Analytics

Truly Understanding Minimum Detectable Effect

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.

How To Reach Desired Confidence & Power Levels with Your Experimentation Programs

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 hereThe 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.

Using Fixed Time Horizon to Generate Credible Optimization Results

This is the first of a three-part, weekly blog series, which shares optimization best practices for test sample size, desired significance, power, and Minimum Detectable Lift (MDL).

Technology and evolving consumer behaviors are transforming the way people evaluate products and services to the way they pay for the things they buy. As optimization experts, Brooks Bell knows testing is the most effective and reliable way for merchants to determine which marketing strategy – from a specific promotion or targeted message to a unique website element such as a Call to Action (CTA) – will produce the highest Return on Investment (ROI).