5 Ways to Kill a Foodtech App Before Users Even Fall in Love With It

You’ve done everything by the playbook: tested the idea, built and validated your minimum viable product (MVP), landed your first orders, and received feedback from beta users. The kitchen is running smoothly, the couriers are on the road, and the carts are filling up. It feels like it’s time to pop the champagne.

Then Friday night hits and everything goes off script. The “2-for-1” promotion crashes your server, couriers can’t update order statuses due to poor internet service, a large corporate order disrupts the checkout process, and payments freeze just when you need your terminal to work nonstop. Minutes turn into lost orders, cold food, disrupted shifts, and unhappy customers.

Small oversights at the beginning often kill great projects faster than competitors ever could.

To avoid this, ask yourself:

• What if the app closes while a customer is placing an order?
• Why might your inventory stop updating during a big sale?
• Will the app lag on older smartphone models?
• What happens if the app can’t send data to the server due to a poor connection? Where does a customer’s order go then?
• How much will hidden technical errors slow down order processing?

We’ve analyzed our recent projects and identified six technical pitfalls that can ruin a promising product. Startups and mature businesses alike often overlook these pitfalls until it’s too late. Read on to learn how to prevent your app from crashing at the worst possible moment.

Why didn’t the order arrive on time? Often, the reason is simple: many processes within an app require an internet connection. Once the connection drops, the entire process breaks down. We’ve seen this happen in warehouses, where barcode scanners freeze due to weak Wi-Fi; in delivery services, where couriers can’t update order statuses when they drive into a “dead zone”; and at pickup points, where a QR code won’t scan until the connection is restored.

When we developed a courier app for Sizl’s dark kitchen in Chicago, we anticipated this problem from the start. For contactless deliveries, couriers must send a photo of the order left at the door so the manager can confirm completion. Without a stable connection, the photo would just “sit” on the courier’s phone, the order wouldn't close, and no new orders could be assigned.

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Take an offline-first approach where your app's core features operate locally without a constant connection to the server. If you plan accordingly from the beginning, your app will continue to function and store data locally even when the internet connection is temporarily lost.

Take an offline-first approach where your core features operate without a constant connection to the server. If you plan accordingly from the beginning, your app will continue to function and store data even when the internet connection is temporarily lost.

This architecture includes:

1. Local storage – everything the user does (photos, status updates, receipts, scans) is first saved on the device: either in the phone’s memory or a local database like SQLite
2. Sync queue – every action goes into a “waiting list” with a timestamp.
3. Background sending – as soon as the connection is restored, the app automatically processes the queue and sends all data to the server in the same order as offline.
4. Retry mechanism – if sync fails (for example, the file is too large or the server returns an error), the app keeps trying until it gets confirmation.

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For users, it means one thing: they can continue working without worrying about the network. For businesses, it means that processes won't freeze because of a random connection drop, whether in a subway, a warehouse basement, or a suburb with poor coverage.

Rapid growth isn’t a gift; it’s the most expensive stress test you’ll ever experience. While you can launch a marketing campaign in an hour, you can’t rebuild your architecture as quickly to handle the resulting spike in traffic. Traffic doesn’t arrive evenly; it comes in waves. If your system isn’t designed for these waves, success turns into downtime. Carts take forever to load, checkout throws errors, the database chokes on identical queries, and the payment queue becomes a traffic jam.

Traffic surges won’t ask if you’re ready; they’ll simply show up and stress-test your system. To ensure that everything works when that moment comes, you need to test and strengthen your architecture ahead of time, before the surge hits your servers. Here’s what to do:

1. Run maximum load tests – simulate a sale or promotion to find out at what order volume your system slows down and where the bottlenecks are.
2. Build in extra capacity – set up auto-scaling in the cloud so that when traffic grows, your system automatically gets more resources.
3. Reduce unnecessary database calls – cache popular data (menus, product cards, prices) and serve it via a CDN.
4.  Decouple heavy operations – let checkout complete immediately, while “heavier” processes (notifications, analytics, receipt generation) run in a background queue.
5. Monitor and act quickly — set up monitoring with alerts for when orders exceed a preset threshold, so you can switch to contingency plans B or C before the system fails.

UI/UX tweaks can also help manage traffic surges. For example, in Sizl’s customer app, we added a special banner that appears during peak hours to limit potential orders and reduce load on the kitchen and couriers.

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You might think you’ve covered every scenario. However, users are the ultimate chaos testers. They’ll always find a button you never checked or enter data in ways your developers never imagined.

Technical systems thrive on order: perfectly formatted phone numbers, valid addresses, and predictable server responses. The real world? Not so much. One extra character in an address, an unexpected data format from an external service, a typo in a name, or a special character, and suddenly, the app doesn't know what to do.

The main goal is to ensure that user errors don't prevent the app from functioning properly or ruin the customer experience. To achieve this, plan protective scenarios in advance: 

• Validate data on input – every form and field should check for allowed characters, length, and format; 
• Plan fallback scenarios – if an external service returns a malformed response or no response at all, provide a backup option instead of halting the process;
• Speak the user’s language – “Service temporarily unavailable” works better than “Error 500”;
• Catch unexpected code failures – use constructs like try/catch to “catch” an error before it breaks the process and triggers a backup flow.

That way, even if a customer enters a pizza emoji in the “Address” field, the order won’t disappear—the app will handle it gracefully and guide the user to the finish line.

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Max B. CEO

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Not all failures are loud and dramatic. Some begin with barely noticeable slowdowns that gradually turn into complete system paralysis. For example, a POS app may open orders instantly in the morning, but by evening, every click may take several seconds to process. A marketplace runs smoothly during the first hour, but after prolonged browsing, product pages begin to load much more slowly. A warehouse system operates steadily at the start of intake but reacts more slowly to each scan after a couple of hours.

You can prevent gradual app degradation by incorporating memory usage controls from the beginning and regularly testing the app's behavior during long sessions. The following will help:

• Long-running tests – run the app for hours under simulated real-world load to catch bugs that only appear “over the long haul”;
• Memory profiling – tools like Android Studio Profiler, Xcode Instruments, and similar solutions show what stays in memory after each action;
• Optimizing large data – avoid keeping huge images or data arrays in memory; load them in smaller chunks as needed;
• Freeing up resources – close connections, delete unused objects, and unload data that’s no longer needed.

The result is that the app remains stable and order processing runs smoothly without any crashes or slowdowns.

Modern applications rarely operate in isolation. They’re deeply tied to external APIs, such as maps, payment gateways, geolocation, notification systems, and barcode verification. This setup works great until something breaks.

For example, in an online store, if a payment service freezes, the checkout process becomes an endless “Loading…” screen. In a marketplace, a map API failure causes pickup locations to disappear for users. In a warehouse, the barcode database stops responding, halting receiving, piling up orders, and frustrating staff.

Although external services are part of your ecosystem, their failures shouldn’t paralyze your entire operation. Your architecture must ensure that the app continues to work, even under those conditions.

Although you can’t control external services, you can control how your app responds when they fail. Plan for:

1. Graceful degradation – if a service is down, the app should keep functioning by showing cached data or informing users: “Service temporarily unavailable, please try again later.”
2. Task queues – actions that can’t be completed right now (sending payment, uploading photos) are queued and automatically retried when the connection is restored.
3. Timeouts and monitoring – the system quickly detects when a service is unresponsive and avoids keeping users stuck in endless loading.
4. Circuit breaker – a pattern that temporarily disables a failing service so it doesn’t block the rest of the app.

The result is that a partner’s outage remains their problem, and your business and customers can continue operating without feeling like "everything is broken".

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Build resilience into your app’s architecture from day one to ensure that traffic spikes, unpredictable user actions, or third-party service outages don’t turn into a crisis.

1. Design for unstable connectionsAn offline-first approach keeps core functions running locally and syncs with the server once the connection is restored. This is critical for delivery, warehouse logistics, and any fieldwork scenarios.
2. Build scalability from the start Architect your system to handle rapid audience growth without performance drops. Auto-scaling, load testing, and query optimization should be standard practice.
3. Handle errors proactively Data validation, fallback scenarios, and clear user messages reduce the risk of failures caused by unexpected formats, typos, or integration issues.
4. Run long-duration testsRegularly check how your app performs after hours or days of continuous operation. Memory profiling and timely resource cleanup prevent slowdowns and crashes.
5. Minimize critical dependencies on external servicesUse graceful degradation, caching, and task queues to keep your app functional even when partner APIs are temporarily down.

An app that can withstand failures is like the team that built it – it anticipates more than the user can see and always knows the next move.