Analytics Overview

The team identified an opportunity to create an Analytics homepage - a central place where security stakeholders could track progress, generate reports, and address different use cases.

My role: Partnered with PMs, engineers, and fellow designers, while facilitating stakeholder workshops to validate the idea and align on direction.

Outcome: Established a visionary design foundation for analytics that now informs ongoing evolution and future features.

  1. 🧢 Role

    Product Designer

  2. 🙌 Collaborator

    Product Managers, Design System Designer

  3. 🗓️ Date

    2025

Problem

AppSec users lack a simple way to understand their overall performance and explore specific areas that align with their interests and needs

Discovery opportunity

Identify which metrics are most valuable for AppSec users to measure performance, and how they prefer to explore data when answering questions or proving impact.

Methods

Run workshop sessions with customers
•  Top-of-mind metrics exercise ( Left)  → uncover which numbers users instinctively track or report first.
•  Wireframe Design review ( right)  → tested early explorations with internal stakeholders and select customers.

JTBD

From the metrics exercise and UI design reviews, we learned the core JTBD for CISOs and AppSec leads - ensuring the analytics experience directly supported their goals.

Analytics model

Zooming out from the JTBD, a universal analytics flow emerged:

👉 Question - Each begins with an intent or a prompt.
     Strategic persona: “Are we improving overall?”
     Operational persona: “Where are the risks?”
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‍👉 Explore Data - They navigate metrics or drill deeper into details.
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👉 Summarize & Interpret - They review trends, patterns, or comparisons to form an understanding of the situation.
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👉 Act on Insights - They take action based on findings.
     Strategic persona: Shares or presents summaries to leadership.
     Operational persona: Prioritizes issues, assigns tasks, or communicates progress.

Initial Sketch

Exploring and applying AI to create more intuitive user flows and interaction models.

Interaction Flow

The interaction flow (early draft) highlights the analytics model into a step-by-step experience. Starting with a guiding question, users explore signals, compare results, and take focused action - whether that means sharing a report, prioritizing an issue, or monitoring compliance trends.

Data Visualization

To make data visualization effective, we grounded visualization in 4 design principles:

👉 Highlight Key Trends → surface what matters most for faster decision-making.
👉 Support Exploration → enable drill-down and multi-level layouts for flexibility.
👉 Show Clarity & Hierarchy → guide attention to high-priority signals.
👉 Ensure Consistency → keep visuals clean, accessible, and systematic across the product.

Prototype

This clickable Figma prototype illustrates the inline chat interaction.
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When users land on the page, they see the standard analytics view. If they want to ask a specific question about the data, they can open the inline chat and save that query as a new view for future reference.

This approach gives users the flexibility to switch between their familiar data dashboards and deeper, ad-hoc exploration. The inline chat maintains continuity without disrupting their workflow.