By now, most brands recognize the importance of high-quality content. The process of interpreting audience data, choosing topics, and creating a content marketing strategy can be time-consuming and tedious. AI content and machine learning speed up the process of content planning while also discovering more relevant topics that are likely to convert customers.
What Is Machine Learning?
Machine learning (ML), a subset of artificial intelligence (AI), refers to a computer’s ability to learn. Using algorithms and pre-programmed rules, AI can not only complete tasks but also improve its performance over time. Machine learning isn’t new. In fact, it has been used in many industries for decades, most notably to make predictions about the stock market. More industries are recognizing the value of machine learning, including marketing, which offers practical applications to content marketing.
Machine learning is also already a part of most people’s lives, whether they realize it or not. Gmail and Microsoft Word both use machine learning to predict the next word a user will type. Editing plug-ins are programmed to pop up and inform users of a typo or an unclear sentence.
How Does Machine Learning Help With Content Marketing?
Machine learning offers value beyond that of basic tasks. Brands can also use machine learning to improve the quality of content marketing strategies. Because machine learning is capable of quickly reviewing and interpreting data, it can offer insight into the type of content that’s most likely to convert. Machine learning helps with content marketing using sentiment and predictive analysis.
Sentiment Analysis
Sentiment analysis uses natural language processing to better understand the emotional complexities of an audience. Machine learning is capable of recognizing and predicting the emotional reactions of audiences, helping brands shape their content for more meaningful targeted customer interactions.
Predictive Analysis
Machine learning is also capable of taking data and using it to predict human behaviors. This enables brands to better understand the type of content consumers want most and when they want it. Because machine learning uses data to make predictions, it often leads to higher engagement and conversions.
Benefits of Using Machine Learning for Content Marketing
Implementing AI content and machine learning into a brand’s content marketing strategy can:
- Predict the type of content that will best resonate with a target market.
- Identify content topics that are likely to get the most customer engagement.
- Determine the appropriate length of content that will hold the reader’s attention.
- Reduce the amount of time it takes to create a content marketing strategy.
- Analyze competitors’ content to gather information on what techniques work best.
- Personalize content based on a brand’s unique goals.
- Interpret large collections of data, identifying what information is most important.
- Review and make suggestions on ways to improve existing content.
AI content is fast and efficient, leaving content marketers more time to focus on the overall quality of content. It can also reduce the cost of analyzing data and planning content, helping brands optimize their marketing budgets.
Perhaps the biggest benefit of machine learning is that it continues to learn. By continually reviewing content and human language, AI is capable of adapting. As brands continue to adjust goals, AI is also capable of quickly changing to accommodate those goals.
Writing Content With Artificial Intelligence
Machine learning is continually improving to the point where it’s not only used to analyze content and choose topics, but in some cases, it can also write content. By reviewing existing content and learning language and communication rules, national language generation programs are capable of creating content that appears to be written by a human.
Practical Applications of Machine Learning in Content Marketing
While most brands aren’t yet ready to hand over the reins and rely fully on AI to handle all their content marketing needs, there are a few ways to practically implement it at this time. Using AI to collect and review data is one of the most effective ways brands can use machine learning right now. Although numerous programs enable brands to collect data, interpreting this data is a challenge in itself.
Machine learning is also practical in competitive analysis. Competitive analysis is important, but because it’s a time consuming task, brands don’t always give it the time it deserves. AI is capable of quickly evaluating competitors, giving brands a competitive advantage. AI is also especially beneficial for SEO strategy. By inputting SEO goals and keywords into a machine learning program, content writers can ensure the content they write is optimized for both user experience and Google bots.
Machine learning and artificial intelligence in content marketing are no longer concepts of the future. AI in content marketing and machine learning can help brands break through the noise and abundance of content on the internet today, helping them reach more customers without going over budget.
