AI in Marketing 2: From Insight to Impact: Harnessing AI for Enhanced Value Delivery

Importance of Customer Value in the Realm of Marketing:

Every business operates as a value delivery system, with the primary goal of providing customer value while ensuring profitability.

The value delivery process comprises three crucial phases:

• Choosing the value
• Providing the value
• Communicating the value

Sustainable success is achieved by optimizing these phases and delivering superior value to well-informed buyers.

"Choosing the Value" is the crux of strategic marketing, encompassing Segmentation, Targeting, and Positioning.

The subsequent phases, "Providing and Communicating the Value," fall under tactical marketing, involving the 4Ps or marketing mix:

• Product
• Price
• Place
• Promotion.

Strategic Marketing and Tactical Marketing collectively form the foundation of Marketing Strategy.

Key tasks in each phase of the value delivery process include

• Customer Segmentation
• Market Selection/Focus
• Value Positioning
• Product Development
• Service Development
• Pricing
• Sourcing-Making
• Distributing-Servicing
• Sales Force
• Sales Promotion
• Advertising.

Value Creation and Delivery Process:

The value delivery process can be optimized in numerous ways, determining how a company sources, creates, sells, communicates, and delivers value.

In recent years, artificial intelligence has emerged as a pivotal source of value creation and delivery, disrupting traditional business processes.

The shift towards AI-driven value delivery is evident in the rise of firms relying on algorithms over conventional processes operated by human workers or managers.

AI and algorithms play a crucial role in understanding, attracting, and retaining customers by providing surplus value, personalized experiences, and real-time feedback.

AI contributes to the efficiency of the value chain through operations optimization. Inefficient operations can impede the movement of products through the value chain, hindering successful purchases.

AI applications, including AI-related C&SI services, computer vision, deep learning, Edge AI, intelligent applications, machine learning robotic, process automation, and virtual assistants, enhance operations efficiency and effectiveness.

• Streamlining operational processes through AI applications shortens the value chain, as demonstrated by examples like JD.com, where the introduction of AI led to 92% of orders being delivered on the same or next day.
• Nike's use of augmented intelligence for designing customized shoes showcases how optimizing operations with AI can lead to faster end-to-end processes, offering unexpected benefits such as increased operational efficiency and agility.

Implementing AI in operations and the value delivery chain should be driven by the desire to achieve these improvements.

The Rise of Ant Financial Services Group:

In a remarkably short span of just five years after its inception in 2014, Ant Financial Services Group surpassed the one billion consumer mark in 2019, showcasing an unprecedented rise in its user base.

Ant Financial leverages the power of artificial intelligence and data harnessed from Alipay, its primary mobile payments platform, to orchestrate a diverse array of business ventures. The scope of Ant Financials’ operations is extensive, encompassing consumer lending, money market funds, wealth management, health insurance, and even an innovative online game designed to encourage individuals to reduce their carbon footprints.

Despite having less than one-tenth of the workforce employed by the largest U.S. banks, Ant Financial serves over ten times the number of customers, a testament to the efficiency and scalability achieved through AI integration.

What sets Ant Financial apart is its departure from traditional models – there are no managers approving loans, no personnel offering financial advice, and no representatives authorizing medical expenses.

In the realm of Ant Financial, every function is orchestrated by artificial intelligence.

Unlike the operational constraints faced by traditional banks, investment institutions, and insurance companies, Ant Financial operates without such limitations.

This lack of constraints empowers the company to compete in unprecedented ways, fostering unbridled growth and influence across a diverse range of industries.

The rise of Ant Financial exemplifies how the fusion of artificial intelligence, data analytics, and innovative business models can redefine the landscape of financial services, allowing for unparalleled scalability and impact.

Value Proposition and Value Chain Dynamics:

The value proposition serves as a strategic component that directs attention outward, focusing on customers and the demand side of the business. In contrast, the value chain is an internal lens that delves into the intricacies of operations.

At its core, strategy is integrative, aiming to bring together the demand and supply sides of the business. The value proposition addresses customer needs and desires, while the value chain concentrates on optimizing internal processes for efficiency and effectiveness.

Value propositions rooted in addressing specific needs have a broad appeal, often transcending traditional demographic segmentation. This approach recognizes the diverse nature of customers and their varied preferences.

Understanding the Value Chain:

The value chain serves as a powerful tool for identifying critical activities that contribute both value and costs within a specific business. It encompasses primary activities directly tied to the creation and delivery of the product or service, as well as support activities that play a vital role in the overall business operations.

These primary and support activities collectively contribute to designing, producing, marketing, delivering, and supporting the product. By scrutinizing each step of the value chain, businesses can pinpoint areas where value is generated and costs are incurred.

AI's Role in Enhancing the Value Chain:

The value chain intricately weaves together a multitude of business activities, forming a complex network that involves various stakeholders. This dynamic process kicks off with the sourcing of raw materials from suppliers and culminates when the finished product reaches the end customer.

Within this intricate framework, artificial intelligence emerges as a pivotal tool capable of enhancing efficiency and driving cost reductions. The multifaceted nature of the value chain makes it an ideal environment for the application of AI technologies.

Businesses can harness the power of AI to make informed and optimized decisions across different facets of the value chain. From judicious material procurement to efficient inventory management, and from streamlined production plans to enhanced distribution strategies, AI contributes to smarter decision-making.

A compelling illustration of AI's impact on the value chain is demonstrated by the United States Cold Storage, a prominent player in the cold chain industry. Recognizing the potential benefits, the company implemented an automated appointment scheduler. This innovative tool accurately predicts the arrival time of carriers and estimates the time required for servicing, all while efficiently scheduling appointments.

The incorporation of AI in the value chain not only streamlines processes but also empowers businesses to navigate the complexities of modern supply chains with agility and precision. The case of United States Cold Storage exemplifies how embracing AI technologies can lead to tangible improvements in operational efficiency, ultimately contributing to enhanced customer satisfaction and sustained competitiveness.

Value Chain and AI:

The firm’s task is to examine its costs and performance in each value-creating activity and look for ways to improve. The rise of AI technologies is generating novel opportunities for companies in each value-creating activity to create additional customer value.

To capture the full promise of AI, companies must reimagine their business models and the way work gets done. The core business processes are highly relevant in a firm’s decision to incorporate AI in strategic decision-making process.

When incorporating AI, the firm should identify a crucial business process (also referred as domain) and rethink it completely i.e., ? Introducing changes throughout an entire core process, journey, or function which will lead to a major improvement in performance that isolated local applications simply cannot match.

It also will enable each AI initiative to build off from the previous one by, for example-

• Reusing data or advancing capabilities for a common set of stakeholders and trigger an organic cycle of change within domains and, ultimately, build momentum for the use of AI throughout the larger organization as business leaders and employees see it work.

Moreover, this approach promotes a mindset of continuous improvement in the workforce, which is crucial because AI technology is advancing rapidly, requiring organizations to think of AI transformations as ongoing rather than one-time efforts.

Value Chain Optimization through AI:

The imperative for any firm lies in scrutinizing its costs and performance across each value-creating activity, seeking avenues for improvement at every turn. The advent of AI technologies presents a transformative landscape, offering companies unprecedented opportunities to augment customer value across diverse value-creating activities.

Realizing the full potential of AI necessitates a fundamental reimagining of business models and workflow methodologies. This extends to core business processes, which play a pivotal role in a firm's strategic decision-making process.

When integrating AI, a strategic approach involves identifying a critical business process, or domain, and undertaking a comprehensive rethinking. This entails introducing holistic changes throughout an entire core process, journey, or function, resulting in substantial performance improvements that surpass the capabilities of isolated local applications.

Crucially, such an approach allows each AI initiative to build upon the successes of its predecessors. This may involve reusing data or advancing capabilities for a shared set of stakeholders, triggering an organic cycle of change within domains. This, in turn, cultivates momentum for the broader adoption of AI throughout the organization, as business leaders and employees witness its effectiveness.

Beyond the immediate gains, this methodology fosters a mindset of continuous improvement within the workforce. Given the rapid advancement of AI technology, organizations need to view AI transformations as ongoing endeavors rather than one-time initiatives.

AI-Driven Value Creation in Various Phases of the Value Chain:

Communication:

• AI enhances communication processes by optimizing speed and precision. Automated chatbots, for instance, streamline customer interactions, providing quick and accurate responses.

Customer Insights:

• AI empowers businesses to derive valuable insights from customer data, improving the precision of targeted marketing and personalized customer experiences.

Design:

• In the design phase, AI contributes to product innovation by analyzing data from various sources. For example, in the fashion industry, AI can predict styles that resonate with customers, as demonstrated by Stitch Fix's use of AI for personalized styling services.

Manufacturing:

• AI automation in manufacturing processes improves efficiency by handling repetitive tasks. Abundant Robotics, for instance, employs AI-powered automated machines for apple harvesting, reducing the need for manual labor in physically demanding tasks.

Delivery:

• AI plays a crucial role in optimizing delivery processes, ensuring accuracy and speed. Route optimization algorithms, for instance, enable more efficient and timely deliveries, reducing costs and enhancing customer satisfaction.

Retail:

• AI enhances the retail phase by improving sales processes. Salesforce Einstein, for example, prioritizes leads for salespersons, focusing attention on high-value prospects and increasing the overall efficiency of the sales cycle.

Key Improvements Enabled by AI:

Process Efficiency:

• AI-driven automation streamlines repetitive processes, freeing up human resources for more complex and value-added tasks. Abundant Robotics' automated apple harvesting exemplifies the efficiency gains achieved through AI.

Process Enhancement:

• AI enhances existing processes by providing intelligent insights. Salesforce Einstein's lead prioritization, for instance, improves outcomes by allowing sales teams to focus on high-potential leads, optimizing their efforts and resource allocation.

Product or Service Innovation:

• AI enables the creation of innovative products and services by leveraging data analytics. Stitch Fix's use of AI in product design showcases how data-driven insights can inform the development of new offerings, meeting evolving customer preferences and demands.

Functional Areas of AI Deployment:

Companies are actively experimenting with and adopting AI technologies throughout their value chains, with a notable focus on non-core support functions.

According to a survey of 3,000 professionals, more than 25 percent reported AI adoption in key support functions, including IT, customer service, marketing, sales, and finance and accounting.

Contrary to the entry patterns of other digital technologies, companies are increasingly investing in AI for core functions. Noteworthy examples include Stitch Fix's deployment of deep learning for understanding user clothing styles and machine learning for stylist-user matching.

Industry Adoption Levels:

AI's role in value chains varies across industries. High-tech and telecom sectors lead in AI implementation, with over 30 percent adoption, while construction lags at 15 percent, according to a McKinsey report.

Opportunities for Traditional Industries:

• Jim Sinai, VP of Product Marketing for Salesforce Einstein, highlights the potential for rapid AI deployment and value addition in traditional industries like manufacturing, retail, and healthcare. Legacy systems in these sectors provide a foundation for efficient AI integration.
• Retail stands in the middle range of AI adoption and investment growth, showcasing its ongoing exploration of AI applications in the value chain.

Value Chain and AI Integration:

AI finds application in corporate support functions, customer predictions, and content effectiveness within the value chain.

Organizations aspiring to invest in key digital technologies, including cloud computing and AI, should focus on the IDEAS framework, comprising Intelligence, Data, Expertise, Architecture, and Strategy. This framework facilitates a comprehensive approach to navigating the evolving technology landscape.

In summary, the current state of AI adoption in value chains reveals a dynamic landscape with active exploration across various functions and industries. Traditional sectors have the potential to bridge the AI gap and capitalize on targeted applications for substantial return on investment. The IDEAS framework provides a structured approach for organizations looking to navigate and harness the full potential of AI in their value chains.

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