<h3>Background</h3>
<ul>
<li>To increase user retention, in addition to in-store scanning (location data collection), provide additional content for users.</li>
<li>Verification of location data re-collection and data research.
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<br></li>
</ul>
<h3>Responsibilities</h3>
<ul>
<li>Android: Design and develop check-in feature (100%)</li>
<li>Server (GCP App Engine / Python 2.7): Design and develop check-in feature API (100%)</li>
<li>Database (MySQL): Design and develop (100%)
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<br></li>
</ul>
<h3>Architecture</h3>
<img src="/images/project_0/figure_1.png" alt="Project Screenshot" style="max-width:100%; height:auto; border-radius:12px; display:block; margin:auto;" />


The CashPlace check-in feature was designed and developed end-to-end. The Android app was implemented to allow users to engage with the app while in-store. Server-side APIs were developed using GCP App Engine with Python 2.7 to handle check-in requests and verify location data. The MySQL database was designed and maintained to efficiently store and manage check-in records. Location data was also researched and validated to ensure accuracy and support strategies for increasing user retention.

Designed and developed the CashPlace check-in feature across Android, server, and database, enhancing user retention through in-store engagement and location-based content.

Check-in Feature

A service that collects in-store data such as Wi-Fi, Beacon, and ambient light through crowdsourcing. Contributors receive monetary rewards for their participation. To prevent abuse during data collection, photos of the store interiors are taken. Captured photos are stored in Firebase and undergo a final approval process via an internal review platform.

Outsourced Location Data Collection Platform