Supply Chain Data Science Company Needed a User Friendly Product to Drive Sales
This case study examines the challenges faced by a supply chain SaaS AI company in providing optimization recommendations to its customers.
The lack of visibility into these results prior to implementation hindered customers' ability to evaluate tradeoffs effectively. In this study, we will explore the approach taken to address this issue by conducting requirements gathering sessions, developing user-friendly UI/UX, and opening up the "black box" of AI recommendations.
The outcome of these efforts resulted in significant new annual recurring revenue (ARR) through the provision of a demo-able tool to the sales team and reduced customer churn by engaging the existing customer base with the product vision.
Problem Statement
A supply chain SaaS AI company had an offering providing optimization recommendations to it’s customers for replenishment, allocation and assortment decisions. Customers and prospects complained they had no visibility to these results prior to implementing and could not evaluate tradeoffs.
Industry
SaaS AI
What We Did
Wireframing
1 Dedicated UX Resource
User Journeys
1 Dedicated UX Resource
User Personas
1 Dedicated UX Resource
High Fidelity Designs
1 Dedicated UI Resource
Interactive Prototyping
1 Part-time UI Designer with Motion Design skills
Strategy and Approach
We conducted deep requirements gathering sessions with users, buyers and internal stakeholders. We developed rough concepts to review with the same stakeholders for feedback.
We developed a UI/UX to put the results at the users fingertips but more importantly, opened the ‘black box’ to enable savvy users a deep understanding of AI recommendations and tradeoffs.
Outcome
By providing sales a demoable tool early, significant new ARR was achieved. Additionally, by engaging the current customer base on the vision, churn was reduced.
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