> For the complete documentation index, see [llms.txt](https://docs.nearby.finance/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.nearby.finance/use-cases/location-based-rewards.md). # Location-Based Rewards ## Location-Based Rewards Location-based rewards are a powerful way to connect digital incentives with real-world activity. They allow applications, communities and protocols to reward users for being physically present, participating in local activity or completing real-world actions. However, traditional reward systems often require users to share exact coordinates, install tracking-heavy applications or expose sensitive movement data. Nearby Protocol introduces a privacy-preserving alternative. With **Proof of Location**, users can prove they were present in a specific area, venue, region or event without revealing their exact location. > **Nearby enables reward systems that are verifiable, privacy-first and connected to real-world participation.** *** ### The Challenge Many applications want to reward users for real-world actions. Examples include: * Attending events * Visiting specific locations * Participating in local communities * Supporting merchants * Completing regional tasks * Joining campaigns * Verifying presence in a physical zone The problem is that most systems verify these actions by collecting precise location data. This creates risks such as: * Excessive data collection * User tracking * Centralized location databases * Privacy loss * Spoofing and fake participation * Low user trust Nearby enables rewards without turning location into surveillance. *** ### The Nearby Approach Nearby uses **Proof of Location** to verify location-based claims cryptographically. Instead of asking users to reveal exactly where they are, the system verifies whether a specific location condition is true. For example: ``` User is inside Event Zone A User is within City Boundary B User is present at Venue C User is eligible for Local Reward D ``` The application receives proof that the claim is valid, without receiving raw GPS coordinates. This creates a better balance between verification and privacy. Users can prove eligibility without exposing unnecessary personal or location data. *** ### How Location-Based Rewards Work A typical location-based reward flow works like this: 1. A campaign defines a geographic boundary, venue, region or event zone. 2. A user enters the eligible area. 3. The user generates a Proof of Location on-device. 4. The proof confirms eligibility without revealing exact coordinates. 5. The application verifies the proof. 6. The user receives a reward, access right, badge or incentive. The reward can be issued based on verified physical presence rather than trust in centralized tracking. **Complete flow:** ``` Enter location → Generate proof → Verify eligibility → Receive reward ``` *** ### Reward Types Nearby can support multiple types of real-world reward systems. | Reward Type | Description | | -------------------------------- | ----------------------------------------------------------------------------------- | | **Attendance Rewards** | Rewards users for being physically present at events, venues or gatherings. | | **Local Participation Rewards** | Incentivizes users for participating in community-based or location-based activity. | | **Merchant Rewards** | Enables businesses to reward customers for visiting physical locations. | | **Network Contribution Rewards** | Rewards users who help strengthen Nearby infrastructure. | | **Regional Campaign Rewards** | Supports campaigns limited to specific cities, regions, venues or countries. | *** ### Attendance Rewards Users can earn rewards for being physically present at an event, venue or gathering. Examples include: * Conference attendance rewards * Festival participation badges * Community event incentives * Proof-of-presence collectibles * Venue-based access rewards * Event participation campaigns This allows organizers to reward real attendance without collecting raw GPS data. *** ### Local Participation Rewards Communities can reward users for participating in local activity. Examples include: * Joining a local mesh network * Supporting a community event * Participating in neighborhood coordination * Engaging with local merchants * Contributing to local communication * Taking part in regional campaigns This creates a stronger connection between digital incentives and real-world community activity. *** ### Merchant Rewards Businesses can reward customers for visiting physical locations without collecting exact location histories. Examples include: * Visit-based rewards * Local loyalty programs * In-store campaign incentives * Geo-gated offers * Venue-based discounts * Merchant participation rewards Nearby allows merchants to verify presence while respecting customer privacy. The user proves eligibility, but does not need to expose exact coordinates or movement history. *** ### Network Contribution Rewards Nearby can reward participants who improve the network itself. Examples include: * Mesh relay participation * Witness attestations * Node operation * Proof generation * Local network support * OfflinePay transaction support This allows Nearby to incentivize real-world infrastructure participation. Users are rewarded not only for being present, but also for helping the network become more useful, resilient and available. *** ### Regional Campaign Rewards Projects can launch campaigns limited to specific cities, countries, venues or regions. Examples include: * City-specific incentives * Country-based access programs * Venue-only campaigns * Community activation campaigns * Regional onboarding campaigns * Local ecosystem rewards This enables precise campaign targeting without requiring invasive location tracking. A user can prove they are eligible for a region-based campaign without exposing their exact position. *** ### Privacy Benefits Nearby location-based rewards are built around selective disclosure. Users reveal only what is necessary. They do not need to expose: * Exact coordinates * Full location history * Personal movement patterns * Continuous tracking data * Sensitive behavioral profiles The system verifies a location-related statement while minimizing data exposure. This makes reward systems more privacy-respecting, user-friendly and aligned with the principles of self-sovereign participation. *** ### Anti-Spoofing Design Reward systems are often vulnerable to fake participation. Nearby reduces spoofing risk by combining multiple verification layers: * Device attestation * Trusted execution environments * Multi-signal location validation * Zero-knowledge proof constraints * Optional witness attestations This makes fake location claims more difficult and economically less attractive. While no location system can eliminate all adversarial behavior, Nearby is designed to make manipulation harder to scale. The goal is to reward real participation, not extractive or fake activity. *** ### Example Campaign Flow A project wants to reward users who attend a conference. 1. The project defines the conference venue boundary. 2. Attendees open the application during the event. 3. Each user generates a Proof of Location. 4. The application verifies the proof. 5. Eligible users receive a reward. 6. Optional witness data strengthens verification. 7. Rewards are distributed through the Nearby incentive layer. The result is a privacy-preserving proof-of-attendance system. **Campaign flow:** ``` Define zone → User enters → Generate proof → Verify proof → Distribute reward ``` *** ### Integration with Nearby Mesh Location-based rewards can also be connected to **Nearby Mesh**. For example: * Users may earn rewards for joining an event mesh network. * Relay participants may earn incentives for supporting local communication. * Communities may reward active local coordination. * Event organizers may reward verified participants inside a mesh network. * Local groups may incentivize users who help maintain communication coverage. This creates a local incentive loop where communication, presence and rewards reinforce each other. Nearby Mesh gives the reward system a real-world social layer. *** ### Integration with OfflinePay **OfflinePay** can be used alongside location-based rewards. Examples include: * Rewarding vendors who accept offline payments * Incentivizing users who transact at local events * Supporting local commerce campaigns * Creating rewards around offline settlement participation * Encouraging use of peer-to-peer payments in disconnected environments * Rewarding users who help propagate offline payment data through local networks This connects physical presence, local payments and economic incentives. Together, Proof of Location, Nearby Mesh and OfflinePay create a complete local reward loop. *** ### Use Cases Nearby location-based rewards can power: * Proof-of-attendance campaigns * Event rewards * Venue-based loyalty programs * Local merchant incentives * Regional community campaigns * Network participation rewards * Location-gated access * Real-world quest systems * DePIN coverage incentives * Community activation programs Any system that needs to reward real-world presence can use Nearby as a privacy-preserving verification layer. *** ### Benefits Location-based rewards built with Nearby can provide: * Stronger proof of real-world participation * Lower reliance on centralized tracking systems * Better user privacy * Reduced location data exposure * More trusted reward distribution * Better resistance to fake participation * New incentive models for physical-world networks This allows applications to reward users based on verified presence without building surveillance-heavy infrastructure. *** ### Summary Location-based rewards should not require users to give up location privacy. Nearby Protocol enables applications to reward real-world participation through cryptographic Proof of Location. Users can prove that they were present, eligible or active in a defined area without exposing exact coordinates. This creates reward systems that are verifiable, privacy-first and connected to real physical activity. **Nearby turns real-world presence into a privacy-preserving incentive layer.** --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. 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