InitiativeCompleted

KYC App Metrics

Metrics dashboard specification for the in-app document submission (KYC) flow: general funnel, completion times, abandonment rates, video help usage, and interaction metrics per module.

Company
Aviva Crédito
My Role
Product Designer
Period
Mar 2025 – May 2025
Key results
  • 59.9% KYC flow abandonment
  • 40.1% completion rate
Start

Team

  • Yamil Arroyo (Design/Product)

Used Tools

ConfluenceAnalytics

Highlights

Dashboard feeding continuous KYC flow iteration. Dashboard data revealed 59.9% abandonment, 40.1% completion rate, and 2.51-day average — directly informing the design of the Home Dynamic Pre-Disbursement Card.

Key metrics

  • KYC flow abandonment59.9%
    • 40.1%completion rate
    • 2.51 daysaverage time

Problem

Without a dedicated KYC flow dashboard, the team couldn't measure client behavior in the new in-app document submission feature or generate data to iterate the experience.

Research

Collaborative definition with product and data teams of the GA4 events needed to build the dashboard. Served as the data foundation for abandonment rates (59.9%) and average time (2.51 days) used in the Home Dynamic Pre-Disbursement Card PRD.

Solution

Specification of 2 metric groups: (1) General funnel — conversion from registration, completion time, abandonment/return, help type selection; (2) Individual interactions per module (offer, checklist, address, CLABE, location, videos). Filters by product (nano/business) and recurrence.

Learnings

1. Defining analytics events before launch is part of the design, not post-launch: without the dashboard, the 59.9% drop-off would have been invisible. Instrumenting GA4 events during the design sprint accelerated the team's ability to make data-driven decisions.

2. Dashboard data revealed unexpected insights: the 2.51-day average to complete KYC showed the flow was inherently multi-session by necessity, not by choice. This redefined the retention problem and directly originated the design of the Pre-Disbursement Dynamic Card.

3. A behavior dashboard can be product discovery: metrics don't just measure the current design — they identify the next problem to solve.

  • Specifying metrics is product work: Defining what to measure, with which filters and at what granularity required as many product decisions as designing the flow itself. Poorly specified metrics produce dashboards that don't answer the right questions.
  • This dashboard's data fed future projects: The 59.9% abandonment and the 2.51-day average came directly from this dashboard and became the baseline for the Pre-Disbursement Dynamic Card project.
  • Per-module granularity is key: The overall funnel masked which specific step had the most friction. Per-module metrics (videos, address, CLABE) allowed much more precise iteration decisions.

Next steps

1. Extend the metrics framework to other critical flows: payments, renewals, and support are the immediate candidates with the highest ticket volume and known drop-off.

2. Create automated alerts in Looker Studio when KYC completion drops below 40% — the dashboard should work as a proactive monitor, not just a reporting tool.