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Cart Insights
An App for simulating Carts
Problem Statement
Business users observed a consistent drop-off where customers added items to their cart but abandoned before checkout, largely due to fulfillment factors such as delivery speed, sourcing complexity, and inventory availability. Business teams lacked a way to proactively analyze how different product combinations, locations, and sourcing paths impacted delivery promises - especially during peak events like Black Friday.
Cart Insights was designed to fill this gap by allowing internal users to simulate customer carts, visualize sourcing across stores and warehouses, and predict delivery timelines before issues reached customers. The solution helped reduce fulfillment-related cart abandonment by an estimated 3–5%, improved delivery promise accuracy by ~15–20%, and enabled faster, data-driven inventory and replenishment decisions at scale.
Objectives & Goals
Enable proactive diagnosis of cart abandonment
Reduce cognitive load in complex cart analysis
Support faster, data-driven decision making
Improve customer delivery experience at scale
Our Process
Dive Deep
Map the Way
Spark Ideas
Bring to Life
Product Users
Our target audience are the Business users from different department like
Supply chain Ops, Replenishment planners, E-commerce Ops, Logistic Strategy team.
Quantitative Research
To gain a holistic understanding of both business user needs and customer pain points, we carried out internal research with business stakeholders and collaborated with the marketing team to reach out to customers who abandoned their carts.
Business User Research (Internal Analytics & Surveys)
minimal steps to add products to a simulated cart
75%
68%
analyzed more than 10 cart scenarios per session
82%
reported switching between 3+ tools to understand sourcing, delivery timelines, and inventory availability
41%
spent over 30 minutes per scenario before the new workflow, indicating high cognitive load and inefficiency
Customer Research (Marketing-Led Outreach)
customers cited slower-than-expected delivery dates as a primary reason
47%
32%
left the cart after finding faster delivery elsewhere
21%
abandoned carts due to unclear delivery timelines for multi-item orders.
Design Opportunities
How might we reduce friction when creating simulated carts so business users can test multiple product combinations quickly and efficiently?
How might we make sourcing paths and delivery timelines immediately visible so users can easily identify fulfillment risks that may lead to cart abandonment?
How might we enable rapid comparison of multiple cart scenarios to support faster, more confident decision-making?
How might we consolidate fragmented fulfillment insights into a single experience to reduce cognitive load and eliminate the need to switch between tools?
User Flow
Mid Fidelity
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