Tag: decision-making

Eight Mistakes Every Rookie Experimentation Team Makes (& How to Avoid Them)

If testing were easy, everyone would do it. But that’s simply not the case. Rather, experimentation requires extensive learning, hard work, lots of experience and a unique set of skills to consistently produce results that have a meaningful impact on a business. At Brooks Bell, we’ve spent the last fifteen years helping global brands build […]

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If testing were easy, everyone would do it. But that’s simply not the case.

Rather, experimentation requires extensive learning, hard work, lots of experience and a unique set of skills to consistently produce results that have a meaningful impact on a business.

At Brooks Bell, we’ve spent the last fifteen years helping global brands build and scale their experimentation programs. Drawing on that experience, we’ve identified eight common mistakes that rookie experimentation teams often make in the first few months of testing. We’ve also detailed useful and actionable strategies to help you navigate these challenges as you work to establish your optimization program. 

Mistake #1: Testing Without a Hypothesis

While the importance of a hypothesis may seem obvious, it’s easy to get swept up in the excitement and politics of launching the first test without realizing you haven’t determined a clear expectation for the outcome.

Without a defined hypothesis, it’s difficult (if not impossible) to make sense of your test results. Additionally, a well-articulated hypothesis can shape the entire test creation, evaluation, analysis and reporting process. It also makes communication and coordination across teams—another common challenge for new programs—much easier.

Learn strategies to avoid this misstep, along with seven other common rookie mistakes for newly established experimentation teams. Get the white paper.

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Part 2: Our Top Takeaways from Click Summit 2018

Last week, we shared the first of many takeaways from Click Summit 2018, our annual conference for professionals in digital experimentation and personalization. This week, we’re back with more insights from each impactful conversation, inspired by this year’s edition of Clickaways. 1. Manage the three P’s of scaling your testing program: people, process, prioritization. Many companies […]

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Last week, we shared the first of many takeaways from Click Summit 2018, our annual conference for professionals in digital experimentation and personalization. This week, we’re back with more insights from each impactful conversation, inspired by this year’s edition of Clickaways.

1. Manage the three P’s of scaling your testing program: people, process, prioritization.

Many companies have found it more effective to establish a dedicated optimization team rather than having these duties dispersed across the organization. However, if that’s not possible for you, let your Center of Excellence take the lead on defining key processes, training and developing a maturity model to determine when each team is ready to start testing.

Develop a formal process for submitting, presenting, prioritizing and executing new testing ideas. Using various automation technologies can further simplify these steps.

Additionally, agree to one source of truth for your test results across multiple platforms. Companies that have various groups looking at different data sources struggle to establish the necessary credibility to scale their programs. This is one area where a knowledge platform that houses testing results, insights and ideas (like Brooks Bell’s Illuminate platform, or Optimizely’s Program Management) can help.

Finally, growing your experimentation program comes with the expectation of more tests, executed faster. When determining your velocity goals, be sure to consider quality over quantity. Always prioritize running a few, quality tests over many, low-impact tests.

2. Personalization and optimization teams should remain separate functions with connected but distinct goals.

Personalization is a worthwhile investment for any online industry, but it has to be adopted as a company-wide strategy in order to ensure you’re delivering a consistent customer experience.

To get the most out of your investment, establish a separate personalization team to run your program rather than looking to your existing experimentation team. Here are a few reasons for this: First, personalization is a longer-term strategy and “wins” occur at a much slower rate. Additionally, while there are similarities between A/B testing and personalization technologies, the questions you ask and the answers you get are very different.

Finally, running split tests is inherently easier and faster than implementing personalization. So long as your team is overseeing both functions, they’re likely to focus more on testing than personalization.

3. Focus on organizational outputs and customer insights, not just test outcomes.



Oftentimes, experimentation professionals find themselves nearest to the customer. Sure, you may not speak with them directly, but your work can have a direct effect on your customers’ experience and brand perception. That’s a lot of power, but also a lot of opportunity.

So here’s the challenge: Go beyond simple tests like button color or check out features and consider the bigger picture. Use testing to seek out insights that would be useful for other departments within your organization.

Here at Brooks Bell, we have our own framework for doing this (and we’d be happy to tell you about it). In lieu of our services, we’d encourage you to take a step back from test outcomes, spot trends and use these to develop testable customer theories.

Developing a customer theory requires you to conduct a deeper interpretation of your results–so don’t do it alone. Look to your working team to brainstorm customer theories and additional tests to validate or invalidate those. Bring in additional data sources like NPS, VOC or qualitative research to paint a more detailed picture of your customers.

Doing this can have huge implications for your customers, your experimentation program and your brand overall.

4. Build a program that strikes the perfect balance of innovation and ROI.

In order for creativity to flourish within your experimentation program, you have to establish clear goals. These are used as a framework within which your team can look for opportunities to innovate.

Develop a process for brainstorming test ideas that encourages participation and creative thinking, like using Post-It notes.



Finally, demonstrate a willingness to take calculated risks in order to make room for creativity in your optimization strategy. There is always something to be learned from negative or flat results.

Like the information in this post? Download this year’s Clickaways to access more tips, tricks and ideas from Click Summit 2018.

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