A b testing conferences

What is a A/B test?

A/B testing is a shorthand for a simple controlled experiment. in which two samples (A and B) of a single vector-variable are compared. These values are similar except for one variation which might affect a user’s behavior.

When did a/B testing start?

Experimentation with advertising campaigns, which has been compared to modern A/B testing, began in the early twentieth century. The advertising pioneer Claude Hopkins used promotional coupons to test the effectiveness of his campaigns.

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What is attending conferences for software testing?

Attending conferences is one of the best ways to keep-up on the latest in software testing and quality and of course connect with your peers in the larger communities. This list only contains conferences, un-conferences and workshops that are specifically for software testing and quality.

Experimentation Platform

Microsoft Teams is a communication platform [1]. It integrates meet, chat, call and collaborate in one place. The application updates multiple times a month [2], with additional new features and iterative improvements to existing features.

Methods considered

We proposed several methods to mitigate the impact of penetration difference and update effect. The key point is to only include users who have experienced application restart or update in the analysis.

Summary

We were trying to use A/B testing to compare build releases for Microsoft Teams. We identified that penetration difference and update effect may introduce bias to the A/B analysis. To mitigate this issue, we introduced an A/A’/B testing framework.

Acknowledgement

Special thanks to Microsoft Teams Experimentation team, Microsoft Experimentation Platform team, Microsoft Teams Client Release team, Paola Mejia Minaya, Ketan Lamba, Eduardo Giordano, Peter Wang, Pedro DeRose, Seena Menon, Ulf Knoblich.

Statistical significance

With the data we collected from the activity of users of our website, we can compare the efficacy of the two designs A and B. Simply comparing mean values wouldn’t be very meaningful, as we would fail to assess the statistical significance of our observations.

Discrete metrics

Let’s first consider a discrete metric such as the click-though rate. We randomly show visitors one of two possible designs of an advertisement, and we keep track of how many of them click on it.

Continuous metrics

Let’s now consider the case of a continuous metric such as the average revenue per user. We randomly show visitors one of two possible layouts of our website, and based on how much revenue each user generates in a month we want to determine if one of the two layouts is more efficient.

Continuous non-normal metrics

In the previous section on continuous metrics, we assumed that our observations came from normal distributions. But non-normal distributions are extremely common when dealing with per-user monthly revenues etc. There are several ways in which normality is often violated:

Mann–Whitney U test

This test makes no assumption on the nature of the sampling distributions, so it is fully nonparametric. The idea of Mann-Whitney U test is to compute the following U statistic.

Conclusion

In this article we have seen that different kinds of metrics, sample size, and sampling distributions require different kinds of statistical tests for computing the the significance of A/B tests. We can summarize all these possibilities in the form of a decision tree.

What is an A/B test?

A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or ” two-sample hypothesis testing ” as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject’s response to variant A against variant B, …

What professions use A/B testing?

Many professions use the data from A/B tests. This includes data engineers, marketers, designers, software engineers, and entrepreneurs. Many positions rely on the data from A/B tests, as they allow companies to understand growth, increase revenue, and optimize customer satisfaction.

Why did Obama use A/B testing?

In 2007, Barack Obama’s presidential campaign used A/B testing as a way to garner online attraction and understand what voters wanted to see from the presidential candidate. For example, Obama’s team tested four distinct buttons on their website that led users to sign up for newsletters.

Why was Google’s first A/B test unsuccessful?

The first test was unsuccessful due to glitches that resulted from slow loading times. Later A/B testing research would be more advanced, but the foundation and underlying principles generally remain the same, and in 2011, 11 years after Google’s first test, Google ran over 7,000 different A/B tests.

Why are A/B tests useful?

However, by adding more variants to the test, its complexity grows. A/B tests are useful for understanding user engagement and satisfaction of online features like a new feature or product.

When was the first randomized double blind trial?

The first randomized double-blind trial, to assess the effectiveness of a homeopathic drug, occurred in 1835 . Experimentation with advertising campaigns, which has been compared to modern A/B testing, began in the early twentieth century. The advertising pioneer Claude Hopkins used promotional coupons to test the effectiveness of his campaigns. However, this process, which Hopkins described in his Scientific Advertising, did not incorporate concepts such as statistical significance and the null hypothesis, which are used in statistical hypothesis testing. Modern statistical methods for assessing the significance of sample data were developed separately in the same period. This work was done in 1908 by William Sealy Gosset when he altered the Z-test to create Student’s t-test.

Can you see significant improvements in a test?

In these tests, users only see one of two versions, since the goal is to discover which of the two versions is preferable.

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Best Conferences of 2022

Attending conferences is one of the best ways to keep-up on the latest in software testing and quality and of course connect with your peers in the larger communities. This list only contains conferences, un-conferences and workshops that are specifically for software testing and quality.

Here is my short list of the Best Testing Conferences and Workshops to attend in 2022

Automation Guild Online Conference 2022 is an online conference from February 7-11, 2022.

Why Is Comparing Builds Through A/B Testing Insufficient?

Methods Considered

We Selected A/A’/B Testing

Summary

• We were trying to use A/B testing to compare build releases for Microsoft Teams. We identified that penetration difference and update effect may introduce bias to the A/B analysis. To mitigate this issue, we introduced an A/A’/B testing framework. The framework enables us to regularly perform product builds comparison in a trustworthy way and serve…

See more on microsoft.com

Acknowledgement

References