Sephora, a multi-national chain owned by luxury conglomerate LVMH, depends on the loyalty of its highly-engaged customer base to drive revenue, customer lifetime value (CLV), and new business through word-of-mouth and product ratings.  As a brand with a large responsibility to cater to its family of customers, the desire for a personalized experience is a critical focus with a direct impact on the bottom line.

Sephora turned to Evolytics for additional hands on deck to progress their personalization practice, as well as an outside view into the structural solidity of its testing culture. 


Through a Team Augmentation partnership, Evolytics was able to increase speed and efficiency of test analysis, freeing up site areas for future tests and ensuring prompt implementation of the highest monetization opportunities. 

In order to progress beyond executional A/B Testing, the corporate testing culture must be inherently understood, practiced, and documented. Delivering a world-class personalization experience in a test and learn culture means leveraging a wide variety of tools such as Adobe Target, Certona, Braze, and APT. It also means cross-channel experimentation to ensure consistent personalization across the user journey. By embedding ourselves as members of the Testing and Personalization team, examining current practices with a fine-toothed comb, bringing to light areas of opportunity, and building upon systemic knowledge, Evolytics was able to create a thorough training curriculum, equipping teams with the confidence and resources needed in order to scale testing and personalization efforts.


In partnership with Sephora, Evolytics maximized the Testing and Personalization team’s potential while bringing added value in the form of documentation and streamlined processes. 

Examples include:

  • Implementation of Adobe Workspace as primary tool for performance analysis and evaluation, inclusive of tracking requirements documentation, project brief access, and results
  • Streamlining of Testing & Personalization  process
  • Development of scalable cross-functional test read templates
  • Construction of statistical analysis metrics within Adobe Analytics
  • Introduced methodologies to track customer behavior prior to and following test live dates

Related A/B Testing Blog Posts

A/B testing and experimentation insights and best practices.

How to Analyze Inconclusive A/B Test Results
How to Analyze Inconclusive A/B Test Results

It’s all fun and games until your A/B Test is flat-tastic. Unfortunately, the ideal isn’t always real, and inconclusive A/B…

How to A/B Test During COVID-19
How to A/B Test During COVID-19

A field guide to experimentation in spite of coronavirus and finding the new normal When the effects of the coronavirus…

Why COVID-19 is a Great Time to Optimize Your A/B Testing Program
Why COVID-19 is a Great Time to Optimize Your A/B Testing Program

Now is the perfect time to start or bolster an experimentation program UnSplash It’s difficult to prioritize experimentation during an…

How to Run A/B Tests with Small Sample Sizes
How to Run A/B Tests with Small Sample Sizes

Successful digital optimization programs don’t need unlimited traffic. How to deal with small sample sizes is one of the most…