A/B testing is a highly demanding and controlled skill that is mainly tested during interviews for data science. But there are very few resources that could assist you in preparing for A/B testing. As a result, most candidates give a poor performance as they lack resources to prepare for the test.

Moreover, the testing sector is also evolving, and with time, new concepts and approaches are being introduced each year. This means even a proficient data scientist who may have gone through A/B testing years back may not be able to crack it this year. If you want to be a skilled data scientist or enroll in data science courses in Bangalore, you should know how to ace A/B testing data science interviews.

What is A/B testing?

In simple terms, A/B testing is assessing and making comparisons of two variants to know which one performs best under a specific metric and in a controlled atmosphere.

It is also known as split testing, which is the process of testing two different versions. It can be either of a web page or product design or layout etc., for comparing their performance under the effect of the selected metric. It is done by casually showing one version to the user to know which suits better under the given metric. These metrics can be a page view, bounce rate, or conversion rate.

A/B testing assists PMs in making a data-driven decision that results in some objective enhancements in the product.

Importance of A/B testing

This type of experimental design is one among many ways to compare various aspects of the product that might be otherwise very difficult to measure. Different product elements are primarily thought to be subjective. Differentiating varied features from a conversion point of view is tricky without the help of a data-driven method like A/B testing.

A/B testing is crucial because it offers objective and measurable data on product elements that might be otherwise qualitative.

The primary goal of A/B testing is to measure that what version of a product gives better performance. Thus, it provides legitimate data to make the best decisions.

If you are undergoing a data science course in Bangalore and looking forward to ace the interview, then here are few things to keep in mind. Mainly an interviewer searches for good experimentation skills, especially for product data scientists or analytical product roles.

1. Examining the question: If the interviewer wants to know about your designing and analyzing skills, ask them questions to learn about their business goals and the product features. Here your interviewer will see whether you are trying to know about the business goals before experimenting. Testing without knowledge of the product goal is one of the big red flags.

Their goal can be anything, whether it is new user acquisition, enhancing conversion, or improving the number of orders. Understand it first before diving into experimenting.

2. Create hypothesis: Your interviewer will try to know whether or not you think of the secondary metrics as well as guardrail metrics along with primary metrics or not. Accordingly, you have to answer based on the business situation and demand.
3. Build a random plan: Selecting the level of significance, MDE, and the power to calculate the size of the sample and the test duration. Here your interviewer is judging you to know about your statistical skills and calculation of sample size as well as the total time. So, to arrive at the experiment design, you have to consider factors like network effect, seasonality, day of the week effect that can impact the test validity.

 Also, know about the baseline rate of conversions, the detectable difference, level of significance as well as your statistical power.

4. Selection of sample size and analysis of outcomes and drawing valid conclusions: Here, your interviewer will look for the best statistical tests that will be used in various scenarios. You can check for randomization and then offer the final suggestion.

Conclusion

Thus, we can say that performing A/B testing or investigation interviews for data science offers an edge to the whole hiring process. It also differentiates you from other aspirants. It is an excellent skill to master, and the returns are surely high.

So, if you are studying a data science course in Bangalore, then it is highly recommended to spend much time focusing on the essential concepts of A/B testing and prepare to face and do best in the interviews.