AI in Marketing and Value Delivery

Introduction to AI in Marketing

  • Definition and Overview: AI in marketing refers to the application of artificial intelligence technologies and algorithms to enhance marketing processes and strategies.
  • Courses Involved:
    • Modules covering basics of AI, AI algorithms, marketing strategies, AI's application in marketing research, and the ethics of using AI in marketing.

Customer Value Delivery Process

  • Business as a Value Delivery System: The main aim of businesses is to provide customer value while ensuring profitability.

  • Phases of Value Delivery:

    • Choosing the Value: Involves strategic marketing, including segmentation, targeting, and positioning.
    • Providing the Value: Tactical marketing—including product development, pricing, sourcing, and servicing.
    • Communicating the Value: Marketing mix (4Ps: Product, Price, Place, Promotion) is utilized to inform customers about value offerings.

  • Strategic Marketing vs Tactical Marketing:

    • Strategic marketing emphasizes long-term business goals and customer needs.
    • Tactical marketing focuses on immediate implementation of marketing strategies.

The Role of AI in Value Delivery

  • Optimization: Utilizing AI to enhance the efficiency of value delivery processes, including sourcing, selling, and serving customers.
  • Algorithm-Driven Value: New business models rely on algorithms for value delivery rather than traditional methods.
  • AI Applications:
    • AI services, machine learning, computer vision, and robotics are employed for operational optimization, improving speed and efficiency.
  • Case Studies:
    • JD.com: Uses AI for fast order processing, achieving high delivery rates.
    • Nike: Implements augmented intelligence for quick custom shoe design, from concept to delivery in two weeks.

AI in the Value Chain

  • Definition of Value Chain: A tool for mapping the key activities within a business that add value and incur costs.
  • AI's Impact on Efficiency: AI enhances decision-making regarding material purchases, production planning, and inventory management, decreasing expenses and improving productivity.
  • Example Impact: The United States Cold Storage company benefits from automated scheduling systems powered by AI, streamlining supply chain processes.

AI-Driven Value Creation Forms

  • Form Categories:
    • Process Efficiency: Automation of repetitive tasks (e.g., Abundant Robotics uses AI for apple harvesting).
    • Process Enhancement: AI tools prioritize tasks and leads for better outcomes (e.g., Salesforce Einstein optimizes lead management).
    • Product/Service Innovation: AI aids in developing new offerings based on consumer data (e.g., Stitch Fix uses AI for predicting fashion trends).

Current State of AI Adoption

  • Trends: AI is mainly adopted in non-critical support roles (e.g., IT, customer service, marketing), but core functions are also gradually integrating AI solutions.
  • Industry Variance: Adoption rates vary by industry, with tech sectors leading (over 30%) compared to lower rates in industries like construction.
  • Future Risks and Opportunities: Companies may face an escalating gap in AI capabilities between industries if traditional sectors do not invest adequately in AI.

Conclusion

  • Summary of AI's Role in Marketing: AI is crucial in enhancing customer value through efficient processes, innovative products, and strategic communication.

  • Implementation and Adoption Levels: Organizations should focus on intelligent strategies that incorporate AI across the value chain and anticipate ongoing advancements.

  • References:

    • Roger, K., Steven, H. & William, R. (2013). Marketing: The Core. McGraw-Hill Irwin, Fifth Edition.
    • Kotler, P., & Keller, K. L. (2021). Marketing Management. England: Pearson, Sixteenth Global Edition.
    • Kurtz, D. L., & Boone, L. E. (2012). Principles of Contemporary Marketing. South-Western, Fifteenth Edition.