Data Gather
Introduction &
Challenge
Data Clinic partners with nonprofits to help further their missions through building data science or engineering solutions. One solution that they've built is called Data Gather, which lets nonprofits collect information from events (such as names and feedback from food box distribution) and automatically have that information sync with their database services like Airtable or Google Sheets.
Upon finding this open source project, I reached out one of the engineers on the project, Pablo, and worked with him to figure out how I can best support the tool. We both agreed that a great place to start was to improve the user experience for the Configure page with allows users to connect and preview their collected data from Airtable or Google Sheets.
What’s a Rich Text element?
The rich text element allows you to create and format headings, paragraphs, blockquotes, images, and video all in one place instead of having to add and format them individually. Just double-click and easily create content.
Static and dynamic content editing
A rich text element can be used with static or dynamic content. For static content, just drop it into any page and begin editing. For dynamic content, add a rich text field to any collection and then connect a rich text element to that field in the settings panel. Voila!
How to customize formatting for each rich text
Headings, paragraphs, blockquotes, figures, images, and figure captions can all be styled after a class is added to the rich text element using the "When inside of" nested selector system.
Process &
Design
I created a project scope and timeline for Pablo so we could identify what our focus would be for each week over the course of ~12 weeks.
The first 2 weeks, I focused on conducting user research to understand the existing flow and pain points for current users. Luckily, within that timespan I was able to speak to 3 target users and record their experience using the application.
The following 2 weeks I spent analyzing the data I collected and laid that out on an affinity map to draw insights from their stories. I also spent this time creating a user persona and user flow based off of Pablo's data on his users coupled with the data that I had collected from my research.
Once I showcased my findings to Pablo and got alignment on the existing experience, I went straight into creating lo-fi wireframes. I used these wireframes to brain dump the different features that the research had suggested while also cleaning up the layout and UX of the existing design. The sky was the limit!
After some iterations and review of what works and what doesn't based on the wireframes I provided, I began finalizing the "look and feel" of the application while tinkering with the best UI suited for certain functionalities. Utilizing the brand colors from the website, I was able to produce multiple flows, components and a prototype.
Closing Thoughts & Reflection
Overall, it was an incredibly fun project to work on. I loved that the tool aids nonprofits in becoming more data-savy and therefore being able to cater to their communities in a more effective way.
Personally, having the creative freedom to explore the design of an open source project was so exciting since Pablo and the team did not have any strict branding guidelines that I had to stick to.
This project was also the first time that I used a formal process for user research and data analysis. It was definitely tricky at first to understand and implement but my mentor was able to guiding me in asking the right questions and supporting my efforts in conducting the research and insights.
You can play with the prototype here while the live page is still being built on the backend!
