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Role

Product Designer, UX Researcher

Timeframe

3 months

Responsibilities

Product Strategy, Vision, Research, IXD, Visual Design

Team

1 PM, 4 Engs, 2 PDs

Adoption

100%

Manual effort cut

50%

Task progression

30%

Task completion time

20%

Context

Preqin, a big name in the alternative assets industry, had a bold plan: become the top player of data quality by 2025. To do this, they had to fix glaring issues in how they managed their data.

Goals

Make data creation faster and less of a hassle while boosting quality with the help of AI.

The idea was to build an AI platform that would simplify data entry and open doors for new ideas and better engagement.

I led the strategy and execution of this along with another product designer.

How AI automate tasks

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Research

We interviewed operations teams, engineers, and managers to understand what the pain points were.

Problem Sign

Questions we asked people to inform design

How researchers were getting their tasks done.

What they saw as most important in their tasks and assets.

Which tasks were repetitive or one-off.

When tasks were expected to be completed.

Comparative analysis

We wanted to create a best-in-class AI task management system and execute it better than anything out there.

Solution

Through a mixture of qualitative and quantitative methods and iterations, it's critical for the AI solution to centralize teams' work, enabling independent planning, management, and tracking of tasks in one place.

View prototype

Task management iteration to get feedback

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MVP

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After launch

Navigating towards personalized progress insights and enhanced adoption

The platform launched on November 3rd, 2020. The company’s KPI was to increase data quality by 2% and decrease manual lift by 50%. The platform’s KPI was to reduce the time it takes to complete a task by 20% and increase task progression by 30%.