Technological advancements can often present new challenges for businesses. The introduction of Artificial Intelligence (AI) and machine learning for digital marketing are no different. Google and other search engines now work on self-teaching algorithms, which makes it challenging for marketing experts to master them and rank the websites higher.
But along with these challenges, technological innovations also come with several opportunities for those ready to learn. The changing landscape of SEO with the inclusion of AI and machine learning is definitely going to transform the future of content marketing and make it more effective.
That is why business leaders and digital marketers should modify their strategies to make room for these advancements to grow SEO traffic and conversions. Here are some ways in which AI is shaping the new landscape for content marketing and SEO.
Search Engine Algorithms
Google and other search engines use to rank websites based on certain rules and logic. Even though the rule-based logic was quite complex, it was still hard-coded. Therefore, web crawlers could simply follow these rules and rank websites that met them.
SEO experts could also find and exploit those rules with repeated experimentation. They could also come up with keyword hacks and backlinking hacks, which could rank a website higher without flaunting those rules.
However, Google has been quite secretive about its algorithm updates since 2015. It was around the time when Matt Cutts left the position of chief SEO spokesperson. Ever since Google introduced RankBrain, the rules of SEO optimization have become uncertain. In fact, other companies like Facebook also followed suit and introduced AI in their algorithms.
Tools to Create Better Content
Even though AI cannot write essays yet, we use several AI-based tools to create content. For example, many writers use Grammarly to correct grammatical errors and write with better language.
The tool uses an AI-based technology called Natural Language Processing (NLP) two suggest corrections and edits. Grammarly can not only rectify common spelling errors but can also find out and offer suggestions for advanced grammatical mistakes to ensure high-quality content.
Some writers also use tools like Sharethrough Headline Analyzer that can check the headlines and titles for articles. They provide actionable insights on whether they can attract high click-through rates. Another tool often used by content creators is Clearscope.
It examines the top 30 results from Google search for a particular keyword and provides actionable data on creating content that can rank higher. It also analyzes some of the other common keywords present in those results so that the writer can include them as well naturally. These tools are extremely critical for content creation because Google’s algorithm focuses more on search intent instead of exact keyword match.
Content creators should focus on good quality and well-written posts rather than keyword-stuffed articles to rank higher on search engine result pages. Business leaders who are still stuck with traditional methods of content creation can also hire SEO experts for better results.
Analyze Content Strategy
Content marketers always wonder what type of content customers want and how to move them from one stage of the marketing funnel to the next one. Traditionally, digital marketers develop buyer personas to research content matter and keywords. However, AI-based technologies can deliver faster and better results than the traditional methods of content strategy.
For example, some brands might have realized that their products are preferred by men but not women. The traditional way to solve this problem would be to create customer profiles and come up with assumptions about what their target female audience wanted. The marketing team could also interview prospective female customers and ask them what they need from those products.
These methods were not full proof because the marketing teams had to assume that the few people they interviewed would represent the thoughts of the entire market. Moreover, people can be quite confused about the reasons for their decisions. Fortunately, AI-powered tools can replace these flawed techniques that are reliant on assumptions.
The customer insights generated by the AI-powered technology allow the content team to form a better-targeted approach and create content designed to attract the attention of various market demographics. For example, the marketing team might find that an influencer or a public figure, who is popular among their target audience, uses their product.
Marketing teams can create specific posts showing the person using their product and boost them on social media or other channels. They can also expand their relationship with a person to create promotional content that showcases their products.
Improve Attribution Analysis
Digital marketers often struggle to measure the impact of their content further along the marketing funnel. In other words, they need to determine which of the content can lead the customers towards conversions. That is because most of the conversion reports give all the credit to the source of traffic that compelled the customer to buy or subscribe.
However, digital marketers are available that customer’s journey along the marketing funnel is not always that simple. Most consumers need to interact more than once with the brand before deciding to purchase or subscribe from the company. Studies have shown that almost 47% of consumers need to interact with at least 3 to 5 content pieces before proceeding to the next step.
Therefore, the model that records the last attribution does not reflect what is happening along the marketing funnel and how the brand-customer relationship develops over the multiple stages. AI-powered solutions offer more sophisticated attribution models that can effectively represent how the customers move along the sales funnel.
Modern tools like Google Attribution or Hubspot can help digital marketers connect all their marketing channels into a unified data set. It allows them to understand which content or advertisements perform better for each step of our customer’s purchase journey so they can use them for scalable and effective campaigns.
Some of the most advanced AI tools have also developed attribution models based on algorithms that analyze consumer behavior. It enables the marketing teams to determine the types of content that drive the customers along each stage of the final to eventual conversion.
So as we can see, artificial intelligence and machine learning are driving the future of SEO. AI-based tools enable digital marketers to create hyper-personalized content that drives engagement, interaction, and conversions. So, instead of relying on traditional methods, marketing teams can utilize these tools to achieve better results for their content.