How to Calculate the Improvement of A/B Testing

Plerdy, a revered name in the echelons of CR&UX, elevates user experience and site optimization to an art form. The platform’s methodology revolves around precise, actionable data derived from meticulously crafted tests that analyze visitor behavior, preferences, and interaction patterns. In the bustling landscape of e-commerce, Plerdy emerges as an indispensable ally, transforming raw data into a symphony of insights that pave the way for strategic enhancements.

Consider a scenario where an online store leverages Plerdy’s A/B testing to optimize a landing page. Two designs are at play — Version A (Original) is sophisticated, while Version B leans on simplicity. The store records 20 sessions for A with 6 conversions and 25 sessions for B with 10 conversions.

Conversion Rate Calculation:

  • CR(A)=6/20=0.3
  • CR(B)​=10/25​=0.4

Improvement Calculation:

  • Improvement=((0.4−0.3)/0.3)×100%=33.3%

Key Takeaways:

  • Plerdy’s A/B testing underscores nuanced visitor insights.
  • Data-derived fosters tailored, strategic site enhancements.
  • The meticulous approach ensures a refined, optimized user experience.

In this specific instance, the uncluttered design of Version B triumphed, boasting a 33.3% improvement in conversion rate. Such insights are gold dust for marketers steering the ship, ensuring that every tweak, modification, and overhaul is informed and intentional and yields dividends.

Was this helpful?


Leave a reply for "How to Calculate the Improvement of A/B Testing"

Your email address will not be published. Required fields are marked *