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Increase in Experimentation Velocity
Faster Decision-Making
Increase in Retention Rate
Fashion Technology
London, United Kingdom
Lyst is a fashion technology company, and premium shopping app. For over 160 million annual shoppers, they offer the most comprehensive range of products from 17,000 of the world’s leading brands and stores.
Snowflake, dbt, Looker, Amplitude, Eppo
Lyst, the global fashion shopping platform, sees experimentation as central to its product development. The team has overhauled its A/B testing framework and processes, with Senior Data Analyst Adam Lambert and Senior Product Manager Rita Steer-Jones ensuring the chosen solution would meet the company’s growing complexity and strategic goals.
The data team evaluated two leading vendors and ultimately chose Eppo as the superior solution, as it effectively solved both the technical and business challenges critical to Lyst's success.
Eppo brought all A/B testing workflows under one roof, drastically reducing the time from hypothesis to actionable insights. “All our experiments are in one place with traceable decision-making—a game-changer for consistency and accountability,” Adam noted.
Eppo’s intuitive design allowed product managers to independently set up and analyze experiments, reducing their reliance on data scientists. Adam noted, “We tried Statsig, but the PMs quickly asked, ‘Can you just give us Eppo, please?’ Rita added, “In just two minutes, I had a dashboard up and running with accurate metrics. PMs loved that Eppo was powerful, yet simple.”
Eppo’s clear documentation and transparency in explaining its Bayesian methodology were crucial. “We were able to easily QA underlying numbers and it built our trust that Eppo was using a well-implemented, rigorous Bayesian approach, instead of patching on Bayesian on top of a frequentist framework” said Adam.
Statsig’s eng-only approach left business users feeling sidelined. In contrast, Eppo fostered a true partnership between business and technical teams. “Eppo ensures everyone in the decision-making process is satisfied, fostering genuine collaboration,” said Rita.
Eppo’s dedicated support team made the implementation process smooth and swift, providing comprehensive training and continuous assistance. Adam noted, “The Eppo team has been outstanding. We were fully operational just two to three weeks after signing the contract.”
Lyst slashed the time from hypothesis to decision from days to minutes, tripling its experimentation velocity and enabling three times more tests each week.
Eppo’s advanced statistical methods like CUPED++, dramatically reduced experimentation run-time, allowing Lyst to make decisions weeks—sometimes even months—sooner. “We’re now seeing results at an unprecedented pace,” Adam shared.
Eppo has significantly improved leadership’s visibility into experimentation and outcomes. “The feedback from the C-suite and across the company has been glowing,” Adam shared. “They love having this level of visibility and access to high-quality analytics. It didn’t take long for them to say, ‘We want more of this—keep going.’”
An experiment to optimize Lyst's product ranking algorithm led to a 1% increase in onsite revenue. Adam emphasized,"Without Eppo, we might have overlooked this experiment. It previously would have been time consuming and hard to measure".
In just 2-3 targeted experiments in Eppo, the app onboarding team revamped the user onboarding flow, driving a 20% increase in app retention rates. Adam noted, “Eppo allowed us to quickly realign our focus, achieving in weeks what would normally take months. This 20% increase in retention significantly boosted our app lifetime value (LTV).
Eppo has enhanced Lyst’s approach to experimentation, improving efficiency, collaboration, and measurable business impact. With Eppo, Lyst has accelerated its decision-making and unlocked new growth opportunities, cementing its competitive edge in the market.