“Are We at Statistical Significance Yet?” – A CRO Analyst’s Guide to Handling Stakeholder Questions
Every CRO analyst eventually gets that message from a stakeholder:
“We made a change and clicks look higher—are we at statistical significance yet?”
“If not, how much traffic do we need before we can call this a result?”
“Should we run an A/B test, or can we just look at before-and-after numbers?”
These are great questions but answering them well requires reframing the problem. Here’s how to turn these stakeholder reach-outs into teachable moments and stronger testing practice.
Question 1: “Are we at statistical significance yet?”
This is the most common one. The instinct is to jump straight into calculations but here’s the catch: if the data comes from a pre vs. post comparison, significance testing doesn’t apply.
Why? Because user behavior changes over time. Different weeks bring different campaigns, traffic sources, and user intent. That means the two groups (before vs. after) are not equivalent. Any test of significance here would give a false sense of certainty.
Best Practice: Significance only makes sense when traffic is split simultaneously and randomly between control and variant. That’s what makes A/B testing the gold standard.
Question 2: “If not, how much traffic do we need?”
Stakeholders want a clear threshold: a finish line that says, “Now we know for sure.”
Here’s the principle to share: the traffic needed depends on the size of the effect you care about. A small improvement takes a much larger sample to detect confidently, while a big improvement shows up faster.
Best Practice: Tie sample size to the minimum detectable effect (MDE). Ask, “What’s the smallest lift that would actually matter for the business?” That sets the bar for how much traffic you need.
Question 3: “Is an A/B test better, or can we use personalization with a holdout?”
This is a strategy question, and the answer depends on timing.
A/B test: Best for proving whether the change works. Traffic is split evenly, so you get clean results faster.
Personalization with a holdout: Best for ongoing monitoring. Once you know something works, you can roll it out broadly but keep a small group as a “reality check.” The tradeoff is slower reads because the holdout group is so much smaller.
Best Practice: Use A/B to validate, holdouts to monitor. Don’t swap their roles.
Takeaway for CRO Analysts
When stakeholders ask these questions, don’t just provide numbers. Provide clarity:
Pre vs. post can hint, but not prove.
Sample size depends on effect size.
A/B tests confirm winners; holdouts track them.
By reframing the conversation this way, you not only answer the immediate question—you also help the team build a stronger experimentation culture where decisions are based on clean, trustworthy evidence.