AI Trends To Follow In 2020 For Content Marketing Excellence

Whatever marketing approach you’re trying to take, it’s almost sure that Machine Learning can take it a step further.

While Artificial intelligence has become incredibly trendy, there’s no reason to brush it off as a fleeting occurrence in tech and marketing.

It has already considerably changed the way businesses and individuals advertise their services to their clientele, how they source their customers, and how they create content.

In this article, we’ll take a look at the most intriguing and compelling AI trends that can help you automate high-quality content and devise a winning content marketing strategy. Let’s dive right in, shall we?

How can AI impact Content Marketing?

It’s essential to underline that Artificial intelligence today is more of an umbrella term for a variety of sophisticated technologies that have a thing in common — learning from datasets and executing a set of tasks based on what they’ve learned from the said datasets.

Some are more popular, some are more niche, but most of us hear about them on a regular basis: Machine Learning, which we’ve mentioned above, natural language processing — commonly used by search engines and voice assistants, along with natural language generation — used by organizations to turn raw data into intelligible and digestible reports. And these are but a few of the subdivisions of AI.

While these technologies are by no means sentient and they don’t choose to make these actions, one thing is for sure — they’re much, much quicker than humans.

More importantly, many of these technologies learn to improve themselves over time — and that’s where it gets interesting.

1. Automated content creation

Content marketers can tap into the power of AI to generate articles, blogs, and listicles — straightforward content that does not demand profound analysis, but mere reporting of events. For example, if you’re looking to update your readers on stock updates, recent sports events, and any type of basic news — AI-powered content creation may be a great option to consider if you’re looking to automate these processes.

Chances are that you’ve been reading stories written by robots for quite some time now. Machine-generated text isn’t ideal, of course. Still, it’s important to underline that algorithms are being continually improved, and technically speaking, it doesn’t take more than 5 minutes to make minor corrections for a human editor/quality assessor, in order to achieve a readable text. This approach is considerably less time-consuming and much more cost-efficient.

Let’s take a look at the following excerpt:

“Artificial Intelligence may as well be the future of automated content creation. I can’t tell whether this is merely a question of time or an inevitable consequence of a few years’ worths of development of AI-powered content creation.

But I can tell you that it’s a big thing. The good news is that the field is already starting to emerge in new and interesting ways.

There are still several interesting approaches to creating AI content (even in this blog), but what we see over the next few years, especially with the advent of DeepMind’s AlphaGo, suggests that one of the leading players in this field is, in fact, a human being. But we’re not yet there. Why?”

This text was generated using OpenAI’s new language model called GPT-2. You feed it a sentence, and it generates a paragraph of text that it considers to be relevant to the original sentence. While AI is no Hemingway at this point in its development, it’s essential to realize its extraordinary potential.

Also, it’s no secret that many news aggregators and services like Associated Press, Yahoo, and Fox have been generating content for years. Therefore, it’s to be expected that AI-generated material will become more common among content marketers in 2020 and beyond.

2. Hyper-personalization

Personalized experiences have defined marketing for some time. A few years ago, businesses did all they could to entice the user by using their first name in emails, mentioning their location, and so forth. This, however, has become almost somewhat of a faux pas in marketing. A new development in this department is hyper-personalization and can do a lot of impressive stuff.

So what’s the difference between personalization and hyper-personalization? This new approach allows businesses to tap into behavioral data that users leave behind and extract valuable insight about their particular interests and behavior patterns. In effect, this will enable you to provide your clientele with highly contextual content that should stimulate their satisfaction and proneness to make purchases with you.

Here’s how you can shape your content strategy so that all of your potential customers extract value from it via automated content creation, which we’ve touched on previously. Let’s say you’re a retailer, and customers use a native app to navigate your products. Let’s zoom in on one particular customer’s experience:

• A user launches your app and searches for a specific query, let’s say they’re looking for sneakers;
• They spend around 8 minutes browsing that particular query;
• Once they’ve found a product that sparked their interest, they add it to the cart;
• They leave the app and abandon the cart.

By tapping into the peculiarities of a user’s behavior patterns, you can get an in-depth understanding of what they’re interested in, and then provide them with relevant content to stimulate them to finalize purchases and advertise certain products.

Here are just a few examples of insight you can get from these interactions:

• This user cares about price — they’re after discounted products;
• This user will purchase summer clothing in the winter when the prices are low;
• This user predominantly uses the app after work and during the morning commute;
• This user doesn’t mind push notifications and engages with them often.

So how do you apply the data you’ve extracted from these interactions? You may send a push notification to the customer that’s looking for sneakers that will send him to an automatically-generated article about the best-discounted shoes your platform has to offer. The possibilities are endless.

This approach to content marketing eliminates the need to have an overall strategy when it comes to content and serve the needs of each particular individual. There are now many writing service review sites like Pick The Writer that can help you find high-quality writers and writing services like Studicus which can help you streamline the process of content creation and have it edited by a human editor.

3. Chatbots and content distribution

Great content is great, but it’s worth nothing if it isn’t distributed correctly. Very often, businesses will just post their content to social media, which is not exactly the most intriguing way of sharing content with your customers.

The path to hyper-personalization brings us to personalize a person’s content experience. Your organization may publish many articles and blog entries to your site, but does your customer need to see all of them, in case you know what their preferences are? Not really. Chatbots can collect data about your clients’ content preferences and distribute only the articles, videos, and infographics that they’ll find relevant. Yes, there might be a small loss in traffic, but a considerable bump in engagement via dwell time.

Moreover, this is an especially relevant approach to content marketing and content distribution if your organization chooses to curate content as well. This way, you’ll be able to provide your customers with value by sharing highly relevant information with them that is tailored to their particular needs.

Conclusion

AI could change a lot in how we perceive marketing. Chances are, marketing specialists will be stopping aiming at selling products, but rather attract customers by providing them with valuable content.

Distributing content via chatbots, hyper-personalizing marketing campaigns, and automated content creation have been around for a while now, but they’re about to become big in the next few years.