Top 7 Applications of AI in Marketing

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By Hiba Akbar

The digital age has significantly transformed marketing with the integration of artificial intelligence. AI in marketing has changed how marketers interact and connect with their target audience. It comes up with personalized customer experiences, predictive analytics, and automated campaign management. 

The global AI in marketing market was worth $12.64 billion in 2022 and is projected to grow at a CAGR of 26.6% from 2023 to 2030.~ Grand View Research

The use of AI in marketing enables businesses to analyze vast amounts of data, derive actionable insights, and automate repetitive marketing tasks. 

Also read: What is Responsible AI?

Applications of AI in Marketing

AI is transforming market research by allowing advanced data analysis and insights. It helps in understanding the audience, optimizing strategies, and making data-driven decisions through applications of AI.

A survey among marketing professionals in the US, UK, India, and Canada revealed that 47% trusted AI for ad targeting, 42% for real-time content personalization, and 39% for email send time optimization. ~Statista

AI in marketing will influence market research in various applications as technology evolves. Let’s explore some applications below:

Applications of AI in marketing

1. Programmatic Advertising

Programmatic advertising is a digital marketing strategy that uses AI algorithms to automate the buying and management of ad space. This method allows marketers to target specific audiences with precision and optimize ad placements. Results in higher returns on investment. 

It uses data-driven insights and predictive analytics to ensure ads are delivered to the right people and at the right time. This approach increases the personalization of advertising campaigns.

Spotify, Amazon, and Nike are some of the examples of brands that run successful programmatic advertising campaigns

2. Audience Segmentation

Audience segmentation is a marketing strategy that divides a larger target audience into smaller groups based on shared characteristics, behaviors, or preferences. With the advent of AI technologies, this strategy has become more sophisticated and effective.

AI algorithms analyze customer data, such as demographics, purchase history, online behavior, and social interactions. This identifies distinct segments within a target audience with greater accuracy. This optimizes marketing efforts, improves engagement, and drives better business outcomes. 

3. Predictive Lead Scoring

Predictive lead scoring is a marketing and sales technique that organizes potential leads based on their likelihood to convert into customers. By analyzing demographic information, past interactions, and engagement, predictive lead-scoring models identify key indicators and behaviors that predict conversion. 

Lead scoring tools are helpful for companies lacking an internal team. They increase conversion rates by accurately redirecting relationships with target audiences and being highly customizable to suit various business needs.

4. Sentiment Analysis

Sentiment analysis is a technique powered by AI that uses NLP to interpret emotions, opinions, and attitudes in text data. It provides valuable insights into customer perceptions and sentiments. It helps marketers monitor brand reputation and understand public opinion about products or services. 

By analyzing social media posts, customer reviews, and online discussions, businesses can identify emerging trends and respond to customer feedback. Sentiment analysis allows marketers to tailor messaging and content strategies to resonate with their target audience and foster stronger customer relationships. 

5. Sales and Demand Forecasting

AI has transformed sales and demand forecasting by allowing businesses to predict future sales and demand with greater accuracy through analysis of historical data and market trends. 

AI-powered forecasting models can detect patterns, trends, and seasonality. AI-driven sales and demand forecasting increases operational efficiency, optimizes resource allocation, and drives overall business success. 

6. Social Media Scheduling and Posting

Social media scheduling and posting empower businesses to optimize their marketing campaigns and reach their target audience more effectively. AI-powered scheduling tools analyze data from various sources to determine the optimal times and frequencies for posting content across different platforms. 

Tools like Sprout Social, CoSchedule, Feedly, Airtable, Tweetdeck, and Planable use machine learning algorithms to identify patterns and trends in audience behavior. They allow marketers to schedule posts when their target audience is most active. AI-driven scheduling platforms also offer advanced features like content recommendations, automatic post optimization, and performance tracking. Scheduling saves time by planning social media content ahead of time and timing posts for various time zones. 

7. Dynamic Emailing

Dynamic emailing is a dynamic approach to email marketing that delivers personalized content to individual recipients based on their preferences and interactions. This technology uses AI algorithms to generate and customize email content. 

AI-driven platforms look over data from various sources, such as past engagement, website interactions, and purchase history, and create highly targeted and personalized campaigns. Dynamic emails may include personal subject lines, images, product recommendations, and other elements.

Why are Marketers Adopting Artificial Intelligence? 

McKinsey’s survey reports that 90% of marketing leaders anticipate a rise in the use of generative AI tools within the next two years.

AI is a rapidly growing tool that can learn and adapt to new situations. It can analyze huge amounts of data and provide immediate insights so that marketers can make informed decisions.

  • Improved Targeting and Personalization: A personalized marketing strategy uses data to target and retarget leads with a brand message that is tailored to specific customer interests, demographics, and buying behavior. It makes customers feel the message is tailored to them.
  • Enhanced Marketing ROI: AI improves marketing return on investment (ROI). AI can identify trends and patterns that impact ROI and provide data-driven decisions and better resource allocation. It can automate tasks like audience segmentation, content personalization, and ad optimization.
  • Improved Customer Insights: AI provides customer insight through the analysis and interpretation of customer data, behaviors, and feedback to enhance product development and customer support.
  • Improved Customer Service: AI chatbots and virtual assistants offer 24/7 customer support. They improve the overall customer experience and develop deeper relationships with customers by resolving their queries.

As businesses continue to adopt AI technologies, marketers must stay ahead of the curve to drive growth and success. Marketers can get new opportunities and deliver superior experiences to their audiences by combining AI-driven tools and strategies.

Marketers use language-based AI as sales tools, payment processors, and engagement managers to improve the user experience. Chatbots can help customers make purchases. AI is continuously improving, learning from previous experiences, and upgrading for better experiences. 

Dive deeper into the world of AI and explore our latest blogs through our website Daily Digital Grind!


How is AI changing marketing?

AI can accurately predict future trends by analyzing social media content. It can give more accurate predictions of consumers’ tastes, preferences, and needs.

What are some common applications of AI in marketing?

AI is being used for fraud detection, risk management, investment decision-making, personalizing shopping experiences, product recommendations, advertising, and inventory management.

How Can Artificial Intelligence Benefit Marketing?

AI can personalize web experiences, automate media buying and campaign management, power dynamic pricing and demand forecasting, and personalize language in online shopping carts, leading to error reduction, and improved decision-making.