In this rapidly evolving digital world of ours, businesses need to continually seek innovative ways to enhance their marketing operations and beat the competition. 

One of the most transformative technologies, especially over the past months, is Artificial Intelligence. You might have heard that a lot of companies are using ChatGPT and GPT technology to build new solutions, improve existing ones, and take their different business areas to new heights. 

Marketing is no exception to this trend. However, ChatGPT isn’t the only way marketers can leverage the powers of AI. In this article, we’ll walk you through other ways you can use AI in your marketing strategy and make the best of it to drive growth. 

Understanding AI in Digital Marketing

AI is a powerful asset for businesses overall, which includes marketing teams. It enables them to automate specific everyday tasks such as campaign management and scheduling, sending newsletters, and even generating content. 

Although it’s seen a boost in popularity in recent months thanks to ChatGPT, AI in digital marketing has been around for a few years now. 

Its initial stages focused primarily on basic automation and simple chatbots that provided audiences with scripted responses. These could be used for tasks like lead generation through a website chatbot and content distribution on conversational apps such as WhatsApp and Facebook Messenger. 

As the technology evolved, AI started to play a more prominent role in digital marketing. Thanks to machine learning algorithms, marketers can more easily and quickly analyze customer data from social media, website analytics, and customer feedback. This information could then be used to segment audiences and personalize content and marketing campaigns for increased lead conversion. 

Further applications of AI in digital marketing through the years included, for example, sentiment analysis and AI-powered, personalized recommendations — think Amazon or Netflix, with their super-targeted content recommendations — as well as more evolved chatbots and voice-activated virtual assistants. 

Recently, advanced technologies like OpenAI’s GPT-3, GPT-3.5, and ChatGPT have opened up even more opportunities for marketers, allowing them to build sophisticated chatbots, as well as use the technology for content creation, summarization, and data analysis, among other tasks. 

Benefits of using AI in Digital Marketing

Thanks to its possible applications, AI allows you to enhance your marketing efforts in several ways. 

• Advanced data analysis: AI algorithms can analyze large data volumes more quickly and accurately than if the process was done by hand. This can help uncover insights, identify patterns, and predict customer behavior, which can help marketers make informed decisions and optimize their marketing strategies based on real customer data.
• Enhanced personalization: as mentioned, AI can analyze vast amounts of customer data and provide personalized recommendations based on individual preferences and behavior. This level of personalization improves customer engagement and satisfaction and can help boost lead conversion. 
• Increased efficiency and employee productivity: AI frees up their time to focus on more creative and strategic tasks by allowing marketers to automate certain tasks like data analysis and campaign optimization.
• Cost savings: AI automation reduces the need for manual intervention in repetitive tasks, saving costs associated with human resources. Additionally, AI helps optimize costs by targeting the right audience and minimizing wasted ad and campaign spending.
• Continuous learning and improvement: AI algorithms continuously learn and adapt based on new data and user interactions. This learning process helps marketers refine their strategies, improve targeting, and enhance customer experiences over time and based on real-life customer data and behaviors. 

AI in Digital Marketing Use Cases & Examples

In the first section of this article, we’ve already scratched the surface of how marketers can leverage the power of AI in their marketing strategies. 

Now, let’s dive deeper into each of the specific use cases of AI in digital marketing. 

Chatbots

AI chatbots can support digital marketing efforts in several ways, including lead generation, lead qualification, running contests and surveys, content distribution, and more. These tasks aren’t much different from what rule-based chatbots were already capable of. 

However, while rule-based chatbots are only able to follow a specific script, leaving no room for open questions from users or deviation from the pre-defined flow, AI chatbots can recognize text and conversation context and reply accordingly. But they still weren’t living up to their full potential, often getting stuck in conversational loops (“Does this answer your question?” “No.” “How about this?” “No.”) and providing wrong or contextually incorrect answers.

That’s not to say that even the most recent technological advancements in AI have made it 100% error-proof; however, they have allowed chatbots to come closer to what has been envisioned for them since the beginning. 

I’m talking about, you guessed it, the natural language processing model GPT-3 and its most widely used application, ChatGPT. It uses advanced NLP models and deep learning techniques that allow it to understand and generate natural language responses to user inputs. This means GPT-powered chatbots can have conversations with people in a way that sounds natural and similar to how humans talk to each other. 

GPT technology hasn’t just changed the way people interact with chatbots. It has also made it possible for *you*, as a business, to easily build and deploy your own chatbot for your own marketing needs. It's shown to be an absolute game-changer for chatbot creation since, in combination with a visual chatbot builder like Landbot, it can make AI bot building accessible to anyone.

At Landbot, we’ve been doing just that.

Landbot AI is a range of features, integrations, and components that bring the power of AI to our no-code builder, and, in turn, can make your marketing chatbot building life easier. 

Our Text-to-Bot feature, for example, allows you to build a chatbot by simply writing a prompt describing what you want your chatbot to do (ask for contact information or make appointments, for example), and Landbot AI will generate the chatbot template for you. You have to be as descriptive as possible in the prompt, and even include the tone of voice you’d like the chatbot to use, so that the result meets your expectations and needs. 

Here is the Text-to-Bot feature in action:

You already didn’t need to be a coder to build a rule-based chatbot for your marketing leads, but now the process is much easier and faster. Plus, you can harness the power of AI’s capabilities to build nearly any chatbot you might need to improve your marketing strategy. 

Customer Segmentation and Personalized Recommendations

Understanding your audience is key to crafting targeted marketing campaigns that yield the best results. The road to uncovering what customers really think and feel about your business and what they want from it isn’t always easy. But that’s what’s necessary to be able to segment your customer database and offer them personalized recommendations that will keep them coming back and repurchasing your product or service. 

Ways to gather customer feedback include satisfaction surveys, monitoring your community, whether that’s a message board or a social media platform, doing interviews, and looking at customer experience metrics, to collect relevant data. 

Going through that data and identifying pain points and opportunities is a more laborious task, and that’s where AI comes in to help. 

AI-based customer segmentation and personalized recommendations work by leveraging advanced algorithms and machine learning to analyze large volumes of customer data and identify behavioral patterns, similarities, and preferences among the different groups that make up your customer base. 

If you’re not already using AI in your marketing operations, the technology might sound like something very complex or unknown to you, but it’s nothing you’re not likely in touch with on a daily basis. 

Have you ever noticed that your Netflix home screen is different from that of your friends or co-workers?

That’s because Netflix uses customers’ viewing data, search history, ratings, the kind of device they use, and at what times they watch the most, to understand what it should recommend to them. This comes in handy not only to improve the experience with the streaming service and keep people coming back for more, but it also reduces churn rates by giving customers exactly what they want. 

Here’s how the process works. 

Businesses collect users’ data, from demographic information to certain behaviors. AI algorithms then analyze this data to identify patterns and preferences. It assigns customers to specific segments based on their common characteristics, which then allows businesses to target each of these segments in the best way possible. 

The same goes for recommendations. After the first steps of data collection and analysis, the recommendation engines generate personalized recommendations for each customer or customer segment. 

And because the algorithms keep learning from customer interactions, it’s possible for businesses to keep improving the accuracy of their segmentation and recommendations, which, in turn, makes for more optimized marketing strategies and campaigns. 

Ad Targeting and Optimization

Thanks to AI’s advanced data analysis capabilities, it also helps marketing teams improve their advertising campaigns through more accurate ad targeting and optimization. 

In the same way that AI algorithms are able to segment your customers and offer them personalized recommendations, they can also target different audience segments with different ads to maximize their performance. 

The amount of data AI is able to work with, and the short amount of time it takes, enables businesses to identify the most relevant audiences for their ads, ensuring that their message reaches the right people at the right time. AI also empowers marketers to adjust their campaigns in real-time, changing ad placements, budget allocation, and bidding decisions as needed.

This has a substantial impact on marketing operations. 

A recent Salesforce report mentioned that 83% of IT leaders state that AI and machine learning are transforming customer engagement, while 69% say it’s transforming businesses altogether. Marketers, in turn, also recognize the importance of using AI to target the right people with the right ads to improve conversion rates. 

By precisely identifying the most receptive audiences, marketing teams can experience higher click-through rates, improved ad performance, and ultimately, a better return on investment. Plus, thanks to the algorithms’ continuous learning capabilities, marketers can constantly leverage data to refine targeting and optimize ad placements for maximum impact.

Predictive Analytics

Marketing isn’t just about targetting the hottest leads for sales to convert to paying customers. It’s also about catering to existing customers, nurturing them, and maintaining a good relationship so that they don’t leave you for the competition.

Churn analysis steps in here to help predict and prevent the effects of the churn rate on your business, by examining customer defection and their tendency to abandon a product or service. It typically uses methods and techniques of predictive analytics, which is to say, a series of forecasts that can be updated in real-time and allows businesses to accurately assess the possibility of a customer churning and try to prevent it. 

The key benefit of AI here is that it can analyze a much wider sample of customer data in less amount of time than if you were to do it by hand, or using other data analysis tools. 

AI analytics utilize advanced Machine Learning techniques to process data in real-time, offering invaluable customer insights, revealing patterns, and establishing data correlations that will help you stay ahead of customer churn. 

So, how does AI accomplish this?

By thoroughly analyzing the responses received from surveys, gauging overall customer sentiment, and reviewing past interactions with clients. In doing so, businesses can identify common characteristics among customers who have ceased using their services. Armed with this knowledge, proactive steps can be taken to improve marketing strategies, nurture customers and preserve user relationships before they reach a critical stage.

Just last month, Mike Sievert, T-Mobile’s CEO, referenced the company’s plans to use AI for predictive analytics and understand why customers leave. 

T-Mobile is currently the only major U.S. wireless company with a declining churn rate among postpaid subscribers. And while that’s a great trend, given the size of the business, there are still millions of customers who churn on a yearly basis. As T-Mobile’s CEO puts it: “Every one of them left a trail of data before they finally threw their hands up and gave up on us. Something was going wrong, something in the network, something in the customer interaction.”

AI-based analytics, then, can help the business better understand the underlying customer experiences that lead them to churn, by analyzing and cross-referencing disparate datasets that allow them to paint a broader and clearer picture of customer behavior. 

Content Generation

Creating content is a time-consuming task. Not just because of all the different types of content that marketers need — from written content like blog articles, use cases, or website copy, to visual assets such as photography, graphics, social media banners, and even video — but also because compelling content isn’t as simple to come up with as people might think. 

Marketers are finding value in leveraging AI for content creation, as it streamlines processes and helps them save time in certain areas. 

‍AI-powered creation tools like Copy.ai, or even ChatGPT on its own, can automate the writing of product descriptions, social media copy, or emails. You can even use it for long-format content like blog articles. Nevertheless, every text produced by an AI tool should still be double-checked by a human. 

It’s not that ChatGPT, for example, will produce content with typos or grammatical mistakes. But its model uses a database containing information up to 2021. It can’t access real-time data, so if you need a research-backed text with recent statistics or examples, it’s likely the chat will produce an inaccurate response. A human review and editing are also crucial to ensure the content is aligned with the brand and adds a human touch to the final piece.

Still, AI presents a great opportunity for marketers to quickly deliver shorter pieces of written content that, all adding up, end up taking up a lot of their time, and freeing up their work day to focus on more creative or strategic tasks. 

In addition to that, AI can help optimize content. By analyzing user interactions with the content businesses put out, AI-powered tools can identify which headlines, images, or content elements generate the most clicks and conversions. This valuable insight allows marketers to refine and tailor their content strategies, maximizing campaign effectiveness and driving better results.

Airbnb has been using AI to generate and optimize its content for a couple of years now. The rental platform applies AI algorithms to AI analyze vast amounts of user data, including search behavior, booking history, and preferences, to create tailored content for different segments of their audience, for example, when sending promotional messages or app notifications.

It also uses AI technology to help homeowners write descriptions for their properties. Airbnb’s AI algorithms analyze property features, reviews, and location data to automatically generate appealing and accurate descriptions for hosts. This not only saves time for hosts but also ensures consistency and quality across the platform.

But I mentioned that text isn’t the only content format marketers need to create, right?

When it comes to image creation and editing, established tools in the market are incorporating AI into their products to offer even better tools to their users. Photoshop, for instance, recently launched Generative Fill. The feature allows Photoshop users to easily create, add, remove, or replace images in the tool through simple text prompts. 

Conclusion

As digital marketing keeps evolving to stay up to date with what’s happening in the world, AI has emerged as a powerful tool to help businesses gain a competitive edge. 

Whether you’re using the technology to build lead generation chatbots, prevent customer churn, or make your content creation process more effective, there’s no denying the numerous benefits AI has to offer. 

By embracing AI in your digital marketing operations, you can unlock valuable insights, automate processes, and propel your business toward new lead conversion and business growth heights. 

"Want to learn more about GPT-tech? Here are guide on how to write prompts to maximize your AI bot efficiency.‍