A UX driven product

TakeProfit is a San Francisco based fintech startup with a very strong visual identity.

At TakeProfit, we use a refined UI and UX as our Unique Value Proposition to differentiate ourselves to competitors like TradingView and RobinHood Legend.

Here's a quick walkthrough trough the platform:

I'm a Senior Product Designer and working in such a design-first environment, where product design is a priority in all product decisions has been a big learning opportunity for me.

Finance is a complicated subject, building a tool to correctly visualize all kind of financial data from a company in a user-centric way and with a distinctively visual UI can be as complicated.

I worked on many aspects of the platform, but to highlight the most interesting:

1. Onboarding

2. Sharing Widgets

3. AI Features
   
   

Highlight 1: Onboarding

TakeProfit is both a platform and a community for traders, but the platform’s advanced customization capabilities were a challenge for new users.

Research showed that newcomers often felt lost—they didn’t know how to navigate pre-configured workspaces or start personalizing their experience.

To address these issues, I redesigned the onboarding flow and empty state for Workspace, adding clarity and improving user engagement.

The problem

• Overwhelm and confusion: users didn’t understand how to customize their workspace or add widgets, often abandoning the platform early.

• Lack of guidance: there was no clear explanation of the platform’s core flexibility or how to get started.

• Missed conversion opportunities: the platform allowed exploration without registration, leading to high user drop-off rates before meaningful engagement.
  
  

The process

Through data analysis, we identified key pain points:

• Users struggled to understand workspace customization.

• Empty states offered no direction, making the platform feel inaccessible.
  
  

Templates

Our hypothesis: Introducing templates and a step-by-step guide would improve engagement, while requiring registration before workspace creation would boost conversions.

• Upon onboarding, users now see a choice: Start with a template or Start from scratch.

• Templates were designed to be visually clear, offering pre-configured workspaces tailored to common use cases.

• Users could also access a "How it works" screencast—a short, focused video demonstrating platform features.
  
  

Interactive Onboarding

For users choosing to start from scratch, an interactive character guided them through adding and customizing widgets.

Previously, users could explore the platform without signing up. The redesign introduced a gated experience:

• Users could browse templates and add widgets to the empty state.

• However, attempting to finalize or create a workspace required registration.

• While this introduced a small risk of increased drop-offs, it also created a stronger incentive to register.
  
  

The outcome

Higher Registration Rates: The gated workspace increased user registrations significantly, as more visitors wanted to explore the platform’s customization options.

Improved Engagement: Feedback and screencast reviews showed that users had a much clearer understanding of how to use the platform.

Positive Reception: The template-based onboarding and interactive guide received praise for being intuitive and making the platform feel approachable.

Why it matters

This project wasn’t just about improving user onboarding—it was about bridging the gap between a powerful tool and its users. By addressing confusion and guiding users through their first interactions, we built a foundation for better engagement and long-term retention.

Highlight 2: Sharing Widgets

One of my biggest projects at TakeProfit was designing the "Sharing Widgets" feature. The goal was to let users share individual workspace widgets—like charts, screeners, or watchlists—with all their user-customizations intact.

This feature needed to be flexible, scalable, and easy to use while aligning with TakeProfit’s emphasis on customization and community engagement.

The problem

Traders work with highly personalized setups—charts with specific drawings, screeners with custom filters, or watchlists tailored to their strategies. Sharing these tools wasn’t straightforward. The challenge was to:

• Create a system that allowed seamless sharing of any widget with full customizations.

• Provide options for sharing within and outside the platform, like via links or images.

• Ensure the system could scale to handle sharing full workspaces in the future.

I owned the design process, from conceptualization to production.

The process

Understanding the Use Case

First, I analyzed how users interact with widgets. The goal was to ensure shared widgets retained their unique configurations, whether it was chart drawings, screener filters, or even visual elements like borders.

Designing the Sharing Flow

I designed a modal-based sharing interface where users could:

• Customize shared content (e.g., rename widgets or adjust settings).

• Choose sharing formats:

• Link sharing for easy collaboration.

• Image sharing for visually rich, static representations.

Creating a Scalable System

The design framework had to work not just for current widgets but also for new ones in development.

I built a modular system where sharing functionality could be integrated into any widget with minimal effort.

Collaborating with Developers

I worked closely with the development team to ensure seamless implementation. The system was designed to handle complex data structures while keeping performance smooth.

Testing and Iteration

We ran usability tests to refine the flow and iron out any issues with customization options. User feedback led to small but impactful tweaks, like clearer formatting options and better visual previews.

The outcome

Sharing functionality for charts, screeners, and financial widgets went live successfully. Additional widgets are being integrated into the system.

The feature quickly gained traction, with users sharing their setups both within the platform and externally.

The modular design supports future updates, including full workspace sharing, without major redesigns.

Why it matters

This project was about enabling users to connect and collaborate. By making the system scalable and flexible, I ensured it could evolve alongside the platform. It was a great example of balancing complexity and usability while staying true to TakeProfit’s focus on customization.

Highlight 3: AI features

At TakeProfit we are working on cutting-edge technology and in 2024 that means AI. At TakeProfit, we chose a targeted approach to its integration. Instead of overwhelming users with general-purpose AI tools, we focused on embedding AI exactly where it could solve real problems for traders. The challenge was to design features that felt seamless and functional in a platform already dense with data and tools.

The problem

TakeProfit is a platform where users work closely with complex numerical data and highly personalized setups. AI needed to add value without creating noise or disrupting workflows. The main challenges were:

• Defining clear use cases where AI would provide real utility.

• Designing AI features that fit naturally into a platform already rich in functionality.

• Establishing a recognizable but unobtrusive design language for AI elements.
  
  

The process

Defining the Concept

The guiding principle was precision over scale: AI would only be used where it added clear value, without overshadowing existing features. This led to:

• A modular concept that allowed AI-powered features to spread across different tools consistently.

• A visual and interaction design that made AI elements easy to spot but not intrusive.
  
  

Collaboration and Roadmap Planning

Together with the development team and stakeholders, I helped formulate a roadmap for AI integration, prioritizing features that solved recurring user pain points and could scale across other parts of the platform without major redesigns.

We settled for these two features:

Pattern recognition on Charts: AI identifies recurring Technical Analysis patterns in trading charts, helping users spot trends faster.

Smart gilter generation: AI analyzes user behavior to suggest tailored filters for their screeners, saving time and improving accuracy.

Both features were designed to feel intuitive and seamlessly fit into users' workflows.

Prototyping and testing

I created detailed interactive Figma prototypes and mockups for these features, ensuring they aligned with the overall platform’s dense, data-focused interface.

User testing sessions were conducted to validate the usability of the new AI elements.

Users saw the ✨ symbol everywhere and we reached a point were they are fatigued by it, that's why I designed an AI symbol that still resembles the now industry-standard Ai symbols, but does so in a way that uniquely reflects our brand. Around this I then built and user-tested various flows with animated and interactable Figma prototypes.

The outcome

Though not yet live, these AI features are ready for production, with a roadmap for scaling their application to other platform areas. Early testing showed users found the tools helpful for reducing manual effort and improving efficiency.

Why it matters

This project highlights how thoughtful AI integration can enhance functionality without overwhelming the user. By focusing on targeted, scalable use cases, I ensured AI could add real value while remaining unobtrusive. The modular system means future AI features can be integrated effortlessly, maintaining consistency across the platform.