Analyst + Product Designer
In June of 1999, the Natural Gas Choice and Competition Act was signed, allowing Pennsylvania natural gas consumers to choose their suppliers. Instead of having to buy gas from a public utility company, consumers were able to benefit from pricing and service competition by third party suppliers of natural gas.
Sales territories were assigned randomly based on hunches, interest, or past experience in the area. In order to work in a specific area, managers had to pay expenses for time-dependent permits. Ineffective use of time and overhead led to decreased sales and profits.
The company launched a proprietary mobile app to verify the geographic location of each salesperson’s knocks and assist in necessary paperwork to convert customers. However, this application collected data likesales, selling price, customer demographic, knocks to conversion rates, as well as date and time
In the Summer of 2015, I was employed by one of America’s largest Natural Gas Suppliers. My daily responsibilities were primarily sales and administrative duties. During this time, I observed first hand, conducted interviews, documented needs, discovered data sources, and created this project to reflect a new way of doing business.
As the company was growing, executives were looking for opportunities to open brick and mortar branch headquarters. This data visualization would allow them to identify gaps between served markets and new markets and understand patterns of customer conversion to inform competitive pricing strategies.
Managers created the strategy for distributing sales teams and secure and pay for permits for advertising in neighborhoods. They needed a way to understand the landscape they were distributing workers to optimize an effective use of resources vs cost of advertising per neighborhood.
The Sales team is responsible for consulting residents in designated territories on their energy options. Sales personnel were interested in highly populated and supplier friendly areas to optimize their commission payout
Describing to executives market expansion and share since deregulation. Because sales were not often determined on price but brand recognition, users of this visualization could start asking questions like : What areas have enough existing customers to enable consumer confidence? How can we optimize this domino effect either through pricing, sales resources, advertising, or branch location?
Enabling managers a better understanding of the territories they assign to sales resources. Managers can see previous history of other sellers in the territory and determine if a territory has been saturated with a high-volume of knocks or if a territory still has consumers to adopt, and identify what sales personnel has had the most success in that area. Additionally, Understanding density of residents, businesses, and commercial entities to land needed to cover, enables effective time-sensitive strategies.
Because the underlying data is stored at a sales record level, an individual seller can have a complete portfolio of their previous sales. This can better enable sales personnel to manage the renewal of their clients, adjust contract prices to best sales price based on price as of sales date. Additionally, rather than rely on heuristics, sales personnel can see success trends in neighborhoods and additional territory analyses.
While conducting door-to-door sales with other sales personnel, I conducted 6 user interviews with expert sales staff and managers to understand common pain points, success stories, and opportunities for assistance.
During this project I learned tableau to aid the aggregation, cleaning, transformation, and visualization of key data sources and metrics.
I wireframed several iterations of animated and exploratory visualizations to enable key strategic decisions for severa targetl audiences.