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Data-led recruitment

How we used data, insight and machine learning to target and boost Anglia Ruskin’s student applications

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At a glance

Data and insight driven recruitment

Widening diversity with machine learning

Boosting engagement with chatbots

Anglia Ruskin needed a boost

Anglia Ruskin’s student recruitment was in decline. They needed a campaign that would boost applications and broaden their target audience beyond the East of England, attracting a wider range of potential students.

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We made data-driven decisions

We used propensity modelling - detailed machine learning analysis - to understand and identify ARU’s target audience. We used this data to develop detailed personas, each defined by what motivates them to study. We could then tailor our messaging and channel strategy to target each of these personas.

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A unique way to boost interactions

We integrated chatbot technology into the digital ads. This proved far more effective than traditional banner ads, driving 1,400 interactions, 11% of which continued to the University website. We also targeted chats at under-represented groups, supporting the University’s D&I objectives.

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Optimising the results

We constantly monitored the campaign, providing end-to-end insights from first click to application. This allowed us to continually optimise activity, using the latest data to deliver better results, including:

  • Attracting 34% more applications, with all faculties seeing an increase

  • Increasing the diversity of applications

  • Increasing postgraduate applications by 50%

Our combination of data-driven analysis and expert media targeting helped ARU achieve sector-leading growth.

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