GrowthRail gives web and mobile teams a dependable way to launch native referral programs without turning attribution and reward delivery into a permanent internal platform project.
Referral programs look simple from the outside: create a link, record a conversion, and deliver a reward. In production, that flow crosses browsers, app stores, authentication systems, billing providers, and background jobs. Each boundary introduces state that must be secured, retried, measured, and explained to both the product team and the customer who expects a reward.
GrowthRail exists to make that infrastructure reusable. Teams can integrate through first-party SDKs or the REST API, present referral experiences that match their own product, connect verified signup and purchase events, and inspect the resulting lifecycle from one dashboard. The goal is not to dictate a campaign strategy. It is to provide reliable primitives so a team can implement the strategy that fits its users and economics.
The same principles guide the API, SDKs, dashboard, documentation, and the claims we publish about them.
GrowthRail separates the referral experience a customer sees from the stateful infrastructure behind it. Product teams keep control of their UI and reward model while the platform provides attribution records, campaign configuration, conversion signals, and retryable reward events.
Referral systems fail quietly when a click, signup, conversion, or webhook disappears between services. GrowthRail is designed around explicit lifecycle states, project-scoped analytics, delivery logs, and replay controls so teams can investigate what happened without reconstructing it from unrelated logs.
The platform provides JavaScript, React, React Native, native iOS, and native Android SDKs alongside a REST API and OpenAPI specification. Identity and purchase integrations connect verified provider events to the same referral lifecycle.
Editorial standards
Product and engineering articles are reviewed against the current public documentation and implementation before publication. When an article discusses browser, mobile-platform, privacy, or payment-provider behavior, it links to the relevant primary documentation wherever possible. Product measurements are labelled as examples unless they come from a reproducible benchmark.
Articles show their publication and substantive review dates. We correct material errors when implementation details change, distinguish deterministic attribution from probabilistic matching, and avoid presenting customer outcomes without permission and a documented measurement basis. Readers can report a technical or editorial issue through the contact page.
The clearest source for current product behavior remains the GrowthRail documentation and its OpenAPI reference. Commercial terms and data-processing commitments are governed by the applicable agreement, not by a marketing article.
Tell us how users sign up, convert, and receive rewards. We will map the implementation path with you.