You Probably Don't Need A/B Testing| Oliver Palmer

Today’s Guest Oliver Palmer

Here's a summary of the great stuff that we cover in this show:

A/B testing involves simultaneously implementing different approaches, measuring results, and determining the most effective one, commonly used in Conversion Rate Optimization (CRO).
Despite its popularity, businesses often default to A/B testing without assessing its necessity, driven by industry success stories and a fear of falling behind, even though actual success rates are relatively low (5-10%).
User research is promoted as a more effective alternative to A/B testing, providing insights into user behavior, needs, and motivations. It is considered cost-effective, less time-consuming, and more likely to lead to sustainable success.
The need for minimum traffic for meaningful A/B testing depends on statistical factors, with larger traffic volumes being more conducive to productive testing. A/B testing calculators can help determine the optimal duration of experiments.
The "Holy Trinity" of optimization comprises User Research, A/B Testing, and Analytics. Analytics tools like Google Analytics are crucial for understanding user behavior, and a balanced approach, considering factors like traffic volume, should guide decision-making.

Links & Resources from today’s show

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