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Artificial Intelligence(AI) is an attempt to simulate human intelligence in machines to enable them to undertake tasks as a human would do. It seeks to enable machines to think and react like human beings while maintaining their superlative efficiency. On the other hand, Machine Learning(ML) is an application of AI. Machine learning enables systems to constantly improve and learn through experience and data use without requiring explicit programming.

  1. Keyword Intent Identification

Google pays close attention to identifying the intent behind a user’s search queries. Its algorithm has undergone multiple changes over the years. These changes have made the algorithm capable of discerning what users want. Given this focus on user intent, content marketing requires businesses to identify the right keyword intent. The AI-powered intent analysis is a boon in this case. It helps content marketing teams create content that satisfies a user’s search intent. We are looking at machine learning here. Machine learning enables systems to make data-driven predictions and decisions. It analyzes and learns from historical user behavior patterns. It studies data and helps content marketers gain valuable insights into the intent of website visitors. A better understanding of user intent helps content creators choose the most suitable keywords.

  1. Topic Generation As An Extension of Content Research

Another challenge in content marketing is identifying topics for creating content. The increasing demand for high-volume content drains content creators’ creative ability. As a result, they often find it difficult to come up with topics that are fresh and relevant at the same time. Topic generation is the starting point of content research. And it is a well-known fact that any piece of content can only offer value if it is based on careful research. AI can help content creators generate relevant and unique topics. AI-powered tools automate topic research based on content trends, search intent, relevant keywords, and more. These tools can conduct a competitive analysis to generate a comprehensive list of topics. Content creators can take inspiration from these topics and conduct their research. They can even sort the most relevant topics based on metrics such as competitiveness and relevancy.

  1. Hyper-personalization and Creating Targeted Content

Content marketing has always revolved around creating personalized content for the target audience. Personalized content helps create a positive impact on the audience about a brand. Therefore, content creatives strive to personalize content as much as possible. Consumers dislike receiving emails and other forms of information that aren’t personalized to their specific needs and tastes. If content marketers want to generate fresh leads, they must research their target customers to offer customized content.Machine learning helps content creators track consumer preferences, behaviors, and content interaction. Based on this information, they can create personalized content pieces that enhance user engagement and lead to conversions.

  1. Editing and Proofreading Content

Content creators need to ensure that they subject their content pieces to rigorous scrutiny and review before it goes public. The process of proofreading and reviewing content is tedious, time-consuming, and more taxing than writing it. Thus, content marketers tend to rely on software solutions to help their cause. AI and machine learning are highly capable in their ability to review and proofread content. There are multiple AI-powered tools in the market today to make life easy for content creators. These tools help content creators identify and remove grammatical mistakes and formatting problems. Moreover, they help suggest relevant edits to make your content more crisp and easy to read. Therefore, these tools enhance the readability of textual content and help improve user engagement.


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