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Case Study · Onboarding · User Activation · FinTech · PTOS

(Case Study) From 9% to 40% Activation: How Monzo US Used Discovery to Find and Fix the Main Onboarding Pain Point

An analysis of the Monzo US case study, where detailed Discovery research helped identify a critical step in the onboarding process that was blocking activation and radically improve it.

(Case Study) From 9% to 40% Activation: How Monzo US Used Discovery to Find and Fix the Main Onboarding Pain Point

This case study from Monzo US is a brilliant example of how disciplined Discovery can lead to explosive growth in a key metric. It shows that the problem often lies not in 'bad design,' but in one specific, yet very painful barrier.

The Problem: Only 9% Make It to the End

The Monzo US team faced a harsh reality: their onboarding was so complex that only 9% of users who started the registration process successfully opened an account. This was a catastrophically low number that was killing growth right at the start.

Step 1: Discover (Diverge) — What's Breaking?

First, the team conducted Discovery to understand what exactly was breaking in the process. They literally broke down the entire flow into atoms:

  • 39 screens
  • ~210 taps

It became obvious that the process was overloaded. The team started by eliminating obvious friction points: they added autofill and simplified address entry. This allowed them to shorten the process to 17 screens and 74 taps.

The result? Conversion increased to 19%. This was already a twofold improvement, but the team understood that this was just the tip of the iceberg.

Step 2: Define (Converge) — Where is the Main Pain Point?

Continuing their analysis, the team discovered a key insight: one specific verification check was causing about a 40% drop-off. This check was a 'carpet bombing'—it was applied to all users equally, creating huge friction even for those who did not pose a high risk.

Here, the team formulated a clear Problem Statement:

'For new users in the account opening scenario, signup completion is breaking because the process is overloaded, and one of the checks creates a disproportionately high barrier for the low-risk segment. This is killing our activation at the entry point.'

Step 3: Develop (Diverge) — What Are the Solutions?

Having formulated the problem, the team moved on to finding solutions. Instead of just 'removing the check,' they rethought their entire risk strategy.

  • Hypothesis: If we can segment users by risk level and remove or simplify the most painful check for the low-risk segment, we will significantly increase conversion without creating unacceptable business risks.

Step 4: Deliver (Converge) — We Test and Implement

The team developed a new logic that allowed low-risk users to go through a simplified onboarding path. After careful A/B testing and monitoring of guardrail metrics (fraud levels), they rolled out this solution.

The final result:

  • Conversion to activation increased from 9% to 40%.
  • The median registration time was reduced to 7 minutes, and for the best segments, to 4 minutes.

Conclusions

The Monzo US case clearly demonstrates the power of Discovery and the entire Product Loop:

  1. Start with data, not opinions. Break down the funnel, find where it 'leaks' the most.
  2. Don't stop at the obvious. The first improvements yielded a 2x result, but the real breakthrough came after finding the root problem.
  3. Formulate the problem clearly. It was the Problem Statement that allowed the team to focus on the main barrier.
  4. The solution should be as focused as the problem. They didn't 'improve the UX'; they changed a specific mechanic for a specific segment.
  5. Always track guardrails. Conversion growth should not be achieved at the cost of unacceptable business risks.

This case is an excellent example of how methodical work in the Problem Space leads to results that are impossible to achieve by simply 'moving buttons' in the Solution Space.