3 keys to maximize the business value of every product feature

Experiment your way to continuous customer delight.

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3 keys to maximize the business value of every product feature

Customer success stories

CCP Games unlocks the experimentation cheat code

Challenge

Makers of the wildly popular EVE Online, CCP Games struggled to connect its releases to real business impact as the company grew and releases became more frequent. The company was limited in their ability to run product experiments.

Solution

LaunchDarkly enabled CCP Games to run experiments that determined which feature variations were driving the most engagement. The solution allowed CCP Games to deliver, control, and run experiments on features in one seamless workflow. Plus, LaunchDarkly enabled those beyond the data science team to run, interpret, and act on experiments.

Results

A new and improved recommendation engine led to a rise in user engagement through longer median session length and more personalized experiences. The company’s engagement with LaunchDarkly also informed its product roadmap for future enhancements, such as the creation of the AIR Career Program—an entirely new feature that helps increase user engagement.

LaunchDarkly has enabled self-serve experimentation at CCP. You don’t have to be a data scientist to run valid, actionable experiments. This is unbelievably powerful.

Nick Herring
Technical Director of Infrastructure, CCP Games

Read: Full CCP Games case study

Ritual experiments its way to healthier results

Challenge

Before LaunchDarkly, Ritual used another feature management solution for feature flagging and running experiments. The solution did a poor job of integrating flags and experiments, creating a lot of extra development work.

Solution

With LaunchDarkly, Ritual can leverage feature flags and run experiments in one place. They can quickly launch experiments, clean them up, and release the winning feature variation of an experiment. They can enable a winning feature for the right audiences without having to make any code changes. And their teams have better visibility into the impact of new features.

Results

Previously, Ritual was only able to run 1-2 experiments per month. Now, they run 5+ per month. With feature flags and experiments in one place, the product delivery team is more agile, data-driven, and collaborative. Ritual uses flags and experiments for a host of critical use cases like conversion and retention optimization. In this way, LaunchDarkly positively impacts the bottom line.

I think that the main benefit of using LaunchDarkly experimentation is that it’s directly tied to the feature flag implementation. It’s not a separate implementation every time we want to test a feature.

Daniel Archer
VP of Engineering, Ritual

Read: Full Ritual case study