A/B Testing Test

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Description: The A/B Testing test evaluates a candidate’s ability to design and analyze A/B tests in order to identify customer preferences and increase customer engagement and conversions.

It’s an ideal test for pre-employment screening of candidates applying for a variety of job roles, including digital marketers, marketing analysts, and user researchers. A good candidate for an A/B testing job will be competent in both test design and results analysis, and will understand how statistical significance impacts confidence levels. 

This test requires candidates to demonstrate the ability to identify appropriate metrics for A/B testing, set up rigorous tests, and produce actionable insights from analysis of test data.

Recommended Job Roles
Data Analyst
Digital Marketing Specialist
Growth Hacker
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A/B Testing Results Analysis Statistical Significance Public New

You were testing two new title ideas for a pricing page with the following results:

  Views Conversions
Original 4,300 436
Proposal A 4,000 440
Proposal B 3,700 415

Low Traffic


A/B Testing Sample Size Public New

You have a new client, who operates an eCommerce business receiving traffic of 500 visitors per week. The client insists on presenting you with a list of ideas for improving their website and expects you to approve or reject each idea after careful consideration.

In the list below, enter “Y” if you would approve the idea and “N” if you would reject the idea.

_____ 1. Testing small changes to the landing page to increase conversions by 2%.

_____ 2. Testing radically different redesigns of the landing page to increase conversions by 50%.

_____ 3. Test variations of the product page to increase Add to Cart clicks by 20%.

_____ 4. Test variations of the checkout process to increase completed purchases by 1%.

_____ 5. Use multivariate testing on your least-popular product pages to increase purchases.

_____ 6. Lower your statistical significance threshold to 75% to see the results of your tests more quickly.

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AB or Multivariate, Optimize Landing, Budget Allocation, Subscribe Button
A/B Testing Multivariate Testing Marketing Funnel Metrics Results Analysis Statistical Significance Test Design
Score Distribution
# of candidates
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