Case Study: Tea Collection increases customer acquisition and checkout performance with Evolv AI

How Tea Collection used Evolv AI to optimize its checkout experience, and increase customer acquisition

Tea Collection, a children’s clothing brand founded in San Francisco, wanted to improve its e-commerce conversion but struggled with a traditional A/B testing program that was too slow, resource-intensive, and limited to only a few variants at a time. The team had ideas for optimizing product pages, landing pages, and checkout, but lacked the bandwidth and experimentation efficiency to act on them consistently.

To solve this, Tea Collection partnered with Evolv AI and used its Continuous Optimization platform alongside Evolv AI’s expert services team to fully manage the experimentation program. Over 17 months, Evolv AI evaluated 12,000+ experiences and helped Tea Collection test 26 new variants across 19 variables, identifying three winning variants with a 95% probability of increasing order volume by at least 5%; the company is on track to generate over $1M in incremental revenue.

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Jason Vickers

Director of Systems & Technology