About the Company

Role Context

Autonmis is a user-friendly, low-code data platform that empowers organizations to efficiently manage, analyze, and visualize their data.

Designed for data professionals within small to medium-sized businesses, it offers robust solutions for ad-hoc data challenges, workflow automation, and actionable insights to drive smarter decision-making.

As a Freelance Product Manager during Autonmis's founding phase, I collaborated closely with the Founder & CEO to shape the product's initial direction.

My primary responsibility was to drive user onboarding and engagement strategies, conduct in-depth user research, and deliver product improvements based on real-world feedback. Additionally, I led a team of six junior associates, ensuring their efforts aligned with strategic goals.

Key Feature/Project

Feature/Project Name

User Feedback-Driven Product Enhancements

Objective

Improve user onboarding and engagement through actionable product changes.

Problem Statement

Data professionals faced challenges such as limited platform usability, lack of EDA (Exploratory Data Analysis) tools, and insufficient support for automating workflows.

User Feedback-Driven Product Enhancements

Approach

  1. Conducted 14 in-depth user interviews with data professionals to identify pain points.
  2. Collaborated with 30+ data influencers to validate assumptions and prioritize solutions.
  3. Integrated feedback into a roadmap focused on usability, AI-powered features, and enhanced documentation.

Solutions Explored

1. UX Enhancements:

  • Added a "How to Use" guide for new users.
  • Introduced raw data preview with classification into categorical and numerical variables.
  • Simplified navigation with user-friendly documentation via GitBook.

2. New Features:

  • Automated email reports similar to Metabase.
  • AI features for industry-specific comparisons and forecasting.
  • Drag-and-drop data modeling for engineers without coding.

3. Actionable Insights:

  • Recommended expanding visualization options with an AI assistant for graph suggestions.
  • Highlighted the need for scalability and robustness for large datasets.

Result/Outcomes

  1. Developed six user-focused product improvements, addressing 80% of reported pain points.
  2. Achieved 8 endorsements from data influencers, bolstering credibility and visibility.
  3. Increased onboarding efficiency by streamlining user documentation and support.

What did I learn from this role?

This role deepened my expertise in user research methodologies, particularly conducting interviews to uncover domain-specific pain points.

I also honed my ability to translate feedback into actionable product outcomes and learned the importance of detailed documentation in technical products.

How did it help me grow as a Product Manager?

Being the point of connection among data users helped me understand the importance of empathy while balancing strategic vision and day-to-day execution.

Managing a diverse team taught me the importance of aligning efforts with overarching business goals.

Moreover, working closely with data influencers gave me insights into leveraging community feedback to shape product direction effectively.