Giving financial advisors and managers new insights with Advanced Analytics.

In 2016, eMoney Advisor set out to revamp its infrequently used and underdeveloped Analytics feature. As the UX / UI designer for the project, I collaborated with a small team of engineers and product managers to create a new à la carte product that would allow users to track engagement, identify business opportunities, and better manage their clients.

The Problem

  • For financial advisors – Data that could help advisors was either spread throughout the application or not surfaced at all. Additionally, users with varying business focuses and priorities weren't necessarily interested in the same information.
  • For managers – eMoney's existing Analytics feature did not aggregate office-level data. Managers or their assistants frequently had to engage in significant manual effort to combine data from various sources.
  • For eMoney Advisor staff – To satisfy customer requests, product managers had been using a complex, third-party charting application to create reports wholly separate from eMoney's software. Ongoing maintenance of this process was largely manual.

A unique challenge in defining the problem for this project was that every chart could potentially solve a different type of problem. And in some cases, visibility into new data could expose a problem that no one knew existed. The interface itself could help define problems and allow us and its users to create new, better solutions in the future.

Initial Sketches

Amongst the concepts I explored, a customizable, tile-based dashboard was the most scalable and capable of satisfying a diverse group of users with different interests and business focuses.

This initial 3-step flow shows how a user could click an Analytics tile to view the full report asscociated with that tile. From the full report, the user could click into any table row to "drill" deeper and see the data behind that row.

Wireframes & User Feedback

I always prefer to put something in front of users as early in the process as possible, especially when there is uncertainty about a particular direction. One such example from the Advanced Analytics project was the dashboard customization flow. Two options were under consideration.

Option 1: Create-Your-Own Tiles

Users could either click the "Create Chart" button or click any tile to go to the custom report page.

On the custom report page, users could use a simple form to create a new report and then click "Save to Dashboard."

Option 2: Tile Library

Users could click the "Add Charts" button on the dashboard to go to a library of pre-configured tiles.

In the tile library, users could view tiles by category, preview them with live data, and add them to their dashboard.

High Fidelity Prototypes & User Testing

I create high fidelity mockups in whatever format is most appropriate for the project. In this case, working with a small development team with only two software engineers, it was most efficient to develop high fidelity mockups in HTML and CSS, producing usable front-end code for the engineers.

Once a working prototype was ready, we conducted remote, moderated user testing with 5 participants. Amongst the findings of our testing, we found that users were having difficulty with a key feature, the ability to filter their data.



The "Final" Product

In November 2017, Advanced Analytics was launched. A customizable dashboard allowed users with varying focuses to see only the data they were interested in. Aggregation of office-level data relieved managers, their assitants, and eMoney Advisor staff from significant manual effort. And simple but powerful charts and drill paths allowed users to identify business opportunities, track engagement, and better manage their clients.

Since its release, the team has gone on to add many new charts, filters, and features as well as maintain and improve the initial feature set.

The default Office Analytics dashboard with multiple filters applied. There were also dashboards for advisors and assistants, each with a different set of default tiles. Users can drag and drop tiles as well as add and remove them.

When clicking a tile on the dashboard, the user arrives at the details view for that chart where they can "drill" further into each row of data.

Multiple levels deep, breadcrumbs above the filter bar show users their location. Also shown, a filter opened for editing.

After clicking the "Add Charts" button on the dashboard, users are brought to the chart library where they can view charts by category, preview them with live data, and add them to their dashboard.