Branch Metrics
American mobile linking and attribution platform company
Branch Metrics is an American mobile technology company known for its deep linking and attribution platform, which lets apps route users to specific in-app content from links clicked outside the app and measure which marketing sources…
Definition
Branch Metrics is an American mobile technology company known for its deep linking and attribution platform, which lets apps route users to specific in-app content from links clicked outside the app and measure which marketing sources drive installs and engagement. Its links work across mobile web, app stores, and installed apps, aiming to preserve the user's intended destination regardless of whether the app is already installed.
Overview
Mobile apps face a routing problem that the regular web does not: a link meant to take a user to a specific piece of content works differently depending on whether the user already has the app installed, is on a device without it, or is browsing from a desktop. Branch Metrics was built to solve this by creating a single type of link that intelligently routes users to the right destination in each of those scenarios, deep-linking directly into an already-installed app or guiding a new user through installation before landing them on the intended content. Technically, when a user clicks a Branch link, the platform first checks whether the app is installed and, if so, opens it directly to the specified in-app screen. If the app is not installed, the user is routed to the appropriate app store, and once installed and opened, Branch's SDK matches the new session back to the original link click, deferring the deep link so the user still lands on the intended content after installation rather than a generic home screen. This same infrastructure captures attribution data about which channel and campaign generated the click. Branch sits at the intersection of deep linking infrastructure and mobile attribution, which differentiates it somewhat from attribution-only providers that measure installs but do not also solve the underlying linking and user-routing problem. Its attribution capabilities compete directly with other mobile measurement partners, while its deep linking technology addresses a distinct but related need that many marketing teams evaluate as a bundled decision. In practice, apps use Branch links in marketing campaigns, referral programs, and content sharing features, so that a link shared by one user, or clicked from an ad, takes the recipient to a specific product page or piece of content inside the app rather than a generic landing page. Marketing teams simultaneously use the attribution data from those same links to evaluate which channels and campaigns are effective. A consideration for teams adopting Branch is that, like other mobile measurement approaches, its ability to precisely attribute installs to specific clicks has been affected by mobile operating system privacy changes that limit device-level tracking, meaning some attribution today relies more on probabilistic modeling than deterministic matching. Teams whose primary need is linking rather than attribution, or vice versa, should evaluate whether a combined platform or a specialized point solution better fits their specific requirements. Because Branch links can carry custom parameters and routing logic, engineering teams also need to plan for how link behavior is tested and maintained over time, since a broken or outdated link configuration silently degrades the user experience for anyone clicking it.
Key Features
- Deep links that route to in-app content regardless of install status
- Deferred deep linking that preserves destination through app installation
- Cross-platform link support for mobile web, app stores, and installed apps
- Mobile install and engagement attribution tied to link clicks
- Referral and sharing link infrastructure for viral growth features
- Analytics dashboards on link performance and channel attribution
- SDK integration for capturing and matching app sessions to link clicks
- Support for privacy-compliant, aggregated attribution approaches
Use Cases
Alternatives
Frequently Asked Questions
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