Learn how Uni Compare records student interactions, reduces duplicate activity, and helps universities see clearer, more meaningful lead data.

In this guide, we’ll cover:

This guide explains how Uni Compare records student interactions, how different lead types are handled, and how we help protect university dashboards from duplicate, spam-like, or unusually high-frequency activity.

Uni Compare tracks student engagement across university profiles, including website clicks, phone calls, prospectus orders, register interest actions, and enquiry forms.

Our aim is to help universities see genuine student intent clearly, while reducing duplicate activity caused by repeat clicks, accidental actions, or non-human behaviour.

Before we talk about lead types, it’s helpful to explain the different types of users who can make interactions on Uni Compare.

A logged-in user is a student who has created an account or signed in before completing an action. Because we can identify the student, some actions may be shown as leads in the university dashboard if the student chooses to share their details.

A guest user is a student who interacts with a university profile without being signed in. Guest users can still click through to a website, call a university, but their details are unable to be recorded, and therefore can now be shown as individual leads in the dashboard.

This means logged-in user activity can create lead records where the right information and permissions are provided, while guest activity is tracked as engagement rather than as a named student lead.

Each student interaction is recorded a lead type. Common lead types include:

Some lead types offer the student the option to share their details before they are shown as leads in the university dashboard.

Where a user does not share their details, or where an action is treated as a moderate repetitive interaction, the activity may still be tracked internally but not shown as a new lead.

In this article, we’ll specifically focus on Clearing Visit Website Click and Phone Call lead types for our flagship Clearing product.

If an institution as a Clearing Profile, with Student Data Unlock they may be able to turn turn high-intent student interactions into contactable leads.

When a student clicks through to your website, calls your institution, or completes selected actions from your Uni Compare profile, they will be given the option to share their details with you.

If they choose to share their data, the interaction can appear as a lead in your dashboard, giving your team a clearer view of interested students and helping you follow up sooner.

Students remain in control of whether their details are shared, while universities get better visibility of genuine student intent.

Often students may engage with a burst of activity and may interact with the same university more than once. This can happen for genuine reasons, especially during Clearing and Results Day, but it can also create duplicate lead noise if the same action is repeated too often

To keep reporting clear, Uni Compare moderately limits how often the same logged-in user can create repeat leads for the same university.

The limit only applies where the same student repeats the same type of activity for the same university, again and again where we may no longer deem it appropriate to show this data.

Website clicks that convert into leads from Clearing Student Data Unlock are limited to reduce duplicate lead noise. For logged-in users, limitations appear with website-click leads per university.

If the same student clicks through to the same university again on the same day, we may treat this repeated action as a guest interaction rather than a new lead, even if they choose to share their details again.

This helps prevent one student from appearing as multiple website-click leads for the same university on the same day. The limit resets within our designated attribution period. This will not affect any UTM or marketing tracking but will serve as a way to protect exports, and dashboard data for our institutions.

Phone calls are handled more flexibly because they are usually a stronger signal of intent, and happen in a bursts across a shorter time period.

During Clearing, and especially around Results Day, a student may call the same university more than once for genuine reasons. They may be checking course availability, following up on a previous conversation, or trying to speak to an admissions team during a busy period.

For logged-in users, calls can be counted as leads, subject to sensible repeat limits.

A single logged-in user can be counted for as multiple calls per university happen within a designated period, with short repeat intervals restricted to reduce spam-like behaviour.

This keeps genuine call intent visible, while preventing excessive repeat activity from distorting the data.

Guest users can still interact with university profiles. Guest website clicks and guest calls are tracked using reliable third-party tracking, but they are not shown as individual student leads in the university dashboard.

This is because the student has not shared their details and is not logged in, meaning we cannot identify them as a named user. Instead, they are treated as anonymous visitors who have completed a meaningful action, such as clicking through to a website or making a phone call.

Duplicate protection helps make dashboard reporting clearer and more useful.

It is designed to reduce:

At the same time, Uni Compare continues to allow genuine student activity through, especially where a student is comparing universities or making high-intent calls during Clearing.

Uni Compare’s lead rules are designed to give universities a clearer view of genuine student intent, whilst protecting the platfrom from harmful actions.

We want students to be able to engage naturally with universities during Clearing, whether they are clicking through to a website, making a call, or comparing different institutions. At the same time, we apply sensible duplicate protection so dashboards are not inflated by repeated, accidental, spam-like, or non-human activity.

Where repeat activity takes place, Uni Compare may continue to track the interaction internally while limiting whether it appears as a new lead in the university dashboard.

This helps keep lead data cleaner, more useful, and easier for teams to act on.

If you would like to find out more, please contact your Client Success representative.