Role: Product Design, UX 

Client: Intellify Learning


“Remove data bottlenecks by bringing your data together in one platform”

Project Description

Essentials is a platform where users can access, customize and visualize their data.  Designed to be a self-service solution that gives users control over their data and the ability to gain insight and gather educational intelligence. Essentials allows for the integration of multiple data streams removing data silos and brings a more user-centered delivery of data accessibility, ability visualize & model your data  and connect to multiple apps/tools. The platform and its tools allow the user to see data processed through various algorithms designed to predict and promote patterns & trends in their data.

Section 1

Sketch/wireframe of the Essentials user flow & connect apps

UX Challenges

We had a pretty aggressive timeline to build out the framework about of a only few months.  Where the task was to design a platform where various types of customer stakeholders would manage all their data  in one place as well as allow for the potential connection to multiple Intellify Apps/Data tools. This platform needed to adapt to growing functionality as customer needs changed and the platform grew.  One common thread was how might we get users access to easier to understand forms of data- typically the data you can get from the various API’s is not streamlined for the typical user. Could they access the data directly and in what form?  How might the users want to access or view their data? Would they want to pull data into third party apps or have a easy to use tool embedded in a LMS? At what level of complexity would a user want in manipulating their data? The technical know how of potential stakeholders ranged from data scientist to a typical Instructor. One of the challenges is that both users would want the flexibility to access their data but not all would want levels of complexity and manipulation.  In addition to having functionality to access and manipulate data, Essentials would also use algorithmic and predictive logic to provide insights or recommendations in the respective tool & apps. Defining what those might look like needed to be researched and validated across multiple types of customers and data sets. Due to the MVP nature of getting this off the ground as quickly as possible we often were designing and building at the same time. Which allowed us to test and iterate quickly through potential use cases.

Section 2

Example of a users view of "Data Sources" and "Data Tools" where they can manage and view thier data

Section 3

Mockups for a WYSIWYG data editor and visualizing app

Section 4

Early sketches of WYSIWYG data editor and environment/data storage UI

Section 5

Help & User sections of the platform

UX Solution 

We had a pretty aggressive timeline to build out the framework, about a few months.  We quickly saw that customers could login easily, set up their data sources and test out their data with some of our template visualizations. Feedback early on was how exciting it was to be able to connect & blend data that was previously siloed. We gathered feedback on how users thought they wanted to access their data and what parts of multiple data sources were important to them.  The platform and integrated apps we designed involved addressing a gap in having access to data but answering “How do I use the data now that I have it?”  We utilised pilot programs to gather research, test algorithms & refine data visualizations. Early adopters allowed for extended research, validation and refinement of solutions to problem questions raised initially.

Initially, we used Tableau visualizations to get the visualization connection part up and running quickly. We explored the option of  in-house visualizations with React, Chart.js, or D3 but ultimately decided the quicker path to getting the data into the customers hands was through a third party software such as Tableau or PowerBI. This allowed us to test out customer problems and solve with visualizations & algorithms in almost real-time. This was incredibly valuable to be able to iterate on views and see which were successful or not.  Ultimately, this proved to be a challenge and created too much work & technical debt to the user so we worked on “starter views” and designing for an integrated visualization view as part of essentials platform. We began work in integrating the data visualization view as part of the essentials platform requiring less heavy lifting on the user. In addition, we started to design for embedded intelligent apps such as the "Student Risk App” which allowed the user to login and see their specific use case answered - but we also allowed for customization on the settings side which was a common user request and introduced the concept of recommendations.  In addition to refining data models and quickly testing hypotheses we continued to grow the Essentials platform.  

Moving forward there is room for progress on integrating the visualization and Essentials App as one seamless platform.  We would like to continue to validate the common question/problems users have and continue to improve our visualizations. Also work on our standalone apps will provide that key missing insight across multiple data sources, specially bringing together quantitative performance data and the "soft skills” that contribute to a student’s success in the education life cycle.

Section 6

The data visualizations view - powered by Tableau

Section 7

Essentials UX screens showing the solutions & integrations the platform offers

Section 8

A intergrated app designed for school administrators designed to visualize KPI and show insights into student performance and cohort comparison

Section 9

The Essentials "Student Risk App" a tool designed to show students risk and allow for customization and predictive insight for instructors

Other Works