Advanced Marketing Technologies in Higher Education 2023 Series…

Installment I: Revolutionizing Higher Education Marketing with Artificial Intelligence and Machine Learning

An important aspect of AI in higher education marketing is the ability to automate repetitive tasks, freeing up time and resources for more strategic initiatives. For example, AI-powered chatbots can handle routine inquiries from prospective students, such as answering questions about admission requirements, campus life, and financial aid. This allows marketing teams to focus their efforts on more high-level tasks, such as developing new marketing campaigns, analyzing data, and engaging with key stakeholders.

Assisting higher education institutions, AI better understands their target audiences through data analysis. By tracking student behavior across various touchpoints, such as social media, email, and web visits, AI algorithms can identify patterns and trends that provide valuable insights into what resonates with potential students. This data can be used to make informed decisions about future marketing campaigns, as well as to optimize existing ones for maximum impact. 

AI and automation can also play a role in creating more engaging and interactive experiences for students. For example, virtual reality and augmented reality technologies can be used to create immersive campus tours and open house events, allowing students to experience college or university in a way that was previously not possible. These types of experiences can be particularly impactful for students who are considering attending college far from home, as they can get a sense of what campus life is like without having to travel. 

The integration of AI and automation will dramatically transform the realm of higher education marketing in 2023. These innovative technologies will enable institutions to design more targeted and efficient marketing plans, leading to improved outcomes. By harnessing AI and automation, colleges and universities will have the opportunity to reach and engage with prospective students in fresh and impactful ways, ensuring their sustained success. To provide a concrete example of the benefits of these tactics below is a case study demonstrating the effective use of AI and machine learning in the education sector. 

Thomas Edison State University Case Study: A Successful Programmatic Digital Campaign with AI and Machine Learning Tactics 


Thomas Edison State University (TESU), a well-respected institution known for its undergraduate, graduate, nursing, and military programs, has set several goals for its marketing campaign. Hired by TESU to execute a comprehensive media plan, DCW Media is tasked with the following objectives:

  • Increase enrollment by attracting more prospective students to TESU’s programs. 
  • Enhance TESU’s online presence through effective digital marketing strategies. 
  • Reach a wider audience of potential students through targeted advertising campaigns. 
  • Enhance TESU’s reputation as a leading institution of higher learning by showcasing its unique programs and resources. across all marketing channels. 
  • Drive traffic to the TESU website and other online platforms through effective SEO and SEM strategies. 


DCW Media utilized a diversified approach to TESU’s marketing campaign, with a focus on program-specific communications and highly targeted placements. To enhance the effectiveness of the campaign, we leveraged various programmatic tactics, including display, mobile, video, audio, native, retargeting, and search engine marketing (SEM). In addition, to stay ahead of the curve, we employed the following AI and machine learning tactics: 

  • Predictive modeling to forecast campaign performance and adjust tactics in real-time. 
  • Automated bidding strategies to optimize ad spend and reach the right audience at the right time. 
  • Personalized and dynamic creative optimization to ensure each ad is tailored to the individual viewer. 
  • Natural language processing (NLP) to analyze and understand audience behavior, preferences, and sentiment. 
  • Machine learning algorithms to analyze and optimize campaigns for optimal performance. 
  • Data-driven insights and real-time reporting to make informed decisions and continuously improve campaign performance. 


The programmatic digital campaign executed by DCW Media for Thomas Edison State University was a remarkable success, achieving significant results for the institution. The use of AI and machine learning tactics played a critical role in the success of the campaign, enabling the agency to reduce waste, improve targeting, and maximize returns. The results of the campaign include: 

  • A 26% decrease in the cost per application year-over-year due to the automated bidding strategies and predictive modeling tactics used to optimize ad spend. 
  • A 35.2% increase in program-specific conversions year-over-year, highlighting the effectiveness of the program-specific communications and targeted placements. 
  • A 123% increase in total conversions year-over-year, reflecting the overall success of the comprehensive media plan. 
  • Improved targeting and audience engagement as a result of personalized and dynamic creative optimization, natural language processing (NLP) analysis, and machine learning algorithms used in the campaign. 
  • Data-driven insights and real-time reporting enabled the agency to make informed decisions, adjust tactics, and continuously improve campaign performance.

These results demonstrate the value of leveraging AI and machine learning in programmatic digital advertising and the impact it can have on driving conversions and engagement for institutions of higher learning. 

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