Business opportunity mining method based on enterprise portraits

Abstract

The invention discloses a business opportunity mining method based on an enterprise portrait, and the method comprises the steps: obtaining structured, semi-structured and unstructured mass data through Internet data and enterprise basic data, carrying out the preprocessing of the data, and forming an enterprise service data center on the basis of the data; dynamically matching deduplication and user basic information through a system to form a unique ID of the whole network of the user; integrating and cleaning the data of each dimension of the enterprise, and binding the data with the uniqueID of the enterprise to form a portrait system; carrying out model training through multi-dimensional enterprise portraits and enterprise historical order data, and improving the user conversion rateand the repurchase rate; enabling different portraits to correspond to different recommendation rules, pushing proper products to enterprises in time, and pushing business opportunities to matched business personnel through an intelligent matching algorithm; obtaining sales feedback data in time through buried points, and building a business opportunity mining evaluation model; and performing secondary optimization on the business opportunity mining model in combination with results of machine learning and business personnel feedback information.

Description

technical field [0001] The invention relates to the field of Internet e-commerce, in particular to a method for mining business opportunities based on enterprise portraits. Background technique [0002] Enterprises are the main participants in market economic activities. The enterprise service industry is the life steward of the enterprise. It is the responsibility of the enterprise to discover the needs of the enterprise in a timely manner and improve the user experience. It is also the way to assign value to the platform and maximize the value of the platform. Therefore, how to accurately locate the target group, improve user retention and user repurchase rate has become a key issue in the enterprise service industry. [0003] The main purpose of the system is to use user data to profile customer companies, tap business opportunities, and provide effective solutions for improving user growth, customer retention and repurchase rates. [0004] The patent with the publicatio...

AI Technical Summary

Problems solved by technology

[0006] The operation mode of the platform is: user acquisition -> conversion of users into customers -> customer retention -> customer repurchase. The traditional operating model focuses on "acquisition of user numbers" and improves performance through the growth of user numbers. However, due to this The cost of this method is relatively high. At present, many platform operations are gradually shifting their focus to "customer repurchase"

In order to obtain the performance brought by retained customers, enterprises often lack overall planning, ignore the value of intangible assets brought by customer data, lack of processing of corporate portraits, lack of understanding of user life cycle, and miss the similarity between customers and the relationship between products and The huge benefits of connectedness between customers

Secondly, affected by the operation value orientation, most of the platform operating systems are based on the RFM (the time interval from the last Recency user to the current time; the frequency of consumption in the latest period of Frequency; the total consumption of Monetary in the most recent period) model, based on the total consumption of users, Distinguish between high-value and low-value users, and focus on high-value users for repurchase, ignoring the value brought by other users; there are also some traditional platforms that increase the repurchase rate through product promotions, which reduces to a certain extent The value of the platform limits the promotion and application of the platform

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