Audrey Guinn is an expert in Advanced Analytics and Marketing Segmentation. Below is a collection of blogs she has written.

Consumer Use of AI

Soggy Socks and Smart Decisions: How AI Is Changing the Way We Shop

AI is transforming moments of cognitive fatigue by acting as a personalized shopping assistant.

Naming Marketing Segments

4 Reasons To Name Your Own Segments

It’s important to name the segments according to your company’s needs.

4 Ways to Rescue a Market Segmentation

4 Ways To Rescue Your Segmentation

Here are four options that can be used to rescue a failing segmentation.

Segmentation Selection Criteria

Segmentation Selection Criteria

Non-mathematical factors play a pivotal role in identifying the best segmentation solution.

States Versus Derived Importance

Stated vs Derived Importance: What’s the Difference?

Stated importance are preferences that are directly articulated by the respondent.

Fancy Statistics do not Equal causation

Fancy Statistics Do Not Equal Causation

The only way to determine cause and effect is to control for all variables by utilizing an experimental design.

The IAT – A Guide for Marketing Researchers

The IAT – A Guide for Marketing Researchers

The Implicit Association Test measures implicit associations about topics such as race, sexuality, weight, etc.

Segmentation Question Types

The Top 5 Question Types to Include in Market Segmentation

Analyzing the data using a variety of these 5 question types gives a holistic view of the consumer market.

Structural Equation Modeling

An Overview Of Structural Equation Modeling (SEM) For Marketing Researchers

Structural Equation Modeling is a flexible multi-use tool in the marketing researcher’s pocket.

Multicollinearity

Multicollinearity – A Marketing Researcher’s Curse Word

Multicollinearity (also known as collinearity) occurs when two or more variables are very highly correlated.

Negatively Worded Items

It’s Time to Put Those Negatively Worded Items Behind Us

How can researchers catch cheaters if negatively worded attributes are no longer included in the survey?

Avoiding Type 1 Error

3 Avoidable Statistical Mistakes

Adhering to the rules of the scientific method ensures that results are valid and unbiased.

Strategy Research

Suppressors Demystified:

The Silent Influencers of Data in Statistical Modeling

What can researchers do when encountering problem suppressors?

Questionnaire Bias

When Results Lie:

Tips for Overcoming Questionnaire Bias

Biased questions can return results that may be untrue which favor a specific outcome. So what can we do to avoid bias in surveys?