What Is AI Marketing? Definitions and Examples (2024)

Jamie Giggs, January 02, 2023
What Is AI Marketing? Definitions and Examples (2024)

Not convinced by AI? You should be. According to Statista, the artificial intelligence (AI) software market is set to grow to approximately 126 billion U.S Dollars by 2025.

AI is disrupting the following major industries:

  • Entertainment
  • Healthcare
  • Financial Services
  • Food Technology
  • Logistics and Transport
  • Manufacturing
  • Real estate
  • Retail and Ecommerce
  • Travel

AI improves operations and streamlines tasks that initially take hours and reduces them to minutes. For example, in healthcare, AI performs specific advanced surgeries alongside humans.

Marketing itself greatly benefits from the use of AI too, with a wealth of tools available that make your job easier, allowing you to work smarter and be more productive.

AI Marketing Statistics
Market value of artificial intelligence (AI) in marketing worldwide from 2020 to 2028. Source: Statista

Not sure where to start with AI marketing? Don’t worry; this guide will cover what AI is, how it works, and AI’s role in digital marketing for 2024.

What is AI marketing?

There is no singular definition of AI yet the basic concept remains the same: a system of different computing technologies working together to think, act and learn with a similar intellect to humans and one that’s able to mimic human behavior.

Machine learning is a form of AI that uses past data to continually improve as it learns through its own experience and data (without human intervention).

Building marketing and advertising campaigns that depend on artificial intelligence (AI) are known as AI marketing.

How it works

The rapid development of AI has skyrocketed, leading to many marketing tools that can automate tasks and help create content. AI makes decisions and reacts accordingly based on customer insights, economic trends, data collection, and analysis.

Key advantages of using AI in marketing

1. Understanding consumer behavior

Knowing your target audience and predicting behavior and potential buying patterns is vital in marketing. AI combines loads of resources and big data and accurately gives more insight into each customer.

What’s more, marketers can use this newfound information to plan, design and deploy their marketing strategies. Campaigns are updated to maximize engagement and focus on the right group of consumers for the product or service.

2. Better customer segmentation

Traditional customer segmentation initially grouped and differentiated customers based on gender, age, demographics, spending habits, and geography. Marketers also looked at if the customer was a first-time buyer or a returning customer.

Yet there are areas for improvement in traditional customer segmentation, such as a lack of personalization, accuracy, and the need to perform time-consuming research.

AI technologies can help here. With machine and deep learning, marketing teams can continuously collate and analyze each brand interaction—the correct information gets researched, and AI gathers high-quality insights automatically. From there, marketers can target specific customers with bespoke messages on a much bigger scale.

AI also predicts the best times for targeted ads, discounts, and emails, so the customer is less likely to feel a sense of distrust.

3. Better personalized content and recommendations

Another benefit of AI marketing is giving accurate recommendations and individualized content. Netflix, for instance, uses AI to suggest what to watch while playing trailers to the user based on likes, dislikes, previously played shows, genres, and films.

The content played advertises programs and keeps re-engaging customers, in turn, they keep subscribing and watching content.

4. Real-time optimization of campaigns

AI uses real-time optimization, which means businesses can track campaign performance and keep tweaking throughout. Companies perform better as they can actively respond to the data as it emerges; it creates a sense of urgency.

5. Improving efficiency and productivity of marketing teams

Work hours are better utilized with AI tools as routine admin tasks can be completed quickly, such as search engine marketing (SEM), email marketing reports, and content briefs.

This freed-up time is spent more efficiently and strategically, and the team is less stretched as a result.

6. Automated decision making

It used to take hours (and even days) to make business decisions or marketing strategies. Now with AI, the data collected gives precise answers fast, so there’s no room for indecision.

How is AI marketing used? 

Customer relationship management 

A winning combination is using customer relationship management (CRM) software and AI to predict the future demand for goods and analyze an individual product’s journey.

Knowing your customers is essential. By predicting their moves you can launch a product at the right time. Similarly, you can contact them at relevant times to minimize a high bounce rate.

For instance, Pipedrive is a CRM platform that deep-dives into sales strategies and comes with AI so you can track deals throughout, visually monitor your campaigns, and see communication tracking for emails, chats, and calls.

Notable examples of CRMs include the following:

Customer segmentation

Marketers can target a specific group of customers with personalized messages (and content) in large volumes thanks to AI’s machine and deep learning techniques. For example, HubSpot offers a wide array of tools, AI insights, and extensive segmentation options.


A chatbot is a software that responds to customers automatically. Key examples of businesses using chatbots for customer support include Amazon, Spotify, and Mastercard. Chatbots can answer specific questions relating to products and redirect customers to live agents if needed.

Natural language processing has made computers more human and can now carry out realistic conversations.


Making sure that your content is search engine optimized is a necessity for every business, specifically to rank higher on Google and to direct traffic to your site. There is a multitude of seo tools that can aid and automate tasks, such as creating outlines for posts.

Creative asset production

Creating digital art has never been more straightforward; AI art generators can edit images, design presentations, and even remove backgrounds from videos. For example, logo makers like Brand.io can instantly create logos based on your choices.

Similarly, AI writing software improves articles and content production by automatically making posts, writing copy, and assisting with grammar. Grammarly, for example, searches your document for errors and scans your piece against millions of others on the web to check for plagiarism.

There’s a whole plethora of excellent tools waiting to be discovered.

AI analytics

Big data is a complex term to define—it consists of massive amounts of structured, unstructured, and semi-structured information collected and mined by companies for different purposes, such as predicting human behaviors and trends. 

AI and big data tools help marketers decide on what type of content to produce and can give first-rate insights that facilitate critical decisions for campaigns. A primary example of AI analytics is Google Analytics.

In a nutshell, the customer experience is dramatically improved when using AI analytics.

Social media automation

Engaging with your audience on social media is crucial to creating your brand and advertising your business. AI can schedule your social media, automate your posts for all social media accounts, and track engagements from the dashboard.

Data Analysis

Manually gathering and collecting massive amounts of information can be stressful and time-consuming, but it’s now a thing of the past with AI.

Media Buying

AI cleverly predicts how to best implement ad and media placements for a company, significantly boosting its ROI.

Challenges to consider

Training time and data quality

AI is like a team member that needs training: it requires time to familiarise itself with a system. The correct details need to be inputted to get accurate information, and the learning process necessitates data quality assurance.

The predictions and decisions made are redundant if the AI isn’t properly trained.


Bear in mind that GDPR standards may be overlooked by AI software when using consumer data for marketing personalization, that is unless it’s specifically programmed to observe legal guidelines.

Marketing team buy-in and adoption

Marketing teams need to provide evidence of how AI benefits the team so that business stakeholders give investment budgets. Using the appropriate measurement tools is crucial to gain funding.

Deployment of best practices

The rulebook isn’t defined because the technology is relatively new. Therefore, digital marketers need to consider an AI marketing strategy’s long-term and short-term effects.

Guidelines to effectively use AI in marketing

Here are some guidelines to make the best use of AI in marketing.

  • Establish your goals: Set clear targets for your AI marketing campaign.
  • Ensure data privacy standards: To maintain consumer trust, follow privacy standards and ensure it gets programmed into your AI.
  • Data quantity and sources: For marketing AI to work successfully, you must have a vast amount of data readily available. The information trains an AI tool in customer preferences, economic factors, and external trends. Adding your CRM’s data informs the AI about campaign history and site data. Marketers can also add third-party and secondary data to assist a purchasing decision.
  • Maintain data quality: Planning before implementing any AI marketing programs is wise. Marketers should collaborate with different departments and data management teams to develop a data maintenance and storage plan. Some data needs cleansing using the seven dimensions as a rough guideline: timeliness, completeness, consistency, relevance, transparency, accuracy, and representativeness.
  • Creating an integrated AI marketing strategy: Make sure that AI tools are used in labor-intensive areas such as data analysis—or other blind spots—to improve your marketing strategy.


The emergence of AI in marketing is as useful as it is disruptive to everyday marketing operations. It’s important to understand how you can best t implement it and find the right AI platform for your business.

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