AI In Marketing: How AI Revolutionizes Audience in Marketing

In today’s fast-paced business landscape, marketing stands as the frontier that reaps the most significant benefits from the integration of artificial intelligence (AI). You’ll learn the exact today at ThinkByter! The core essence of marketing revolves around understanding customer needs, aligning them with products and services, and persuading individuals to make a purchase – all of which can be profoundly enhanced through the power of AI in Marketing. A comprehensive analysis by McKinsey in 2018, which evaluated over 400 advanced use cases, highlighted marketing as the domain poised to gain the most from AI.

Embracing AI’s Potential

Chief Marketing Officers (CMOs) are increasingly embracing AI technology. A survey conducted by the American Marketing Association in August 2019 revealed a remarkable 27% surge in AI implementation in the preceding year and a half. Furthermore, a 2020 Deloitte global survey among early AI adopters indicated that three out of the top five AI objectives were marketing-focused: enhancing existing products and services, creating new offerings, and improving customer relationships.

The Current State of AI in Marketing

AI has already made significant inroads in the marketing landscape, and its role is poised to expand further in the coming years. To harness this immense potential, it is crucial for CMOs to familiarize themselves with the existing AI applications in marketing and anticipate how they will evolve. Drawing from more than a decade of expertise in data analytics, AI, and marketing, and advising companies across various industries, we have developed a framework to assist CMOs in categorizing existing AI projects and planning the integration of future endeavors. But before we delve into the framework, let’s examine the current state of AI in marketing.

AI’s Diverse Applications

In today’s marketing landscape, AI plays a pivotal role across the entire customer journey. From targeting potential customers during the consideration phase to guiding their search, AI enhances marketing activities. For instance, online furniture retailer Wayfair employs AI to identify and engage with persuadable customers based on their browsing history. Additionally, AI-powered bots, such as those offered by Vee24, help marketers comprehend customer needs, boost engagement, and facilitate seamless transitions to human sales agents when necessary.

AI also streamlines sales processes by utilizing detailed individual data, including real-time geolocation, to craft highly personalized product or service offers. Moreover, AI assists in upselling and cross-selling, reducing cart abandonment rates. For example, AI bots can provide testimonials to encourage purchases, significantly increasing conversion rates.

After the sale, AI-enabled service agents from firms like Amelia and Interactions are available round-the-clock to handle customer requests efficiently. They excel in handling simple queries and can escalate more complex issues to human agents, all while providing valuable insights to enhance customer satisfaction.

Understanding the Framework

Marketing AI can be classified based on two key dimensions: intelligence level and integration into existing systems. While some technologies, such as chatbots or recommendation engines, can straddle these categories, their classification depends on how they are implemented within specific applications. Framework

1. Intelligence Level:

   – Task Automation: These applications handle repetitive, structured tasks that require relatively low levels of intelligence. They follow predefined rules or execute a predetermined sequence of operations based on input.

   – Machine Learning: These algorithms, trained with extensive data, make complex predictions and decisions. They can recognize patterns, segment customers, and anticipate responses to various initiatives.

2. Integration:

   – Stand-alone Applications: These are distinct AI programs separate from primary customer-facing channels or employee-facing platforms.

   – Integrated Applications: These AI applications are embedded within existing systems, often less visible to customers and employees.

This classification results in four quadrants within our framework: stand-alone machine-learning apps, integrated machine-learning apps, stand-alone task-automation apps, and integrated task-automation apps.

A Step-by-Step Approach

We believe that the greatest value in marketing AI will be derived from integrated machine-learning applications. However, rule-based task-automation systems can also enhance structured processes and yield reasonable returns. It’s worth noting that task automation is increasingly combined with machine learning, creating a hybrid approach that straddles multiple quadrants.

While stand-alone applications still have their place, we recommend a gradual transition toward integrating AI within existing marketing systems. Many companies are already heading in this direction, with 74% of global AI executives agreeing that AI will be integrated into all enterprise applications within three years.

Getting Started

For organizations with limited AI experience, a practical approach is to develop or acquire simple rule-based applications. Many follow a “crawl-walk-run” strategy, starting with stand-alone non-customer-facing task-automation apps. As they gain expertise and access to more data, they can progress to machine learning, leveraging data sources like internal transactions and external suppliers to fuel AI applications.

Challenges and Risks

Implementing AI applications, even the simplest ones, can present challenges. Careful integration of AI into workflows is crucial to avoid potential pitfalls, ensuring AI complements human skills rather than causing disruptions. Furthermore, as AI becomes more sophisticated and integrated, considerations like third-party platform integration and customer privacy and security come to the forefront.

In Conclusion

Marketing AI holds immense promise, but it’s essential for CMOs to have realistic expectations about its current capabilities. While it can enhance various aspects of marketing, it cannot replace the entire marketing function. Nevertheless, AI’s capabilities are rapidly evolving, and it’s a journey that will unfold over decades. To seize the opportunities presented by AI in marketing, organizations must invest in building AI capabilities and address potential risks. By developing a strategic approach today, CMOs can capitalize on AI’s current functionality and its promising future.”