- £35 Cost per lead.
- £145 cost per application.
- 6,187% return on investment.
A small university with three unique main campuses as well as learning centres across the UK. With unique campuses, the university also had a unique student profile.
Their problem? They didn’t have insight on exactly what that student profile looked like. This also meant they didn’t know what messaging to engage them with, nor what social channels were best to target them on.
That’s where we came in. We used our three-stage process to develop students’ profiles building profile dashboards, developing creative and amplifying content.
Building profiles with past and present applications data
Our data consultants worked closely with the marketing team in order to find the appropriate data to build the segmentation. Then, utilizing Alteryx and Tableau server and client software, we built a dataset of past year’s application data and combined with a live data pipeline for current applications to be included in the visualisation in real-time. With the live data dashboards, external agencies as well as internal stakeholders at the university could segment and build profiles on the fly, per campus, per area of study, programme and location. Using their own application data to build messaging and deliver relevant and targeted content.
£35 cost per lead.
£145 cost per application.
6,187% return on investment.
Amplifying content to the University audience
Once we had a clear picture of the university audience and the perfect creative for them, it was time to widen our net. We used clever media campaigns to reach new audience personas and drive them to key conversion points on the site. Our approach was to take a data-led approach to the university’s campaign to ensure we were targeting the right person no matter what channel they were using. We used multiple datapoints to refine the campaign including:
- Historic data: our data profiling dashboard provided us with the perfect foundation for our initial audience creation
- Emotive data profiling: we also analysed emotive profiling data to understand the personality profile of their students
- Look-a-like data: we utilised look-a-like data from their website to identify and target students who were most likely to apply to the university
- Remarketing data: we used clever remarketing technology to target audiences who had visited the site with personalised messaging for them
- Media data: with our audience personas in mind, we used research tools like Alexa and Google Trends to identify the perfect media mix for the university.