Semantic Differential: When to use it, when not to and why

The semantic differential is one of the most common tools to measure attitudes in marketing research. It is based on cognitive psychology and aims at understanding how specific consumer experience such as building brand loyalty is represented in consumer mind. Semantic rating scales help measure connotative meaning of consumer products or concepts and then the connotations are used to extrapolate foundational attitudes towards a specific product.

The essence of the semantic differential is the bipolar adjectives. Consumer products or concepts are measured by a series of bipolar scales such as

Slow __ __ __ __ __ Fast

Weak __ __ __ __ __ Powerful

To use it effectively we need to understand where it works well, where it doesn’t work so well and how to analyze the data.

LEVEL 1 – RATIONAL PRODUCT RELATED BENEFITS: One of the most typical ways to use semantic differential is to formulate rational product benefits. For example, in evaluating cars we might want to use adjectives like fast – slow, powerful – weak, safe – unsafe.

Benefits: Respondents find it easy to express their perception of a product or concept based on these adjectives. Also it is clear how to utilize findings from this type of exercise in the design of marketing strategy by emphasizing the relevant product benefits.

Drawbacks: However, when it comes to the effectiveness of such adjectives to predict consumer behavior, there are a number of studies showing that rational product benefits are not the strongest “drivers” of consumer choice.

LEVEL 2 – BENEFITS RELATED TO EMOTIONAL STATE OF THE RESPONDENT: Many brands try to convert functional benefits into emotions. For example, BMW transforms performance into a form of emotional aggression. Mercedes translates reliability into a form of emotional reassurance. Consequently, some researchers find it useful to measure products or concepts using expected emotional states that these products would be associated with in the consumer mind.

Benefits: Consumers generally find emotions a relevant measure of their perception of a product. Also emotional benefits are better predictors of consumer behavior and can serve as a solid foundation for marketing strategy.

Drawbacks: At the same time it is difficult to interpret the ratings of emotional benefits in an actionable way and convert “courage” or “closeness” into marketing and branding tactics.

LEVEL 3 – ADJECTIVES RELATED TO SENSUAL MODALITIES: Some researchers go even deeper and scale products based on adjectives that are related to sensual modalities such as “clear”, “eye-catching”, “loud”, “bitter”, “sweet”. This level of analysis is actively utilized in different psychological theories such as “subjective semantics” (developed by Soviet psychologist Elena Artemyeva) and neuro-linguistic programming (NLP)

Benefits: Arguably this is the most basic level that every cognitive experience is built on and can provide the best explanatory power in our attempt to predict consumer choice.

Drawbacks: The obvious challenge is how to utilize these findings in the design of marketing strategy.

How to analyze the results: The most typical analysis of semantic differential data is mean or median of the scale. Some researchers use factor analysis trying to group different scales into more general “themes” to improve the interpretability of the results. It is also useful to run regression analysis of the scaled responses against the consumer self-reported behavior (such as likelihood to choose a specific product) to identify the most critical adjectives to use in the marketing planning.

When it comes to generating consumer insights market researchers have many options in their toolkit. Semantic differential is one of them that should be utilized when it comes to the measurement of consumer attitudes.


Dr. Sergey Veselovsky

Dr. Sergey Veselovsky is Vice-President of Leger Analytics. He has a Ph.D. in Political Science and 15 years of experience in providing innovative research solutions for a wide variety of industries. He has taught market research and social system analysis at Brock & Kiev State Universities, and has held senior research positions with several research and consulting companies in North America and Europe. He has worked with numerous Fortune 500 brands, including pharmaceutical, financial and not-for-profit organizations. Dr. Veselovsky has co-authored several articles on market research design and advanced analytics.