In our last post of our brand-new series, “Oh, BEhave!,” we announced that Brooks Bell has partnered with Irrational Labs to bring behavioral economics (BE) into your experiment ideation process. Why? There are decades of experiments that your program could be using to inform your strategies! If you missed it, check it out here.
Testing tools are not all created equal. Here, we break down the WYSIWYG and share a guide to the pros, cons and perfect time to implement them.
Remarkable plans lead to remarkable performances, which lead to remarkable rewards. For optimization programs, proper planning is essential for quality tests, efficient execution, data-driven analysis and incremental revenue gains.
We didn’t listen to Willie Nelson, but we did gather a team, plan a road trip and head to the West Coast for two leading industry conferences.
Introducing “Oh, BEhave,” a new series to pique your behavioral economics interest!
Tune in every month with our strategy guru, Suzi Tripp, and her fellow behavioral economics enthusiasts from Irrational Labs, a nonprofit behavioral consultancy. Together, they’ll explore the principles and methodologies of behavioral economics (BE) – and try to BEhave!
A stellar holiday retail season is just around the corner, and according to Deloitte, retail sales are expected to top $1 trillion from November to January. Huge traffic increases and motivated shoppers provide a unique opportunity for your experimentation program.
Project management will help you win higher conversion rates, customer loyalty and revenue – it’s become a must-have in experimentation.
At Brooks Bell’s 8th annual Click Summit in May, I had the pleasure of leading a conversation titled, “What’s Fueling Your Experimentation Ideation?” Throughout the session, participants talked about the ways to use quantitative and qualitative data, past test learnings, behavioral economics principles and the challenges they face with executing tests to their full potential. (Download the top takeaways from this session, as well as all the “Clickaways” here.) But there was one more important attribute we discussed – the importance of the team!
Now you know how to Predetermine Your Test Sample Size and How to Reach Statistical Significance & Power within Your Experimentation Programs. Our final blog concludes the series and will expand your understanding of how to use Minimum Detectable Lift, or Minimum Detectable Effect for optimum test design and results.
Economists predict e-Commerce sales will range from $427 – $443 billion in 2017, a growth rate of three times higher (8-12 percent) than the entire retail industry. This upward trend will continue. In fact, Business Intelligence forecasts consumers will spend $632 billion in 2020.
This is the second of a three-part blog series. If you missed the first post, “Using Fixed Time Horizon to Generate Credible Optimization Results,” read it here. The final blog, “How to Understand Minimum Deductible Lift,” will be published next week.
Enterprise businesses continue adopting the concept of data-informed decision-making. They are shifting their organizational cultures to those where more and more decisions are based on facts and insights. At the same time, optimization continues growing in popularity among top brands and is essential for business success in today’s digital world.