customer's transaction intention, the content of the transaction, etc., so as to divide the text data and extract the corresponding key information. For example, if the transaction time, quantity, product type, etc. need to be extracted, the text data will be divided according to the above needs to extract the transaction time, quantity, and product, and obtain different key information for each group.

[0084] The speech processing submodule is used to receive speech content, perform denoising and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into the deep learning model, map the extracted speech features to acoustic units of phonemes or subphonemes, generate a vocabulary sequence according to the acoustic unit sequence and the natural language model, normalize the identified vocabulary sequence, perform semantic analysis on the normalized vocabulary sequence through natural language processing technology, and obtain key information;

[0085] Since the speech content may be disturbed by the environment during recognition, it needs to be denoised and filtered before being converted into text content to reduce the impact of external factors on the speech content during the recognition process. When performing speech recognition, it can be recognized through the existing deep learning model. The deep learning model maps the extracted speech features to the acoustic units of phonemes or subphonemes, and then generates the corresponding vocabulary sequence based on the acoustic unit sequence and the natural language model. The recognized vocabulary sequence is normalized, such as adding punctuation marks according to the pause position, and finally a complete text sentence (normalized vocabulary sequence) is obtained. Then semantic analysis can be used to obtain key information.

[0086] The image processing submodule is used to receive image content and call the OCR (optical character recognition) interface to extract text content in the image content through OCR technology and perform semantic analysis on the text content through natural language processing technology to obtain key information.

[0087] Preferably, the information extraction module further includes an input submodule;

[0088] The input submodule is used to clean key information and remove redundant, erroneous or irrelevant data;

[0089] And map the cleaned key information into the defined information groups.

[0090] The input module can be used to clear redundant information and ensure the cleanliness and accuracy of information, so that the content of the corresponding sentences generated later will be more realistic and fluent.

[0091] Preferably, the structuring module includes a sentence-making module, which is used to call the artificial intelligence language model interface to output each information group to the artificial intelligence language model in sequence, and the artificial intelligence language model reorganizes the content of the information group through semantic analysis to obtain a reorganized sentence;

[0092] Combine the restructured statements and customer information sources to obtain complete business opportunity information.

[0093] Through the existing artificial intelligence language model, multiple independent words in the information group can be compiled into a complete reorganized sentence. The reorganized sentence is short but includes all the information that is helpful for the transaction. It can help the salesperson quickly get to know the customer again.

[0094] In addition, since the reorganized sentences are synthesized by the artificial intelligence language model and have not been manually reviewed, sometimes the constructed reorganized sentences may not meet the usage standards. Therefore, the customer information source will be attached to the business opportunity information. When the salesperson feels that the reorganized sentence is not useful, he can re-understand the customer's information based on the customer information source.

[0095] A business opportunity information management method, applied to the business opportunity information management system, comprises the following steps:

[0096] Step S1: Collect customer information;

[0097] Step S2: Segment the customer information and fill the segmented customer information into the information groups according to the preset information groups;

[0098] Step S3: using time and customer name as indexes and using semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information;

[0099] Step S4: Use the customer name to search the database to determine whether the customer is in the data to construct a corresponding storage document. If not, a storage document is constructed by adding the customer name to a randomly generated ID, and the business opportunity information is stored in the storage document. If it exists, the time in the business opportunity information is obtained, and the business opportunity information is sorted according to the time of different business opportunity information;

[0100] Step S5: Read the business opportunity information sorted at the front in the storage document, determine whether the current time reaches the scheduled time, and if so, send the business opportunity information to the corresponding business personnel;

[0101] Step S6, determining whether feedback information from the salesperson is received within the time threshold. If feedback information is received within the time threshold, the business opportunity information ranked at the front in the storage document is removed. If no feedback information is received, step S5 is re-executed.

[0102] Preferably, the step S1 specifically includes the following steps:

[0103] Generate a first program interface, and obtain text content in the specified chat software through the first program;

[0104] Generate a second program interface, obtain the voice content in the specified chat software through the second program, or obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the salesperson;

[0105] Generate a third-party program interface, obtain the image content in the specified chat software through the third-party program, or connect to the customer's official website, and use web crawler technology to crawl network information in a targeted manner to obtain the image content.

[0106] Preferably, the specific steps of step S2 are as follows:

[0107] Used to receive the text content, perform semantic analysis on the text content through natural language processing technology, divide the text data according to the semantic analysis results, and extract key information therefrom;

[0108] Receive speech content, perform denoising and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into the deep learning model, map the extracted speech features to acoustic units of phonemes or subphonemes, generate a vocabulary sequence based on the acoustic unit sequence and the natural language model, normalize the recognized vocabulary sequence, perform semantic analysis on the normalized vocabulary sequence through natural language processing technology, and obtain key information;

[0109] Receive the image content and call the OCR interface to extract the text content in the image content through OCR technology, perform semantic analysis on the text content through natural language processing technology to obtain key information;

[0110] Clean key information and remove redundant, erroneous or irrelevant data;

[0111] And map the cleaned key information into the defined information groups.

[0112] Preferably, the specific steps of step S3 are as follows:

[0113] Calling the artificial intelligence language model interface, outputting each information group to the artificial intelligence language model in sequence, and the artificial intelligence language model reorganizing the content of the information group through semantic analysis to obtain a reorganized sentence;

[0114] Combine the restructured statements and customer information sources to obtain complete business opportunity information.

[0115] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0116] Although the embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A business opportunity information management system, characterized in that: include: The information collection module is used to collect customer information and send the customer information to the information extraction module; The information extraction module is used to segment the customer information, and fill the segmented customer information into the information group according to the preset information grouping, and send the content of the information grouping to the structuring module, wherein the information grouping includes at least a time grouping and a customer name grouping; The structuring module uses time and customer name as indexes and uses semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information, and sends the business opportunity information to the storage module; The storage module is used to search the database using the customer name, determine whether the customer is in the data to construct a corresponding storage document, if not, construct a storage document by adding the customer name to the generated ID, and store the business opportunity information in the storage document, if it exists, obtain the time in the business opportunity information, and sort the business opportunity information according to the time of different business opportunity information; A reminder module, which is used to read the business opportunity information sorted at the front in the storage document, determine whether the current time reaches the scheduled time, and if so, send the business opportunity information to the corresponding business personnel and trigger the feedback module; The feedback module is used to receive feedback information from the salesperson within a time threshold, and if the feedback information is received within the time threshold, a deletion instruction is sent to the reminder module; if the feedback information is not received within the time threshold, a resend instruction is sent to the reminder module; After receiving the deletion instruction, the reminder module removes the business opportunity information sorted at the front in the storage document; After receiving the resend instruction, the reminder module resends the business opportunity information to the corresponding business personnel and continues to trigger the feedback module.

2. A business opportunity information management system according to claim 1, characterized in that: The customer information includes text content, voice content and picture content; The information collection module includes a document information acquisition submodule, a voice information acquisition submodule and an image information acquisition submodule; The document information acquisition submodule is used to generate a first program interface, and acquire text content in the specified chat software through the first program; The voice information acquisition submodule is used to generate a second program interface, obtain the voice content in the specified chat software through the second program, or obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the salesperson; The image information acquisition submodule is used to generate a third program interface and acquire the image content in the specified chat software through the third program.

3. A business opportunity information management system according to claim 2, characterized in that: It also includes an official website information acquisition submodule, which is used to generate a fourth program interface. The fourth program is used to connect to the customer's official website and perform targeted crawling of network information through web crawler technology to obtain text content and / or image content.

4. A business opportunity information management system according to claim 1, characterized in that: The information extraction module includes a text processing submodule, a voice processing submodule and a picture processing submodule; The text processing submodule is used to receive the text content, and perform semantic analysis on the text content through natural language processing technology, divide the text data according to the semantic analysis result, and extract key information therefrom; The speech processing submodule is used to receive speech content, perform denoising and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into the deep learning model, map the extracted speech features to acoustic units of phonemes or subphonemes, generate a vocabulary sequence according to the acoustic unit sequence and the natural language model, normalize the identified vocabulary sequence, perform semantic analysis on the normalized vocabulary sequence through natural language processing technology, and obtain key information; The image processing submodule is used to receive image content, call the OCR interface, extract text content in the image content through OCR technology, and perform semantic analysis on the text content through natural language processing technology to obtain key information.

5. A business opportunity information management system according to claim 4, characterized in that: The information extraction module also includes an input submodule; The input submodule is used to clean key information and remove redundant, erroneous or irrelevant data; And map the cleaned key information into the defined information groups.

6. A business opportunity information management system according to claim 1, characterized in that: The structuring module includes a sentence-making module, which is used to call the artificial intelligence language model interface and output each information group to the artificial intelligence language model in sequence. The artificial intelligence language model reorganizes the content of the information group through semantic analysis to obtain a reorganized sentence; Combine the restructured statements and customer information sources to obtain complete business opportunity information.

7. A method for managing business opportunity information, applied to a management system for business opportunity information as claimed in any one of claims 1 to 6, characterized in that: The steps include: Step S1: Collect customer information; Step S2: Segment the customer information and fill the segmented customer information into the information groups according to the preset information groups; Step S3: using time and customer name as indexes and using semantic analysis to reorganize the content of the information grouping to obtain corresponding business opportunity information; Step S4: Use the customer name to search the database to determine whether the customer is in the data to construct a corresponding storage document. If not, a storage document is constructed by adding the customer name to a randomly generated ID, and the business opportunity information is stored in the storage document. If it exists, the time in the business opportunity information is obtained, and the business opportunity information is sorted according to the time of different business opportunity information; Step S5: Read the business opportunity information sorted at the front in the storage document, determine whether the current time reaches the scheduled time, and if so, send the business opportunity information to the corresponding business personnel; Step S6, determining whether feedback information from the salesperson is received within the time threshold. If feedback information is received within the time threshold, the business opportunity information ranked at the front in the storage document is removed. If no feedback information is received, step S5 is re-executed.

8. A method for managing business opportunity information according to claim 7, characterized in that: The step S1 specifically includes the following steps: Generate a first program interface, and obtain text content in the specified chat software through the first program; Generate a second program interface, obtain the voice content in the specified chat software through the second program, or obtain the voice content in the telephone communication through the second program interface after receiving the request instruction of the salesperson; Generate a third-party program interface, obtain the image content in the specified chat software through the third-party program, or connect to the customer's official website, and use web crawler technology to crawl network information in a targeted manner to obtain the image content.

9. A method for managing business opportunity information according to claim 7, characterized in that: The specific steps of step S2 are as follows: Used to receive the text content, perform semantic analysis on the text content through natural language processing technology, divide the text data according to the semantic analysis results, and extract key information therefrom; Receive speech content, perform denoising and filtering operations on the speech content to obtain preprocessed speech, input the preprocessed speech into the deep learning model, map the extracted speech features to acoustic units of phonemes or subphonemes, generate a vocabulary sequence based on the acoustic unit sequence and the natural language model, normalize the recognized vocabulary sequence, perform semantic analysis on the normalized vocabulary sequence through natural language processing technology, and obtain key information; Receive the image content and call the OCR interface to extract the text content in the image content through OCR technology, perform semantic analysis on the text content through natural language processing technology to obtain key information; Clean key information and remove redundant, erroneous or irrelevant data; And map the cleaned key information into the defined information groups.

10. A method for managing business opportunity information according to claim 7, characterized in that: The specific steps of step S3 are as follows: Calling the artificial intelligence language model interface, outputting each information group to the artificial intelligence language model in sequence, and the artificial intelligence language model reorganizing the content of the information group through semantic analysis to obtain a reorganized sentence; Combine the restructured statements and customer information sources to obtain complete business opportunity information.

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