Shani Leibner

Hotjar, behavior analytics

Revealing accessibility gaps in user behavior

The Accessibility analysis page: a table of issues, each with the affected group, page, share of users and links to heatmaps and session replaysAccessibility analysis page

Turning accessibility challenges into actionable behavioral insights.

Role
UX research and UI design
Team
Team of 4 students
Type
Academic
Year
2025–26

What is Hotjar

Hotjar is a behavioral analytics platform. Product teams use it to see how people use a website, through heatmaps, session recordings and feedback.

The problem

  • Hotjar sees behavior, not who is left behind.It records how people use a site, but shows nothing about accessibility issues or their impact.
  • The gaps don't look like bugs.When interfaces ignore differences in ability, culture or digital literacy, some groups get unequal access, and nobody goes looking for it.

The solution

A centralized Accessibility Issues page that transforms accessibility into actionable user insights.

Research

Cultural gaps don't always surface as bugs. The challenge lies in how they are surfaced and communicated. This process helps identify which indicators are truly relevant and how to present them clearly.

We reviewed recurring usage patterns in Hotjar, with a strong emphasis on table based data exploration.

To validate and sharpen these insights, we spoke with Product Managers and Business Analysts to understand how issues are currently detected, interpreted, and prioritized across teams.

Findings

01

The problem is cultural, not only technical.

Design rule: Organize every gap by population. The affected group is the point of each issue.

02

Teams explore data mostly through tables.

Design rule: Build on what users already know. Heatmaps, recordings and tables, not a new tool to learn.

03

A number alone doesn't drive action.

Design rule: Measure against the average. Deviation from the overall average is the signal.

Guiding rules

  1. 01Builds on behavioral data and existing Hotjar tools (heatmaps, recordings, and flow data).
  2. 02Surfaces accessibility gaps by user populations.
  3. 03Identifies behavioral patterns in comparison to the overall average.

The flow

A product manager checks the site on Monday morning:

Notice

On the home dashboard, the Accessibility issue impact card shows how many new issues.

Home dashboard with the Accessibility issue impact cardHome dashboard with the impact card

Accessibility Dashboard

The table shows that users aged 60+ on desktop leave the homepage more than average, 7% of users.

Issues table showing users aged 60+ on desktop leaving the homepageIssues table

Heatmap and session replay

She opens the heatmap and the session replays, already filtered to users aged 60+, and sees where they get stuck.

How the experience works

  1. 01

    Detects

    Finds behavior that deviates from the average, like early exits, repeated clicks or partial scrolling.

  2. 02

    Shows who it affects

    Every issue comes with the affected group (age, device, location) and the share of users impacted.

  3. 03

    Links to the evidence

    Each issue opens straight into a heatmap or session replay.

Iterations

9 options explored across 2 decisions

01. How a table row explains an issue

Explored
A minimal table, expandable rows, everything inline, demographic tags.
Why not
The issue wasn't understood, key details were hidden, visual overload, tags looked clickable.
Final
The issue first, then the affected group, in one readable row, with heatmap and replay links.
The final table row design An explored table row design Explored optionFinal

02. Where the feature lives

Explored
A standalone tab with alerts, a tab inside the main dashboard, a layer inside Heatmaps.
Why not
Off Hotjar's language, unclear it was about accessibility, added complexity.
Final
A dedicated tab in the primary navigation, easy to find and close to existing tools.
The final placement: a tab in the primary navigation An explored placement for the feature Explored optionFinal

User testing

We tested the prototype with a product manager from the industry (not from Hotjar), and with students and lecturers. Some participants found parts of the feature hard to understand, which showed us what to develop next.

Future direction

Identifying accessibility gaps through user behavior.

Estimating business impact, such as conversion drops or revenue loss.

AI driven recommendations for corrective actions.

Learnings

1. Accessibility is also cultural.Gaps between groups don't show up as bugs. You only see them when you split the data by population.

2. A new feature has to speak the product's language.Most of the options we rejected failed because they didn't feel like part of Hotjar.

3. Data needs explaining.In testing, not everyone found the data easy to read. Making the metrics clearer is the first thing to improve.