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Artificial intelligence or AI is a progressively vital part of many businesses, including marketing. In recent years, marketers have started to integrate artificial intelligence in their countless digital marketing tactics to create data-based decisions for their market. Through the years, AI has established its value with the pertinent outcomes it provides in various fields. They are also proficient of surpassing human competence in specific aspects. But while we frequently talk about utilizing or integrating AI in marketing, what do we mean by that? What does it look like when applied in the real world?

Applying AI Across All Touch Points in a Customer's Journey

The use of AI was once understood as marketing expertise that only large and successful businesses could use. However, today, even smaller or startup companies can apply off the shelf machine learning services or openly obtainable algorithms to produce helpful insights and generate prediction models based on the consumers' behaviors. Today, we've identified ten artificial intelligence practices that businesses of all sizes can utilize, rather than methods which only main tech giants can dedicate resources to.
1. Data Learning and Chatbots
With the late involvement of AI, chatbots embody a more unique role than ever. It is providing marketers unmanned client support services that improve sales, reduce business costs, and increase engagement. Chatbots assist online stores in running 24/7 customer service. They provide answers to basic questions in real-time, track customer behaviors, generate unique content for emails, and provide product recommendations. Through machine learning and AI, chatbots are now proficient of offering human-like replies to intricate inquiries. Using natural learning processing, they can evaluate keywords and encourage buying decisions in customers.
2. Generating Substantial Contents
What? A machine that functions by itself and creates content from scratch? Yes, friend, there's a way! Even though AI still can't form its own political opinion for a blog post or create the best and most real-world advice for particular commerce, there are specific extents in which content generated by AI can be valuable and influence visitors to visit your website. Substantial content by AI can help you save lots of resources and time. For instance, it can already write news and reports founded on data and information. Using fill-in-the-blanks and templates to enter keywords and data can produce unique content that gives the impression of human work on it.
3. Content/Product Recommendations
Few of the most effective digital businesses have assembled their product offerings around the capability to deliver highly personalized and relevant content or product recommendations. This all arises from AI-based clustering and understanding of consumer data matched with demographics and profile information. These AI-based systems recurrently become accustomed to your likes and dislikes and respond with new real-time recommendations. Publishers are also applying AI-driven content and product recommendation widgets that can classify correlated content to surface to consumers. They even personalize those recommendations grounded on the consumers' browsing behaviors.
4. Image Recognition & Visual Search
Developments in AI image recognition and analysis are making it conceivable to attain remarkable things with visual search. While it is still early for the technology, visual search is becoming more ordinary thanks to technology like Google Lens, and platforms like Pinterest. Visual search uses search to look for results that are visually similar to one another, in the same way, that traditional text-based search obtains results of a similar topic. Visual search has several beneficial applications in retail and marketing. For instance, it can personalize the shopping experience and improve merchandising. Instead of endorsing products based on a shopper's past purchases or habits, visual search technology can recommend related products based on how they look. Through this, it helps customers to find items of a complementary style.
5. Sentiment Analysis & Social Listening
Improvements in natural language processing have demonstrated enormously useful applications for marketers who want to evaluate their online presence and use those to target movements. AI enables product brands to perform sentiment analysis on social conversations and recognize the dominant behavior towards their products and brands. This application allows them to detect potential problems and counter them before becoming too prevalent. For instance, Samsung, which partners with AI consumer insights company Crimson Hexagon, was able to spot and respond to customer discontent with a tint on the screen of its newly released smartphone model. And that's thanks to social listening. Sentiment analysis and social listening can also detect purchase intent by examining the ways that consumers are discussing a specific product. This application can allow sellers to target them with publicity or possibly a strategically placed markdown. With that said, marketers should step lightly with this kind of aiming or risk looking creepy.
6. Improved User Experience
Amplified user experience or UX is an outstanding metric of effective marketing. When it comes to collaboration, customers want a unified UX and excellent customer service from beginning to end. With the assistance of AI, marketers can independently design and tailor marketing campaigns for every user, making them persuaded to take anticipated actions. The AI-driven tailored solutions and messages primarily emphasize on the current setting of where customers are and what they are doing. Thus, resolving the particular problem they have at that moment. Good user experience is what preserves consumers browsing a site. The more time they devote on it, the higher the likelihood of conversion. Automation and AI can be useful to UX design in the form of self-optimizing websites. Meaning, the customers will relish an amplified user experience from start to finish.
7. Sales Forecasting and Predictive Analytics
One of the main advantages of AI in digital marketing is its ability to predict sales and foresee customer behaviors. Predictive analytics is the practice of taking out information from data sets to forecast future trends. It can be used to excellent outcomes in refining both customer service and experience. With the use of predictive analytics, AI combines statistics, sales modeling, and data mining to foresee future results for online markets. With the rise of big data and machine learning, potentials have further expanded for digital marketers who can amount their activities more precisely and concentrate on particular areas in their digital tactics. Predictive analytics evaluates customers' purchase behavior and regulate when they might be probable to either make a repeat purchase or to buy something new. With predictive analytics, marketers can reverse-engineer buyers' actions and experiences to control which marketing strategies lead to a positive outcome.
8. Digital Advertising
Without a doubt, digital advertising is the area of digital marketing that's most effectively implemented artificial intelligence. For instance, Google and Facebook ad platforms already utilize artificial intelligence and machine learning to find people more susceptible to making the advertiser's anticipated action. To achieve this, they examine the user's information, such as their interests, demographics, and more aspects to detect and learn the best audience for their product and brand.
9. Data Analysis and Filtering
Marketing is becoming a progressively data-driven discipline. With this, more effective use of data is crucial to cultivating customer experience, personalization, and targeting. However, merging that data once it has been collected, and examining it to determine patterns, is tedious for human beings. In this case, AI comes in. One of the definite high points of AI in a business is its ability to take on complex analysis and organizational functions that would be challenging or impossible for humans to carry out. This frees up humans to do the more intuitive, artistic work that they are better matched to.
10. Dynamic Pricing
Every marketer knows that sales are effective at shifting more products. Discounts are powerfully influential, but they can also cause pain to your bottom line. When making twice as many sales having a two-thirds smaller margin, you've produced less profit than you should have if you did not have a sale. Sales are so useful as they get customers to buy your product that formerly wouldn't have considered themselves able to validate the cost of the purchase. However, they also mean consumers that would have paid the higher value pay less than they would have. Machine learning can form a tendency model of which behaviors display a customer is possible to need an offer to convert, and which are probable to turn without the need for any offer. Meaning, you can raise sales while not reducing your profit margins by much, hence making the most of profits.

Ingredient in Every Startup's Marketing Mix

Artificial intelligence may be humankind's most astounding formation to date. With its rising presence, its applications have infused every aspect of humanity, business, and even power. From the smartphones we bring about in our bags to the banks where we save our money, AI optimizes numerous aspects of our daily lives. However, the most useful applications of machine learning and AI have been utilized in the field of digital marketing.


In 2022 and beyond, AI is going to play a dynamic role in digital marketing. Marketers need a personalized approach, better customer experience, and the most pertinent content to stay ahead in the competition.
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