When this topic matters
You have two scripts. Which is better? Without testing methodology, answer is based on feelings, not data.
Testing scripts requires: clear metrics, sufficient sample size, and control of other variables.
What happens in practice
Most "testing" is: 1) Too small sample (10 calls is not a test). 2) No variable control (different operator, different time). 3) Wrong metrics (connection rate instead of conversion rate).
Result: script changes based on impressions, not data.
Why it fails
Small sample: random fluctuations look like trends. 5 meetings from 20 calls vs 3 from 20 may be chance.
Uncontrolled variables: different operator, different hour, different segment — you do not know what caused the difference.
How to think about it
A/B test methodology: 1) One operator, one segment, same time. 2) Minimum 50-100 calls per variant. 3) Measure conversion rate to next step, not just connection.
Rule: test one thing at a time. If you change opener and closing simultaneously, you do not know what worked.
- Control: same operator, segment, time
- Sample: 50-100 calls per variant
- Metric: conversion rate to next step
- Isolation: one change at a time
What you gain and what you lose
Rigorous testing: reliable data, better decisions. But takes longer and requires discipline.
Quick "testing": faster decisions, but based on low-quality data.
When to apply
Rigorous testing makes sense for repeated campaigns where small improvement has large cumulative effect.
For one-time campaigns, quick iteration may be more effective than waiting for statistical significance.
Test one thing at a time, with sufficient sample size (50-100+), and control other variables. Measure conversion rate, not connection rate.