Why do experiments?

Why do experiments?

L’expérimentation consiste simplement à appliquer les principes scientifiques pour établir la causalité entre les changements apportés au produit et leurs résultats.

Why do experiments?

What is experimentation in the context of product development?
Experimentation is simply the application of scientific principles to establish causality between product changes and their outcomes. This topic has become more relevant over the past decade as products have become more complex and product managers have had to continually add value. Running experiments adds a structured approach to discovering unbiased learnings and uncovering the real cause of changes in metrics, even when they are too small to be measured independently.

Why should you conduct experiments?

○ Understand the real impact of change – In an organization where many teams take various initiatives to achieve a key performance indicator, it is very difficult to attribute the exact impact of each change. Experimentation reduces this noise and makes it easy to identify the drivers of change.

○ Continuously optimize design – Designers often have many ideas for a single feature. Experimentation allows them to optimise the user interface based on how a large number of customers interact with the feature.

○ Reduce the risk of complicated releases- By releasing a version to a small portion of customers, the product team will have the opportunity to understand the full impact on all key performance indicators, the risk of service disruption, and how best to evolve the version. These learnings can then be applied to a full release or become part of the release playbook.

○ Plan for change in a complicated system with hard-to-measure interdependencies – For example, in a two-sided market, any change on one side of the market will have ripple effects that are hard to predict. Experimenting with a small cohort will allow the team to see these effects in real time to reduce unwanted side effects.

○ Get a quick signal with minimal investment and disruption – It is often possible to test a hypothesis with a simplified implementation (minimum viable test) and reduced risk to extract lessons and plan the next steps. This allows your team to focus their time and talent only on ideas that are validated and prioritized based on measured impact.

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