Author: Zen and the Art of Computer Programming
Marketing automation is an increasingly hot topic. From the earliest telephone marketing to Internet marketing, to mobile Internet marketing and online marketing, marketing automation has become a very important link in all walks of life. As the socio-economic environment continues to change, the demand for marketing automation is also changing. For example, e-commerce business in various industries is booming recently, and I believe that the demand for marketing automation will become stronger and stronger. However, because traditional manual marketing processes are too time-consuming and inefficient, machine learning is needed to improve marketing efficiency during the transformation of business models. Machine learning (ML) is an artificial intelligence science that provides an effective way to solve problems. It can learn from data and use its own analysis capabilities to predict unknown data, making computers intelligent. In the field of marketing automation, traditional rule engines cannot handle fast and accurate matching of unstructured data and complex business logic. At the same time, they cannot provide personalized customization or personalized recommendations. Therefore, machine learning-based methods emerged. This article will elaborate on my views on the field of artificial intelligence marketing automation from the following three aspects: First, machine learning, as an emerging technology field, has its unique research direction and development prospects; second, the key to optimization of marketing automation processes It is business personnel who know how to "machine learning" and use machine learning methods to achieve marketing automation; third, the application scenarios of machine learning in the field of marketing automation.
2. Explanation of basic concepts and terms
2.1 Definition
Machine Learning (English: Machine Learning), also known as artificial intelligence (AI), is a type of artificial intelligence method that aims to equip computers with the ability to learn in order to find patterns in data and use these patterns to analyze new inputs. Make predictions and decisions.
2.2 Terms and abbreviations
- Data SetData Set: