LeadDyno

Reducing churn through data visualization

Problem

Managers struggle to understand the performance of their affiliate programs.

Churn was slowly increasing month over month, with users citing frustration over their inability to drill into granular program details like affiliate performance and purchase data. Even more, generating a data export required users to submit help desk tickets which impacted the support team with busy work.

Solution

Strengthen performance insights through data visualization for reporting dashboards.

Provided a comprehensive dashboard that displays both overall purchases and affiliate-specific transactions, enabling managers to quickly gauge performance at a glance. The solution also includes purchase attribution in a table format, allowing managers to filter or export data as needed for a detailed evaluation of individual affiliates.

Process

Finding the the root of user frustration through feedback and research.

I began by combing through help desk tickets to identify users who had a ticket history related to data or reporting. This method helped streamline my recruitment process for the interviews and essentially screen for potential participants to reach out to about research initiatives.

Process

Crafting the solutions from concept to delivery.

In shaping the solutions, I began by closely examining the research insights to identify the core frustrations users faced with the current reporting system. Developing key questions for each reporting section, focusing on what users most needed to know to achieve their goals.

By centering the design process around these essential questions, we ensured that the solutions were not only functional but also highly relevant to the users' needs. After we established feasibility and viability, I worked closely with the UI designer, creating and refining components and translating the wireframes into high-fidelity mocks.

Reflection

Challenges, considerations, and constraints.

Due to time constraints, I wasn't able to test prototypes with users. If I had to go back, I would prioritize another round of testing prior to developer handoff. I was able to gain feedback about our early high-fidelity designs from users we had previously interviewed which garnered positive feedback and continued to work with the PM to conduct flash interviews with users for our design concepts.

Reporting consisted of various screens; visitors, leads, customers, purchases, commissions, and affiliates. Rather than bundling them as one large update, we opted for a phased approach over the next several months. In order to introduce the updates to users, I worked closely with the PM and growth team to design comprehensive communication releases to users as well as design a tool-tip walkthrough for users that see the updated designs for the first time.

We knew the risk of forgoing usability tests, and focused on functionality expecting corner cases to surface. We wanted to set the expectation for our users that it would not be a perfect release, so we branded the redesigned screens as beta to help ease the transition. I set up an in-app survey using a tool called Refiner to solicit feedback through in-app surveys and encouraged users to contact the team about any bugs or issues. All of this feedback was stored in a research file for iterating.

Behind the screens

There's more to this story.

This page is intentionally lean. Grab some time on my calendar and I'll walk you through everything behind it: the constraints, the pivots, and what I'd do differently.