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03
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09
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21

New Ways of Understanding What Drives Your Market

Path Analysis: New Ways of Understanding What Drives Your Market

Do you ever wonder about the mental path a consumer takes from feeling a certain way about a product and then making the decision to buy it? Path Analysis is a statistical tool that has been around for 100 years but only recently has been seen as a way of understanding consumer purchase decisions. Market researchers can use it to build models of the variables that lead to a decision - such as the emotions and feelings consumers have about brands and the way they choose between them.

Path analysis is applied to a body of data that measures feelings and attitudes to one or more brands in a category. The first step is to create a correlation matrix - a table that contains how each attribute is correlated with every other attribute. Somewhere in this data are the causal connections between them. Usually, with correlated data, inferring causality is a no-no. There are many examples of so-called ‘spurious correlations’ (the correlation between Engineering doctorates awarded each year in the US and the consumption of Mozzarella cheese each year; the number of murders each year by steam and the age of Miss America!). Clearly no one can claim any causal link between these kinds of correlations, and indeed any other observed correlation between two measurements. However, and back to our correlation matrix, there are techniques for looking at the relationship between one particular measure against a collection of other measures in the correlation matrix. 
However, with a large number of brand attributes, the number of potential causal connections becomes huge. So, it’s no good just trying to search for them, a strategy is needed. This involves developing a theoretical model of the relationships between the attributes and the behaviour. Once we have a model we can then test it using the method of Path Analysis.

But what is Path Analysis?

Path Analysis is a type of structural equation modelling (SEM) that focuses on a series of multiple regression analyses. A multiple regression analysis can tell if two or more variables, like brand attributes rated by a consumer, have a causal relationship with another, such as purchase intention.
Path Analysis can be used to validate a model of consumer behavior because it examines a large number of multiple regressions. We can use it to build a psychological model of the drivers in a market category. It can answer questions such as which emotions need to be experienced before consumers will consider Brand X? These insights can inform new product development, brand promises and brand creatives in marketing

Applying Path Analysis

A recent article showed how Path Analysis can be used to help identify causal connections between the purchase of organic foods and specific psychological rewards that the authors termed “warm glow” and “self-expression”.

Warm glow is described as an intrinsic good feeling, a strong feel good factor. Environmentally friendly behavior can make one feel respected, it makes us feel like we are making a contribution to society. It makes one experience “the warm glow of giving” and the feeling that one is healthier.

When we make the choice of being a green consumer, others may express gratitude or admiration for our behavior. This overt announcement of one’s green credentials brings happiness and self-expressive benefits. When people project a socially acceptable green image, they get approval and validation. They are showing that they care about environmental issues, but also that they want to be seen as someone who is concerned about these issues.

The research shows that these two constructs drive positive attitudes and purchase behaviour among the consumers of organic food. We can conclude that people buy organic food products because they promise a higher sense of personal reward and because they help consumers feel socially validated. Marketers can then use this information by developing brand propositions and marketing creatives that bring this insight to life.

As we saw, Path Analysis can be a useful tool in our journey to understand why people buy stuff, especially in relation to the need for personal reward and social validation. Other research shows that these basic needs are associated with three psychological benefits: an increase in positive self-esteem, in the feeling of having a meaningful existence and a stronger sense of identity.

If you want to learn more about how Split Second Research applies Path Analysis in a range of diverse market categories, contact our experts.


ebooks
07
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08
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21

Brand Equity and Brand Associations

03
.
08
.
21

New Ways of Understanding What Drives Your Market

Path Analysis: New Ways of Understanding What Drives Your Market

Do you ever wonder about the mental path a consumer takes from feeling a certain way about a product and then making the decision to buy it? Path Analysis is a statistical tool that has been around for 100 years but only recently has been seen as a way of understanding consumer purchase decisions. Market researchers can use it to build models of the variables that lead to a decision - such as the emotions and feelings consumers have about brands and the way they choose between them.

Path analysis is applied to a body of data that measures feelings and attitudes to one or more brands in a category. The first step is to create a correlation matrix - a table that contains how each attribute is correlated with every other attribute. Somewhere in this data are the causal connections between them. Usually, with correlated data, inferring causality is a no-no. There are many examples of so-called ‘spurious correlations’ (the correlation between Engineering doctorates awarded each year in the US and the consumption of Mozzarella cheese each year; the number of murders each year by steam and the age of Miss America!). Clearly no one can claim any causal link between these kinds of correlations, and indeed any other observed correlation between two measurements. However, and back to our correlation matrix, there are techniques for looking at the relationship between one particular measure against a collection of other measures in the correlation matrix. 
However, with a large number of brand attributes, the number of potential causal connections becomes huge. So, it’s no good just trying to search for them, a strategy is needed. This involves developing a theoretical model of the relationships between the attributes and the behaviour. Once we have a model we can then test it using the method of Path Analysis.

But what is Path Analysis?

Path Analysis is a type of structural equation modelling (SEM) that focuses on a series of multiple regression analyses. A multiple regression analysis can tell if two or more variables, like brand attributes rated by a consumer, have a causal relationship with another, such as purchase intention.
Path Analysis can be used to validate a model of consumer behavior because it examines a large number of multiple regressions. We can use it to build a psychological model of the drivers in a market category. It can answer questions such as which emotions need to be experienced before consumers will consider Brand X? These insights can inform new product development, brand promises and brand creatives in marketing

Applying Path Analysis

A recent article showed how Path Analysis can be used to help identify causal connections between the purchase of organic foods and specific psychological rewards that the authors termed “warm glow” and “self-expression”.

Warm glow is described as an intrinsic good feeling, a strong feel good factor. Environmentally friendly behavior can make one feel respected, it makes us feel like we are making a contribution to society. It makes one experience “the warm glow of giving” and the feeling that one is healthier.

When we make the choice of being a green consumer, others may express gratitude or admiration for our behavior. This overt announcement of one’s green credentials brings happiness and self-expressive benefits. When people project a socially acceptable green image, they get approval and validation. They are showing that they care about environmental issues, but also that they want to be seen as someone who is concerned about these issues.

The research shows that these two constructs drive positive attitudes and purchase behaviour among the consumers of organic food. We can conclude that people buy organic food products because they promise a higher sense of personal reward and because they help consumers feel socially validated. Marketers can then use this information by developing brand propositions and marketing creatives that bring this insight to life.

As we saw, Path Analysis can be a useful tool in our journey to understand why people buy stuff, especially in relation to the need for personal reward and social validation. Other research shows that these basic needs are associated with three psychological benefits: an increase in positive self-esteem, in the feeling of having a meaningful existence and a stronger sense of identity.

If you want to learn more about how Split Second Research applies Path Analysis in a range of diverse market categories, contact our experts.


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