Artificial intelligence (AI) and natural language processing (NLP) have collectively caused significant changes in the content marketing industry. If that reality makes you feel like grabbing a stress ball off your desk to cope, take a breath.
AI and NLP can feel overwhelming at first, but you don’t have to incorporate them into your workflow all at once. Here are some practical ways to adapt to what these technologies can do and discover how they might help you.
1. Consider Using NLP for Sentiment Analysis
One important part of successful content production is verifying whether the audience responds as expected. Natural language processing can help by studying how people feel about certain topics.
An example of what’s possible came from researchers at the University of Finland. They focused on the northern white rhino, which had recently suffered from ecocide (destruction of their natural environment) near the time of the study. NLP helped the team understand how people online reacted when the last known creature died.
They had a vast collection of online content comprising approximately 5,000 Twitter posts and 1,000 articles representing 20 languages via daily collection to capture all the relevant rhino-related events.
The NLP takeaways revealed some fascinating insights that could help in all types of content marketing. First, the most prominent caring responses came after tragic events. However, people also liked to celebrate happy things, such as the birth of a rhino calf. Additionally, most responses came from people who do not live in places with native rhinos.
Content marketers can apply this technique in other ways, too. For example, they might use NLP to get an idea of how people discuss newly launched products, campaigns or websites. After confirming the trends associated with the public’s feelings, they can adjust content marketing strategies accordingly.
2. Recognize That Changes Often Happen Gradually
It takes time and effort to figure out if using AI or NLP would be genuinely helpful in your content marketing strategy. It’s not enough to merely adopt one or both of those technologies because competitors are doing it. Take a closer look at your most pressing current challenges. Then, explore how these technologies could ease those struggles or streamline the workflow.
Another comforting thing to remember is that you’re not alone in your attempt to adopt these new technologies or at least see whether they could work for you. A January 2022 survey of executives in the United States found that 78.3% used AI for content development and execution purposes. Additionally, 53.9% of respondents opted to use AI to give customized content to customers.
One possibility is to use AI to create personalized videos. Another study showed that people spend more than 60% longer on landing pages after being directed to them in personalized videos.
Even though most of the leaders polled in that study use AI to help with content, that doesn’t mean they all began as experts. Give yourself time to ease into the tech adoption journey and accept a certain degree of trial and error. You’re not likely to find what works best right away, and that’s OK.
3. Use AI Content Generation With Care
There are already AI content-generation tools on the market. However, people familiar with them say they still have many limitations over human creators. For example, an AI tool can’t understand what it produces. Instead, it typically takes what’s already published on certain topics and tries to make something new out of what’s there.
Additionally, these AI tools can’t give subjective context, such as to help people compare products or understand the differences between two schools of thought. Expecting an AI tool to achieve emotive writing is also too much to ask for at this point. It’ll fall short with things like humor and anecdotes.
A study also indicated that people have preconceived expectations for AI content, and they don’t always respond well to it. Researchers wanted to see how the public responded to Airbnb hosts who used AI to write their profiles. The results found that they perceived AI as trustworthy if every profile they saw included it.
However, participants believed profiles that seemed mechanical or senseless were more likely to have been AI-generated, and they didn’t trust them as much. They even said major spelling errors in Airbnb profiles were signs that made them more likely to be human-made.
It’s premature to expect AI to do all the content writing for you. However, it can help with some parts of the process, such as preparation and research. Some products can suggest outlines for articles or recommend what subheadings should say. Those tips can cut down on formerly time-consuming processes.
4. Understand How Technology Could Curb Content Problems
Emerging technology has tremendous potential to reduce or eliminate some common content production problems. Many NLP dictation tools can help people record their thoughts and save them from much of the typing they do on a typical day.
AI products can also help identify specific attributes of content assets that dictated good performance versus pieces that got less traffic than expected. They excel at finding patterns in large groups of data that humans may miss.
In another case, researchers used advanced algorithms, including NLP, to differentiate between Twitter bullies and people who use the platform normally. The system achieved 90% accuracy. Researchers believe this is an early step toward thwarting cyberbullying.
Content marketers could use this to find early signs of social media accounts dominated by malicious parties. That makes it easier to intervene sooner with stricter moderation or other measures, preventing those intruders from disrupting a wider strategy.
AI and NLP Could Get You Closer to Your Content Goals
AI and NLP are not magic fixes that will immediately improve content production. However, they can prove beneficial, especially when people take the time to learn what’s available and clarify their needs. Try not to get upset if it takes longer than expected to implement either of these technologies. Almost all changes require time for the machines to learn and people to adapt to them. However, staying dedicated to the process can often pay off.
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