Sales activity-based event recording system and data processing method

Abstract

The invention relates to the technical field of data processing, and discloses a sales activity-based event recording system and a data processing method, and the system comprises an acquisition module, a completion module, an association module and a recording module. The acquisition module is used for acquiring sales behavior data; the complementing module is used for automatically complementing the sales behavior data into an equivalent complete type according to the sales behavior data when the sales behavior data is of a fragmented type; when the sales behavior data is in a complete type, integrity checking is carried out; if the integrity check is passed, not processing, and if the integrity check is not passed, complementing to be an equivalent complete type; the association module is used for positioning a sales behavior stage, automatically associating a next sales behavior stage according to a sales process, and completing corresponding input of data; and the recording module is used for outputting a behavior summary based on the sales behavior stage in which the basic data is input. According to the method, comprehensive and intelligent sales activity associated data recording and management can be realized, the operation convenience is high, and the adaptability is relatively high.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an event recording system based on sales activities and a data processing method. Background Art

[0002] In today's era of accelerated digital transformation, companies are facing unprecedented challenges and opportunities. With the rapid development of Internet technology, consumer behavior patterns have undergone profound changes. They are no longer limited to traditional shopping methods, but are increasingly turning to online platforms to choose goods and services, and consumer needs have become more complex. This change has forced companies to more keenly capture market dynamics in order to adjust their marketing strategies and service content in a timely manner. In this context, effective management of sales activities has become a vital task.

[0003] During sales activities, a series of related data will be generated, such as sales follow-up records, customer information, order information, contract information, etc. These sales activity related data can help companies obtain more sales opportunities and improve customer satisfaction. In addition, these data record the interaction between sales staff and customers, which helps companies understand customer needs more deeply and provide companies with sales leads that can be traced, thereby providing more targeted services.

[0004] In the collection of related data, early data collection methods were relatively simple and limited, mainly relying on manual entry by sales staff or order records generated after the transaction was completed. However, this method has obvious limitations: on the one hand, manual entry is prone to errors and is time-consuming and laborious; on the other hand, relying solely on post-event records cannot reflect the complete customer interaction process and will miss a lot of key information. With the advancement of information technology, especially the application of emerging technologies such as big data, cloud computing and artificial intelligence, the more advanced data collection methods currently use a more intelligent way to collect and process data. For example, modern CRM systems (customer relationship management systems) can obtain customer information from multiple channels and store these scattered data in a unified database by integrating a variety of automation tools, and can use preset rules to automatically perform repetitive tasks, such as sending emails, assigning work orders or reminding sales staff to follow up with potential customers. However, existing CRM systems still have the following problems: (1) The threshold for use is high and there is a lot of room for improvement in operational convenience. Users are required to fully master the system's preset rules, and professional IT personnel are required to configure and manage them. (2) The requirements for data sources are high and they are highly dependent on data sources. The effective operation of the CRM system is highly dependent on accurate and timely updated data. Any data entry errors or incomplete information will directly affect the quality of analysis results and decision-making. (3) Incomplete data management. The CRM system focuses on the collection and management of customer information, but the collection of related data in sales activities is not comprehensive and the management is not flexible. Summary of the invention

[0005] The present invention aims to provide an event recording system and data processing method based on sales activities, which can realize comprehensive and intelligent recording and management of sales activity-related data, and has strong operational convenience and strong adaptability.

[0006] To achieve the above objectives, the present invention provides the following basic solutions.

[0007] Solution 1

[0008] An event recording system based on sales activities, including a collection module, a completion module, a correlation module and a recording module;

[0009] The collection module is used to collect sales behavior data; the sales behavior data includes: fragmented or complete text, image or audio;

[0010] The completion module is used to automatically complete the sales behavior data into an equivalent complete type according to the sales behavior data when the sales behavior data is of a fragmented type; when the sales behavior data is of a complete type, a completeness check is performed; if the completeness check passes, no processing is performed; if the completeness check fails, the missing part is completed and completed into an equivalent complete type; the sales behavior data of the complete type and the equivalent complete type together form the basic data;

[0011] The association module is used to locate the sales behavior stage according to the basic data, and automatically associate the next sales behavior stage according to the preset sales process, and complete the corresponding entry of the basic data;

[0012] The recording module is used to output a behavior summary of each sales behavior stage based on the sales behavior stage with basic data entered through a preset AI model.

[0013] Furthermore, the sales behavior stages include preliminary communication, confirmation of demand, quotation, interview, order completion, no demand, order loss and abandonment.

[0014] Furthermore, the sales behavior data includes contact information, communication channels, initial communication impressions, communication records, demand records, product information, interview records, interview materials, order information, payment vouchers, and customer return visit records.

[0015] Furthermore, the integrity verification includes using a verification model for verification; the verification model is constructed based on a random forest algorithm; when performing the verification, the verification model identifies data patterns to discover missing parts.

[0016] Furthermore, it also includes a correction module; the correction module is used for the user to modify the input sales behavior data.

[0017] Furthermore, after the user modifies the data, the correction module performs linkage modification on other items associated with the data item modified by the user.

[0018] Furthermore, after the linkage modification is completed, the correction module also cleans up the stored historical sales behavior data.

[0019] Furthermore, the recording module also outputs behavioral suggestions for each sales behavior stage based on the sales behavior stage in which the basic data is entered through a preset AI model.

[0020] Furthermore, the preset AI model is a BERT-based deep learning model; the recording module performs semantic matching, answer extraction and multi-hop reasoning based on the preset AI model, and integrates them into a behavior summary.

[0021] Solution 2

[0022] The data processing method based on sales activities uses the event recording system based on sales activities as described in Solution 1 to process data; the method includes the following steps:

[0023] The collection module collects sales behavior data; the sales behavior data includes: fragmented or complete text, image or audio;

[0024] When the sales behavior data is of a fragmented type, the completion module automatically completes it into an equivalent complete type based on the sales behavior data; when the sales behavior data is of a complete type, the completion module performs a completeness check; if the completeness check passes, no processing is performed; if the completeness check fails, the missing parts are completed and completed into an equivalent complete type; the sales behavior data of the complete type and the equivalent complete type together form the basic data;

[0025] The association module locates the sales behavior stage based on the basic data, and automatically associates the next sales behavior stage according to the preset sales process, and completes the corresponding entry of the basic data;

[0026] The recording module outputs the behavior summary of each sales behavior stage based on the sales behavior stage with basic data entered through the preset AI model.

[0027] The working principle and advantages of the present invention are:

[0028] The present invention is based on the event recording system and data processing method of sales activities, which can realize comprehensive and intelligent recording and management of sales activity-related data, and has strong operational convenience and strong adaptability. The key points are:

[0029] First, the recording scope of this solution covers the entire sales process and is comprehensive - sales behavior data covers all interactive information generated from the first contact with potential customers to the final completion of the purchase process. These data not only include static attributes such as customer personal information and contact information, but more importantly, they include the behavior trajectories of customers and users (i.e. sales staff) at different stages, such as contract content, negotiated product information, changes in customer needs, and whether the order is finally completed. By comprehensively and accurately collecting this data, companies can gain a deep understanding of each customer, thereby achieving personalized communication and service.

[0030] Second, this solution can be used as an automated tool that can help users automatically track activities at every customer touchpoint with simple data entry, and convert them into structured digital information and store them in the database. This means that whether it is a phone conversation, email exchange or interaction on social media, it can be seamlessly recorded by the system. Not only that, with the help of advanced natural language processing technology and speech recognition algorithms, unstructured content can also be converted into valuable insights, further enriching the analysis dimension of the system. In addition, the recording module can also summarize the sales behavior at each stage and has the ability to integrate data from various touchpoints.

[0031] Third, this solution has high data processing efficiency and a low threshold for use. For companies with a large sales team, a huge amount of communication records are generated every day. Without effective means to manage and analyze them, even the most experienced managers will find it difficult to extract useful information from them. By deploying this system, each sales behavior stage can be automatically associated, and the sales behavior data can be automatically linked to the corresponding sales behavior stage. For users, there is no need to learn complex system rules, only to enter their daily record data. For deployers (enterprises), there is no need to spend money on system configuration.

[0032] Fourth, this solution has strong adaptability. Compared with the existing CRM system, in this solution, although the record of all sales behaviors needs to rely on the input of the data source, this solution has lower requirements for the data source, and the input data is classified and completed. Even if the input data is incomplete, it can support the accurate recording of sales behaviors through the processing of the completion module, and the record quality can remain stable. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 It is a schematic diagram of the system structure of Embodiment 1 of the event recording system and data processing method based on sales activities of the present invention. DETAILED DESCRIPTION

[0034] The following is a further detailed description through specific implementation methods:

[0035] Embodiment 1

[0036] The embodiment is basically as shown in the attached Figure 1 As shown: An event recording system based on sales activities includes a collection module, a completion module, an association module, a recording module and a correction module.

[0037] The acquisition module is used to collect sales behavior data. The sales behavior data includes: fragmented or complete text, image or audio. The sales behavior data specifically includes contact information, communication channels, initial communication impressions, communication records, demand records, product information, interview records, interview materials, order information, payment vouchers, and customer return visit records.

[0038] Specifically, the sales behavior data can be imported or input by the user through the collection module; or extracted from the associated software (such as the existing CRM system) by the collection module. In this embodiment, the user can collect the sales behavior data by importing text, images or audio.

[0039] The fragmented type refers to that the text, image or audio does not have complete structure and event information; the complete type refers to that the text, image or audio has complete structure and event information.

[0040] When distinguishing the types of sales behavior data, the acquisition module first pre-processes the sales behavior data of text, image or audio type, and then provides fragmented type and complete type tags for users to choose. If the user skips tag selection, the sales behavior data imported by the user is preliminarily checked according to the preset rule set.

[0041] The preprocessing includes: based on OCR recognition, NLP recognition and speech recognition, converting the text information that can be extracted from the image and the speech data that can be extracted from the audio into text data; and performing standardization processing and data cleaning on all text data.

[0042] The preset rule set contains the project combination that needs to be filled in each sales behavior stage. During the preliminary verification, the collection module performs verification based on the fuzzy matching principle. If the matching degree between the sales behavior data and the project combination in the preset rule set is higher than the corresponding threshold, it is judged as a complete type; otherwise, it is judged as a fragmented type.

[0043] With this setting, the preliminary verification is carried out based on the combination of items required to be filled in at each sales behavior stage. The verification efficiency is high, and the data that passes the verification basically contains the information required for that sales behavior stage, which can prove that it has relatively complete event information and structure.

[0044] The completion module is used to automatically complete the sales behavior data into an equivalent complete type based on the sales behavior data when the sales behavior data is of a fragmented type; when the sales behavior data is of a complete type, a completeness check is performed; if the completeness check passes, no processing is performed; if the completeness check fails, the missing parts are completed and completed into an equivalent complete type; the sales behavior data of the complete type and the equivalent complete type together form the basic data.

[0045] Specifically, the integrity verification includes using a verification model for verification; the verification model is constructed based on a random forest algorithm; when the verification model is performing verification, the verification model identifies data patterns to discover missing parts.

[0046] In this embodiment, the verification model is pre-trained using a historical sales data set, and the historical sales data set includes a complete type of historical sales behavior data corresponding to each sales behavior stage.

[0047] When completing data, the following completion strategies are included: searching for equivalent information of the missing part from other sales behavior data to complete it; when there is no equivalent information, setting a fill character for equivalent completion. When new sales behavior data is imported, search again until the completion is completed. Preferably, for the equivalently completed part, when the subsequent recording module outputs the behavior suggestion, it also suggests that the user pay attention to collecting the information of this part in the subsequent sales behavior stage.

[0048] The association module is used to locate the sales behavior stage according to the basic data, and automatically associate the next sales behavior stage according to the preset sales process, and complete the corresponding entry of the basic data.

[0049] The sales behavior stages include preliminary communication (corresponding to contact information, communication channels, initial communication impression and other data), confirmation of needs (corresponding to communication records, demand records, communication time and other data), quotation (corresponding to product information, contract information and other data), interview (corresponding to interview records, interview materials and other data), order placement (corresponding to order information, payment vouchers and other data), no demand (corresponding to customer return visit records and other data), order loss (corresponding to review reports and other data) and abandonment.

[0050] The recording module is used to output behavior summaries and behavior suggestions for each sales behavior stage based on the sales behavior stages with input basic data through a preset AI model.

[0051] Specifically, the preset AI model is a BERT-based deep learning model; the recording module performs semantic matching, answer extraction and multi-hop reasoning based on the preset AI model, and integrates them into behavior summaries and behavior suggestions.

[0052] The correction module is used for users to modify the sales behavior data they have input. After the user modifies the data, the correction module performs linkage modification on other items associated with the data item modified by the user; after the linkage modification is completed, the correction module also cleans up the stored historical sales behavior data.

[0053] This embodiment also provides a data processing method based on sales activities, which uses the above-mentioned event recording system based on sales activities to process data; the method includes the following steps:

[0054] The collection module collects sales behavior data; the sales behavior data includes: fragmented or complete text, image or audio;

[0055] When the sales behavior data is of a fragmented type, the completion module automatically completes it into an equivalent complete type based on the sales behavior data; when the sales behavior data is of a complete type, the completion module performs a completeness check; if the completeness check passes, no processing is performed; if the completeness check fails, the missing parts are completed and completed into an equivalent complete type; the sales behavior data of the complete type and the equivalent complete type together form the basic data;

[0056] The association module locates the sales behavior stage based on the basic data, and automatically associates the next sales behavior stage according to the preset sales process, and completes the corresponding entry of the basic data;

[0057] The recording module outputs the behavior summary of each sales behavior stage based on the sales behavior stage with basic data entered through the preset AI model.

[0058] The present embodiment provides an event recording system and data processing method based on sales activities, which can realize comprehensive and intelligent recording and management of sales activity-related data, and has strong operational convenience and strong adaptability.

[0059] Embodiment 2

[0060] Based on the event recording system of sales activities, the collection module and the correction module are adjusted on the basis of the first embodiment.

[0061] The acquisition module also establishes a two-way signal connection with the user's personal terminal. In specific applications, the personal terminal can be a mobile phone, tablet or other terminal. The user can open or close the automatic acquisition permission to the acquisition module through the personal terminal. When the automatic acquisition permission is turned on, when the user uses the personal terminal to record sales behavior data on a daily basis, the acquisition module automatically collects it, which can save the user's self-import process.

[0062] The correction module is also used to perform linkage approval and to correct data when the linkage approval fails.

[0063] The linkage approval includes: when there is a linkage relationship between the record items of each sales behavior stage, the record items in different sales behavior stages are called according to the linkage relationship, and the data consistency of each record item is verified; if the data consistency is greater than the corresponding threshold, the approval is successful; otherwise, the approval fails.

[0064] The linkage relationship between the record items at each stage of sales behavior can be preset by the user. The linkage relationship refers to the correspondence between the data in the two record items, such as the correspondence between contract information and product information, and the correspondence between the purchase order and the receipt (invoice) record issued by the supplier after the transaction is completed (the amount is equal), so as to ensure that the purchased goods or services are consistent with the payment, etc.

[0065] Preferably, the correction module further records the linkage relationship set by the user, and adds the linkage relationship to the record items of the same type.

[0066] The information modification includes: for the record item that fails to be approved, sending an information verification notification to the corresponding user, and including the record items associated with the record item in the approval notification to facilitate the user to verify the data.

[0067] The present embodiment provides an event recording system and data processing method based on sales activities. Compared with the first embodiment, the present embodiment has stronger data mining and analysis capabilities for sales behavior data. It can verify the data based on the correlation between the recorded items and the inherent matters of the sales process itself, which helps to ensure the consistency, integrity and traceability of the data records, and avoids the quality of the sales event records affected by the input of erroneous information.

[0068] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is not described in detail here. The ordinary technicians in the relevant field are aware of all the common technical knowledge in the technical field of the invention before the application date or priority date, can obtain all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement the scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for the ordinary technicians in the relevant field to implement this application. It should be pointed out that for the technicians in this field, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicality of the patent.

Claims

1. An event recording system based on sales activities, characterized in that: It includes a collection module, a completion module, a correlation module and a recording module; The collection module is used to collect sales behavior data; the sales behavior data includes: fragmented or complete text, image or audio; The completion module is used to automatically complete the sales behavior data into an equivalent complete type according to the sales behavior data when the sales behavior data is of a fragmented type; when the sales behavior data is of a complete type, a completeness check is performed; if the completeness check passes, no processing is performed; if the completeness check fails, the missing part is completed and completed into an equivalent complete type; the sales behavior data of the complete type and the equivalent complete type together form the basic data; The association module is used to locate the sales behavior stage according to the basic data, and automatically associate the next sales behavior stage according to the preset sales process, and complete the corresponding entry of the basic data; The recording module is used to output a behavior summary of each sales behavior stage based on the sales behavior stage with basic data entered through a preset AI model.

2. The event recording system based on sales activities according to claim 1, characterized in that: The sales behavior stages include initial communication, demand confirmation, quotation, interview, order placement, no demand, order loss and abandonment.

3. The event recording system based on sales activities according to claim 1, characterized in that: The sales behavior data includes contact information, communication channels, initial communication impressions, communication records, demand records, product information, interview records, interview materials, order information, payment vouchers, and customer return visit records.

4. The event recording system based on sales activities according to claim 1, characterized in that: The completeness verification includes using a verification model for verification; the verification model is built based on a random forest algorithm; when the verification is performed, the verification model identifies data patterns to discover missing parts.

5. The event recording system based on sales activities according to claim 1, characterized in that: It also includes a correction module; the correction module is used for the user to modify the input sales behavior data.

6. The event recording system based on sales activities according to claim 5, characterized in that: After the user modifies the data, the correction module performs linkage modification on other items associated with the data item modified by the user.

7. The event recording system based on sales activities according to claim 5, characterized in that: After the linkage modification is completed, the correction module also cleans up the stored historical sales behavior data.

8. The event recording system based on sales activities according to claim 1, characterized in that: The recording module also outputs behavioral suggestions for each sales behavior stage based on the sales behavior stage with input basic data through a preset AI model.

9. The event recording system based on sales activities according to claim 8, characterized in that: The preset AI model is a BERT-based deep learning model; the recording module performs semantic matching, answer extraction and multi-hop reasoning based on the preset AI model, and integrates them into a behavior summary.

10. A data processing method based on sales activities, characterized in that: The method of applying the sales activity-based event recording system as described in any one of claims 1 to 9 to perform data processing comprises the following steps: The collection module collects sales behavior data; the sales behavior data includes: fragmented or complete text, image or audio; When the sales behavior data is of a fragmented type, the completion module automatically completes it into an equivalent complete type based on the sales behavior data; when the sales behavior data is of a complete type, the completion module performs a completeness check; if the completeness check passes, no processing is performed; if the completeness check fails, the missing parts are completed and completed into an equivalent complete type; the sales behavior data of the complete type and the equivalent complete type together form the basic data; The association module locates the sales behavior stage based on the basic data, and automatically associates the next sales behavior stage according to the preset sales process, and completes the corresponding entry of the basic data; The recording module outputs the behavior summary of each sales behavior stage based on the sales behavior stage with basic data entered through the preset AI model.

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