Aegon: Turning Unexplained Drop-Offs Into Replay-Backed Fixes with AI Insights

Overview

Aegon runs InfiniteWatch AI Insights in production to continuously analyze real sessions across its website. Issues that analytics could not explain become prioritized, replay-backed fixes, and within the first week Aegon's engineering team had the three first tickets ready to act on.

Headline Results

The Challenge (Before InfiniteWatch)

Before InfiniteWatch, Aegon faced familiar challenges:

• Analytics showed the what, not the why. Dashboards flagged drop-offs, but not the friction or errors behind them, leaving teams to guess at root cause.
• Issues detected too late. Critical UX problems often surfaced weeks later, after the revenue impact had already happened.
• Slow, manual session review. Reviewing sessions by hand was time-consuming, and problems were hard to reproduce on the team's own devices.
• Prioritization by loudest voice. Without a clear view of where value leaked, fixes were prioritized by opinion rather than impact.

A Concrete Example: A Province Dropdown That Silently Killed the Form

Before InfiniteWatch: On a multi-step signup form, the user picks their region from a dropdown, but the selection never reaches the form's validation logic, so the “Next” button stays disabled and greyed out. Analytics shows only a drop-off at this step: a number with no reason attached. No error is thrown, nothing is logged, and the team can't reproduce it on their own devices. The user re-taps the same option several times, then abandons, and the marketing spend that brought them there is lost, with no trace of why.

With InfiniteWatch: The same session surfaces automatically as a replay-backed issue: the dead dropdown, the disabled CTA, the repeated taps before exit, plus device and browser context. It is prioritized by how often it occurs and how severe it is, and a full block on the form ranks high on both, so it arrives as a ticket with a recommended fix ready for engineering.

The Solution: AI Insights

Aegon deployed InfiniteWatch to analyze real sessions automatically and surface UX issues proactively, with no extra manual effort from the team.

• AI-powered session analysis. Every analyzed session is read by an agentic engine and turned into actionable signals, automatically.
• Automatic friction and anomaly detection. UX friction, errors and abnormal behavior are flagged the moment they appear inside a session.
• Impact-based prioritization. Issues are ranked by occurrence and severity, so the most frequent and most damaging problems are addressed first.
• Replay-backed tickets, ready for engineering. Each issue ships with a session replay, the failing event, device and browser context, and a recommended fix.

The Outcome

As a result of running InfiniteWatch in production, Aegon operates better and serves its clients better:

• Teams ship with higher confidence, backed by evidence rather than guesswork.
• Less time spent reacting to incidents, and more time planning and improving.
• High-intent traffic is recovered on the steps closest to conversion, turning fixes into revenue recovered.
• Clear, continuous visibility into the real customer experience.
• Sensitive customer data stays protected, with PII automatically redacted before analysis, so deeper insight never comes at the cost of privacy or compliance.

What's next: expand coverage across more journeys and scale session volume as the partnership grows.