A/B Testing Website Load Time Per-User Calculator FAQ
Answers to common questions about comparing control and variant load times, per-user waiting time, traffic splits, and result interpretation.
This FAQ explains the inputs and results in the A/B Testing Website Load Time Per-User Calculator. The calculations estimate differences in average waiting time and should be interpreted alongside a properly measured experiment.
General Calculator Questions
Basic questions about the calculator's purpose and outputs.
What does the A/B Testing Website Load Time Per-User Calculator measure?
It estimates the load-time difference per variant user, the percentage change versus control, the traffic-weighted average test load time, and cumulative time saved or added.
What does time saved per user mean?
It is the estimated difference in waiting time experienced by a variant user across the entered average number of measured page loads.
What does a negative result mean?
A negative time-saved result means the variant is slower and adds estimated waiting time for each exposed user.
Does this calculator predict conversion lift?
No. It measures load-time differences only and does not predict conversion, engagement, revenue, or retention.
Inputs and Measurement
Questions about selecting and entering consistent data.
Which load-time metric should I enter?
Use the same clearly defined metric for both control and variant. Do not compare different metrics between versions.
Why is page loads per user included?
It accounts for cases where a user experiences the measured page or event more than once during the test.
What should total test users include?
Use the users included in the relevant test period and population for the measured experiment.
How should I set variant traffic share?
Enter the percentage of total test users assigned to the variant, such as 50 for an even split.
Calculation and Interpretation
How the main results are calculated and read.
How are variant users calculated?
Total test users are multiplied by variant traffic share divided by 100.
How is the load-time percentage calculated?
The control-minus-variant difference is divided by control load time and multiplied by 100.
What is average test load time?
It is the control and variant load times combined using their traffic shares as weights.
Why is total time saved limited to variant users?
Only users who receive the variant experience its load-time difference relative to the control.
Accuracy and Use
Important boundaries when using load-time estimates.
Are the results statistically significant?
The calculator does not evaluate significance, confidence intervals, sample adequacy, or experimental validity.
Can averages hide performance problems?
Yes. Average figures can conceal slower experiences for particular devices, locations, networks, or user segments.
Does a faster variant prove a better user experience?
A faster measured load time indicates a performance difference, but broader user experience and experiment outcomes require separate evaluation.
Can I use the result to estimate a full rollout?
You can model a hypothetical full rollout by setting variant traffic share to 100%, while recognizing that real-world conditions may differ from the test.
What does this A/B testing load-time calculator measure?
It estimates per-user and cumulative waiting-time differences between a control and variant using average load times, traffic share, and page loads per user.
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