Problem and context
Learning flower names and pricing in retail contexts often relies on static notes and inconsistent onboarding routines.
The objective was to build a fast, game-like training loop that works on phones and remains usable offline.
Learning Product
Case Study
Florist Quiz
A mobile-first training app for florists with quiz modes, real catalog data, and installable PWA behavior.
Feature deep dive
Multiple quiz formats keep repetition effective while avoiding monotony in daily training.
Swipe-like navigation and concise feedback loops are tuned for short sessions between operational tasks.
Architecture and implementation
The app organizes data around flower entities, quiz modes, and progress interactions with touch-first navigation.
PWA behavior is integrated to support installability and offline continuity in shop-floor environments.
Tooling and product stack
The app combines mobile-focused UI patterns with PWA capabilities to maintain continuity across unstable connectivity.
Data structures were shaped for practical retail relevance rather than generic quiz abstractions.
Outcome and impact
Training shifted from passive memorization to active recall workflows that better fit store-level learning constraints.
The product improves repeatability of onboarding and daily reinforcement without requiring separate training infrastructure.
Constraints and tradeoffs
Mobile-first simplification improves usability but limits depth per screen compared to desktop-heavy training systems.
Offline support adds complexity to data synchronization and update handling.
External links
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Is this a game or an education tool?
It is an education product with game mechanics to improve retention.
Does it work offline?
Yes, it is built as an installable PWA with offline behavior.
What data is used in quizzes?
A real flower and pricing dataset aligned with practical retail usage.