Flagship consultants

Q: What is feature flagging and why does it matter?

Feature flagging is a software development practice where new features are wrapped in conditional flags that can be turned on or off without deploying new code. This matters because it decouples code deployment from feature release, letting teams deploy code continuously while controlling exactly which users see which features and when.

Q: How does Flagship support A/B testing?

Flagship allows you to create experiments where different user groups see different variations of a feature. The platform tracks user behaviour for each variation and provides statistical analysis to determine which version performs better against your chosen metrics, such as conversion rate, engagement, or revenue.

Q: Can Flagship target features to specific user segments?

Yes. Flagship supports targeting rules based on user attributes such as location, plan type, account age, device, or any custom property you define. This means you can release a feature only to users in a specific region, on a particular subscription tier, or matching other criteria relevant to your rollout strategy.

Q: Does Flagship work with mobile apps as well as web applications?

Flagship provides SDKs for web, iOS, Android, and server-side environments. This means you can manage feature flags consistently across your web application, mobile apps, and backend services from a single platform, ensuring users get a coordinated experience regardless of how they access your product.

Q: How does progressive rollout work with Flagship?

Progressive rollout lets you start a feature release with a small percentage of users — say 5% — and gradually increase that percentage as you monitor performance and user feedback. If problems arise, you can halt the rollout or roll back instantly without deploying code, minimising the blast radius of any issues.

Q: Can Flagship integrate with analytics and monitoring tools?

Yes. Flagship integrates with analytics platforms, monitoring tools, and data warehouses so that feature flag states and experiment results can be correlated with your broader product metrics. This gives product and engineering teams a complete picture of how feature releases affect user behaviour and system performance.

We can help you automate your business with Flagship and hundreds of other systems to improve efficiency and productivity. Get in touch if you’d like to discuss implementing Flagship.

Get in touch

Book a call

About Flagship

Flagship is a feature management and experimentation platform that gives development teams control over feature releases, A/B testing, and progressive rollouts without requiring code deployments. It lets you wrap features in flags that can be toggled on or off remotely, target specific user segments, and measure the impact of changes before committing to a full release.

Releasing new features to every user at once is risky. A bug, a performance issue, or a poor user experience can affect your entire customer base before you have time to react. Flagship mitigates this by letting teams roll out features gradually — starting with internal testers, expanding to a percentage of users, and scaling to full availability only after confirming the feature performs as expected. This approach reduces risk and gives product teams data-driven confidence in their releases.

Osher Digital works with Australian product teams to build intelligent, data-driven systems. Our custom AI development services often involve deploying AI-powered features that need careful rollout and monitoring. Platforms like Flagship pair well with our development approach because they allow AI features to be tested on controlled user segments before wide release. Our automated data processing team can also connect Flagship’s experimentation data with your analytics pipeline for deeper analysis.

Whether you’re testing a new recommendation engine, rolling out an AI-assisted workflow, or simply managing feature access across user tiers, feature flags give your team the control to move fast without breaking things. Our AI agency services include implementation support for the tools and platforms that make this possible.

Flagship FAQs

Frequently Asked Questions

Common questions about how Flagship consultants can help with integration and implementation

What is feature flagging and why does it matter?

How does Flagship support A/B testing?

Can Flagship target features to specific user segments?

Does Flagship work with mobile apps as well as web applications?

How does progressive rollout work with Flagship?

Can Flagship integrate with analytics and monitoring tools?

How it works

We work hand-in-hand with you to implement Flagship

As Flagship consultants we work with you hand in hand build more efficient and effective operations. Here’s how we will work with you to automate your business and integrate Flagship with integrate and automate 800+ tools.

Step 1

Install the Flagship SDK

Add the Flagship SDK to your application using the appropriate package manager for your platform — npm for JavaScript, CocoaPods or Swift Package Manager for iOS, Gradle for Android, or the relevant server-side SDK. Initialise the SDK with your Flagship project credentials.

Step 2

Create Your First Feature Flag

In the Flagship dashboard, create a feature flag for the feature you want to control. Define the flag key, set its default state (on or off), and configure any variations if you plan to run an experiment with multiple versions of the feature.

Step 3

Wrap Your Feature Code with the Flag

In your application code, use the Flagship SDK to check the flag state before rendering or executing the feature. If the flag is on for the current user, the feature runs; if not, the user sees the existing experience. This conditional logic is typically just a few lines of code.

Step 4

Configure Targeting and Rollout Rules

Define who should see the feature by setting targeting rules based on user attributes or percentage-based rollouts. Start with a small group — your internal team or a low percentage of users — so you can validate the feature in production before expanding access.

Step 5

Monitor Performance and Collect Data

Watch your application’s performance metrics, error rates, and user behaviour data after enabling the flag. If you are running an A/B test, let the experiment collect enough data to reach statistical significance before drawing conclusions about which variation performs better.

Step 6

Decide: Expand, Iterate, or Roll Back

Based on the data, either increase the rollout percentage toward full release, make adjustments and run another round of testing, or turn the flag off entirely if the feature isn’t meeting expectations. Once a feature is fully released and stable, clean up the flag from your codebase.

Transform your business with Flagship

Unlock hidden efficiencies, reduce errors, and position your business for scalable growth. Contact us to arrange a no-obligation Flagship consultation.

Get in touch

Book a call