1. Strategic approach
In the first step, we defined the goals, data culture, and data maturity. An important preliminary process to make the team aware of the importance of a strong data culture and how they need to think about personalization to address it from a well-founded strategy. The focus was mainly on defining key personas: students looking for higher education, current staff, and others like high schools, job seekers, and companies. Among the student persona, we distinguished 2 types of students:
- generational students, graduating from high school
- lateral students, adult students who are reorienting or doing a side course and thus often study and work at the same time
An important finding to keep in mind is the significant rise of the second type, the lateral students. An audience to target with relevant personalization.
What is relevant personalization? To make sure visitors get the right information, relevant to their profile, content is personalized for their specific needs. If you’re labeled under the category ‘lateral student', the website is adjusted with information to your profile. For example, you’ll automatically get extra information on work-student facilities, exemptions, educational leave… that regular students don’t see.
2. Data magic for personalization
To set up the personalization for Odisee, no structured or historical data is needed. Via a script in Google TagManager, a tracking script is activated. The data capturing can now begin! There are 2 kinds of data:
- Device Data: screen size, location, language, touch, OS,...
- Behavioral data: pages, clicks, text selected, traffic source,...
Next to that, the AI algorithm of our platform, Dropsolid Experience Cloud, also detects behavioral patterns. Cool, right?!
The marketing team of Odisee can now build segments to use for personalization across all owned channels of Odisee based on the insights of the data they’re now collecting. These segments are either proposed by AI algorithms, on rules they define themselves via a user-friendly UI in the platform, or a combination of both.
The setup and the script can be set up in just one day, and the first AI learnings can be captured after only two weeks.
3. Take action
Step three is to take action, directly in the CMS and via Analytics. The real magic happens when the data is analyzed, conclusions are drawn, and actions are executed. The marketing team of Odisee can now start personalizing their content in their CMS (Drupal). The platform is designed this way so that it can be set up directly into Drupal without any barriers.
Next to that, the marketing team also gains insight into the behavior of key segments in Google Analytics and can, for example, build reports to track conversions and engagement by segment and compare it with the general visitor population.
To make it a bit concrete: the sign-up form for new students can be personalized on the website, so it’s more prominent for students. Yet, for staff and researchers, it won’t be the main eminent CTA.