Customer Analytics
Sales Leaders need to identify where their profitability is maximized, where it is draining, and how they can adjust it. I designed an experience to analyze the data and discover useful insights.
Role: UX Designer, UI Designer, UX Researcher
Software: Figma
The Problem
Customer profitability margin is usually buried in data, difficult to parse and analyze. We need to help Sales Leaders analyze profitability opportunities.
UI Clarifies Data
With a mass of data, it’s important to provide categorizations and structure that put data points in context.
Verified Usability
At each step of the process, I tested the designs with users. The adjustments made from the research verified the usability of the product.
Interactive Prototyping
Highly interactive and dynamic prototyping in Figma sets up authentic user testing
The Process
Product presents the Problem
How can Sales Leaders analyze the profitability of their most important customers?
Team Ideation
To start the problem solving, I brought together the product team to ideate possible solutions. The goal here is to understand the different needs for the design.
Ideation on Paper
Now that I better understood the problem, I quickly iterated possible solutions on paper.
Low-fidelity iterations
In the low-fidelity phase, I designed our best two options from paper ideation. The goal is to quickly represent an idea os that we can identify the best one.
AB User Testing
Using AB testing, I tried out both ideas with our users. This made it clear which option was preferred, but also showed growth opportunities in the design.
Iterations
With the new feedback, I got to fixing the preferred design to ensure usability. The biggest changes revolved around clarifying the overall definition of the graph, as well as what the dots represented.
High-Fidelity
With iterations in place, I focused on polishing details so that user testing would be as authentic as possible.
Prototyping
Now that the high-fidelity design was in place, I prototyped the filters and interactions, allowing users to really test out all the features on the page.
Usability Testing
High-fidelity usability testing focused on giving users authentic tasks and monitoring how they moved through it. This round of testing confirmed the usability of many of the features, but revealed a new challenge.
Iterating: Summary Header
Users didn’t know how many customers to look at at once. Some businesses may use 20, some use 500. We needed to give users a way to identify how important any given set of customers was.
Final Product
Impact
Profitability
Now that Sales Leaders had the ability to analyze margin on their most important customers, they could evaluate where to increase prices, and where to give discounts.
Takeaways
Clarity is key with data
It’s essential to have clear headers to allow users to know what they are looking at. Generalizations and context also help understand data.
Dynamic over deterministic
Different Sales Leaders used the data differently: some looked for individual customers, some looked at general trends. It was key that the design accommodated both.