Last week our team attended Opticon 2017. Here, we’ve gathered the team’s thoughts on the biggest announcements and feature updates.

#1 Program Management

The announcement: Optimizely Program Management is a new suite of solutions that will help Optimizely customers manage experimentation programs throughout the entire lifecycle.

Emily Wilhoit, Head of Business Development: The new Program Management feature stood out to me as the most relevant for Blue Acorn and our clients. PM will remove the multiple spreadsheets, document, post it notes and other on-the-fly documentation that everyone uses to collaborate on optimization projects. The PM tool means everything from the early ‘idea’ state to active experiments and results are in one place that is easy to use. So long spreadsheets and Power Points!

Jared Hellman, Head of Client Success at Blue Acorn: This is a refreshing example of a new feature that directly answers a serious business challenge for optimization practitioners. Whether you’re a smaller outfit looking to begin inputting concepts or you’re running a sophisticated program and trying to control the firehose of ideas from within your organization, a centralized tool for cataloging and prioritizing hypotheses is a huge value add. Doesn’t hurt that the interface is sleek as hell either.

Nik Budisavljevic, Head of Strategy & Analytics at Blue Acorn: Our goal at Blue Acorn is to build a culture of optimization that spans the entirety business of our clients. The best way to do that has been to foster collaboration in the strategic and ideation phases of our engagements as well as making sure we can distribute insights and outcomes to a diverse range of stakeholders and teams. The new Program Management feature is going to significantly streamline our ability to coordinate and engage these audiences, build momentum that really drives the development of that optimization culture as well as help achieve broader and more impactful business results.

#2 Feature Management

The announcement: Soon, Optimizely X Full Stack will enable product and engineering teams to go beyond experimentation and control the roll out of new features with three new capabilities for Feature Management: Feature Flags, Feature Rollouts, and Feature Variables.

Emily: This goes above my head but something about allowing engineers to try a feature then easily roll it back if test. During keynote announcement they had a good story about NYTimes using this for their Crossword puzzle app. They wanted to add social element that told users ‘ Congrats on completing the puzzle… but your friend Joe Schmo did is X minutes faster than you!’ and they got lots of angry tweets about it… So they rolled it back and changed messaging to say ‘ Congrats, you BEAT Sally by Xminutes!’ and people liked it.

Jared: If it’s shiny and new it must be good for my conversion, right? We’ve seen that mindset disproven time and time again. Decision makers no longer have an excuse for blindly rolling out features without first validating their impact. Feature management takes a huge step towards a centralized process for product backlog, rollout and measurement.

#3 Support for Dynamic Websites

The announcement: Optimizely has completely re-engineered Optimizely X to work with dynamic content and support for dynamic websites is on the horizon.

Jared: Our engineers keep telling me that Angular and React have changed the game as far as allowing them to develop self-sustained interfaces. They’re smarter than I am so I’m inclined to believe them. Optimizely is way ahead of the curve on this one, adapting their technology to support these new frameworks. We’re excited to get the opportunity to test this one out in the wild.

#4 Stats Accelerator

The announcement: Stats Accelerator will use machine learning to automate traffic flow to accelerate your learnings and impact, making it possible to achieve statistical significance up to 300% faster.

Emily: I’ve learned over years that one of the biggest hurdles to successful experimentation is achieving statistical significance on a given test. This is usually due to low amount of traffic to the experiment. The Stats Accelerator got lots of cheers at OptiCon because it means it will help you achieve significance up to 300% faster! Sounds good to me. How? Something about AI and better traffic optimization. Wahoo!

Jared: Achieving stat sig is a huge challenge for experimenters with low traffic. Leveraging machine learning to step on the gas is a powerful tool (and way better than relying on “directional learnings” to inform business decisions).

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