Advancing Visual Marketing Strategies Through Deep Learning-Based Image Recognition for Improved Customer Engagement and Brand Visibility

This paper aims at analyzing the effectiveness of utilizing deep learning-based image recognition in enhancing the visual marketing thereby determining the extent to which clients' attention and brand awareness are likely to be affected. It uses convolutional neural networking (CNN) to analyze and classify the visual content and the models used include VGG16, ResNet50, InceptionV3. An effective implementation of the data gathering, feature engineering, and algorithm development can be seen in the enhancing of the marketing effectiveness. This entails better accuracy of images in classification. This involves gaining high engagement rates from the customers. probabilities of high visibility of the brands across the various platforms. The study points at the possibility of deep learning technologies in changing visual marketing practices and therefore serves as a useful reference guide to business entity that wish to align themselves with adequate marketing practices in the growing digital landscape.

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