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Glossary of A/B Testing Terms for Marketers

A visually engaging digital library setting with books and floating 3D words such as conversion rate, control group, variable, and statistical significance, subtly incorporating modern digital tools l
Ada Astralis
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Glossary of A/B Testing Terms for Marketers

Welcome to the ultimate glossary of A/B testing terms for marketers. Whether you’re a seasoned pro or a newbie in digital marketing, understanding these terms will help you navigate the world of A/B testing with ease. Let’s dive right in and decode the lingo that powers successful A/B tests.

A

  • A/B Test: A randomized experiment with two variants, A and B. It’s used to compare two versions of a webpage or app against each other to determine which one performs better.
  • A/B/n Test: Similar to A/B tests but with more than two variations, often referred to as multivariate testing.
  • Alternative Hypothesis: The hypothesis that there is a significant difference between the variations in your test.
  • Average Order Value (AOV): A metric that measures the average total of every order placed over a defined period of time.

B

  • Baseline: The control version of the test, typically the existing version of whatever you’re testing.
  • Bayesian Statistics: An approach to statistics that interprets findings in terms of probability statements that express a degree of belief.
  • Bounce Rate: The percentage of visitors who navigate away from the site after viewing only one page.

C

  • Call to Action (CTA): A prompt on a website that tells the user to take some specified action, often presented as a button or hyperlink.
  • Confidence Level: A measure that indicates how certain you are that your sample accurately reflects the population.
  • Conversion: The process of turning a visitor into a customer or getting the visitor to complete a desired action.
  • Control: The version of a webpage or app that you are testing against; the ‘original’.

D

  • Dependent Variable: The variable you measure in the experiment and what is affected during the experiment.
  • Direct Traffic: Visitors who enter your site’s URL directly into their browser or have it bookmarked.

E

  • Experimentation: The process of conducting tests or trials to discover how different features or experiences perform.

F

  • Funnel: The path or steps visitors take from initial interest to final conversion.

G

  • Goal: The specific target you aim to meet through your marketing efforts, like sign-ups, purchases, or engagement.

H

  • Heatmap: A visual representation of where users click or scroll on a page.
  • Hypothesis: A proposed explanation made on the basis of limited evidence as a starting point for further investigation.

I

  • Independent Variable: The element you change in an experiment to test its effects on the dependent variable.

K

  • Key Performance Indicator (KPI): A measurable value that demonstrates how effectively a company is achieving its key business objectives.

L

  • Landing Page: The webpage on which a visitor first lands or arrives after clicking a link or ad.
  • Lift: The increase in performance you see from your new variation versus the control.

M

  • Multivariate Testing (MVT): Testing multiple variables at the same time to understand the effect of changes.

P

  • P-value: A measure of the probability that an observed difference could have occurred just by random chance.

R

  • Randomization: The process of making something random; in the context of A/B testing, ensuring test subjects are allocated randomly.
  • Reach: The total number of people who see your content.

S

  • Segmentation: The process of dividing your audience into segments based on characteristics like demographics, behavior, and more.
  • Statistical Significance: A determination that the relationship between variables in your experiment is not due to random chance.
  • Split Testing: Another term for A/B testing, where traffic is split between two versions to determine which is more effective.

T

  • Traffic: The visitors to your website.
  • Treatment: Another term for the variation in an A/B test.
  • Turnover Rate: The rate at which visitors leave the site after visiting.

V

  • Variation: The different versions or alternatives in a test.
  • Visitor: An individual who goes to your website.

Now that you’re armed with a comprehensive glossary of A/B testing terms, go forth and optimize! Remember, every term you grasp gets you a step closer to mastering the science of A/B testing and making data-driven decisions that propel your marketing strategies forward.

 

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