Introduction –

In marketing, artificial intelligence (AI) is increasingly used to automate processes, such as identifying and targeting users with ads on a website or in an app. Marketers today have sophisticated audience targeting and segmentation choices at their fingertips thanks to tools, platforms, and services, making it easier than ever to attach your products and services to customers.

Marketers nowadays are constantly on the lookout for innovative strategies to locate and entice their ideal audience. It is becoming increasingly hard to reach your target audience and deliver results in today’s fast-paced, ever-changing digital marketing landscape.

Many people think of AI in marketing as science fiction, but it’s not a far-fetched notion; it’s already here. According to AIxOutlook, just 35% of marketing executives employed AI in 2019, but by 2021, that figure had risen to 90%. Global investment in artificial intelligence hardware, software, and services is estimated to surpass $530 billion by the end of 2022.

What Is Artificial Intelligence Marketing, and How Does It Work?

Artificial intelligence marketing (AI Marketing) is a technique for predicting your client’s next step and improving the customer journey by combining customer data and AI principles such as machine learning.

Artificial Intelligence advancements have made it easier for businesses to apply new methods of marketing. AI can contribute to the creation of more successful marketing strategies, the enhancement of the customer journey, and the transformation of how firms attract, nurture, and convert prospects.

Important Use Cases of AI in Marketing –

1. Creating Intelligent Advertising

With artificial intelligence, it is possible to create highly personalized advertising materials and marketing campaigns. An algorithm can determine the style of design, or the color scheme employed in a marketing campaign to ensure they have the best chance of grabbing your audience’s attention and inspiring further engagement. As a result, algorithms can evaluate the effectiveness of different combinations of design elements and audiences and adjust where necessary.

2. Identification of images

A computer vision system enables computer software to see – or understand visual information. To better understand how and where products or services are being used, marketers can scan the millions of images that are uploaded daily to social media platforms. Marketers can now evaluate factors such as market penetration and brand awareness in this way. Influencers can also be identified that already have a connection to your brand, which can help produce more authentic engagements.

3. A try-before-you-buy experience with AR

By offering augmented reality (AR) tools that superimpose computer-generated graphics over real-world images, Ikea lets customers view products in their own homes to see how they might match their existing decor. A user’s phone camera can be used to generate realistic-looking composite images using artificial intelligence (AI), generally in real-time. Using the same technology, beauty brands such as L’Oreal allow their customers to try on make-up and other products to see how it looks on them. The functionality has been available to big players for some time, but it is increasingly available as a service through platforms that allows retailers of all sizes to use it.

4. Search Engine Optimization (SEO) –

Search engine optimization (SEO) is still widely recognized as the most important driver of marketing success, despite the emergence of social media and influencer-driven marketing initiatives. It has been proven that Google is the first stop on the way to making up to 85% of purchasing choices.

When applying machine learning methods to SEO, information can usually be organized as,

  • Keyword and phrase analysis – extracting meaning from search terms
  • Content analysis – analyzing the relative merits of content received for specific queries and phrases
  • Format and structure analysis – analyzing pages to determine the correct formatting, and if there is duplicate content.
  • Embedding information in contextual data – by merging information over all words on a page, to provide extra connections with other themes on the page.

5. Curation of content

Nothing is more frustrating than finishing a fantastic new Netflix series. Fortunately, owing to AI, you can usually start binge-watching another show right away.

AI is already being used by companies like Netflix and Amazon to curate suggestions in order to keep people engaged, consuming, and subscribing. Brands can learn more about their customers by studying their behavior and delivering customized information and recommendations for them, thanks to AIs like IBM Watson.

6. Email Automation-

Brands are utilizing AI to personalize marketing emails based on consumer preferences and behavior in order to increase customer engagement and, perhaps, trigger conversion or purchase.

7. Personalization of Social Media Platforms –

What makes social media so appealing is its capacity to bring individuals from all over the world together to discuss and share issues or stories that they are passionate about. Given the billions of people that use social media worldwide, it’s evident that users have picked up on it.

As a result, social media platforms such as Facebook, Instagram, and Twitter have made it easier for users to hide ad content they don’t like or find valuable, and this information helps customize the user experience for them while also offering marketer and media companies with more viewers insights on the platforms.

Conclusion –

An array of marketing applications already relies on artificial intelligence. Many brands already use a variety of tools in their marketing campaigns — not only to make people’s lives easier but to improve their effectiveness.

When business processes are optimized and made faster by technology, not only can businesses achieve better outcomes, but humans also have more time for critical thinking, data analysis, and long-term planning.