Scaling and Modernizing a Location-Based Social Media AppScaling and Modernizing a Location-Based Social Media App
A consistent 99.2% crash-free user rate
Smooth delivery of new features on a bi-weekly release cycle
A more scalable and maintainable codebase
A modern, stable foundation that supports 2M+ monthly active users
Business Challenge
The iOS app was originally written in Objective-C, with parts of the legacy codebase becoming harder to maintain and scale. The customer needed help migrating to Swift, implementing complex new features like private chat, and maintaining a high level of performance and stability.
Description
Contributions
As part of the client’s product team, we contributed to the ongoing modernization and feature development of the iOS app:
- Migrated key components from Objective-C to Swift for better performance and maintainability
- Adopted SwiftUI for new and static screens to accelerate UI development
- Contributed to a fully custom private chat system which includes a two-sided invitation flow, image sharing and voice memo support
- Integrated a flexible monetization system, including in-app purchases, subscriptions, and paid features like post boosts, read receipts, and gifts
- Helped implement a user moderation system, allowing trusted users to review flagged content based on their reputation and karma
- Supported a complex ad delivery system using Google Ad Manager (GAM), dynamically inserting banners from multiple external sources into user feeds
- Supported a data-driven release cycle with A/B testing and analytics usage
Key Expertise
This project highlights our ability to ship a wide range of features inside a fast-moving, large-scale consumer app:
- Contributed to wide range of features, from private chat and dynamic UI to ads, monetization, content moderation, and analytics
- Helped modernize the app by carefully migrating legacy Objective-C code to Swift while keeping things stable and production-ready
- Contributed to core features like location-aware feeds and replies, enabling real-time conversations with people nearby
- Designed features with local communities in mind, supporting geo-targeted rollouts, A/B tests, and market-specific segmentation
- Acted as a long-term, trusted member of the product team, helping ship new releases every two weeks to millions of users
Case Studies
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Real Results
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