Multi-Provider Cart for the Catalog

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Making it easier for users to collect, manage, and purchase scenes from multiple data providers.

This project transformed the Catalog from a linear provider-based flow into a true multi-provider shopping experience, enabling users to explore, collect, and purchase imagery with far more flexibility. By focusing heavily on cart-specific UX patterns, the solution balances familiarity with the sophistication required for geospatial data.

 

UP42 2025

Product Designer

The Challenge

The Catalog is a core entry point for users exploring available imagery. While users could discover scenes across multiple providers, they could only check out items from one provider at a time. This created friction, especially for workflows requiring mixed datasets (e.g., combining optical and radar imagery).

To unlock more flexible ordering, we needed to introduce a universal cart—a place where users could add, review, and modify items from any provider before purchasing.

This required a clear, intuitive cart experience that aligned with diverse geospatial providers and their ordering rules.

Why This Work Mattered

  • User Expectation: Nearly every digital platform has a cart pattern; users expect to add, remove, and adjust items easily.

  • Workflow Efficiency: Researchers and analysts often compare data from multiple sources. A single cart simplifies cross-provider selection.

  • Business Goal: Supporting multi-provider checkout increases order efficiency and reduces drop-off during the selection phase.

Research & Discovery

Before designing, the focus was on understanding cart behavior, not just checkout flows.

What We Studied

  • How users adjust quantities or variations

  • Patterns for removing items

  • How carts display provider differences

  • How to handle mixed-product rules

  • Feedback visibility (e.g., “item no longer available,” “updated pricing,” etc.)

User Pain Points Identified

  • Adding items from multiple providers often broke the flow—users didn’t know why.

  • Carts in the platform were almost non-existent; users immediately entered checkout instead.

  • No place to “hold” items while browsing.

  • Confusion about why items disappeared or became invalid when switching providers.

Key Insight:

Users didn’t necessarily need a complex checkout—they needed a stable, predictable, e-commerce-style cart where they could collect imagery while exploring the catalog.

Design Solution

A Universal, Provider-Agnostic Cart

The new cart allows users to:

  • Add scenes from any provider

  • View all selections in one place

  • Understand provider-specific details (e.g., resolution, revisit date, pricing model)

  • Remove, reorder, or update scenes

  • Validate item availability before checkout

Cart Interactions Designed

  • Add / Remove items — clear, consistent controls

  • Multi-provider grouping — items grouped or labeled by provider

  • Availability checks — warnings for outdated or invalid scenes

  • Persistent cart state — items remain saved during browsing

  • Provider rules surfaced inline — e.g., ordering minimums, AOI restrictions, licensing differences

Focus on Familiar Patterns

To reduce cognitive load, we grounded the UX in common cart mental models:

  • Checkbox + bulk actions

  • Expandable item details

  • Inline notifications

  • Dedicated "Review & Checkout" CTA

Validation

Tested prototypes with current catalog users.

What We Learned

  • Users immediately understood the cart interaction because it mirrored patterns they already knew.

  • Multi-provider grouping reduced confusion when mixing imagery sources.

  • Users appreciated being able to “stage” selections before ordering.

One participant said:

“I finally feel like I can shop around properly instead of committing provider by provider.”

Impact

For Users

  • A more flexible, natural browsing experience

  • Ability to build mixed-provider datasets

  • Fewer errors and less context switching

For the Platform

  • Higher order completion rates

  • Increased catalog exploration time

  • Paves the way for more complex ordering logic (e.g., bundles, multi-scene optimization)