Digital Marketing and Social Media Strategy – Leveraging Analytics and Artificial Intelligence

Leonard N. Stern School of Business

Leonard N. Stern School of Business


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Who should attend

Although there are no formal education or background requirements, this course is designed for executives who meet the criteria below. While we strongly encourage global participation, please note that all courses are taught in English. Proficiency in written and spoken English is required.

  • Years of Experience – Designed for professionals with 5+ years of work experience
  • Job Functions – Ideal for individuals interested in a high-level understanding of digital marketing from a strategic perspective (B2C space as well as B2B space)
  • Prerequisites – Intended for professionals with a basic familiarity with digital media strategy

About the course

The emergence of the Internet has drastically changed various aspects of an organization’s operations. Some traditional marketing strategies are now completely outdated, others have been deeply transformed, and new digital marketing strategies are continuously emerging based on the unprecedented access to vast amounts of information about products, firms, and consumer behavior.

In this program, we will examine best-practices related to the business use of social media and digital marketing. While there will be sufficient attention given to top level strategy used by companies adopting social media and digital marketing, the course will also focus on digital analytics oriented tools: how to make organizations more intelligent in how they conduct business in the digital age. Measurement plays a big role in this space. Thriving in such an environment requires the understanding and leveraging of the major mega-trends of today such as Digital Attribution Social Listening, Big Data and the Social-Graph for external and internal business innovation. Based on the composition of the participants, we will discuss how specific firms can create a comprehensive social media and digital marketing plan and execute it.

Program Takeaways

  • Artificial Intelligence - Understand how artificial intelligence and machine learning have changed the digital landscape, and use these tools to enhance your marketing strategies and better understand your customers
  • Analytical Insights - Use analytical insights to develop compelling integrated marketing campaigns, build your customer base and maximize their value for your business
  • Innovation & Best Practices - Learn how businesses can tap into open innovation opportunities and best practices in social media and digital marketing from multiple perspectives and in multiple industries



Session 1: 4Ps 2.0. - A Framework for Digital Marketing in the Age of AI

  • Changes in the Consumer Decision Journey in the digital age and its implications on the classic Four Ps of marketing
  • Discuss the disruptive role of new “Four P’s 2.0” of digital marketing – participation, phones, prediction and platform
  • Action Learning Activity: Analyze your company’s consumer decision journey, how it has changed, and what opportunities and challenges does it provide

Session 2: Harnessing and Integrating Digital Media Channels

  • Branded vs. generic search
  • Getting top ranking in organic search results and Search Engine Optimization (SEO)
  • Display Advertising and Online and offline advertising
  • Use cases of integrated digital media campaigns

Day 2

Session 3: Exploring Digital Marketing and Attribution Analysis

  • Strategic search engine marketing, web analytics, and digital advertising models.
    • New metrics (audience/channel specific/universal engagement metrics) for evaluating success of digital marketing campaigns.
    • Team Session: Hands-on case analysis on how to leverage search advertising in generating customer sales in a cost-effective manner.
  • A framework for digital marketing attribution.
    • Digital attribution across different media and different devices.
    • Hands on data analyses of multi-channel budget allocation in digital marketing.

Session 4: Social Media for Awareness and Conversions

  • Offense and Defense for your brand using social media
  • Targeting niche audiences for awareness and conversion
  • Influencer marketing best practices
  • Power of authentic social communities
  • How things go viral?

Day 3

Session 5: Deep Dive into Social Listening and Big Data Analytics

  • Social listening and text analytics
    • Sentiment analyses and opinion mining of user-generated content.
    • Generating marketing intelligence from mining social media content.
  • Methods for measuring the true impact of social networks and word-of-mouth
    • Executing statistical tools, experimental testing and randomized trials in the digital world.

Session 6: Painting the Mobile Landscape: Mobile Marketing Strategies and Analytics

  • Mobile internet, mobile apps, mobile ads, mobile commerce
    • Key metrics and analytics in quantifying the value of mobile marketing.
    • Mobile and tablet consumption in consumer path to purchase.
    • Team session: Value of mobile apps for brands, marketers and firms.
    • Case analyses of mobile marketing and mobile advertising adoption.

Day 4

Session 7: Promotions Using Social Advocacy, Engagement and Analytics

  • The Freemium pricing model and monetizing free users
  • Ingredients of a successful referral marketing program
  • Optimizing call-to-action, incentive split and receiver messaging for referrals

Session 8: Next Gen Marketing Using Machine Learning and AI

  • Machine Learning for Customer Segmentation
    • Leverage popular clustering algorithms for segmenting customers in a data-driven manner
    • Using clustering for product mix planning
    • Uses cases from various industries ranging from retail to travel to services
  • Recommendation engine design and applications
    • Understand the power of algorithms used by Amazon and Netflix to recommend products
    • Discover co-purchase patterns and recommend products to upsell and cross-sell
    • Use cases from variety of industries
  • Predictive modeling using machine learning and AI
    • Understand the framework and key metrics of predictive modeling
    • Distinguish between good and not-so-good metrics
    • Gain intuition around popular ML/AI techniques such as decision trees, random forests and neural networks for marketing applications
    • Optimizing direct marketing campaigns based on historical data
    • Uses cases from a variety of domains

Day 5

Session 9: Action Learning Activity

  • Revisit your consumer decision journey from Day 1.
  • Describe how you will use different types of digital and social media, and newer channels such as mobile and Augmented Reality for your business most effectively – Think Big!

Session 10: Toolkits and Lessons Learned

  • Presentations of newer consumer journeys
  • Toolkit: A set of digital tools to continue your learning after the Program
  • Concluding thoughts and “hands-on” discussion on implementing social media and digital marketing
  • Lessons learned and next steps for action


Anindya Ghose

Anindya Ghose is a Professor of Information, Operations and Management Sciences and a Professor of Marketing at New York University's Leonard N. Stern School of Business. He is the Director of the Center for Business Analytics at NYU Stern, and the co-Chair of the NYU-AIG Partnership on Innovatio...

Ravi Bapna

Dr. Ravi Bapna is the Curtis L. Carlson Chair in Business Analytics and Information Systems, Associate Dean for Executive Education and the Academic Director of the Carlson Analytics Lab at the University of Minnesota’s Carlson School of Management. Bapna''s expertise lies in helping companies le...

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Digital Marketing and Social Media Strategy – Leveraging Analytics and Artificial Intelligence at Leonard N. Stern School of Business

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Coursalytics is an independent platform to find, compare, and book executive courses. Coursalytics is not endorsed by, sponsored by, or otherwise affiliated with any business school or university.

Full disclaimer.

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