A/B-testing is an integral part of modern product development. It used to be limited for mega tech companies, but tech and tooling has made it available for companies at every stage. At least to get started.
When trying to scale experimentation, however, many companies still run into barriers stopping them from spreading the experimentation culture and capabilities beyond specialist teams or disciplines.
In this webinar we will go through four common pitfalls and what you can do to overcome them.
What is stopping us from doing more and better A/B tests?
With experience from global growth rockets like Airbnb and Webflow and Swedish frontrunners like SVT and Polestar, we have teamed up with the great team at experimentation platform Eppo to answer this question. We will go through four barriers that we ourselves have struggled to climb when scaling experimentation.
In the webinar we will run through
- What an experimentation system is
- Four common pitfalls and what to do about it
- “All in one” tools are not flexible enough
- Too much time spent cleaning up the data
- Every experiment requires a data scientist
- Lack of organizational trust
- How Eppo can help overcoming these barriers
- Open Q&A around your experimentation pains and gains
Who is it for?
This webinar is targeted towards you who work in an organization that
- Have started experimenting, but want to scale it even further
- Looking to launch experiment systems and wants to avoid future pitfalls
Who will be speaking?
We are so excited to do this webinar together with Che Sharma, who will be sharing his experience from building experimentation program and capabilities from some of the worlds most successful companies.
Che is the Founder & CEO of Eppo, a next gen AB experimentation platform that is designed to spur entrepreneurial culture. As the 4th data scientist at Airbnb and early data scientist at companies like Webflow, Che has been focused on the maturity curve of growth stage companies and how to establish data as a central stakeholder of decision making. Che previously led the team that developed Airbnb’s knowledge repo, and has led data teams focused on production machine learning and instrumentation integrity.
At Signific, we have worked with Eppo ourselves and just by using the product you know it’s built by people with deep knowledge of product experimentation.
From Signific, Max Dyrhage will be sharing the barriers we’ve seen at many Swedish companies using experimentation and A/B-test to grow their products. Max has been part of starting up and leading experimentation efforts at SVT in both data and product roles as well as building data driven products at mobility company Voi.