In the process of digital transformation

electric power enterprises can effectively reduce their operating costs and provide customers with more convenient and efficient services by building a multi- channel service system and making full use of the Internet + physical channels. Under the above background

a power marketing channel diversion strategy based on improved collaborative filtering algorithm is proposed. Firstly

the customer attribute data matrix is constructed

and the matrix decomposition algorithm is used to recover the missing data in the original customer attribute matrix

and the K-means algorithm is used to cluster the customer attributes. Then

using the customer mixed type attribute dissimilarity measure

through the user based collaborative filtering recommendation algorithm

the target customer’s K- nearest neighbor matrix is found

and the diversion strategy of travel alienation is formulated.Finally

taking 100 000 payment work order data as an example

the influence of customer attribute matrix filling

different measurement methods and the number of nearest neighbors on the drainage accuracy are analyzed

and the effectiveness and feasibility of the proposed algorithm are found.