Rise of AI and Machine Learning: Can Content Analysis Software Help You Produce Better and More Powerful Content?

Content marketers use many tools, leveraging technology to improve processes and quality. AI (artificial intelligence) and machine learning are two technology innovations that can have a significant impact on content marketing. One of the biggest use cases revolves around data scientists using machine learning platforms to quickly answer questions about audience segments so that marketers can more effectively target customers. But how will these innovations influence the next generation of content marketing? Will content analysis software help you produce more relevant and engaging content?

AI and machine learning inform content marketers with insights. These insights go beyond content analytics, which measure the performance of your content based on consumption.

In this post, we’ll share what we’ve learned about content analysis software and how it can play a role in creating a better and more fruitful content experiences for your customers.

What Is Content Analysis Software?

Content analysis software is a platform that uses AI and machine learning to analyze and evaluate content. It performs a quick analysis of all kinds of content, structured or unstructured, and then it can report on insights and trends that it is asked to find. Its adoption is not widespread, but it’s currently in use for research applications. Content marketers often have to put on their research hat in order to derive value from this type of software.

How Do You Use Content Analysis Software?

You begin by importing data. The content you’re feeding into the software is mostly feedback. You are trying to understand the motivations, needs, and challenges of your audience. This information could include reviews, social media posts, articles, focus group interviews, and more.

You would then organize your data into relevant groups and begin the process of analysis based on what you want to know. For example, you might want to…

  • Search for keywords: Identify topics that you want to know more about.
  • Summarize content: If you have a substantial amount of customer feedback, say from a beta test, you can deliver expert summaries of the findings.
  • Connect data points: Find correlations and connections in your data for fresh insights.
  • Practice quantitative analysis: Go deeper into the content to look at the frequency of words and phrases. This feature is especially helpful if you are trying to pinpoint common issues your audience has.

You’re Probably Already Using an Analysis Tool with AI

Some of these functions probably sound familiar because you’re likely using some type of content analysis software. For example, Grammarly is a favorite proofing and editing tool writers use.

Grammarly does assess content, looking for grammar and syntax issues. It also provides you with stylistic assistance. It alerts you and prompts you to make a different word choice if it calculates too much repetition.

A fairly new feature is “rewriting” a sentence for clarity. Grammarly isn’t always right. You, as a human, still must make choices to act on those recommendations.

Grammarly is like a foundational content analysis tool. It can improve your content, from a grammatical and readability angle. The next level of content analysis will do much more.

How Will Content Analysis Shape the Future of Content Marketing?

Let’s explore some ways that content analysis can improve content marketing.

Improve Content Personalization Efforts

One big focus of content marketing right now is personalization. Being relevant in your messaging to a customer matters. A survey found that 87 percent of consumers agreed that personalized branded content influences their feelings about that brand.

How does content analysis help you become more relevant? Personalizing at scale has always been a challenge. Automation enables you to execute this, but you have to create the personalized content first.

Right now, personalization plays out based on customer behaviors and preferences. It’s solely dependent on how someone interacts with your brand, mostly in the digital realm.

You can better inform personalization with content analysis. Load your system with customer behaviors, feedback, and words. From this assessment, you can see trends about what’s important to customers. This can significantly inform your content strategy.

Identify Gaps in Your Content Calendar

When your content analysis software has many different types of inputs (including your existing content), it can help to identify topics and trends that you haven’t covered before, or recently.

One of the best practices of a content strategy is to identify the primary content themes that you need to cover on a consistent basis. Those themes can then be flushed out into topic clusters that drive the planning of your content calendar. However, this may result in such a full calendar that content gaps go unnoticed.

By utilizing a content analysis engine as part of your ideation and planning process, new topics and trends can be uncovered that may dictate you make room for other things. New opportunities may present themselves at a moment’s notice, thus having an agile content calendar ensures those opportunities aren’t missed.

Perform Competitive Research

You can also use content analysis to uncover what your competition is focusing on. For example, if you have a competitor that consistently publishes quality, high-ranking blog content, analysis is one more way to understand how they are achieving that level of performance.

Evaluating your competitors’ blogs helps you discover their keyword focus, topic clusters, foundational messaging, and more. Once you add this information to your competitive analysis, you’ll have an even broader sense of your competition’s content marketing efforts.

Discover Your True SEO Performance

SEO has three major aspects—on-page, technical, and off-page. While you may have SEO best practices in your content strategy, it doesn’t mean that there aren’t issues. Analyzing your website’s SEO would include looking at the content itself and the technical aspects (meta, alt tags, etc.).

From this, you may find that meta titles aren’t consistent. Fixing those could improve SEO. Or you may find that you aren’t using any long-tail keywords. This may prompt you to do some more keyword research.

Content Analysis Could Boost Content Quality

Content analysis software should be on your radar as a content marketer. If you aren’t using it, consider these use cases and how they can boost content quality. For more great tips and insights on content marketing, subscribe to the DivvyHQ blog.