Transforming Dashboard User Experience
Overview
Utilized UX research methods, like building personas, conducting user and stakeholder interviews, task analysis, and prototype testing to transform the design of an inefficient, over-engineered dashboard into a streamlined visual data story.
Goals
1. Examine the current business processes to understand the user needs and simplify the design of the dashboard accordingly.
2. Automated the identification of promising sales prospects for the Sales Desk.
Team
Cross-functional Agile team (Developers, Product Owner, Business Stakeholders)
Role
Collaborated with users and the business to redesign the dashboard
Owned the coding and technical development
Tools
Salesforce Sales Cloud, CRM Analytics, CRMA Recipes, Snowflake, Jira
The Business Planning dashboard is the first fully automated tool used to identify key sales prospects in the market using industry data.
***For privacy reasons, some data has been redacted.
Background
Pacific Life is an insurance company with a unique distribution model.
-
The salespeople, field wholesalers (FWs), work with internal wholesalers (IWs) to secure sales with insurance reps in the industry.
-
These reps then sell PL products to carriers like State Farm or Morgan Stanley
-
These carriers then sell them to the policy holders, me and you.
The Goal?
Sell Insurance!
How do salespeople identify potential sales?
FWs work with their IWs to leverage information relevant to sales, like:
Existing customer relationships
Market Data
Market Data
Market data can take many forms, but Pacific Life is mostly interested in how much opportunity there is for sales at a branch, so they can secure more of the market share.
​
The Business Planning dashbaord takes this market opportunity data and displays it in a way that is simple and easy to digest.
My Role
I transformed the user experience of this dashboard, making it easier for FWs and IWs to find opportunities. I also automated the discovery of promising sales prospects which was a process that previously took weeks for the sales desk.
01
Examine Previous State & Business Need
Previous Dashboard State
The dashboard was overengineered, attempting to throw lots of heavy charts at users and did not examine the business need.
See examples below:
***For privacy reasons, some data has been redacted.
Manual Opportunity Discovery
Additionally, salespeople spent ~40 hours quarterly slicing and dicing their market opportunity data, manually adding context to it with information from Salesforce, our CRM system.
Opportunity
We saw an opportunity to enhance the current design and process by:​​
-
Developing good information architecture
-
Simplifying and reducing the amount of data
- Automating opportunity discovery through workflows and quality data engineering
User Interviews
We had meaningful conversations with the salespeople and their managers to understand how they use the data in their current processes.
​
Do they cold call the reps with the most opportunity? Do they schedule meetings with them?
Task Analysis
We spent time shadowing IWs and FWs, learning about their day-to-day tasks and observing them conduct their daily tasks using market data. This gave us a good understanding of how they use the data in their business processes, which informed the information architecture.
Prototyping
We iterated through multiple designs with IWs, FWs, and even their managers, creating both low and high-fidelity prototypes.
02
Research Methods
​
​
Low-Fidelity
High-Fidelity
***For privacy reasons, some data has been redacted.
The end result was a streamlined visual data story that automated the discovery of promising reps.
***For privacy reasons, some data has been redacted.