Here’s How to Build a Culture of Experimentation

Get a team on board and your framework in place, then add a touch of courage to think creatively.

Written by Kevin Li
Published on Mar. 07, 2024
Here’s How to Build a Culture of Experimentation
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In the world of technology, organizational culture is hard to solve for. Despite its intangibility, a culture rooted in experimentation unlocks tangible benefits for teams looking to stay competitive.   

3 Benefits of a Culture of Experimentation

  1. Teams can gather empirical evidence, make data-driven decisions and remove guesswork workflows.
  2. It helps avoid unnecessary headaches and expense when adding new tech to the business.
  3. It speeds up progress and minimizes risk.

A culture of experimentation is grounded in a shared mindset that encourages exploring, testing and implementing new ideas. It goes beyond the standard tech adage to move fast and break things — it’s not about disruption at all costs. Experimentation prioritizes studying a well-developed hypothesis and using data to validate the outcome; it’s about trying new things and learning from successes and failures.  

I’ve been fortunate enough to work with a company that has a culture and history rooted in experimentation. Optimizely has incorporated a test-and-learn philosophy into its DNA since the initial explosion of A/B testing, enabling it to equip digital marketers with invaluable data, improved targeting capabilities and reduced risk as they’ve designed and shipped websites, apps and emails.

There’s more transformation to be found where philosophy and technology intersect. Here’s the playbook we’ve adopted to build a productive culture of experimentation. 

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Get the Full Team on Board

Experimentation is not something you can do on your own. While it may be hard for an entire unit to dive headfirst into wild and quick experimentation, the more teammates you have interested in testing and learning, the better your outcome will be.  

The outcomes of the experiments, not the opinion of the highest-paid person in the room, should inform strategy. 

At Optimizely, sometimes six or seven teams must be looped in when working on something as minor as testing a new website feature. Our developers and designers and our analytics and compliance teams all work together to change the color of a button on our homepage. Even executives need to have faith in the tests being run. The outcomes of the experiments, not the opinion of the highest-paid person in the room, should inform strategy.  

To get others on board, emphasize the value experimentation adds for everyone from the marketing team to those in R&D. Assure team members that they will be free to explore their ideas, test hypotheses and make decisions independently within a collaborative environment that values their contributions and trusts their skills. You should also highlight that experimentation allows engineers to gather empirical evidence, make data-driven decisions and remove the messy guesswork from workflows.


Get the Right Framework in Place

As product professionals, we’re no strangers to trying to make sense of data and digital noise.  

At first glance, adding variables into a workflow might seem like it adds unnecessary complexity to solidified operations. But at the end of the day, experimentation aims to generate data to support or reject a hypothesis.  

The right frameworks and tools for experimentation will be the ones that seamlessly integrate with existing systems, making it easier for teams to incorporate experimentation into their day-to-day tasks without disrupting ongoing projects or processes. My team has unlocked immense value by finding harmony between elements of our tech stack and leaning on tools that can talk to others.  

I’d even go so far as to suggest you bring the same energy to your tech adoption. Use a test-and-learn approach as you’re figuring out the right tools to make your experimentation program work. Testing the time, cost and employee bandwidth inputs required to use a new platform or software against another allows you to assess the limitations and strengths of the individual models before fully adapting them to your workflows. A bonus of experimentation: you can avoid unnecessary headaches and expenses.   

 

Have the Courage to Think Outside the Box

A hard truth that guides our organization’s experimentation mindset is this: Eighty-eight percent of feature or web experiments are not winners.  

That means a few isolated A/B tests aren’t enough to sustain ongoing, confident marketing decision-making. It also shows the importance of constantly being open to new ideas because someone’s first guess for a feature or project is likely not a winner. The best experimenters are always searching for informed choices about which tests to run and thinking outside the box for what’s next.  

New technology, like generative AI, can push us outside our comfort zone. There’s potential for any savvy user to let AI discover options for experiments they never would have thought of themselves, becoming a critical tool in brainstorming. AI-powered conversational chatbots will be invaluable partners in the creative and technical process, serving as sounding boards with access to boundless information.

For example, a marketer at my company might ask a conversational chatbot how a call-to-action for a campaign can be personalized. On the receiving end, a chatbot might surprise them by recommending testing the call-to-action’s length instead of its tone.  

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Test Constantly

Although experimentation may be new to your team, there’s no reason to shy away from it. By constantly testing and iterating, organizations can optimize processes, products and strategies over time, leading to better outcomes and performance. 

A culture of experimentation is a natural progression for innovation-minded tech professionals. Experimentation pushes the boundaries of what’s possible, and with every test we run, we all get closer to true certainty amidst our industry’s chaos.  

Cultivating, then sustaining, a culture of experimentation has encouraged us to boldly test-drive new ideas at Optimizely for years. Today, every company employee is constantly looking to test parts of their workflow. We have this legacy of experimentation to thank for our success in everything from improved customer relationships to their new exploration of AI. It’s a tried and true strategy that accelerates progress, minimizes risk and optimizes value endlessly.

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