A Study on the Influence of User Behavior Data on Brand Strategy in Mobile Computing Environment

Abstract

Ordinary brand strategy can't attract users' attention and consumption psychology, in order to improve the brand's strategy, this paper firstly analyzes the consumer's behavior and the relationship between consumers and brand strategy, to obtain the psychology and behavior of consumers when they buy goods. Secondly, transfer learning algorithm is used to process the user behavior to make the data more complete and accurate. Finally, the neural network is used to predict the user behavior, so as to formulate a reasonable brand strategy. Analyzing the formulated brand strategy from various aspects such as conversion rate, market evaluation and user activity, the results show that the formulated brand strategy has a high conversion rate, increasing the conversion rate of the brand to 88%, so that the benefits of the enterprise can be improved, and the number of times the brand has been exposed is also higher, up to about 90 times. It can accurately locate the target users, attract the attention of users, and effectively interact with them, which improves the brand awareness in the mobile environment and promotes the positive development of the brand.