Data Analytics and Predictive Modeling: How Artificial Intelligence Can Help Marketing Teams Better Predict Market Trends and Predict Marketing Effects

Author: Zen and the Art of Computer Programming

1 Introduction

In the past few years, with the development of information technology such as the Internet, mobile Internet, and e-commerce, marketing activities have also experienced social marketing, personal brand image building, free promotion services, A transition period for paid subscription products. As a marketer, successfully building a benign, brand image, and personalized consumer relationship network is a process of continuous accumulation. In this process, how to improve marketing efficiency, reduce costs, improve customer satisfaction, and better predict the market Identifying trends and ultimately influencing marketing strategies is a challenge for all marketers. Artificial intelligence (AI), an emerging field based on machine learning and data science, is becoming a new marketing tool and predictor, especially at the marketing strategy level.

It is one of my important tasks as a technical expert to improve the prediction accuracy of the marketing team, improve the efficiency of marketing decision-making, and improve the marketing effect by in-depth understanding of the principles of artificial intelligence (AI) technology and the exploration of its latest applications. This article will elaborate on this from the following aspects:

1. Composition of data features, feature selection methods, model evaluation methods and comparison
2. Construction and evaluation methods of artificial neural network (ANN), random forest (RF) and support vector machine (SVM)
3. Selection of model fusion methods and evaluation of model performance
4. The application and advantages of deep learning framework TensorFlow and PyTorch
5. Practical application cases of AI algorithms in the field of marketing
6. AI+ Market Research Method and Effect Evaluation
7. Design and deployment of AI+ marketing model
8. Design and implementation of AI+ marketing strategy
9. Summary and Outlook

Welcome everyone to pay more attention to our WeChat public account "AI Marketing" and continue to share the latest developments about AI technology and marketing.

2. Composition of data features, feature selection methods, model evaluation methods and comparison

2.1 Composition of data features

After determining the target variables, we need to