Analyzing Consumer Perceptions
Understanding how consumers “see” the firm, brand, or product relative to competitors is important It is helpful to check whether the desired product positioning has been achieved or not
Data Collection & Profile Analysis
There are a variety of ways to collect perception data, including:
1. Rating Scale (ex. L’Oreal used a 1-10 scale to indicate the extent to which consumers agreed with statements such as “Plentitude is technologically advanced”; where 1 = completely disagree and 10 = completely agree.
2. Semantic Differential Scale – a variant of the rating scale, the semantic differential scale has five or seven points with polar adjectives at either end of the spectrum (ex. Barco Projectors are:
Unreliable ______ ______ ______ ______ ______ Reliable
Poor Value ______ ______ ______ ______ ______ Good Value)
Perception Data – What people see
Preference Data – What people like
When analyzing perception data, we are more willing to live with an assumption of homogeneity in responses across consumers (i.e. two people are both likely to perceive Volvo as a safe car, but our desires for a safe car might be very different)
If one suspects that perception data varies across groups, then the data can be broken out and analyzed by specific groups (i.e. Inexperience users vs. Experienced users; Young vs. Old)
If one suspects that perception data is the same across all respondents, then the data can be averaged. Once averaged, the data can be visually represented in a Profile Analysis or Snake Plot).
Snake plots work best when the number of brands/products compared is small (2-3).