When I think about machine learning in content marketing, I think about one thing, money. The content marketing space is growing exponentially and with that comes plenty of changes to the landscape. This isn’t your dad’s content marketing we need to stay on board with the growth or risk getting run over.
What’s the Difference Between Machine Learning and Artificial Intelligence?
The main thing you want to understand is that machine learning is a subset of AI. Algorithms learn from Big Data, and machine learning analyzes the data to help B2B marketers develop a better strategy.
Personalization and targeted content are the two key factors each marketer should understand. These two points will separate the content marketer who is closing deals from the content marketer who is left behind.
Machine learning will help us create more personalized and better-targeted content which, as a result, brings more leads to the table.
9 Ways Machine Learning Is Impacting B2B Content Marketing
1. Content automation
Not only is machine learning helping us create more personalized content, but it’s also helping with the content creation process as well. These algorithms can understand English and help you improve your content. They can also translate sheets of data into languages which saves content marketers a ton of time. The only issue with machine learning is that it lacks emotion and empathy, which is tough in an informal content marketing landscape.
Either way, automation is an essential part of digital marketing for small and medium businesses. Utilizing tools that save time help the smaller businesses stay on pace with what larger companies are doing.
2. Less time, more money
One of the greatest things that machine learning does for content marketing is it saves us time. There are a variety of steps that go into creating each piece of content. You need to brainstorm, research keywords, and gauge competition. Luckily, those three steps can be taken off your hands using smart automation tools.
Using specific content management systems, you can fill in a quick form, and the tool will generate keywords and basic research information for you on a topic of your choosing. With the mundane work over, you can now focus your energy on creating the best content possible and getting it out to your audience with the most success.
From a B2B content marketing standpoint, this is ideal because it’s highly competitive. You’ll want to spend much less time on these “non-result” producing tasks and more time generating backlinks, pushing content, and advertising.
3. Personalization is key for B2B
4. Analyzing data
5. Video Content
IBM Watson is a great example of how machine learning can change video content. The supercomputer generated a highlight reel from the U.S Open through machine learning algorithms. They taught the computer to identify the most emotional and impactful moments in the tennis match and to compile those moments into a video. The result was astounding.
While we don’t have this type of technology at our fingertips quite yet, we will. Soon we’ll be able to create videos and use machine learning to help cut and edit them without having to go through and review every minute manually. We’ll be able to train the computer to identify faults and mistakes and cut them from the film.
This will help reduce human error, and of course, it will save a ton of time. You can take that time and spend it on on result generating tasks like trying to get that content to rank.
6. Custom page algorithms
This one is exciting for me because I think it’s incredibly cool. The same way that we have artificial intelligence to customize news feeds on social networks; imagine if your own blog or website could be customized based on the reader’s interests. This type of technology happens all the time with news sites, and most of us don’t even know it.
Sites like TIME magazine and CNN use algorithms to display information that appeals to the individual reader, so they spend more time scouring the website. As a result, they are collecting more data about what interests their readers the most, and the machine learning continues to take off from there.
I expect to see more and more of this technology implemented on a smaller scale on blogs and personal websites.
7. Predictive analysis
For B2B content marketers, lead scoring is an important factor. How many times have you wasted 30 minutes or even an hour going back and forth with a client who wasn’t qualified to work with you? I’ve done that dozens of times.
Predictive analysis helps you personalize your content to bring in the most qualified candidates to work with you. It also helps marketers determine where the reader is in the buying process. This type of machine learning will help you decide which piece of content will work best for them at that exact time.
8. Predictive optimization
Have you ever used a travel website to book a trip somewhere? You go onto the site and take a look at a bunch of different days only to find out that the price varies from one week to the other. Do you think the hotel is going in there and manually inputting the price for each day?
Of course not.
Using machine learning, the computer can input prices based on peak times, costs, holidays, projections, etc.
Apps like Microsoft Azure are helping individual marketers use this type of technology to develop a competitive pricing model for their products and services. Using metrics like sales period, customer outlook, and product positioning machine learning is helping marketers price their offerings more effectively.
9. Automated cross-sells and up-sells
Written by Tristan Pelligrino
Tristan Pelligrino is the Co-Founder of Motion. He’s a serial entrepreneur who started his career as a consultant with large IT companies such as PwC, IBM and Oracle. After getting his MBA, he started and grew one of the fastest video production companies in the country – which was listed on the Inc. 5000. Tristan now enjoys leading the content marketing strategies of some of the most innovative B2B technology companies in the country. You can find him on LinkedIn and Facebook.