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Tips & Tricks for Building Your Experimentation Program

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Last week, we hosted our second annual Developer Night @ Opticon18, sponsored by Heap. Over 170 people showed up to listen to the lightning talks and watch the live demos. From experimenting on Alexa skills to integrating with analytics platforms, and integrating with other developer tools we covered a lot of ground. Read on for the highlights, and mark your calendars to join us for Opticon next year and at upcoming meetups.

Experimenting in Serverless Applications
Using an Amazon Echo + Optimizely Full Stack, Andreas Bloomquist showed off how to run experiments on a serverless environment. He demoed how a hypothetical pet store could test different daily deals via an Alexa Skill and optimize for the deal that drove the most revenue. Download the demo code from Github to try out your own Alexa Skill experiment.

Manage Your Experiments from Your Own Repo
Travis Beck, Staff Engineer on the Optimizely backend team, demoed optimizely-cli, a command line tool that he built on top of the Optimizely REST API make it easier to work with Full Stack experiments from your own code repo without needing to switch back to the Optimizely UI.

Using optimizely-cli, developers can easily pull down the latest state about all of their experiments, features, and rollouts to make it easier to integrate experimentation into their development workflows. Even better, developers can push changes back to Optimizely to programmatically create audiences, events, or even turn on experiments or roll out a feature. Download it from our github repo or install it using pip install optimizely-cli.

Journey Up Mount Experimentation
Mike Ng and Ali Rizvi, Staff Engineers on the Full Stack team discussed how Optimizely’s engineering team developed its own testing infrastructure on top of the Optimizely Full Stack platform to drink their own champagne and fuel product experimentation. They showed off best practices for retrieving the datafile, managing async event dispatching, and providing convenience methods and SDK wrappers to ensure everyone internally was using the same process for experimentation. They demoed a forced variation query parameter tool they built to help make it easier for teams to QA different experiments and rollouts internally at Optimizely.

Going Deeper with Heap and Optimizely
Taylor Udell, Lead Solutions Architect from Heap showed off how you can to use analytics together with experimentation to better understand your customer’s behavior. She demoed an Heap-Optimizely integration that helped pinpoint where in the funnel an experiment had the greatest impact on metrics along with how to validate secondary metrics without having to rerun the experiment.

We had a number of other great talks. To see them all, check out the slides on Slideshare. Join our Optimizely Developer Community to connect with developers to ask questions and share knowledge about Optimizely’s platform.

 

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