Intelligent clue matching method based on algorithm model

Abstract

The invention relates to the field of information processing, in particular to an intelligent clue matching method based on an algorithm model, and the method comprises the following steps: S1, obtaining clue information; S2, filling and perfecting clue content by a main engine plant; S3, further filling and perfecting clue contents through third-party data; S4, data preprocessing; S5, carrying out feature engineering; and S6, model training and optimizing. According to the method, the problem of transformation of existing clues from manual matching to model automatic matching in the marketing process of the main engine plant is mainly solved, extensive clue distribution in the clue matching process is solved, human intervention is reduced, and distribution precision is improved.

Description

technical field [0001] The invention relates to the technical field of information processing, in particular to an algorithm model-based intelligent clue matching method. Background technique [0002] After obtaining a large number of clues through multiple channels, the OEM will distribute the clues. Before the clues are distributed, the clues need to be processed. The relevant employees of the OEM will use the existing information of the clues, such as gender, age, income level, address, etc. After the leads are allocated to the corresponding 4S stores, the relevant sales staff of the 4S stores will follow up the leads until the transaction succeeds or fails. At this point, the lead marketing link in the OEM marketing scenario is completed. [0003] shortcoming: [0004] 1 Due to different acquisition channels, the completeness of the content of each clue is not uniform, and it is difficult for the OEM itself to complete all the clue information; [0005] 2. Due to the i...

AI Technical Summary

Problems solved by technology

[0004] 1 Due to different acquisition channels, the completeness of the content of each clue is not uniform, and it is difficult for the OEM itself to complete all the clue information;

[0005] 2. Due to the inconsistency in the completeness of clue content, it will be difficult for employees to form standardized distribution rules when assigning clues;

[0006] 3. There is human intervention in the distribution, and different people will have deviations in understanding some marginalized indicators, which will increase the instability of the distribution effect;

[0007] 4 After the leads are assigned to the 4S store, in the process of assigning the leads to the specific sales personnel, due to the lack of a unified quantitative standard, it may cause a mismatch between the leads and the sales personnel, resulting in the loss of leads

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