Demo: Optimizely’s ‘Best in Class’ Digital Experience PlatformPhil Yates
8:30 - 9:00
Join Phil Yates, Director, Solution Architecture EMEA for an interactive demo of Optimizely’s open, extensible platform providing one consistent foundation behind every digital touchpoint and enabling you to create and optimize a seamless digital journey for your customers. Provide your customers a ‘best-next’ experience with your brand so that every time your customer digitally interacts with your organization, it’s a better experience than the last.
Opening Remarks Day 19:00 - 9:15 Virtual Platform
A brief introduction to the day's event and information on what to expect
Product Experimentation With Limited Tools & ResourcesKasia Furlong
Kristin Chen
9:15 - 9:45Virtual Platform
Creativity and innovation thrive under constraints. Join SoundCloud Product Leaders, Kasia Furlong & Kristin Chen, to learn how to experiment with limited tools and resources. You’ll learn three simple principles that will level-up your experimentation skills and empower you and your teams in entrepreneurial environments. We’ll discuss how to make your experiments count, how to improve reliability and validity, and how to accelerate creativity and innovation, all within a scrappy environment.
Product Experimentation: An Evolving PracticeBlake Blanchard
10:00 - 10:30 Virtual Platform
A few years ago, the role of the Product Manager was to be omniscient - predicting their customer’s desired features and anticipating behavioral changes. Now, the majority of Product Organizations are utilizing experimentation and feature flagging for a multitude of goals: improving feature adoption, mitigating risks, and ideally, driving more revenue. Using a series of Optimizely experiments, Blake will highlight some of the different use cases for experimentation in the product lifecycle that prove the cost of waiting to experiment is simply too high!
Panel Session: Best Practices in Building an Experimentation PipelineJessica Olivera
Abhishek Shastry
Nina Foroutan
Tenni Theurer
Manash Bhattacharjee
10:45 - 11:30 Virtual Platform
Got Data? AI for Product ExperimentationJason Copeland
11:45 - 12:15
Many companies are experimenting with AI to create better customer experiences, higher conversion, lower costs, and drive innovation. Most AI projects begin as a proof of concept. Deep Learning neural nets are the leading technology for AI, and these algorithms are developed by crunching massive amounts of data. Without data, machine learning would be stuck in an AI winter. Supervised machine learning, the most common method, requires labeled data in vast quantities. Quality labeled data is perhaps the single most critical resource for developing an AI-powered product, and it is necessary even to assess the development of a POC. Without the proper data set, there is no path to a trained machine learning algorithm. This is where many companies get stuck on their AI journey – before it’s even begun. Where does this data come from? What are options for acquiring labeled data?
Lessons in Establishing a Test & Learn CultureSaleem Malkana
12:30 - 13:00Virtual Platform
In this talk, Saleem will walk through common pitfalls that can happen to teams as they look to establish an experimentation-driven culture of testing and learning. We will identify each pitfall and talk through actionable advice on how to avoid or solve these problems.

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