Corbu.ai

Redefining Onboarding Experiences and AI Interactions.

Web App

Generative AI

Startup

B2B

Product Design

Web App

Generative AI

Startup

B2B

Product Design

TEAM

Product Designer‍ (me)

Engineers x 3

TOOLS USED

Figma, FigJam, Google Forms, Google Meets, Miro, Adobe Suite

DURATION

Current

OVERVIEW

What is Corbu?

Corbu is a startup building a generative rendering product for architects and spatial designers. It addresses the time-consuming nature of traditional rendering workflows.

OVERVIEW

What is Corbu?

Corbu is a startup building a generative rendering product for architects and spatial designers. It addresses the time-consuming nature of traditional rendering workflows.

By mimicking architects' workflows and leveraging precedent images, Corbu accelerates the creation of polished renderings, offering architects the control lacking in current image generation tools.

The Problem

Why are new users struggling with onboarding?

Architects found the initial image upload process confusing and lacked guidance on how to utilize the auto-label feature.

The Problem

Why are new users struggling with onboarding?

Architects found the initial image upload process confusing and lacked guidance on how to utilize the auto-label feature.

CONTEXT

Limitations

CONTEXT

Limitations

As an early stage startup with limited resources and time, I was constrained to use the existing UI kit.

Old Onboarding Experience

Jump to solutions HERE!

The Process

Heauristic Evaluation

Precedent Analysis

Revising User Flows

Iterating on Design

Heauristic Evaluation

Understanding the Problem

To identify key issues during the onboarding experience and where users are being stopped, I conducted heuristic evaluation of current onboarding experience: image upload and auto labeling.

Heauristic Evaluation

Understanding the Problem

To identify key issues during the onboarding experience and where users are being stopped, I conducted heuristic evaluation of current onboarding experience: image upload and auto labeling.

Core Issues

Outdated UI made navigation confusing.
Lack of guidance for the Auto-Labeler feature for new users.
Non intuitive screen progression during the image upload process.

Heauristic Evaluation

Documenting Existing Flows

To understand current user flows and where problems/ oppurtunities lie.

Heauristic Evaluation

Documenting Existing Flows

To understand current user flows and where problems/ oppurtunities lie.

Core Findings

Image upload flow was treated the same as browsing images and didn't anticipate user actions.
Metadata image search wouldn't display load time or error when users tried to search a resource that was still embedding metad ata.
Auto-Labeler flow lacked guidance or education for user encountering a new feature.

Image upload flow was treated the same as browsing images and didn't anticipate user actions.
Metadata image search wouldn't display load time or error when users tried to search a resource that was still embedding metad ata.
Auto-Labeler flow lacked guidance or education for user encountering a new feature.

Image upload flow was treated the same as browsing images and didn't anticipate user actions.
Metadata image search wouldn't display load time or error when users tried to search a resource that was still embedding metad ata.
Auto-Labeler flow lacked guidance or education for user encountering a new feature.

Precedent Analysis

How Do Other Tools Architects Use Function?

To reduce confusion during onboarding, I conducted precedent research on common file-upload and image databses commonly used by architects to see what user flows they are familiar with.

Precedent Analysis

How Do Other Tools Architects Use Function?

To reduce confusion during onboarding, I conducted precedent research on common file-upload and image databses commonly used by architects to see what user flows they are familiar with.

Common Trends

Provide user with feedback on system status and functions.
Centralized "creation" button
Allow users to create hierarchy through folders
Allows users to edit files after uploading
Add filtering options for optimal file retrieval

Revising User Flows

Improving the Onboarding Experience

Revised existing user flows issues found during heuristic evaluation with insights from precedent analysis.

Revising User Flows

Improving the Onboarding Experience

Revised existing user flows issues found during heuristic evaluation with insights from precedent analysis.

Streamlined the image upload flow by eliminating unnecessary screens, and provided more guidance to users when using the auto label feature.

Changes

Eliminated redundant screens in the image upload flow
Asked background info on why users are creating auto labels.
Educated users on auto label capabilities through suggestions.
Offer more control to users by breaking complex task down into multiple steps.

Iterating on Design

Iterated on the onboarding design decisions with input from users.

Iterating on Design

Iterated on the onboarding design decisions with input from users.

Soltuions

Anticipating User Needs During Initial File Upload

Soltuions

Anticipating User Needs During Initial File Upload

Guiding Users Through The Auto Label Feature

RESULTS

How Did We Do?

RESULTS

How Did We Do?

70%

Decrease in User Drop-off Rate

42%

Less Time Spent on Onboarding!

Learnings?

Iterate Fast and Iterate Often

Speed is the name of the game in a startup environment. It is important to iterate as often as possible, making mistakes at every pass and incrementally improving the product!

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