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Transforming applicant engagement using AI
Predict. Engage. Convert. Repeat.
Generative AI is clearly getting a lot of attention at the moment – but other applications of AI, which have been around for some time, continue to be powerful tools for marketers to positively impact engagement with prospects and applicants.
Oracle's recent survey, spanning the UK, US, India, and Canada, discovered that marketing professionals trust the use of AI in determining conversion probabilities as one of the top five most trusted AI-based tasks. So, are you capitalising on this opportunity yet, which is already being used by so many outside of the higher education sector?

Looking back to 2015, when we first started using AI and machine learning techniques for propensity modelling at SMRS, it's incredible to see the journey we've been on. Our vision was always clear: to give our university clients a detailed understanding of their market opportunities and a keen awareness of the investment and resources required for effective engagement.
We built a process that involved examining millions of data points through our unique data modelling techniques. The result was extraordinary - we could identify a clear set of, targetable audience segments, which were bespoke and different for each provider we worked with. This approach provided our clients with the clarity they needed. Whether they aimed to attract higher quality students, encourage more diverse cohorts, or increase enrolment volumes with minimal investment, we could help illuminate the best path forward.
Seeing the transformation of strategies across numerous UK universities has been one of the most rewarding aspects of this work. We've seen an increase in click-through rates of around 40% and an incredible 80% reduction in Cost per Acquisition (CPA). But, to me, the real success lies in the improved acquisition journeys we've been able to craft for prospective students, and it’s all been driven by AI – enabling us to do things we never could without the application of technology.
Today, in a world where budgets are tighter than ever, the value of propensity modelling is even more crucial. Universities need practical and actionable insights to make the most of their squeezed resources. And I truly believe that's exactly what our approach to propensity modelling provides. By understanding and leveraging audience data, we can help universities create more personalised, engaging, and effective recruitment strategies.
As we look to the future, I'm confident that the importance of propensity modelling will only continue to grow, as will trust of these activities by using AI. Universities will continue to need tools and strategies that deliver maximum impact with minimum investment. And we'll be there, ready to provide the insights and efficiencies that they need to meet their objectives.
If you're interested in how to use AI to calculate propensity and help your university navigate today's challenges, I'd love to chat.
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