McGaw.io AB Testing Tracking Tool

This extension allows you to calculate the statistical significance & conversion rate of your A/B tests.

McGaw.io AB Testing Tool | Statistical Significance

McGaw.io AB Testing Tracking Tool is a Chrome extension designed to simplify the process of calculating statistical significance and conversion rates for A/B tests. It features a color-coded bar for easy understanding, a split test calculator, and direct comparisons of conversion results. With this tool, users can efficiently assess the performance of tests across various digital marketing mediums, ensuring they launch only significant and effective outcomes.

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Extension stats

By: https://mcgaw.io

Users: 602

-8

Rating: 5.00

(6)

Version: 3.0.0 (Last updated: 2022-08-01)

Creation date: 2018-04-06

Risk impact: Very low risk impact

Risk likelihood:

Very low risk likelihood

Manifest version: 3

Permissions:

storage

Size: 1.09M

Email: an*****@mcgaw.io

URLs: Website ,Privacy policy

Ranking

# 38,271 ▼ 18

Other rankings

#1668 in Workflow & Planning ▲ 9 #14 in testing keyword 9 ▲ 2 #42 in winner keyword 15 ▲ 4 #248 in analytics keyword 13 ▼ 4

Other platforms

Not available on Android

Not available on Firefox

Not available on Edge

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Extension summary

Analyze keywords

Our Statistical Significance Calculator features:

Color coded bar to show Statistical Significance
Split test calculator
AB Test Calculator
Direct comparison of conversion results.
Ability to calculate significance of ab tests anywhere and with any tool

You may be asking yourself, what is ab testing? Or even, why do I need to calculate it?

Well, lets makes this easy for you. AB testing is one of the cornerstones to digital marketing, it is when you test two version of your site, email, ppc or other mediums against each other to see which one win. That said, when you run one of these comparative tests, you need to make sure you have a calculate statistical significance.

See this great video to better understand ab testing: https://www.youtube.com/watch?v=QSk4czi3TCs

How do we calculate statistical significance? We use a probability calculator based on statistics which will help us know if one test has enough volume and distribution to have a higher probability of being the correct outcome. If you do not measure the level of significance, you may launch a split test winner to production and find out that the results were not good.

User reviews

It's a great start, but it'd be better if you could add multiple variants

Alex Merrick, 2023-04-11

Having my calculator right there all the time makes it so easy to monitor test results, no matter what tool I'm using for testing.

Nik Friedman TeBockhorst, 2020-04-03

This tool is a blessing! Makes it easy as pie to quickly determine A/B test winners and drive critical CRO decisions. Best of all, it sits right inside your browser so it's always just a click of a button away.