AI in content marketing includes content personalization, predictive analytics for customer insights, conversational AI for customer service, and improving marketing ROI, among other use cases. Learn five ways to apply AI into your content marketing program in this post.
Sixty-two percent of companies don’t use data to make decisions. They do things the hard way, despite the fact that AI can make your content marketing more efficient by using your data more effectively.
So how do you start using AI for better content marketing?
These insights came from 5 Applications of AI for Content Marketers, an AI Academy for Marketers course presented by Katie Robert (@katierobbert) of Trust Insights. Watch the video below for a course overview, or read on for key takeaways.
First, let’s establish what AI is not. AI is not a robot seen in movies. It’s not magic, or a cyborg of any kind.
The truth is that AI is primarily math.
It is likely you have loads of data relevant to your content marketing, and you don’t know what to do with it all. The good news is: AI can help you manage your data and organize it in a way that will be useful for you and will improve content performance.
You may be managing every type of marketing channel known to man—all at once (yikes). With all this data rolling in, it’s likely you have no idea what is truly working. Luckily, AI can help you identify top-performing content channels by helping you better understand your customer’s journey.
The Markov Chain Model is an algorithm that allows you to understand a non-linear customer experience journey. Overall, this gives you a better sense of which channels are converting and where you should place your content.
So you have focused your data (yay) and can look in your Google Analytics account to see who has visited your website, which pages, and more. However, you are not shown which specific pages created conversions. The Markov Chain Model can help you identify these. Once you figure out which pages drive conversions, you can create more of that type of content or set up simple recommendation engines. For example, you could add footers to your website that state “You may also enjoy…” increasing your chances of even more conversions.
So far, we started with our baseline Unfocused Data, allowing us to identify our customer’s buyer journey. We then covered Unclear Data, which identifies which pages drive conversions. Next, we want to dissect and utilize conversations taking place online and on social media.
Social listening tools are great, but they only focus on social media. There are conversations happening all over the internet that you don’t want to miss out on. AI called Topic Modeling is a good place to start. It will scrape the content from a webpage, forum, or wherever the context/text lives. By identifying the top phrases discussed, you can modify your content based on that data.
With the keywords and data you have collected so far, you can now plan out the timing and trends of your content with an AI-powered Time Series Forecast. A good (free) tool to use is Google Trends, a data source about search intent for marketers. The data it provides will help you create your Time Series Forecast.
For example, you may see that “Google Data Studio” will be heavily searched for in September. If it is currently June, it would be smart to begin creating that content for the arrival of September. If this content is already on your website, then refresh and re-optimize your older content to keep it relevant.
The same idea can be applied to identifying trends and planning timing for social media posts and advertising spend to maximize results.
For 52 weeks, a predictive forecast was used and found an:
The lesson here: once you have your useful data identified, use AI to successfully plan out how to utilize it for your company.
It is now time to publish and amplify your data, which naturally leads to influencer marketing. Having a public figure or other influencer promote your product is great. However, social media algorithms are evolving in a way that makes this type of marketing difficult. For example, Instagram is taking away “Likes” on posts, making it hard to keep engagement rates up.
Another way to think about influencer marketing is using vectorization, a type of AI. Vectorization is the newness and relevance of topics/people. You’re identifying the people you should be engaging with on social to improve the odds your content is amplified.
A good way to study this is through a spreadsheet, in which you identify the handles of people, their location, descriptions, preferred contact methods, and much more.
Overall, figure out how to best amplify your content through vectorization, then use influencers as a tool to execute.
AI will not take over your job, here is why:
It is normal to fear the unknown, but AI should not be feared. We use AI everyday to assist in daily tasks and it is important to continually integrate it into our work life.
This content came from 5 Applications of AI for Content Marketers by Katie Robbert. If you want to gain more insight on how AI can be applied to content marketing, you can access the rest of this course by becoming a member of AI Academy for Marketers.
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