Mar 02, 2025·8 min
How to Build a Mobile App for Simple Location-Aware Prompts
A practical guide to building a mobile app that triggers simple prompts by location—MVP planning, geofences, permissions, testing, and privacy.
A practical guide to building a mobile app that triggers simple prompts by location—MVP planning, geofences, permissions, testing, and privacy.
A location-aware prompt is a message your app shows when a user enters or leaves a real-world place. Think of it as a reminder tied to where you are, not what time it is.
At its core, a location-aware prompt has three parts:
Example: “When I arrive at the pharmacy, remind me to pick up my prescription.”
Location-aware prompts work well for everyday nudges that benefit from context:
The key is that the prompt shows up at the moment it’s easiest to act—when the user is already in the right place.
“Simple” doesn’t mean low-quality—it means focused:
You’re not building a full “if-this-then-that” system. You’re building a reliable reminder tool.
This guide walks from idea to release: defining an MVP, choosing an architecture, handling permissions clearly, detecting location efficiently, delivering prompts with good UX, and shipping with privacy in mind.
It won’t cover advanced routing, turn-by-turn navigation, social location sharing, or high-frequency tracking for fitness analytics—those change complexity, battery requirements, and privacy expectations significantly.
An MVP for location-aware prompts isn’t “a smaller version of the full app.” It’s a clear promise: when someone reaches a place, the app reliably nudges them in a helpful way—without draining battery or sending spammy alerts.
Start by defining three things: trigger types, prompt formats, and the rules that keep the experience sane.
Keep the first release to triggers you can explain in one sentence each:
If you’re unsure, start with Enter + time window. It covers most reminder use cases and keeps edge cases manageable.
Pick one primary delivery method and one fallback. More formats can wait.
A practical MVP combo is notification + in-app card: notifications catch attention; the app shows what fired and why.
Even a simple location-based reminders app needs guardrails:
These limits make the app feel thoughtful, not noisy.
Before adding features, decide what “working” means. For a first version, focus on a few measurable signals:
If those numbers improve, you’ve earned the right to expand trigger types, add widgets, and build smarter scheduling.
Your tech choices should follow one question: how reliably can the app notice a place-related trigger and show a prompt—without draining battery or confusing users?
Native (iOS with Swift + Core Location, Android with Kotlin + Location APIs) tends to be the most predictable for background location behavior, system restrictions, and debugging. It’s often the fastest route to a “works everywhere” MVP if your team already knows the platforms.
Cross-platform (Flutter, React Native) can speed up UI development and keep one codebase, but location features depend heavily on plugins. That can be fine for a simple app, but timelines can slip if you hit edge cases (background limits, manufacturer quirks, OS updates) and need to patch native code anyway.
A practical rule: if location triggers are the main feature, default to native unless your team is already shipping location-heavy apps in your chosen cross-platform stack.
If you want to prototype quickly (or ship a first version with fewer handoffs), a vibe-coding platform like Koder.ai can help you generate a working app from a chat-based spec—often using Flutter for mobile, with optional React for web and a Go + PostgreSQL backend when you decide you need sync.
For an MVP, keep it small:
This approach supports offline use naturally: prompts still work even with no signal.
Add a backend when you need multi-device sync, shared lists (family/team), analytics, or server-driven experiments. Otherwise, a backend increases cost, privacy surface area, and failure modes.
If you do add a backend, keep the boundary clean: store only the objects you need for sync, and keep trigger evaluation on-device when possible.
Keep the core objects clear and boring:
With this model, you can iterate later without rewriting the app’s foundation.
Location features fail most often at the moment you ask for permission. People aren’t refusing “location,” they’re refusing uncertainty. Your job is to explain exactly what will happen, and when.
Don’t lead with the OS dialog. Show a simple, one-screen explanation first:
Keep it plain, specific, and short. If you can’t explain it in two sentences, the feature is probably too broad.
On iOS, most users will choose between When In Use and Always. If your app needs prompts while the app is closed, explain why Always is required—and ask for it only after the user has created at least one location prompt.
On Android, users typically grant foreground location first, then you request background location separately. Treat this as a two-step trust flow: earn foreground access with visible value, then request background access when it’s necessary.
Many phones allow precise or approximate location. If the user picks approximate, don’t break the experience. Instead:
Provide a fallback: allow time-based reminders, manual “I’m here” check-ins, or a saved-address picker that triggers only when the app is open.
Also add a clear path to re-enable permissions later (e.g., a settings screen with an explanation and a button that opens system settings).
Choosing how your app “knows where the user is” is the biggest decision for battery life and reliability. For simple location-aware prompts (like “remind me when I arrive at the grocery store”), you usually want the lightest option that still feels accurate.
Geofencing lets you define a virtual boundary around a place (a circle with a radius). The OS watches for “enter” and “exit” events and wakes your app only when needed.
This is ideal when your prompts are place-based and binary: arrive, leave, or both. It’s also easier to explain to users: “We’ll alert you when you get near this location.”
Recommended defaults for simple apps:
If you need “roughly where am I” updates (for example, to refresh nearby rules), significant location change is a good middle ground. The device reports updates only when it detects meaningful movement, which is far less power-hungry than constant GPS.
Continuous GPS tracking should be reserved for genuinely real-time needs (fitness tracking, navigation). It can drain battery quickly, increases privacy sensitivity, and is overkill for most reminder-style prompts.
A practical approach: start with geofences for primary rules, then add significant-change updates only if you need extra reliability.
A location trigger is only useful if the prompt shows up at the right moment and feels easy to act on. Treat delivery as a product feature: timing, wording, and the “next tap” matter as much as detecting the place.
For most MVPs, local notifications are the fastest path to reliable prompts. They fire on-device, work without a server, and keep your architecture simple.
Use push notifications only when you truly need server-driven behavior—like syncing reminders across devices, changing prompts remotely, or sending prompts tied to shared calendars or teams.
Even a helpful reminder becomes noise if it repeats too often. Add lightweight controls you can explain in plain language:
These rules also protect your app’s reputation: fewer annoyed users, fewer uninstalls.
A good prompt answers: “What should I do next?” Build notifications that do something:
When users open the app from a prompt, land them on a focused screen: the reminder text, quick actions, and a subtle confirmation (“Done” state). Avoid dumping them into a busy dashboard—keep the experience consistent with the urgency of the interruption.
A location-aware prompt is only as good as the moment someone can set it up without thinking too hard. The goal is a “create prompt” flow that feels familiar, forgiving, and quick—especially because location selection can be the most confusing part for non-technical users.
Keep the flow focused on three decisions:
A practical default is to prefill the message field with a short template (for example, “Remember to…”) and preselect a reasonable radius so users aren’t forced to understand meters/feet before they can proceed.
Offer multiple ways to select a place, but don’t show everything at once.
Search first is often the fastest option: a search bar with places autocomplete helps people find “Home,” “Whole Foods,” or a specific address without fiddling with a map.
Add two supporting options:
Most users don’t think in meters. Use a slider with plain-language labels (for example, “Very close,” “Nearby,” “A few blocks”) while still showing the numeric value for clarity. A small preview line like “Triggers within ~200 m of this place” reduces surprises.
Once prompts exist, people need quick control without deleting work:
Keep the list scannable: show the place name, a one-line message preview, and a subtle status (“Enabled,” “Paused,” “Archived”).
Location UX often relies on small map controls—so accessibility needs to be intentional:
A setup experience that’s quick, clear, and reversible will reduce support issues and increase the chance users keep creating (and trusting) location-based reminders.
A location-aware prompts app should still work when the user has spotty reception, low battery, or the app hasn’t been opened in days. Designing for those constraints early keeps your “simple” app from becoming unreliable.
Treat the device as the source of truth for triggering reminders. Store prompts locally (for example: name, latitude/longitude, radius, enabled state, last-edited timestamp). When the user edits a prompt, write it to local storage immediately.
If you plan any kind of account or sync later, queue changes in an “outbox” table: create/update/delete actions with timestamps. When the network is available, send the queued actions and mark them as completed only after the server confirms.
Both iOS and Android limit what apps can do in the background, especially if users don’t open them often.
The dependable approach is to rely on OS-managed location triggers (geofences / region monitoring) rather than running your own background loop. OS-managed triggers are designed to wake your app at the right moment without keeping it active all day.
Be careful with assumptions:
Frequent GPS polling is one of the fastest ways to drain battery and get your app uninstalled. Prefer:
If prompts can be edited on multiple devices, decide a simple conflict policy up front. A practical default is “last write wins” using a server timestamp, while keeping a local edit timestamp for transparency and debugging. For deletes, consider a tombstone record so a deleted prompt doesn’t reappear after an older device syncs.
Location-based reminders feel personal, which means users will judge your app by how respectfully it treats their data. Good privacy isn’t just a policy—it’s product design.
Start with the smallest possible dataset. If a reminder only needs to fire when someone enters a place, you usually don’t need to store a trail of where they’ve been.
If your app can decide “trigger met, show prompt” locally, do it. On-device processing reduces exposure and simplifies compliance because less data leaves the phone.
Don’t hide privacy behind legal text. Add a short, plain-language screen in onboarding and in settings.
Treat stored locations like sensitive data.
A simple rule: if you can’t clearly explain your data use in two sentences, you’re probably collecting too much.
Location features often “work on your phone” but fail for real users because conditions are messy: weak signal, different devices, battery restrictions, and unpredictable movement. A good test plan makes these failures visible early.
Do at least a few runs outside with the app installed on a normal build (not a debug-only shortcut).
Keep notes on: expected trigger time, actual trigger time, and whether the app was open, backgrounded, or force-closed.
Real-world tests are essential, but they’re slow. Add repeatable tests with:
Mocking lets you reproduce a bug exactly and confirm the fix without needing to revisit the same street corner.
Location behavior varies across Android vendors and OS versions. Cover:
Treat logs as a debugging tool, not a location diary. Record events like:
Avoid storing raw coordinates or long location trails. If you need location for debugging, keep it optional, short-lived, and clearly user-controlled.
Getting a location-aware prompts app approved is mostly about clarity: you must justify why you access location, especially in the background, and show users you’re respectful with data.
iOS (App Store):
Apple reviews the permission text you provide. Your location permission “purpose strings” must plainly explain what users get. If you request “Always” location, be prepared to justify why prompts won’t work reliably with “While Using.”
Android (Google Play):
Google is strict about background location. If you request it, you’ll likely need to complete a Play Console declaration explaining the feature and why foreground-only access isn’t enough. You’ll also need to complete Data Safety details (what you collect, how it’s used, whether it’s shared).
In your App Store / Play Store listing, describe the user benefit in one sentence before any technical detail:
“Get reminders when you arrive at the grocery store, so you don’t forget your list.”
Also mention:
Use a simple rollout sequence:
Track crash rates, permission opt-in rates, and whether triggers fire reliably.
Shipping a location-aware prompts MVP is only half the job. The other half is proving it works for real people, then deciding what to build next based on evidence—not guesses.
Track a few events from day one:
These three alone tell you whether users are setting up prompts, whether the app can legally detect location, and whether the core feature actually runs.
If you build with a backend (for example, for multi-device sync), keep analytics privacy-first: aggregate where possible, avoid raw coordinates, and clearly document what you record.
High trigger counts can still mean a bad experience. Add quality signals:
A practical goal for an MVP is to reduce false and missed triggers week over week.
Plan ongoing work beyond initial build:
If you’re aiming to ship faster, consider tooling that reduces boilerplate and iteration time. For example, Koder.ai supports snapshots and rollback plus source code export, which can be helpful when you’re testing lots of OS and device permutations.
Prioritize features that increase re-use:
A location-aware prompt is a reminder that triggers based on where the user is, not when it is.
It typically includes:
A solid MVP focuses on reliability and clarity:
This keeps setup simple and avoids “notification chaos.”
Start with Enter + time windows.
Add Exit or Dwell later, once you’ve validated reliability and UX.
Use defaults that balance accuracy and reliability:
Also enforce sensible bounds (e.g., don’t allow 10 m or 50 km radii).
Ask for permission only after you’ve explained the benefit in-app.
Practical flow:
If denied, keep the app useful with fallbacks (time-based reminders or “run when app is open”).
Don’t break the experience—adapt it:
Design so the app still functions, just with less precision.
For simple arrive/leave reminders, prefer OS-managed geofencing/region monitoring.
Default to geofences, then add significant-change updates only if you need extra reliability.
Start offline-first:
If you add sync later, queue edits (create/update/delete) and use a simple conflict policy like last write wins, plus tombstones for deletes.
Make notifications actionable and predictable:
This reduces fatigue and increases trust in the reminders.
Use a mix of real-world and repeatable tests:
Log events without collecting sensitive history (e.g., timestamp, trigger type, prompt ID, permission state—avoid raw coordinate trails).