What Is AI Marketing? How It Improves Customer Experience

When thinking of artificial intelligence (AI), the first thing that crosses people’s minds isn’t marketing.

If anything, AI & machine learning operationalization (MLOps) software is associated with the tech sector – with healthcare coming in at a close second.

People know what marketing and AI are, but the two together? Not so much.

Importance of AI marketing

Traditional data analysis is time-consuming and restricts marketers from finding and implementing real-time insights from customer data. AI marketing solutions enable marketers to make proactive decisions with business intelligence (BI) software. This market intelligence is crucial for marketers to project outcomes of different scenarios. Furthermore, AI in marketing is revolutionizing the way marketers personalize content delivery.

Other reasons marketers choose AI marketing include data visualization for anticipating trends, analyzing rich campaign information, discovering customer interaction trends, and creating meaningful bonds with customers.

Types of AI marketing applications

Marketers categorize AI marketing applications into four types, depending on their intelligence level and structure.

1. Stand-alone applications use AI programs and natural language processing (NLP) to offer personalized recommendations to customers.
2. Integrated applications remain invisible to customers and support stand-alone applications with behavior tracking.
3. Stand-alone task automation applications perform repetitive tasks using rules or instructions.
4. Integrated task automation applications use algorithms to make complex decisions and predictions.

AI marketing components

AI humanizes marketing by bridging customer data collection and actionable campaign idea execution. AI marketing tools analyze customer behavior and help marketers find opportunities to engage consumers in preferred ways. Three key components that fuel AI marketing technology adoption are as follows.

1. Big data and analytics: Big data aggregates, segments, and analyzes large volumes of structured and unstructured data sets with minimal manual efforts. Marketers rely on big data processing to gauge the impact of marketing efforts and take suitable action. Big data analytics ​​ensures that the best content and messages are reaching and positively impacting the appropriate audience.
2. Machine learning: Marketers use ML algorithms to identify historical data trends, insights, patterns, and commonalities for marketing decisions. ML platforms help marketers decode the cause of repetitive events and actions. While big data extracts and sorts data, ML solves issues and predicts future outcomes.
3. AI platform solutions: Organizations using AI-powered marketing tools discover insightful concepts and themes across datasets faster. This marketing intelligence enables marketers to make data-driven decisions and understand open form content (social networks, natural language, and email) responses. For example, the Bayesian Learning and Forgetting framework evaluates customers’ reception to specific marketing efforts.

AI marketing use cases

Different industries, including healthcare, retail, government, and financial services leverage marketing AI tools to streamline marketing operations, enhance customer experience, and boost performance marketing results. Use cases of AI in marketing are as follows.

• Programmatic advertising places ad space bids and delivers the right content to target customers at the right time.
• Intelligent account-based marketing uses AI to discover insights from keyword searches, online data, and social profiles.
• Search pattern analysis aids marketers in identifying key marketing areas.
• AI bots or chatbots streamline customer relationship with direct-to-consumer engagement and save employees time.
• Predictive analytics uncovers outreach campaign insights and facilitates real-time decision-making.
• Intelligent advertising design assesses and tweaks design elements to improve target audience engagement.
• Image recognition analyzes visual information to evaluate brand awareness, market penetration, and influencer association.
• Social listening uses NLP to discover brand mentions and gauge brand sentiment.
• Automated email content curation finds and shares relevant and engaging content with your audience.
• AI-driven dynamic pricing offers personalized e-commerce pricing with cookies, history, searches, and other online activity monitoring.

AI marketing in digital marketing

Artificial intelligence, like what some think, is not a threat. AI software supplement business strategies, automate tasks like data extraction, sorting, and analysis. AI is becoming increasingly more intelligent while performing human data analysts' functions at an unprecedented speed.

Artificial intelligence has grown to the point that it can benefit multiple facets of digital marketing platforms, such as customer service and user experience (UX).

Predictive analysis, audience targeting and segmentation, and chatbots are three examples showing how AI marketing can benefit digital marketing strategies.

Predictive analytics

The core of AI marketing is using big data and machine learning to gather and analyze data against several factors. Some of these factors might include demographic information, while others focus more specifically on website analytics.

Predictive analytics often include metrics like page views, time spent on a page, bounce rate, and click-through rate on calls-to-action (CTAs). These metrics can be tracked by AI so that you, the marketer, can make informed decisions about which areas you should be concentrating more concentrated focus on regarding your marketing strategy.

Extracting data from the above metrics can help you make informed predictions about future engagement. Rather than using data to analyze why something happened retroactively, you can now predict how to prevent the same thing from happening twice.

This capability not only amplifies future audience engagement by driving more people to your content, but AI allows you to enhance user experience on your site, encouraging new users to sign up and current users to continue regular engagement.

Audience targeting and segmentation

Knowing how to target the right audience for your content helps you create a personalized digital marketing experience for customers. ML algorithms use customer data to learn and identify important, recurring patterns, such as demographic information about users based on specific pieces of content produced.

For instance, if your ML algorithm notices that 18 to 30-year-olds visit your social media articles, but the 40 to 60-year-olds read articles about small business ownership or how to manage remote employees, you may want to focus content dissemination to each audience on different platforms: social media, email, via banner ads, and so on. Organizations across industries use content optimization tools to improve such content marketing efforts and digital marketing initiatives.

Additionally, the algorithm will gather information about the time of day and days of the week that your content is accessed the most via social media platforms. Since this information can't be tracked well by a human data analyst, AI machine learning algorithms can garner this information and help you learn the best time to post on Facebook or other social platforms for the highest levels of user engagement.

Chatbots

Using AI-powered chatbots for marketing can bring a wealth of benefits to your digital marketing strategy. Chatbots are chat robots that can converse with a human user through text or voice commands. The most apparent use of chatbots for marketing is customer-centered interactions. As a digital marketing platform, it's crucial to have multiple ways for customers to contact your company during on- and off-hours.

Suppose you have customers who live on a different continent than you. In that case, you'll want to be accessible to answer their questions – especially something time-sensitive that could be the determination between a sale, a sign-up, or them moving on to a different company with a faster response time.

AI chatbots assist with customer inquiries and gather user data in a way different from ML algorithms do. A chatbot can garner data by sending a post-conversation survey to a customer. A survey might ask for a user's demographic information and their purpose for visiting your site.

Chatbots can easily ask for – and often receive – user data much more quickly than other methods that rely on big data to access, sort, and filter user information.

AI marketing benefits

AI marketing software systems use algorithms to collect and analyze data, predict outcomes, and help marketers make informed decisions. AI marketing enables organizations to:

• Increase marketing return on investment (ROI) with fund allocation and ad placement strategy recommendations.
• Personalize content delivery based on demographics and previous interactions.
• Improve campaign management and reporting with intelligent campaign analytics and reporting insights.
• Boost market team performance by automation repetitive and mundane tasks.

AI marketing challenges

AI marketing tools aren't aware of organizational marketing goals or ways to fulfill them. That's why companies spend considerable time training AI tools on customer preferences, trends, and behavior patterns with historical data. This time-consuming AI marketing implementation process often results in challenges such as:

• Privacy issues attract penalties when a marketing team doesn’t comply with standards such as the General Data Protection Regulation (GDPR).
• Buy-in difficulties arise when organizations can’t demonstrate AI investment value to stakeholders.

AI is here to stay

As marketers grow more comfortable with the idea of adding AI into their marketing strategies, site visitors, new and old, will feel the benefits of artificial intelligence integration. There's nothing to fear about big data, machine learning, or chatbot automation – all of these benefits and more will enhance the effectiveness of marketing campaigns and customer accessibility to come.

Learn more about artificial intelligence and how it works.