Study your data

Learn how your education institution can benefit from modern and intelligent insights.

Like any other organisation, education institutes benefit from understanding their customers, i.e. students, better. Today, modern analytics tools can offer sophisticated options for analysing and interpreting data from any point of the student lifecycle, but where does one start?

This post will look at how analytics can help your education institute at different phases of the student’s journey.



1. Capturing new leads

Your organisation probably wants to entice new students to enrol for your upcoming courses. The marketing team has a dedicated budget for marketing campaigns on various channels. After running the campaign, they want to see your sales pipeline’s impact on CRM systems such as Salesforce.

When connecting marketing analytics and other data sources with the CRM system, your marketing team (and the wider organisation) can see an overview of the lead funnel through the initial contact to an actual sale. The marketing team can compare different marketing channels against each other and, if taking advantage of advanced analytics, even check scenarios and hypotheses for various options. They can also form similar target groups to the students in the most successful campaigns.

This type of insight enables data-driven marketing: marketers can calculate the ROI of their marketing activities. They can dedicate their budget and resources to the most successful activities.

2. Recruiting

This team is actively working on recruiting students online and at different events. To help their efforts, you can score applications and build up a visualisation, for example, how well you did with your recruitment campaign (similar to marketing). You can even trigger actions here, so, say you realise that a specific group or region lacks applications, you can trigger a rule to book appointments with local universities.

Advanced analysis and predictions can also help with forecasting. When you have all the required data from past recruitment cases, you can see expected results or what if-scenarios, which would give you more enrollments.

3. Student enrollment

Dashboards and data visualisation can help analyse the performance of the student enrollment process. You can show students applying, student gathering, interviews, financial validation, etc. The visual workflow is beneficial as you can see where your bottlenecks are. For example, why are students saying yes but not signing? Do they have a problem with money? You can then plan what kind of support and actions you could take to support them.

4. Courses

Are you sometimes wondering how well you are doing with your courses? Reducing student churn is essential in controlling drop-off rates.

Similar to recruitment, but based on the faculty and the teachers’ performance, you can see how satisfied students are with different reports and dashboards. That will allow you to understand which teacher is most engaging. You can see where the dropouts have happened the most, with which teacher, and can think about actions to prevent students from dropping off.

Interestingly, you can see what students who drop out look like, so you can flag them early so the faculty can reach out to them. Also, when a student with similar background appears, you can flag it to the appropriate person and support them early.

5. Student engagement

Student engagement is essential for modern universities. With visualised dashboards within Service Cloud you can see all the touch points a student has had with you. You can follow all courses they have completed, their financial situation, all information about the previous student contacts with the education institute, etc. You have everything in one place, and the view is also customisable for specific agents to get insights about your students at the right time and context.

You can also deflect cases to chatbots. Let’s say you find difficulties in knowing which case should be handled by a bot or agent. You can define rules on which cases the system should take directly to an agent. For example, if the model says it’s 90% sure that directing the student to a webpage will solve this case by going to the web page, it saves the agents’ time tremendously.

Furthermore, you can leverage the information you already have available to attend to some of your student requests. For example, the bots can guide the student to course information already available on your website. As a result, you can get cost savings by reducing the cases taken by your agents and the case handling time.

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