Decentralised Data Indexing

Objective

SubQuery Kepler aims to provide developers with easy access to indexed data from various blockchain networks, enabling efficient and fast querying for decentralized applications (dApps). The article delves into the design process, user research, and iterative design solutions to create a seamless user experience.

Research + Iteration

Target User Persona

The SubQuery's primary users were developers who needed efficient and decentralized indexing and querying of blockchain data. These developers were building various blockchain-based applications and services, including:

1. DeFi Developers: Developers working on decentralized finance applications that required real-time access to blockchain data, such as lending, borrowing, and trading platforms.
2. NFT Developers: Creators of NFT (Non-Fungible Token) marketplaces and digital art platforms that needed to index and retrieve data related to NFTs.
3. DApp Developers: Developers building decentralized applications in various domains, including gaming, supply chain, identity management, and more.
4. Blockchain Projects: Teams behind blockchain networks and protocols that aimed to provide better data accessibility for their users and developers.
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Customer Interview

We conducted 8 in-depth interviews with blockchain developers. Before start the interview, we made a mind chart to demonstrate the possible questions that we can ask to customers. The insights revealed that users were often overwhelmed by the complexity of existing tools and desired a more easy interface.

User Journey

Next, I created a visual user journey map the user's path from start to finish. Include touchpoints with the product and any relevant actions, which help to understand the steps users take to achieve their goals within the product.

Design Sprint Planning

When we work on a complex project/feature, I will buid a design sprint plan to help the design team to collaborates to solve a particular problem. I found it helps team to brainstorm effectively and speed up the decision making process.

Phase1 Establish the main problem to focus during the sprint, create a design roadmap for the whole week and gather the information

Phase2 Ideate solutions. The focus of this phase is brainstorming, ideating features, and discussing user flows and journeys

Phase3 Decide which solution is the best and prepare for prototyping

Phase4 Create a rapid prototype of a chosen solution, which will allow you to visualize your idea.

Phase5 Gather feedback after testing a prototype with real users.

User Flow

Streamlined the user flow, allowing users to select specify data parameters, and visualize results without unnecessary complexities.

Prototyping

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Funnel analytics by MixPanel

To continually improve our product’s usability and deliver a seamless experience, we implemented MixPanel to track user interactions and measure task completion rates. Our goal was to identify specific stages in the user journey that might lead to drop-offs or slow task completion, providing us with actionable insights to refine the UX further.

The primary aim was to understand user behavior across key tasks, enabling a data-driven approach to optimize the user journey. By tracking specific events, we could pinpoint challenges users encountered and assess the effectiveness of our UI changes.

Process

1. Defining Key User Tasks

We began by identifying critical tasks that reflected the core functionalities of our product. These tasks were essential to user engagement and retention, as they formed the basis of users’ daily interactions within our app.

Each task was broken down into its main components, which we mapped out in a user journey framework. This ensured we captured the full scope of each task, from initiation to completion.

2. Event Tracking Setup in MixPanel

Once we defined the key tasks, we set up five specific events in MixPanel to monitor:

• Event 1: Onboarding Completion
  Goal: Track how many users complete the onboarding flow, understanding if the onboarding design effectively prepares users to engage with the product.
• Event 2: Feature Usage (Project deployment)
  Goal: Observe interactions with Feature A, one of the core functionalities. We aimed to see if users quickly deploy and publish their project on our Network.
• Event 3: Publishing
  Goal: Track the completion rate for projects publishing within the app. This metric was vital for understanding the success rate of core workflows.
• Event 4: Settings Interaction
  Goal: Determine the frequency and depth of user engagement with the settings page, providing insights into users’ preferences and customization needs.
• Event 5: Logout/Exit Action
  Goal: Analyze the completion of logout actions to understand typical session lengths and identify patterns in user retention.

3. Metrics and Measurement

For each event, we defined specific metrics:

• Completion Rate – The percentage of users successfully completing each task.
• Time to Complete – The time spent on each task, helping us gauge efficiency.
• Drop-off Points – Events or points in the flow where users tend to abandon tasks.

We also set up funnels in MixPanel to visualize the user journey across these events, focusing on the sequence from onboarding to task submission.

Challenges Overcome

‍One major challenge was balancing the need for a powerful tool with the simplicity desired by new users. Iterative testing and feedback were crucial in achieving this balance.

This project underscored the importance of user-centered design in the complex field of decentralized data. It taught us the value of iterative development and constant user feedback.

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