Sales Management Dashboard
1 Product Manager
1 Business Analyst
2019 - 2021
My team at Fidelity's Center for Advanced Technology received company funding to build a client management interface for the sales department. Our project's primary objectives were to consolidate existing tools on a single platform; offer product data analysis to create sales opportunities for Managing Directors and Account Executives; and present those opportunities in a visually dynamic and easily digestible way.
A management system that leverages AI insights and Salesforce technology to improve product sales and client relationships.
I'm always hunting and pecking
- user observation
We began the project by meeting with Managing Directors (MDs) and Account Executives (AEs), two of the primary roles on the Fidelity sales team. Documenting and sorting through the resulting 30+ hours of interviews helped us understand their current sales experience, the tools they used, and how they managed clients and products.
User Journey Mapping
To better define our users' specific needs, we mapped workflows for both AEs and MDs through their respective sales cycles. This also allowed us to pinpoint moments for AI intervention and data sourcing.
MD Journey Map
Sales cycles are complex and require months of preparation. To accurately capture pain points, we broke the cycle up by client interactions.
AE Journey Map
Sales uses a wide range of platforms to organize client meetings and notes
Users often “hunt and peck” to find client information
Current platform holds lots of data but is overwhelming and
difficult to navigate
Incorporate sales insights generated through machine learning algorithm
Utilize and consolidate Salesforce's data repository
Because our interface would be pulling data from so many applications, we quickly determined that the dashboard should be expanded to include multiple landing pages. I began arranging cards according to client needs.
Quick sketches organizing cards and Salesforce information
After determining the rough outline and informational hierarchy of each dashboard page, I built out lo-fi wireframes. Rapidly iterating helped me test layouts, play with progressive disclosure, and consider different ways users might interact with page content.
I designed our final interface for MDs and we prototyped and built four landing pages to organize the management dashboard.
This is a study in progressive disclosure
- our design perspective
MDs can have over 20 clients per sales cycle. This side bar shows a list of clients and helps users filter by account name or team member. Selecting the tab then displays that corresponding client's information.
This section, in particular, was what our team called "a study in progressive disclosure." Client can have multiple products and those products can have multiple. Categorizing and displaying that information quickly becomes confusing. To help users prepare for meetings, we consolidated plan data, previously located across multiple pages, to a single card. MDs can view plan details according to products and use a segmented controller to compare their client's stats with competitor's.
Search dropdown gives filter options for clients and helps MDs
Benchmarking averages from competitors appears next to corresponding data categories
Utilizing Limited Real Estate
During interviews, we learned that most users log to-do projects in tables, either in Salesforce or through Excel. To economize on space and not overload users with spreadsheets of data, I split their projects between in progress and awaiting action. MDs can click on either tab to view their action items and reveal more information through accordions.
Card progressively reveals action items according to progress made
Utilizing scroll within cards and accordions to economize on page space without overwhelming users
Action items that require attention, grouped by business quarter
AI-generated analytics for participant calls
Next Best Page
Feeding the Algorithm
We built this page around an AI-algorithm that recommends the products and product features MDs should sell to clients - i.e. "the next best product." Users can provide feedback on these recommendations, to continually improve the algorithm.
MDs can assess recommendations through feedback form and compare potential products with existing peer data
AI Insights in Context
We also designed a slide-out drawer that, when opened, highlights and explains AI-generated insights in the context of the page.
Users see tagged insights by opening insights panel
Book of Business Page
Users specifically wanted a view of all their clients and the products they currently have, could have, and can't have (called a Book of Business). This grid needed to be understandable at a glance, with the option for users to reveal more information by interacting with the grid cells. I utilized color and iconography to differentiate between product viability.
Clicking on grid cell gives an overview of product, possible growth, and retention (if product is owned)
Users can toggle between prospective or current products and apply filters to further drill down to specific client opportunities.
Our team conducted regular interviews with MDs throughout the research and designing phases. These interviews allowed users to review the interactive prototype and provide detailed feedback that we could apply before the dashboard went into development.
Several users reported being confused by the page for their Book of Business, namely the interactive grid feature. Based on these responses, we added an interface key.
We finished transitioning all MDs over to the new sales dashboard by February of 2021, with a 100% adoption rate.