November 4, 2022
Charlotte Fulcher
Path Analysis: Understanding what drives your market category

Path Analysis: Understanding what drives your market category

Understanding the mental path consumers take from brand perception to purchase decision is critical.

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.

“…what series of emotions or feelings need to be experienced before consumers will consider Brand X?”

Correlation Matrix

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 correlation matrix is 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’. For example, the correlation between Engineering doctorates awarded each year in the US and the consumption of Mozzarella cheese each year! Or, the number of murders each year by steam and the age of Miss America.

Clearly no one can claim any causal link between these 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.

With a large number of attributes, the number of potential causal connections is huge. So, the first step is to develop a theoretical model of the relationships between the attributes and the behaviour. Next, to test the model using Path Analysis.

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 examines a large number of multiple regressions among the variables. It can therefore be used to validate a model of consumer behaviour.

This is a powerful technique because it means we can build a psychological model of the drivers in a market category. We can answer the question; “what series of emotions or feelings need to be experienced before consumers will consider Brand X?”. These insights can inform new product development, brand promises, and brand creatives used in marketing.

Applying Path Analysis

A recently published article by Boobalan et al (2021) showed how path analysis can be used to identify causal connections between specific psychological reward systems and the purchase of organic foods. In particular, how the purchase of organic food is driven by 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 behaviour can make us feel useful, respectable, and as though we are making a helpful contribution to our community. This could be coined as “the warm glow of giving”, even inferring a sense of health and wellbeing.

Self-expressive benefits arise from the signalling of our interests. Demonstrating our green credentials brings happiness as others express their gratitude or admiration in the behaviour. By being green, people can project a positive image and get social approval or social validation. It shows that they care about something greater than themselves, that they are concerned about environmental issues and that they want to be seen as someone who is concerned about environmental issues.

These two constructs were shown in this research to drive positive consumer attitudes and in turn to drive purchase behaviour in the context of organic food consumption. 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.

By understanding Path Analysis, we can understand the benefits of the model of brand equity developed by Split Second Research and our account of why people buy stuff – in particular the need for social validation. This basic need is associated with three main psychological benefits: an increase in positive self-esteem (the need to be valued by other people and is the difference between where one wishes to be in life and how close they are to attaining it), an increase in the feeling of having a meaningful existence (to feel connected to one’s past and one’s future and the pursuit of fulfilment) and a stronger sense of self-identity (the need to feel distinct as a person and expressed by overtly identifying with a sentiment fad, fashion, or idea).

About Split Second

Split Second Research has been using Path Analysis for clients in a range of diverse market categories across the globe, from establishing why people opt for certain types of holidays to understanding what makes them visit their favourite store to buy products for their children, to what drives shopper behaviour when they are in a hurry, and similar.

If you are interested in finding out more about how we can apply our technology to you brand, product or service

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