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AI in Marketing: Beyond Content Creation

Most discussions about AI in marketing center on content creation, but AI’s capabilities extend far beyond that.

If you rely on AI solely for content creation, you’re missing the technology’s broader potential. AI’s capabilities include search engine optimization, insightful data analysis, and personalized customer experiences. 

Leveraging AI to automate time-consuming tasks in these areas can free up time for you to tackle bigger, more tasking marketing challenges and strategize more effectively. 

Here are some ideas for using AI in marketing beyond content creation.

AI-Powered Search Engine Optimization

One of the ways you can leverage AI in your content marketing strategy is through AI-powered search engine optimization.

When you’ve done your keyword research and identified your seed keywords—broad terms that define your niche or core business offerings—AI tools can quickly help you identify long-tail keywords and categorize them by search intent. Long-tail searches are important because they more precisely target intent and capture traffic from users further along in their buyer journey.

For example, take the seed keyword “running shoes.” There are many reasons why someone would search for running shoes, and there are thousands of types of running shoes. That’s a lot of possibilities. You could ask AI to generate a list of long-tail keywords related to the seed keyword “running shoes.” Then, you could ask the AI to categorize the keywords thematically to make prioritizing easier.

Here are a few of the long-tail keywords AI recommended to me for the seed keyword “running shoes”:


  • “Running shoes with the best durability”
  • “High endurance running shoes for trails”
  • “Durable running shoes for harsh weather”


  • “Most comfortable running shoes for long distances”
  • “Running shoes with superior cushioning”
  • “Lightweight comfortable running shoes for daily wear”


  • “High-performance running shoes for athletes”
  • “Best running shoes for speed training”
  • “Running shoes with optional grip for racing”


  • “Affordable running shoes under $100”
  • “Best value running shoes for beginners”
  • “Budget-friendly running shoes with good support”

When you understand the nuances of search intent, you can produce content that more directly addresses real users’ search queries. This improves your chances of attracting the right audience, ranking higher on SERPs, and reducing bounce rates.

Competitive Analysis 

Competitive analysis is another part of your marketing strategy that can benefit from integration with AI. 

Conducting a competitive analysis provides detailed insights to help you understand where you stand relative to your competitors, identify market trends, and uncover gaps in the market that can help you position your products and services to meet your customer needs and preferences better.

Using AI tools to help kickstart your competitive analysis can save time and help you identify your blind spots.

Here’s a quick example. I prompted a generative AI tool to identify a direct competitor (in this case, Brooks Running), the objectives of the main competitor, and perform a quick SWOT assessment: 

Identify My Main Direct Competitor
Brooks Running 

Identify Competitors Objectives
Brooks Running: Aims to be the leading brand for serious runners seeking durable and high-performance shoes.

Identify Their Strengths, Weaknesses, Opportunities, and Threats

  • Strengths: Strong brand in running community, high-quality and durable products.
  • Weaknesses: Higher price points, limited appeal outside serious running circles.
  • Opportunities: Growing market for running as a fitness activity.
  • Threats: Competitive market, price sensitivity among new runners.

Using AI to perform a quick analysis on your key competitors is an easy way to jumpstart a more thorough competitive analysis project. It forces you to think outside of your brand and identifies important avenues for further research.

Chatbots for Customer Support

In the early days of online chatbots, their limitations were obvious after just a few messages. That’s because marketers and developers had to make educated guesses about what a website visitor might ask for and provide canned responses to those questions. 

Chatbots could be useful for responding to very specific scenarios for customers, but if the customer steered away from the predetermined paths, the illusion of having an actual conversation would fade, leading to a frustrating experience.

Today’s AI-powered chatbots function differently and can be quite useful for customers. For example, an AI-powered chatbot on your website can give customers instant answers to common questions, freeing up your team to work on more complex issues. They can also engage customers proactiveally, initiating conversations based on browsing history, activity, or other user behavior on your website.

The most important aspect of building your own AI-powered chatbot is training it. Your chatbot should act as a representative of your brand, so feeding it data like transcripts of past customer interactions, prepared scripts, and other training materials can help it respond more effectively to your customers.

Several AI frameworks, including Google Dialogflow, Microsoft Bot Framework, IBM Watson, and OpenAI GPT, allow you to build chatbots. 

Email Marketing Optimization

Beyond quick chat conversations, AI can also play a pivotal role in ongoing customer communications, particularly through email and SMS. Leveraging AI for smarter marketing automation streamlines processes and personalizes interactions for higher engagement and conversion rates.

Let’s look at a few specific examples of using AI for email and SMS marketing: send times and smart segmentation.

As long as we’ve sent marketing emails, we’ve all known how important it is to send at the right time. It’s email marketing 101. In the past, that meant following a few basic rules:

  • Send on Tuesday, Wednesday, or Thursday mornings
  • Avoid Mondays, Fridays, and the weekends
  • Send at a fixed time, like 9:00 AM

For a long time, that’s all the wisdom we had. We sent emails in large batches simultaneously, ignoring time zones, to land in a customer’s inbox below a dozen other marketing emails. 

But with AI, we can finally move beyond generic “best practices.” 

We can analyze past engagement data to predict when our subscribers are most likely to engage with our emails, offering a level of personalization that goes beyond inserting their first name with a personalization token.

Besides optimizing send times, smart segmentation is another powerful AI tool for marketing automation. While segmentation has been around for decades, AI truly elevates it by dynamically addressing the interests and behaviors of your subscribers. AI continuously analyzes behavior data to create and adjust your subscriber segments in real time so that you can send highly targeted and highly relevant content that addresses the needs and preferences of each segment.

If you’re unsure how to get started, check with your email service provider or marketing platform to see the available features. Many ESPs already have built-in tools, like Klaviyo’s smart segmentation, to help you leverage AI in your marketing communications. 

Predictive Analytics

Perhaps the most powerful thing AI can do for marketers is predictive analytics. With the help of AI, you can analyze years of historical data to forecast future behaviors and trends. By understanding past consumer actions, AI enables you better to anticipate their future needs, preferences, and decisions.

Predictive analytics is especially useful for predicting an individual customer’s behaviors, including what future purchases they will make. 

Using data points like past purchasing behaviors, website navigation paths, and various other engagement metrics, you can more easily identify which customers are more likely to convert and which are at risk of churning. This powerful insight lets you implement targeted strategies to maximize conversions while increasing retention. 

Based on this kind of customer behavior, you can also use AI to help your lead score, ranking your prospects based on their similarity to people who have already purchased from you. 

Lead scoring prospects is incredibly valuable for saving time; instead of your sales team treating every lead the same, they can quickly and easily know how to prioritize their outreach to the most promising leads. High-potential leads can receive more focused attention through personalized follow-ups, and higher leads in the marketing funnel don’t get bombarded with calls and emails from salespeople.

Several CRMs, including Salesforce and Zoho, already offer a version of predictive analytics, and it’s also available using marketing automation tools like Klaviyo, Marketo, and HubSpot. 

AI’s role in marketing has to extend beyond content creation. The future of marketing requires embracing the full spectrum of AI’s capabilities, moving beyond foundational applications, and exploring its potential to transform every touchpoint in the customer journey. 

Thinking outside the content creation box and embracing AI allows for the automation of routine tasks and refines strategies across digital platforms, making our marketing efforts more efficient and significantly more effective. 


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