Digital marketing AI is revolutionizing the way brands connect with consumers by automating tasks, personalizing experiences, and optimizing campaigns with unprecedented precision. From analyzing data to predicting customer behaviors, AI technology allows marketers to streamline operations and make data-driven decisions faster than ever before. All of this results in increased overall digital marketing efficiency. If, in 2016, Harvard Business Review reported that AI is capable of increasing leads by an outstanding 50%, how much is this index today, when AI is far better developed? The same surely goes for AI’s impact on conversion rates.
This is why understanding how to use AI in digital marketing can give companies a competitive edge. In this post, we’ll define digital marketing AI, explore practical ways to incorporate it into real strategies, and provide examples of successful AI applications across various marketing channels.
Key takeaways:
- Digital marketing AI automates marketing tasks to improve efficiency and save time.
- Common AI applications in digital marketing include predictive analytics, dynamic pricing, programmatic advertising, and natural language processing.
- Digital marketing AI boosts conversion rates by using personalized recommendations, predictive audience targeting, improving A/B testing, and producing more relevant content.
- The most important skills in AI digital marketing are data analysis, machine learning, NLP, users segmentation, predictive analytics, personalization, and familiarity with privacy issues.
- Overall, ChatGPT is still the best AI digital marketing tool, but Landingi is the top one for landing pages.
Let’s kick things off!
What is AI in Digital Marketing?
AI in digital marketing refers to the use of artificial intelligence and tools to enhance marketing processes, improve customer experiences, and optimize campaigns through automation, data analysis, and machine learning. More specifically, AI enables marketers to:
- analyze large datasets,
- predict consumer behavior,
- personalize content,
- and automate tasks (like customer segmentation, targeted advertising, and chatbot interactions).
Common applications of AI in digital marketing include predictive analysis, dynamic pricing, programmatic advertising, and natural language processing (NLP) for personalized communication.
Why AI in Digital Marketing is Important?
AI in digital marketing is crucial because it automates tasks, enhances customer experience, and allows for data-driven decisions. With AI, marketers can process large volumes of data in real time, deliver personalized content for web pages and other digital channels, and optimize campaigns efficiently, helping businesses stay competitive and responsive to customer needs. No wonder, then, that 87% of companies believe that – according to the Massachusetts Institute of Technology’s report – implementing AI solutions may give them a competitive advantage in the business or allow them to sustain it (MIT Sloan Management Review, 2020).
What are the Benefits of AI in Digital Marketing?
The benefits of using AI in digital marketing are related to increased work efficiency, more accurate data collection, processing and analysis, as well as to growing revenue caused by both mentioned phenomena. If we go down from the general concepts to details, we’ll be able to enumerate the following AI advantages for digital marketers:
- improved targeting (AI analyzes user behavior and preferences, helping businesses reach the right audience with precision, resulting in higher engagement and conversions);
- personalization at scale (AI delivers personalized content and recommendations to individual users, enhancing customer experiences and fostering loyalty);
- automation of repetitive tasks (tasks like email marketing, social media scheduling, and customer segmentation can be automated, saving time and reducing human error);
- data-driven decision making (AI provides actionable insights from large datasets, enabling marketers to make more informed and accurate decisions);
- predictive analytics (by forecasting trends and consumer behavior, AI tools help companies stay ahead of the market and optimize for future campaigns);
- enhanced customer experience (AI-powered chatbots and virtual assistants offer 24/7 support, improving customer satisfaction and reducing wait times);
- real-time optimization (AI can adjust marketing campaigns in real-time, ensuring the best performance based on current data and trends).
Involving the above-mentioned or other solutions based on artificial intelligence should finally result in tangible business outcomes including:
- cost efficiency (AI marketing tools automate labor-intensive processes, reducing operational costs and allowing marketing teams to focus on strategic tasks);
- better ROI (by optimizing ads, personalizing content, and predicting trends, AI helps companies achieve higher returns on their marketing investments);
- scalability (AI allows companies to scale their marketing efforts efficiently, handling increased workloads without requiring a proportional increase in resources).
How to Use AI in Digital Marketing?
In digital marketing campaigns, AI can be applied to content creation, SEO strategy, PPC, data analytics, social media tracking, performing email campaigns, A/B testing, and voice search. Let’s take a closer look at each of them and check out the most popular applications.
1. Content and Image Creation
AI writing tools can generate tailored content, such as blog posts, social media updates, and even images. Even if they don’t replace talented and professional copywriters, they are capable of making their work easier by, for example, doing research, eliminating errors, changing tone, suggesting alternatives or generating automated translations.
AI-generated content itself requires some polishing to be nop-notch and sound like one created by humans, but the editing process is much faster than writing from zero, right?
On the other hand, AI-powered image creation tools (quickly developed last time) can generate unique visuals tailored to specific campaigns in no time.
Generally, content marketing is now the domain that is hard to even imagine without AI.
Most common applications:
- generating dynamic email content based on user behavior,
- AI-generated custom product images for e-commerce,
- personalized blog resources for scaling up content marketing strategies,
- crafting social media content aligned with the brand’s DNA.
2. Search Engine Optimization
AI marketing tools can also help in structuring content to be more crawlable by search engines, optimizing internal links, and suggesting content based on semantic searches.
Some companies try to use AI tools and deep learning technology to predict search engine algorithm changes and adjust content before those changes happen. Does it work? If AI-driven predictions are accurate in many other sectors, why wouldn’t they work in SEO?
Most common applications:
- doing keyword and topical analyses,
- internal link structure suggestions,
- optimizing content for semantic and long-tail keywords,
- generating SEO briefs for copywriters,
- creating schema markup.
3. Pay-Per-Click Advertising
In recent years, AI has advanced to analyze customer behavior across multiple devices and platforms, building a comprehensive profile for each user. By gathering data from various touchpoints, AI understands individual preferences and behaviors in greater depth. This data enables highly optimized ad targeting, ensuring that users encounter consistent and relevant ads throughout their digital journey. The result is a cohesive, personalized advertising experience that increases engagement and enhances brand loyalty.
Most common applications:
- content creation and adjusting for different segments of the audience,
- cross-device ad targeting optimization,
- behavioral targeting based on cross-platform usage.
4. Data Analytics
AI enhances digital marketing data analytics by processing massive datasets. It results in uncovering patterns and trends that might otherwise go unnoticed. It helps predict customer behaviors and preferences, allowing marketers to tailor campaigns more accurately.
AI can also generate reports with data-driven insights, highlighting the most crucial metrics and relationships.
These advantages allow companies to save time on routine data tasks, allowing marketing teams to focus more on strategy rather than manual analysis.
Most common applications:
- virtual simulation of multiple marketing strategies,
- predictive analytics to forecast market shifts,
- simulation testing for pricing models and discounts,
- analyzing conversion patterns and suggesting strategies to improve CR,
- detecting anomalies and unusual patterns in analytics, identifying potential issues early, when it’s possible to prevent their consequences.
5. Social Media Monitoring
In this area, AI can identify key influencers in niche markets and suggest collaboration opportunities based on engagement data. It can also predict which changes in the social media realm will gain traction and hence help marketers create content aligned with those emerging trends.
Most common applications:
- AI-generated influencer recommendations,
- predicting future social media trends,
- real-time social media trend alerts.
6. Email Marketing
AI has the capability to automate email marketing campaigns, tailoring content for each recipient (or group of recipients) by analyzing their browsing behavior, purchase history, and past interactions. Such a personalized approach means that emails are more relevant to the user, making them more likely to engage with the content.
By delivering messages at optimal times and with customized recommendations, AI can significantly boost open rates, click-through rates, and conversion rates. The result is a more efficient and impactful email strategy that drives customer loyalty and maximizes revenue potential.
Most common applications:
- generating content for e-mail campaigns,
- optimal email send-time predictions for individual recipients (or groups/segments of target audience),
- predictive email subject line generation,
- automated email copy personalization based on user behavior
7. A/B Testing
AI not only automates A/B testing but also enhances it by running continuous multivariate tests on multiple campaign elements simultaneously. It allows to experiment with variables such as headlines, images, and calls to action all at once, evaluating performance across combinations (not across individual elements).
Additionally, by adjusting and optimizing different elements in real-time, AI can quickly identify the most effective combinations, vastly accelerating the testing process. This dynamic method achieves faster, more accurate results than traditional A/B testing, enabling campaigns to adapt rapidly to audience preferences.
Most common applications:
- continuous multivariate testing across campaign elements,
- real-time optimization of landing page elements,
- AI-driven adjustments to headlines and CTAs.
8. Voice Search
As voice assistants become more popular, optimizing for voice search has become crucial for digital marketing. AI leverages natural language processing (NLP) to analyze how users phrase their voice queries, gaining insights into conversational search patterns. This allows marketers to adapt and optimize content to align with the unique language and intent behind voice searches. By fine-tuning content for voice, brands can better capture search traffic and connect with users in a more natural, accessible way.
Most common applications:
- voice-friendly content creation,
- keyword optimization for voice search,
- optimizing content for conversational search patterns,
- structuring websites for better voice search recognition,
- keyword suggestions based on voice search queries.
4 Examples of AI in Digital Marketing
Now that you know the possible applications of AI in digital marketing, it’s high time to see some real implementations by recognized companies.
1. AI Product Recommendations (Netflix Use Case)
Netflix uses AI-powered algorithms to provide personalized content recommendations to their users, tailoring suggestions based on viewing history, search behavior, and genre preferences. By analyzing patterns and preferences, Netflix’s recommendation engine helps keep users engaged and encourages longer viewing times. This AI-driven approach has become a core part of Netflix’s success, creating a highly personalized experience that adapts to each user over time.
Advantages of this solution:
- personalized recommendations enhance user engagement, keeping viewers on the platform longer and boosting interaction,
- the data-driven personalization model processes extensive user data, accurately predicting and suggesting relevant content,
- by consistently offering content that aligns with user preferences, Netflix strengthens customer retention and reduces the likelihood of churn,
- reducing decision fatigue, Netflix makes content discovery easier and more enjoyable, saving users from endless scrolling.
2. AI-based SEO and Content Marketing Automation (Ranktracker Use Case)
AI can also streamline digital marketing efforts in content production at scale with SEO best practices in mind. Although AI-generated content may lack some creativity and human touch, it usually is at least equally good (sometimes it’s even better) in terms of structure and information provided.
Most digital marketing companies use AI in the content domain to support copywriters in research, analyzing information, creating listings, or rephrasing, but RankTracker… went all out! They generate all their blog content from AI and make no secret of it. Just see the screenshot below and check out the number of pages with blog posts. It’s a true avalanche of content! They perform not so well as posts created with 100% human effort, but in their massive volume, they give business much more!
Advantages of this solution:
- by automating content creation tasks, AI enables increased efficiency, allowing for the rapid production of content at scale without heavy time investments,
- following SEO guidelines, AI-generated content ensures enhanced SEO compliance, maintaining visibility and ranking through keyword optimization and structural consistency,
- through reduced reliance on human resources, this approach provides cost savings, offering a steady stream of content without continuous input,
- AI allows for producing content that maintains a uniform tone and format across numerous posts to meet growing content demands,
- supporting human teams, AI aids in research, ideation, and rephrasing, freeing writers to concentrate on creativity and quality.
3. AI Chatbots (Zendesk Use Case)
The next way to involve AI in digital marketing strategy is to use chatbots. Zendesk leverages an AI-powered chatbot to handle customer inquiries, provide instant responses, and offer 24/7 support, greatly enhancing customer experience. This chatbot (the same one they offer to clients) can manage routine inquiries, direct users to relevant resources, and even escalate complex issues to human agents as needed. By using AI chatbots, Zendesk not only improves response times but also increases client satisfaction and streamlines customer support operations.
Advantages of this solution:
- with 24/7 availability, AI chatbots provide around-the-clock service, ensuring customers receive timely support, regardless of time zones or business hours,
- AI chatbots increase efficiency by handling a high volume of inquiries simultaneously, allowing human agents to focus on complex, value-added customer interactions,
- through cost reduction, chatbots manage repetitive tasks, lowering the need for large customer support teams and saving on operational expenses,
- personalized interactions are possible as AI chatbots recognize customer data and preferences, enabling more tailored responses and enhancing UX.
4. Paid Advertising and AI Consumer Behavior Predictions (Volkswagen Use Case)
While known for its innovations in automating vehicles, Volkswagen also leverages AI for ad-buying decisions, moving beyond personal interpretations provided by media agencies to data-driven insights. By relying on AI to analyze consumer behavior patterns and forecast buying decisions, Volkswagen optimizes its ad spend, ensuring that campaigns reach audiences most likely to convert. This approach not only increases the precision of targeting but has also led to significant results, such as a 20% increase in dealership sales while reducing the hidden costs previously charged by traditional ad agencies.
Advantages of this solution:
- by using AI-driven predictions, companies can achieve enhanced ad targeting, reaching the most receptive audiences and improving overall campaign effectiveness,
- data-driven and AI-based decision-making helps to avoid the subjective interpretations of media agencies, ensuring objective, precise ad placements,
- AI solutions in PPC entail cost efficiency, as they reduce unnecessary spending and hidden fees, optimizing the ad budget for better ROI,
- companies like Volkswagen can gain adaptability by continuously refining ad strategies based on AI-driven insights, staying competitive and responsive to changing market conditions.
What are the Most Common Skills Used in AI-Driven Digital Marketing?
The most common and profitable skills for AI-driven digital marketers include analyzing large datasets (which itself requires understanding a little bit of statistics too), creating and transforming machine learning models or/and NLP algorithms, segmenting audiences, performing predictive analysis, running conversion rate optimization, implementing the art of personalization, and being aware of law and ethical concerns around AI use cases. Let’s briefly cover all of these skills.
Data Analysis
This skill involves interpreting large datasets to extract valuable insights on customer behavior, market trends, and campaign performance. Effective data analysis enables marketers to make data-driven decisions, optimizing their strategies for better results.
Machine Learning (ML)
Machine learning is used to create algorithms that predict customer actions, optimize ads, and personalize content based on past behaviors. Marketers with ML knowledge can set up models that continually learn and improve, enhancing campaign accuracy over time.
Natural Language Processing (NLP)
NLP enables AI to understand and generate human language, which is essential for chatbots, sentiment analysis, and voice search optimization. With NLP, marketers can better analyze customer feedback, identify trends, and communicate more effectively with users.
Customer Segmentation
This skill involves dividing customers into distinct groups based on behaviors, demographics, and preferences. AI enhances segmentation by identifying patterns in data that human analysis might miss, allowing for highly targeted marketing.
Predictive Analytics
Predictive analytics uses historical data to forecast future outcomes, such as customer purchase likelihood or engagement trends. Marketers use this skill to anticipate customer needs and optimize campaigns accordingly.
A/B Testing and Optimization
A/B testing involves running variations of ads or content to determine which performs better, a process that AI can automate and analyze faster than traditional methods. Marketers with this skill can continually refine campaigns based on real-time feedback.
Personalization
Personalization skills allow marketers to deliver tailored content and offers that resonate with individual users. AI aids in tracking user preferences and behaviors, enabling marketers to automate personalized experiences at scale.
Ethical and Privacy Awareness
As AI uses vast amounts of customer data, an understanding of ethical guidelines and privacy laws is crucial. Marketers skilled in this area ensure compliance, building trust with consumers by protecting their data and using it responsibly.
What is the Best AI Digital Marketing Tool?
The best AI marketing tool is ChatGPT powered by OpenAI because it’s trained on vast datasets that cover a wide range of topics and industries. Therefore, it outperforms similar AI marketing tools in the fields of precision, quality and versatility. Its super-easy interface is also an advantage, as no technical skills or knowledge are needed to benefit from using it. Exemplary applications of ChatGPT in digital marketing include:
- content generation (automating the creation of blogs, social media posts, email content, or even expert writings),
- personalization (delivering tailored marketing messages in various formats based on customer preferences),
- SEO assistance (optimizing content with keyword suggestions and structure improvements),
- customer support (providing 24/7 chatbot assistance to answer common queries),
- ad copywriting (crafting persuasive ad copy for various platforms, target audience segmentation, proposing “flow”),
- A/B testing ideas (suggesting variations for split testing in campaigns, interpreting results and suggesting improvements),
- data analysis (analyzing extensive datasets to improve marketing strategy and allow making informed decisions),
- market research (analyzing customer data to determine trends for future strategy adjustments),
- social media marketing (helping with post scheduling, giving ideas for content, writing copy pieces and more),
- email campaign optimization (enhancing open and click-through rates with AI-driven insights, e.g. adjusting appropriate tone, leveraging persuasion techniques, etc.).
What is the Best AI Digital Marketing Tool for Landing Pages?
Landingi is currently the best AI digital marketing tool, as it offers not only features for generating content but also AI-driven SEO optimization and some AI-based image editing features.
Landingi’s AI Assistant surpasses similar solutions, as the copy generated with it is of far better quality than that created in competitive tools. That’s because it is based on the latest version of ChatGPT, “fed” however with plenty of additional training data, and enhanced with a system of predefined prompts. With this, it’s able to keep the messaging concise, relevant, and more sticky to the user’s requirements in terms of tone of voice, goal, and product characteristics (all of these can be adjusted in the tool). AI Assistant needs only a few moments to provide you with a ready-to-use copy on your landing pages (CTA, headlines, descriptions, benefits, contact sections – all included!).
Separately, AI Assistant can generate for you on-page SEO, including:
- meta titles,
- meta descriptions,
- and keywords.
To ensure accuracy, this tool uses the existing content on your page.
A constantly developed tool for image editing currently allows you, among other things, to remove the background of an image (it’s super convenient, for example, when you aim to cut out your silhouette from a photo and paste it directly into the landing page background).
What is the Best AI Digital Marketing Agency?
The best AI digital marketing agency is NoGood from New York due to their deep specialization in implementing cutting-edge technologies and years of experience working with large companies from the Fortune 500 list (including Google, Microsoft, Meta, HubSpot, Salesforce, TikTok, etc.) and the most demanding projects.
They offer setting up whole digital marketing funnels, strategies, platforms, and apps (also based on artificial intelligence). Additionally, you can order more specific marketing services focused on branding, SEO, digital advertising, web page conversion optimization, social media campaigns, email marketing, etc.
Key industries they serve comprise:
- SaaS,
- technology,
- healthcare,
- and fin-tech.
They implement machine learning and generative AI to automate marketing tasks, forecast consumer behavior more effectively, and make use of AI data-driven capabilities to improve customer service (e.g. with chatbots).
Is AI Replacing Digital Marketing?
AI is not replacing digital marketing but is transforming and enhancing its capabilities and efficiency. While AI automates many standard and/or repetitive tasks – like data analysis, reporting, and generating various digital content – it complements rather than replaces human creativity and strategic thinking, which are often the key features of digital marketers. They can use AI to make data-driven decisions, predict trends, and improve customer engagement, but the need for human insight, professional brand storytelling, or crafting innovative strategies (activities reserved for digital marketing pros) remains and probably will remain critical.
What is the Difference Between Digital Marketing and AI Marketing?
Digital marketing refers to promoting products or services through online channels like social media, email, websites, and search engines. It involves creating content, managing ad campaigns, and using digital tools to reach and engage customers. AI marketing, on the other hand, integrates artificial intelligence into digital marketing strategies to optimize and automate processes like data analysis, audience segmentation, and personalized content delivery.
While digital marketing requires manual efforts to plan and execute strategies, AI marketing leverages machine learning and predictive analytics to enhance efficiency and provide real-time insights, helping marketers make data-driven decisions and tailor experiences at scale.
What are the Limitations of AI in Digital Marketing?
Limitations of AI software in digital marketing are related to dependency on data input and its quality, relatively poor performance on highly creative tasks, significant implementation costs and increasing ethical concerns.
First, AI relies on large volumes of accurate, relevant data to function effectively, meaning that incomplete or biased datasets can lead to inaccurate insights and flawed recommendations. Data inconsistency or poor integration across sources can result in gaps that undermine AI’s predictive and analytical capabilities. Consequently, maintaining clean, high-quality data is crucial, requiring regular monitoring, updates, and sometimes costly data-cleansing processes.
Secondly, while AI excels at processing and analyzing data, it lacks the human intuition and emotional depth required for creative tasks like storytelling, developing unique campaign concepts, crafting compelling narratives and brand positioning. AI-generated content can feel formulaic or impersonal, missing the nuance that resonates with audiences on an emotional level. That said, AI marketing tools are not capable of replacing professional marketers.
Thirdly, implementing AI-driven solutions involves significant investment not only in software but also in hardware and skilled personnel who can manage and optimize AI systems. Smaller businesses may struggle with these upfront costs, as well as the ongoing expenses associated with maintenance, data management, and software updates. Additionally, AI integration often requires restructuring existing processes and training teams, adding further complexity to implementation.
Finally, the use of AI in digital marketing often involves collecting and analyzing vast amounts of personal user data, raising concerns over data privacy and security. As regulations tighten around data usage, businesses must ensure AI applications comply with legal standards, which can be both complex and costly. Transparency in data usage is also critical, as misuse of data can erode customer trust and harm brand reputation, impacting long-term marketing success.
Step Into AI Universe with Landingi
The theory is just behind you. If you feel ready to dive into the real AI digital marketing universe, there is probably no better tool to start your adventure than Landingi. Apart from a bunch of aforementioned built-in AI marketing tools, the platform excels as a digital marketing solution chosen eagerly by big brands (like Sony, Opera, or DAT), as well as by newcomers in the business. This is because it perfectly combines two essential values: user-friendliness and versatility.
When it comes to the latter subject, you can use the platform to:
- build landing pages, microsites, mobile pages, pop-ups, lightboxes and forms (all can be created from hundreds of templates or from scratch),
- optimize created pages for conversions with A/B testing console, on-page user behavior tracking tools and customizable dashboards,
- integrate with over 170 other digital marketing tools (or other software),
- scale up your business with automated multilingual translations, Smart Sections and programmatic pages,
- and much more!
Try it out for free and start your digital marketing journey right now!
