StoreSense

Inspiration

We were inspired by the reality of neighborhood convenience stores, bodegas, and small grocery shops that operate with very little operational support. Many owners still make pricing and reorder decisions from memory, handwritten notes, or instinct because enterprise retail software is too expensive, too complicated, or built for large chains.

One supplier invoice with creeping costs can quietly erase profit margins for weeks before anyone notices. At the same time, slow-moving inventory ties up cash and shelf space. We wanted to build something that feels less like a dashboard and more like a smart store assistant that simply tells owners what matters today.

StoreSense was designed around one idea: small stores deserve actionable retail intelligence without needing a data analyst.

---

What it does

StoreSense is a POS-connected reorder, invoice, and profit-leak assistant for small stores.

The app analyzes simulated POS, inventory, invoice, and pricing signals to surface plain-language recommendations such as:

• What products should be reordered
• Which SKUs should not be reordered
• Where supplier cost increases may require a retail price adjustment
• Which invoices need attention
• Which products are underperforming or tying up shelf space

The MVP includes:

• Home Dashboard with KPIs, alerts, and AI-style action cards
• POS Activity view with transaction and hourly sales trends
• Reorder Planning with recommended and non-recommended purchases
• Product Insights for SKU-level profitability analysis
• Invoices & Alerts for operational follow-up
• Profile & Settings with Free vs Pro plan preview
• Market Price Benchmark (Pro Preview) comparing store pricing against illustrative nearby averages

Everything is presented through a polished mobile-first experience designed for real store workflows.

---

How we built it

StoreSense was built as a frontend-first hackathon MVP focused on UX clarity, product direction, and realistic retail workflows.

Tech Stack

• Next.js 16 (App Router)
• React 19
• TypeScript
• Tailwind CSS 4
• Lucide React

Architecture

• Mock operational data is loaded from CSV files and typed TypeScript fixtures
• Demo authentication uses cookie-based auth middleware
• Plan state (Free vs Pro) is persisted locally using localStorage
• Market benchmark visualizations use lightweight CSS bars instead of charting libraries
• Shared UI state is synchronized through a custom provider using useSyncExternalStore

Product Design Focus

We intentionally avoided building generic dashboards. Instead, we focused on:

• clear operational recommendations
• simple mobile-first flows
• “what should I do next?” guidance
• realistic retail copy and interactions

The result is an MVP that feels believable even without production integrations.

---

Challenges we ran into

One major challenge was balancing realism with hackathon scope.

Retail analytics systems are normally powered by:

• live POS integrations
• historical sales data
• supplier APIs
• invoice OCR
• forecasting systems
• external pricing feeds

We needed to create an experience that felt real without building a full backend ecosystem.

Other challenges included:

• Designing actionable insights instead of cluttered dashboards
• Structuring believable mock retail data
• Creating a convincing Free vs Pro SaaS flow without payments
• Building mobile-first layouts that still displayed dense operational information clearly
• Making demo AI recommendations feel useful without using production AI services

We also spent time refining the UX language so recommendations sounded practical and understandable to non-technical store owners.

---

Accomplishments that we're proud of

We are especially proud that StoreSense feels like a real product rather than just a prototype screen collection.

Highlights include:

• A polished multi-screen retail workflow
• Realistic operational narratives and recommendations
• Smooth Free ↔ Pro preview experience
• Consistent mobile-first UI design
• Typed data architecture that can evolve into production integrations
• A believable “AI retail assistant” experience without relying on flashy gimmicks

We’re also proud that the app focuses on underserved small businesses rather than enterprise users.

---

What we learned

This project taught us that small business software succeeds when it reduces decision fatigue, not when it adds more charts.

We learned:

• Retail owners care more about actions than analytics
• UX copy matters as much as technical architecture
• Simulated data can still communicate strong product vision
• Mobile usability is critical for operational software
• Feature prioritization is essential in hackathon environments

Technically, we also deepened our experience with:

• Next.js App Router patterns
• TypeScript state architecture
• frontend-only SaaS prototyping
• local persistence patterns
• scalable mock data organization

---

What's next for StoreSense

Our next goal is transforming the MVP into a production-ready retail operations platform.

Planned improvements include:

• Real POS and inventory integrations
• Invoice OCR and automated supplier ingestion
• Multi-store and multi-user support
• Durable SKU and vendor cost history
• Real market pricing feeds with verified data sources
• AI-powered demand forecasting
• Exportable reports and PDF summaries
• Stripe-powered Pro billing
• PWA/offline support for store counters and tablets
• Human analyst workflows for Pro users

Long-term, we want StoreSense to become the “operating system” for independent retail shops — helping small stores compete with the operational intelligence usually reserved for major chains.

Built With

• data-csv
• frontend-next.js-16-(app-router)
• frontend/public/mock-data
• frontend/src/data/*.ts
• frontend/src/data;
• lucide
• react
• react-19
• tailwind-css-4
• typescript