5 minute read
We always talk about the importance of continuous delivery and measurement. This isn’t just to sell our Feature Data Platform. At Split, we practice what we preach. In fact, we’re currently using our own technology to build and scale the company, empowering a culture of measurement and experimentation from within. We call this effort Split @ Split.
Our Experimentation Advisors on our Customer Success Team are partnering with Split’s internal product and engineering squads to grow their usage of the Split platform and advance their experimentation best practices. As these teams use Split for feature flagging, progressive rollout, monitoring, measurement, and testing, our advisors are checking in to gain a greater understanding of what they’re experiencing. It’s meant to uncover some of the things our customers endure on their journey to best practices, and every new perspective gained is extremely valuable.
The goal of Split @ Split is to continuously improve our platform. We achieve this by gathering best practices and tips from the pros, as well as strengthening our support for customers. We guess you could say: “Split is officially driving Split.” Pretty meta, right?
Today, we’re catching up with Tu Nguyen, Director of Data & Experimentation at Split, to talk about the Split @ Split program.
The Value of Split @ Split
“Split @ Split started as a way for our engineering and product teams to take their experimentation chops to the next level,” says Tu Nguyen. “But, the value of Split @ Split to the Customer Success process has also been pivotal. Because we can receive feedback from internal teams, we’re able to improve the way we train customers on the platform. As we’re documenting the journey people make with Split, challenges, learnings, and solutions have quickly surfaced.”
The Challenges of Experimentation
Nguyen says, “We often hear from our customers that they want to experiment, but they don’t know how.” Nguyen’s team identified the top challenges that customers face when building out successful experimentation programs, so they could be used to create improvements for internal testing.
“Most challenges fall under two categories,” stated Nguyen. “The first category revolves around experience, which is easier solved with training and resources. The second category is more about culture and ongoing nurturing, which is a bit more nuanced and difficult.”
What’s holding back people and teams who want to experiment? Here’s what they’re saying:
There’s a Lack of Experience
- “I’m too scared to learn new tools and processes.”
- “I’ve never experimented before.”
- “I have so many ideas, but I don’t know where to start? How do I prioritize what to experiment with?”
- “My hypotheses and experiments aren’t solving the right problems.”
- “What does this data even mean? I’m not sure how to analyze and interpret results.”
There Are Too Many Cultural Hurdles
- “Leadership says my focus is to deliver code/product, not to waste time experimenting.”
- “Whatever the highest paid person in the office decides, we follow.”
- “We just don’t have the resources, bandwidth, or time to do this.”
- “Teams are too siloed to collaborate on experiments.”
- “We’re just not a data-driven company; we’re not structured to look at reports or to interpret results.”
How Split @ Split Is Optimizing the Customer Experience
Recently through Split @ Split, our Experimentation Advisors tested new training materials and techniques on internal product and engineering teams. “We tried a fresh approach to instructor-led teaching and online education, because one of the challenges of onboarding customers was the complexity. The goal of this experiment was to develop digestible workshops and education that could remove friction and confusion,” said Nguyen. “Upon implementation, Experimentation Advisors discovered opportunities to improve, making several changes to the curriculum in the process. This was an insightful exercise, and it will evolve the way we train our customers moving forward.”
Plus, the benefits were a two way street. For the internal product and engineering teams who participated in Split @ Split, they discovered new ways to incorporate measurement, learning, and experimentation into their roles. In a safe environment on the Split platform, they were able to try, succeed, make mistakes, and learn throughout the process. “As they say in the experimentation world,” adds Nguyen, “you win some, you learn some”.
At Split, we reinforce that everyone should be in-tune with their data. From engineering to product metrics, understanding what’s important to the organization is crucial to making prioritizations and decisions. If teams have a sense of their feature performance and product usage, they can make data-driven decisions and further focus their experiments.
Rethink what’s possible in a space of psychological safety that lets you iterate without fear. Split is the platform to help you operationalize this across your organization.
Want to Dive Deeper?
For additional educational and relevant content, be sure to check out the following articles:
- 7 Ways We Use Feature Flags Every Day at Split
- Simultaneous Experimentation: Run Multiple A/B Tests Concurrently
- If Your Experiments Are Gray, Dimensional Analysis Adds Color
Deliver Features That Matter, Faster with Split
Split is a feature management platform that attributes insightful data to everything you release. Whether your team is looking to test in production, perform gradual rollouts, or experiment with new features–Split ensures your efforts are safe, visible, and highly impactful. What a Release. Get going with a free account today, Schedule a demo to learn more, or contact us for further questions and support.