What are the most valued marketing AI use cases?

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Gartner predicted that by 2021, 80% of technology would be built on an AI foundation. And as artificial intelligence (AI) has become increasingly prevalent across industries, there is no denying that the marketing industry has had its fair share of AI’s impact in its processes.  

The reason therefore is that automation and tools that provide insights, strategy and control are considered the most valuable. The use of AI in many cases have led to an increase in productivity, sales and profitability. In the last year, many top marketers have added artificial intelligence to their marketing campaigns. As a result, more businesses are exploring the potential benefits using such tools. In fact, more companies are utilizing these types of tools than ever before. AI in many cases have led to an increase in productivity, sales, and profitability.  

While some marketers are content to leave the task of developing and implementing new campaigns to capable marketing professionals, others prefer to focus on leveraging existing technology and knowledge. As a result, many marketers today are using advanced technology to provide insights into both the current state of the market and the prospects.

Data credit: Mckinsey

What is AI marketing?

Many businesses – and the marketing departments that help them – are quickly embracing intelligent technology strategies to boost operational efficiency while also improving customer satisfaction. Marketers can achieve a more complex and complete understanding of their target market by using these channels. The information collected during this process can then be used to increase conversions while also reducing marketing teams’ workload.

AI marketing makes automated decisions based on data collection, data interpretation, and additional observations of audience or economic patterns that can affect marketing efforts. When pace is crucial, AI is often used in marketing campaigns. AI tools learn how to better interact with customers based on data and customer profiles, then serve them personalized messages at the right time without the need for human interaction, ensuring maximum productivity. Many modern marketers use AI to supplement their marketing teams or to complete more tactical tasks that require less human complexity.

Components of AI in marketing.

Artificial intelligence is undeniably essential in assisting marketers in connecting with their customers. The following AI marketing components make up today’s leading strategies for bridging the gap between vast quantities of consumer data and actionable next steps that can be applied to future campaigns:

Machine learning.

Artificial intelligence is at the heart of machine learning, which entails computer algorithms that interpret data and learn on their own. Machine learning devices examine new data in the light of applicable historical data, allowing them to make decisions based on what has worked and what has not in the past.

Big data and analytics.

The rise of digital media has resulted in a flood of big data, allowing advertisers to better understand their activities and accurately attribute meaning across platforms. As many advertisers fail to decide which data sets are worthwhile to obtain, this has resulted in an overabundance of data.

AI platform solutions.

Effective AI-powered solutions offer marketers a centralized framework for handling massive quantities of data. These tools will provide you with actionable marketing information about your target audience, allowing you to make data-driven decisions about how to better reach out to them. Frameworks like Bayesian Learning and Forgetting, for example, can help marketers better understand the responsiveness of a customer to a particular marketing campaign.

Importance of AI marketing.

Marketers may use AI marketing to quickly consolidate and analyse large amounts of data from social media, e-mails, and the internet. Marketers can then use these insights to improve campaign success and ROI in a shorter amount of time. AI marketing solutions, in essence, refine and streamline campaigns while removing the possibility of human error.

In the e-commerce, retail, and business sector, as customer preferences change with technology, there has emerged a strong desire to provide highly personalized and customized experiences as quickly as possible. AI marketing assists businesses in determining who their target audience is so that they can provide each customer with a tailored experience.

Insightful AI use cases:

With AI marketing expected to conquer the industry in 2021, there is no better time for marketers to learn how to use this amazing technology than now.

Data credit: Everest Group

AI for content creation and curation

The development of high-quality content is an important part of establishing authority in your industry or niche. To improve organic rankings and popularity in the SERPs, you must first establish authority. Marketers might be reluctant to hand over control and let AI build content on its own, but the technology is closer than one would expect. Several global brands, including Forbes, are currently publishing content that is at least partly created by AI.

In addition, AI software can parse web traffic data and curate content recommendations based on searcher purpose. This is another example of artificial intelligence reducing time spent on a routine mission, in this case deciding content topics and publishing content on the most successful platform at the most opportune time.

With more time on their hands, marketers will focus on strategic growth plans, face-to-face contact, and other areas where the human touch is more important than AI.

Optimize digital advertising campaigns

Although there are numerous methods for optimizing digital ads and account-based marketing, AI solutions allow marketers to go a step further in terms of insight and analysis. For smarter and more powerful digital advertising, AI will tap into the abundance of customer data concealed in keyword searches, social profiles, and other online data. Without the need for manual human labour, the findings are human-level outcomes and insights.

Social media feed personalization

According to the Havas Group’s Meaningful Brands 2019 research, 81% of European brands could go extinct if they don’t develop relevant content and can’t give targeted discounts. Only 19% of companies analyze customer behavior, accurately categorize their audiences, and customize their offers. Social media is one tool that can bring people from all over the world together to discuss and share issues or stories that are important to them. It is something that consumers have obviously noticed, with the billions of people who use social media across the world.

Of course, this means that advertisers continue to take advantage of the success of social media — Customer engagement is determined by the appropriate content marketing strategy and activities. A Gartner research suggests that one of the most common barriers to content creation, according to 50% of marketers, is a drive for perfection which is why marketing teams devote around 30% of their spending to content generation in order to fuel a variety of engagement activities. However, less than 40% of marketers who use content marketing have a defined and documented strategy. As a result, social media sites such as Facebook, Instagram and Twitter have made it easier for users to conceal ad content they do not like or find valuable, and this knowledge helps tailor the user experience for them while also providing marketers and publishers with more viewer data on the platforms.

Social media management

When embarking on a content marketing marathon, we must take periodic breaks to analyse our progress and plan our next steps. This is where social media marketing tools may help. In 2021, social media was the most popular marketing channel according to a HubSpot report. Eight out of every ten firms invest in social media, with 39% aiming to expand their spending in the coming year. Marketing technology has proliferated as social media has risen in popularity over the previous decade.

Data credit: Forrester


Many businesses have begun to communicate with customers via messaging apps such as WhatsApp, Facebook Messenger, and Slack. It is quick; consumers are already using these tools to connect with friends and colleagues and let us face it, you do not always want to pick up the phone to call somebody. Chatbots are attempting to make the process even more easy thereby increasing the adoption rate. As a matter of fact, the COVID-19 pandemic has increased chatbot adoption rates beyond expectations. Spending on cognitive and AI systems will reach $77.6 billion in 2022, according to the International Data Corporation’s (IDC) assessment on the condition of the conversational AI market, more than three times the $24 billion anticipated for 2018.

Voice search

Voice search has swiftly established itself as an important component of Search Engine Optimization (SEO), and it isn’t going away anytime soon. Because it is significantly more convenient than typing, voice search is now extensively utilized to find products and services online.

Google for instance currently utilizes speech recognition in over 120 languages and dialects. We can expect this list to increase dramatically as voice search gets more popular. AI has also had a significant effect on how people perform web searches which are affecting how advertisers build and optimize content. People can perform searches with the touch of a button thanks to innovations like the Amazon Echo, Google Home, Apple’s Siri, and Microsoft’s Cortana. Users can now ask a computer, “Where should I go for dinner tonight?” rather than typing in “Restaurants in my area.”

While a marketer may eventually want to implement hundreds of AI use cases, they should first prioritize their top prospects based on two criteria: value and practicality. It’s fine to think big at first, but you’ll need to cut down your options later. Once the marketing teams have determined which processes, they want to improve with AI they can begin to identify the people who will lead the implementation and the technologies required to make those use cases a reality.

What is your opinion? Leave us a comment and speak to our data experts.

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