When we talk about content creation and content marketing, there’s a common notion attached to them. It is about the importance of creativity. Traditionally, content creation has been perceived as an extension of the creative pursuit of human beings.
No doubt that this thought holds substance since content creation and content marketing are all about channeling creativity and combining it with data and information. The idea behind content marketing is to woo the target audience of a business and get them hooked to explore more. The relevance, quality, and ease of consumption of a given piece of content be it a blog, video, or something else, determine its effectiveness.
Creating, publishing, and distributing valuable content isn’t an easy task as it is. With the addition of videos, podcasts, and live streams in content strategy, content marketing has evolved drastically. Moreover, today it has become even more challenging to use the same data sets to create large volumes of distinctive and impactful content.
The challenge is not because of a dearth of creative thinking but the ever-increasing demand for high-quality content for marketing. In other words, it’s difficult to maintain quality standards of content while creating it at scale according to the exponentially rising demand.
Businesses often seek assistance from a digital content marketing agency or content creation experts to get their content strategy right. But even these agencies have found themselves in a pickle owing to the challenge mentioned above. This is where AI and ML enter the picture.
Wanna know how AI and ML are up for tackling this challenge? Keep on reading.
In this article, firstly, we will begin by discussing the basics of artificial intelligence(AI) and machine learning(ML). Secondly, we will talk about the implications of using AI and ML in content marketing strategies. Lastly, we will take a look at some crucial ways in which AI and ML can shape the future of content marketing. Let’s dive in.
Basics of AI and Machine Learning
We are sure that you will be familiar with AI and ML, even if at a surface level. But since these are complex and nuanced concepts, we will first talk about some basics.
Artificial Intelligence(AI) is an attempt to simulate human intelligence in machines to enable them to undertake tasks as a human would do. This process is possible with the help of annotations, data labeling, and so on. They help to train AI models and work more accurately. 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.
AI is a catch-all phrase for a collection of disparate but related technologies in various stages of development. In addition to machine learning, neural networks, deep learning, and natural language processing (NLP) are a few more examples.
Now, AI and machine learning have a range of practical applications for every industry, which includes our topic of interest – content marketing.
It’s vital to note that AI is not a new concept, but its effectiveness and penetration have risen exponentially in the last decade. Today, AI and machine learning have reached a stage where they are more than capable of assisting us to automate repetitive tasks. Moreover, they have the potential to take over strategic and creative endeavors as well — case in point, various AI-powered content creation tools out there.
Implications of AI and ML on Content Marketing
Content marketing is an amalgam of mundane and repetitive activities in addition to the creative process. The mundane activities include, but are not limited to:
- Researching and finalizing keywords
- Planning blog posts and videos
- Writing and optimizing for the web
- Personalizing and automating content
- Reviewing analytics
- Designing and shaping overall content strategy
AI and ML can perform the majority of these tasks and allow content marketers to focus more on the other aspects of marketing. They allow content creators to focus on improving business performance through other higher-value activities.
Many big organizations already use AI and machine learning for more than just data analytics and generic email automation. A case in point is the publishing powerhouse Associated Press. They use Wordsmith, an AI-powered, natural language generation platform, to write top-notch articles.
There are a range of benefits of using AI-powered content creation tools. These include:
1. Better ROI
AI-writing tools help improve the return on investment since they are capable of making consistent posts. Moreover, they can tailor their output based on different platforms.
2. Saving Time
AI writing tools are naturally faster than their human counterparts. Therefore, they help businesses and content creators save time. The time thus saved can be used in crucial activities such as enhancing the creativity of the AI-generated content.
3. Improved Sales
AI-powered processes help brands create consistent and high-volume content for blogs and social media. These channels help build users’ trust. Trustworthy businesses generate more sales.
4. Beating the Competition
AI tools help content marketing agencies create top-quality, web-optimized content at scale. They help maintain the consistency and quality of content, which helps in brand building. Brand building is directly linked to gaining a competitive edge.
How AI and ML Will Power Content Marketing
By now, we have established that artificial intelligence is here to stay to support content marketing. In this section, we will take a look at various ways AI and ML can tangibly do so.
Artificial Intelligence and machine learning are primed to transform content marketing in the following ways:
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.
There are various AI-powered tools such as MarketMuse and BrightEdge that help marketers conduct keyword research, discover users’ search intent and more.
2. Topic Generation As An Extension of Content Research
Another challenge in content marketing is identifying topics for creating content. The content format could be anything, an article, a blog, a video, a podcast, etc. 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.
AI-powered tools such as HubSpot’s content strategy tool use machine learning to offer relevant and intelligent topic suggestions. They identify topic clusters by analyzing and learning from past data on user engagement.
3. 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.
You can, for example, personalize emails and generate personalized greetings for each subscriber. In addition, you can write articles for buyers at various points of the sales cycle. It’s no more a one-size-fits-all strategy but rather the most advanced level of content customization.
There are AI-powered tools such as Personyze, OneSpot, and more that leverage the best of machine learning to offer one-of-a-kind content personalization.
4. 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. Popular AI-powered tools such as Grammarly and Hemingway App analyze content and offer suggestions and changes.
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.
5. Predictive Analytics To Improve User Experience
Content marketers aim to improve user experience with their content. They need to predict user responses to create content that adds value to users. This is where predictive analytics comes into the picture.
AI-powered predictive analytics uses consumption statistics, historical data patterns & trends, and data modeling to predict the responses of the target audience. It can uncover correlations and similarities in your audience that content teams might overlook.
Using this information, marketers can create buyer personas based on demographics and interests. Content teams can use these personas to create customized content.
Predictive analytics also helps identify strategies to assist current consumers in resolving issues. When you’ve spent time researching their needs, presenting your products/services as a solution won’t feel like a sales pitch. Conversely, you’ll have established yourself as a trustworthy expert.
Therefore, AI-powered predictive analytics has the potential to transform how content marketers function.
6. Data Analytics & Processing
Content marketers need to do much more than create content. They have to deploy content according to the overarching content strategy. Additionally, they need to review and analyze the statistics of various content marketing campaigns.
AI-powered tools help content marketing teams pursue these tasks through advanced data analytics. Such tools can process large amounts of data in a jiffy and produce accurate actionable insights. Marketing teams can use these insights to improve the content and make it more palatable for the audience.
AI-powered data processing helps coarse through large data sets. It processes complex data and simplifies it for content marketing teams. This enables the teams to execute their campaigns to perfection. AI tools such as Curata and Scoop.it can measure, promote, and analyze content performance.
7. Content Automation and Optimization
One of the biggest challenges faced by content marketers is the increasing demand for content. Scaling content creation is not an easy undertaking because of human limitations. This is where AI-powered content automation and optimization become vital.
Natural language generation(NLG) is a branch of AI that can make it easy to scale content creation. It offers real-time content suggestions and makes it easy for marketers to create high-volume and unique content. It offers a range of other capabilities that include:
- Making it easier for newer content writers to enhance their content copies.
- Offers suggestions to make changes to your content based on the analysis of your blog or website. The suggestions seek to align new content with the tone of the existing content.
- Reduces human intervention by auto-generating editorial text.
An AI-powered tool such as Automated Insights helps in scaling content creation. On the other hand, tools like Acrolinx help optimize and plan content.
8. Making Content Creation Cost-Effective
Manual content development is a time-consuming and expensive process that needs much research, preparation, and creativity.
AI and machine learning automate the majority of manual tasks, saving time for content creators. They process data in a matter of seconds and make adjustments that boost ROI. As a result, content marketing becomes more influential and cost-effective.
Conclusion
Based on our discussion in this article, we can safely conclude that artificial intelligence and machine learning are the future of content marketing. The numerous practical applications of these technologies are already revolutionizing content creation.
