Machine learning is everywhere: self-driving cars, paid ads, fraud protection – they are all powered by data.

Google just developed its Flights app to predict flight delays by looking at common patterns in delays. Facebook uses AI to recognize your friends’ faces, so you can tag them in your photos. 59% of fashion retailers in the UK admitted using the same technology to track customers by using cameras, so they could send them personalized offers. I know, it does sound creepy.

But there is more! Uber’s system uses real-time data to estimate the price and waiting time. Netflix uses machine learning to recommend the next movie we would love to watch. Not to mention Alexa and Siri…

Marketers realized that they had to catch up too, so they started using data to develop demand forecasting and build smarter, customer-oriented strategies.

What is machine learning?

Machine learning is an application of AI (Artificial Intelligence) where computers access data and teach themselves to take certain actions.

These self-driving systems don’t need to be told what to do. They learn from experience and can change their algorithms based on historical data and patterns. The more data they collect, the more accurate they become.

This large amount of data is called Big Data. Machine learning can leverage big data, create insights and help build a personalized strategy. By using data insights, content marketers have a better chance at creating audience-tailored content which is easy to discover on the SERPs.

Why Savvy Marketers should use machine learning?

The way consumers make purchase decisions has changed. And since brands realized that content is the best way to build trust with their audience, articles started flooding in.

Making your voice heard above the digital noise is getting harder by the day. That’s why you need to use data to create more efficient content to reach your overall marketing goals.

1. Improve content marketing productivity

The algorithm of machine learning helps do repetitive tasks based on data. Collecting keywords with the highest search volume and the lowest keyword difficulty can be time-consuming. But intelligent automation can do it for you, so you can focus on writing instead.

Once you give the initial data – which requires experience and knowing the best practices – the difficult and boring part can be done by the computers much faster and with better results. You can optimize this process and pick the low-hanging fruit by using the right data powered CMS.

2. More precise targeting with tailored content

Traditional content marketing strategy is built around buyer personas. However, producing content tailored for demographics doesn’t help us figure out what the consumer intent is.

Personalization is a hot digital marketing trend in 2018. Since technology can collect accurate, real data, the system can learn about the audience.

As the users engage with an article or other materials, machines can predict what kind of topics they are interested in. Understanding the audience’s existing problems helps you give helpful answers to your readers’ questions.

The computers can group your audience based on previous actions and predict how the group reacts to certain events. It helps you create content for each customer journey stage and focus on the person. It’s an important aspect because one-to-one marketing does work.

3. Find the gap in content creation

As I said before, detecting the customer intent is extremely important to create valuable, in-depth articles. AI collects behavioral data such as trending topics on social media or queries on search engines and predict the “future”.

Google (yes, it uses machine learning too) aims to give the most relevant and valuable answers to the user’s question – and should you.

Writers may need to go through 30-40 articles to understand what topics to cover and how they could write a better piece of content than their competitors.

Computers can help find high quality content that triggered the highest social engagement in real-time. This social share insight implies what kind of content is valuable for people.

By using tf-idf, computers can understand the topic of each article as well. This method can be mixed with Latent Dirichlet to help writers create better content than the ranking ones.

4. Tracking data to optimize your article

The success of digital marketing is based on analyzing the outcomes and learning what works. This is necessary to optimize the marketing strategy.

The power of tracking data lies in predicting the future based on patterns in the past. Based on real-time data, machines can predict what changes could improve your performance.

You may miss an important keyword you should optimize your article for. Or another author’s article might be successful on social and your article could be a great fit as a backlink. These are suggestions that computers can boost your performance with.

5. Allocate your resources wisely

Content marketers often plan the marketing strategy based on educated guesswork. However, creating articles that no one reads is a waste of time.

Budget can be spent on a smarter way thanks to optimized workflows. Machine learning can provide a guideline for marketers to develop data-driven strategy and create valuable content. Producing materials that have a higher chance to attract high quality leads pays off in the long-term.

Since machines can do repetitive tasks, you can also spend your resources more wisely. There is no need to use 4 tools to find the best keywords or best backlinks. There are tools such as Intellyo that helps you through the creation process within one single platform.

6. Content automation

Machines can understand English language and make suggestions to improve the copy. They can recognize passive voice and can exclude clichés. But they can do more sophisticated tasks as well.

Natural Language Generation process translates data into human language. To do so, engineers teach the computers to understand the relationship between data and text.

It seems like an easy solution. Several tools promise the dream of creating articles by one click. But it has limitation. The emotional touch is missing. Generating text automatically can save time but can’t eliminate human actions.

7. AI used for video content

Computers can be trained to recognize the content of images. However, so many things are going on in a video, one single footage can’t tell what is going to happen. Will it ever be possible? Several companies experiment with using data for video and some results are quite exciting.

In 2016, IBM Watson created its very first movie trailer by AI. The computer analyzed the movie and generated the trailer automatically. It detected sentiment changes and cut the movie. The result is thrilling.

Will AI replace content marketers?

The short answer is – no, they won’t.

Computers are great for collecting data and helping writers create SEO optimized content. I can assure you that using machine learning to create content will be the norm.

However, machines can’t give the insight perspective. It’s something that only the human mind and heart can do.

About the Author:

Erika is the Content Marketing Manager at Intellyo. She is a strong advocate of data driven marketing and loves tech.

Posted by Guest Author

This article was submitted as a guest post and it doesn't represent the views and perspectives of the Technivoz Editorial Team.