Case Study

NYU Tandon

By implementing an advanced feedback loop between first party data and media campaign machine learning capabilities, we increased lead volume and quality within one enrollment cycle.


The Challenge

NYU Tandon School of Engineering needed to drive well-qualified leads for their new online programs aimed at attracting students with STEM and non-STEM experience and driving enrollment without increasing their existing paid media investment.

What We Did

  • Paid Media Strategy
  • Paid Media Execution

The Approach

To capture additional impression share and establish Tandon as the preeminent institution for students seeking STEM-specific online degrees and executive and professional education programs, we worked with the Tandon team to implement Offline Conversion Tracking. This allowed us to create a feedback loop between the Google Ads platform and Tandon’s Salesforce CRM system and build an audience targeting profile from existing leads data. With access to this information, the media platform “chooses” which queries it will bid on within our campaign parameters that are most likely to not only visit the landing page and complete a request for information (RFI) form but those users who are likely to convert to “application started” status. This connection also allows us to rely on historical CRM data, rather than campaign pixels that have a shelf life of 30 days or less, which means performance attribution is more accurate over the long term.

While setting up offline conversion tracking, we were also optimizing and streamlining tactics to focus on the highest-converting channels.

The Impact

After implementing offline conversion tracking and streamlining campaign focus, along with ongoing campaign monitoring and keyword optimizations, this approach drove significant improvement.


increase in RFI form submissions


increase in application start rate (versus the previous enrollment period)