Along with the development of technology, artificial intelligence has been being used in many different fields such as labor, health, security, transportation, marketing ... With related AI marketing and application to research customer behavior, collect customer information, answer customers about the company's products.

Currently, many big companies invest in and apply artificial intelligence such as Google, Facebook, Amazon, IBM, Microsoft or Baidu, Xiaomi and other Chinese companies. To be able to grasp and keep up with technology trends, and effectively exploit artificial intelligence to apply in business operations, businesses need to research and apply AI effectively.

In this article, we introduce the meaning of AI, the benefits of Artificial Intelligence and applications of artificial intelligence in the real world. Let's check out 15 Applications of Artificial Intelligence in Marketing now.

1. What is Artificial Intelligence?

Artificial Intelligence (AI) is a branch of computer science involved in building intelligent machines capable of performing tasks that often require human intelligence. AI is an interdisciplinary science with many approaches, but advances in machine learning and deep learning are creating a paradigm shift in almost every sector of the tech industry.

Artificial intelligence differs from programming logic in programming languages by applying machine learning systems to simulate human intelligence in processes where humans do better than computers.

2. The benefits of Applications of Artificial Intelligence in marketing

The benefits of Applications of Artificial Intelligence in marketing

Artificial intelligence in digital marketing play an important role. Here are the most expected benefits AI will bring to marketing:

• High-quality opportunities and leads are ranked as the most highly anticipated AI benefit to feed into marketing and sales at a 67% rate.
• Better engagement with prospects and customers ranked as the second-most expected benefit of implementing ai in marketing and sales at 56%.
• Next is a better understanding of the buyer's intentions. This is the expected benefit to sales and marketing when implementing artificial intelligence at a rate of 52%.
• A higher conversion rate is also listed as the benefit artificial intelligence will bring in sales and marketing at a 50% rate.

3. 15 Applications of Artificial Intelligence in Marketing

The applications of artificial intelligence - stage 1: Reach

1. AI-generated content

AI-generated content is one of the applications of artificial intelligence. This is a really interesting area for AI. Even though AI still can write its own blog post on the best or opinion on the best way to develop sales funnel and practical advice for a specific industry, there are certain areas in which contents created by the artificial intelligence can be useful and help attract customers to your website. It helps to save your time and resources.

AI-based content writing programs can select elements from datasets and “human-like” article structures that are personalized for a particular prospect. An AI program called ‘WordSmith’ produced 1.5 billion content in 2016 and is expected to become even more popular in the coming years.

If you are in a banking or credit union, an AI writer can assist with quarterly income reports and market data.

2. Smart content curation

Artificial intelligence-powered content curation allows you to better engage visitors on your website and deliver a satisfying experience by displaying relevant content to them. This technique can be understood that showing visitors relevant content to them based on what other people like potential customers have purchased in the past. In short, this can be a form of recommendation tool that includes products, offers and content.

It's also a great technique for registered businesses, where the more people use the service, the more data the machine learning algorithm has to use and the better content recommendations become. Like the Netflix app, it can continuously recommend you shows that you would be interested in it.

3. Voice search

Voice search is one of the applications of artificial intelligence. To improve reach, AI-driven voice technology uses technology developed by major companies (Google, Amazon, Apple) to help increase organic search traffic using Digital personal assistant. A brand that plays an important role in voice search is able to capitalize on huge profits in organic traffic with high purchase intent thanks to increased voice search traffic thanks to fish virtual assistants controlled by AI.

4. Pop up

Regular pop ups will appear as soon as a user visits the page. However, it can be frustrating to show up repeatedly and visitors will leave immediately. However, Leadflow - branch of Leadee ai application is created by some professional developers that allow pop-ups to appear only when users express interest in a product, service, or information by moving the mouse pointer to near the bottom of the page or preparing to leave. That is made to target advertising to the most relevant audiences who show an interest in the products you offer.

In addition, Leadee ai also owns an application to automatically post on websites - Social Lead. Creating backlinks, sharing promotion of an event marketing on websites or social networking sites, groups on Facebook will now be done in a blink of an eye with just one click.

The applications of artificial intelligence - stage 2: Act

This is the stage in the consumer journey that aims to engage consumers and make them aware of your products or services.

5. Propensity modeling

Propensity modeling is a machine learning algorithm that is provided a large amount of historical data to generate propensity models (in theory) so that accurate predictions of the real world can be made. Machine learning at this stage helps direct consumers to the right message and place on your website. You can see a simplified diagram of this process:

6. Predictive analytics

Artificial intelligence is primarily used to interpret demographic information and website analytics information.

Propensity modeling is applicable to many different disciplines. Using Propensity modeling can help predict a customer's conversion capability, predict the price at which consumers are most likely to convert, or predict which customers are most likely to make a repeat purchase. This application is called predictive analytics because it is based on collecting data and making predictions about customer behavior. However, it is important here that the data is accurate. Because if there is an error in the data collection, it can make inaccurate predictions.

7. Lead scoring

The propensity model can be trained to score customers based on certain criteria so that your sales team can determine how hot a prospective customer is. and whether we should make time for them or not. This is useful in B2B businesses with sales consulting processes that take a significant amount of time to convince customers. By focusing on the most potential customers, sales teams can save time and effort. In addition, insights in buying behavior can also be used to know what weaknesses of customers you should attack, as well as use promotions where they are most effective.

8. Ad targeting

Ad targeting is one of the applications of artificial intelligence Machine learning algorithms can analyze large amounts of historical data to work out which ad setups will work best on who and at what stage in the purchase process. By using continuous machine learning, you can serve them with the best content at the right time and this is more efficient than the traditional method. However, one thing that machine learning still can't compare to humans is doing the creative parts.

The applications of artificial intelligence - stage 3: Convert

Stage 3 is the key stage in transitioning from a potential customer to a real customer.

9. Dynamic pricing

Discount is always a strategy to attract customers to buy and increase sales. However, a discount can lead to lower margins. So what's the strategy here?

Dynamic pricing – one of the applications of artificial intelligence can avoid this issue. Dynamic pricing (also called algorithmic pricing) is where the price is flexible is based on demand, supply, competitive pricing, subsidiary product pricesfa. Prices may even change from customer to customer based on their buying habits. Dynamic pricing allows vendors to be more flexible and adjust prices for more personalization. Machine learning can build a propensity model in which sign show that the customer is likely to need a suggestion to convert, and which are likely to convert without the need of an offer. This means you can increase your sales while not reducing your margins by much, thereby maximizing your profits.

10. Web and app personalization

Using propensity model to predict the customer's stage in the buying journey, thereby allowing you to serve that customer on the app or on the web.

11. Chatbots

Chatbots are the biggest example of the use of artificial intelligence technology. They act as a virtual assistant for consumers. It mimics human intelligence, thereby acting almost like a real human, including explaining consumer inquiries, completing orders, taking care of customers. You may think that using chatbots will be expensive, but in fact, by using the open chatbots development platforms, it is relatively easy to create your own chatbot without the need for a team of developers. development. Currently, Facebook and Messenger platforms have created guidance on building a chatbot for their brand.

Check out the overview of What Is Facebook Chatbot Messenger Marketing?

12. Re-targeting

Machine learning can be used to establish which content is most likely to bring customers back to the site based on historical data. This helps optimize ad retargeting to make them as effective as possible. The most realistic example of ai in digital marketing is Facebook or Google, when you search for a Cloodo shirt, then you turn it off. The next time you use Facebook or Google, you will see the Cloodo shirt appear on your Facebook.

The applications of artificial intelligence - stage 4: Engage

13. Predictive customer service

Predictive analytics is used to find out which customers are most likely to unsubscribe from a service, by assessing which features are most common among customers who do unsubscribes. You can contact these customers with suggestions, reminders, or support to stop them from churning.

14. Marketing automation

Marketing automation techniques often involve a series of rules, triggering interactions with customers via email messages, smartphone notifications or web personalization. The application of marketing automation has been limited by the time it takes to set up and optimize these rules.

Machine learning can analyze customer interaction data and establish when is the most effective time to contact, which words in subject lines are the most effective, and more.

15. Dynamic emails

Predictive analytics using propensity model can leverage previous behavior to best promote products and services in email communication. The results from these exchanges are then modeled and improved in the future.

Conclusion

Hopefully, this article of 15 Applications of Artificial Intelligence in Marketing has brought to you much essential information.

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