Interview Take-Home — 72 Hours

Sumble: Solving the "Data Dump" with Logic-First UX

Reframing a profile viewer into a decision tool for GTM teams.

ContextSeries A, Data Heavy, B2B

The Challenge

GTM managers were overwhelmed by "noisy" data. They needed to identify high-intent leads within non-deterministic datasets, requiring a way to "steer" the data filtering without losing the big picture.

The Ask

This exercise involves taking a rapid first-pass at rethinking the view in the wider context of the application.

The screen I was asked to improve

Fig: The screen I was asked to improve

My process

Fig: My process

01Design Process

Scenario

A head of technology and innovation at Jaguar Land Rover, arriving via a filter for the MATLAB technology.

What decision are they trying to make?

Is this the right MATLAB decision-maker at JLR, and what should I do next?

02Questions

Scope Sharpening Questions

Primary Decision

What single first move should this page drive: qualify, or contact?

Right Person, Right Time

How is this defined in GTM terms, and which data proves it (role/seniority, tech mentions, recent hiring/posts, location, timing)?

CTA Hierarchy

Which action is primary and why: Contact, Add to List, Compose Message, Share?

Data Variance

How often is data sparse/fuzzy, and how should the UI degrade gracefully?

03Product Auditing

Where Is the Current Layout Failing?

Before designing, I audited the existing platform to find where the view was failing the user.

  • Data Dump vs. Decision Tool: The original UI optimized for data volume rather than decision-making, forcing users to manually scan biographies to find relevance.
  • Layout Fragility: The existing design failed to degrade gracefully; sparse data profiles resulted in a broken user experience with no clear call-to-action.
  • The "Recency" Blindspot: Vital GTM signals (recent hiring, MATLAB mentions) were buried, missing the "Right Time" window critical for successful outreach.
Example of sparse profile - to highlight inconsistency

Fig: Example of sparse profile — to highlight inconsistency

04Perspective

Talking to GTM Users

GTM is a new field for me; to understand how agile they move, what volume they face, and what the active challenges are in finding good leads, I talked to 2 users to get their perspective.

A snippet of user interview insight from 2 GTM folks

Fig: A snippet of user interview insight from 2 GTM folks

05Low-Fi Solutions

Reducing Cognitive Load

Aimed at reducing cognitive load and time-to-decision.

Rapid first-pass 1

Fig: Rapid first-pass 1

06The Why

The Why Behind My Design Decisions

Shifting the platform from a "profile viewer" to an agentic decision tool.

  • The "One-Line Why": Replaced dense biographical text with an AI-interpretable summary that answers the user's primary question: "Is this the right decision-maker right now?"
  • Modular Extensibility: Engineered a component-based layout that prioritizes high information density regardless of data completeness, ensuring the UI remains functional for sparse profiles.
  • Recency Signal Architecture: Promoted "Timing" to a primary data dimension, using time-relevancy badges for tech mentions and hiring spikes to drive immediate action.
  • Actionable Hierarchy: Refactored the CTA logic to prioritize "Contact" and "List-building," aligning the UI with the user's high-velocity workflow.
Rapid first-pass 2

Fig: Rapid first-pass 2

07Trade Offs

Time vs. Solution

Two critical cuts made to protect the core value proposition in 72 hours.

  • Deep vs. Wide User Segments: I intentionally ignored SDR and Marketing personas to solve exclusively for Sales Leadership. By narrowing the scope, I could obsess over the "One-liner Why" — the primary signal a leader needs to authorize outreach.
  • Logic over Analytics: I deprioritized historical outreach data to focus on real-time relevance. In GTM, the "Right Time" is often a transient signal (recent job posts, tech mentions); I chose to build a robust UI for these "live" signals rather than a mediocre retrospective dashboard.

08Future

How I'd Improve With More Time & Resources

  • Understand the different user segments and how success differs with each segment (RevOps, SDRs, AEs, Sales leadership, Marketing).
  • What signals have historically predicted successful outreach (for both precision and volume GTM workflows)?
  • How do GTM teams operationalize "right person + right time" today?

09Testing

How I'd Evaluate the Design

Measure lead qualification time and confidence rating after 10 profiles each.

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