Saturday, October 17, 2009

What is a Perceptual Map?

When you reach the point of analysing your own product in the marketing strategy section of your marketing plan, this is when you will come across the necessity of creating the perceptual map. This will help you understand how your product is perceived by consumers relative to competition.
Based on a visual 2D representation of how target customers view the competing alternatives, this comparison will combine both the product’s segmentation and positioning with the aim to understand the correct product position so a competitive advantage can be identified.
In these conceptual maps there are two axes, and all competing products will be assigned to one of the four quadrants that best describes the customer’s perception of that product according to those axes categories. So, if we are analysing a stomach ache relief medicine, for example, we will consider as the two dimensions as taste (good or awful) and efficacy (works fast and well to doesn’t work at all).

From the example above we verify that Product D is seen by the consumers as the one that tastes the best and is also quite efficient. Product D is also the one with the largest market share hence its larger circle representation. Product A and B are percepted as very similar products and product E is the worst perceived product as it neither works well or tastes good.
The product’s position is defined through statistical calculations based on consumer preferences that can be acquired through questionnaires. Other than the simpler version of the conceptual map of competing products as above, products can also be analysed in accordance to the ideal vectors established by the consumers. An ideal vector will indicate the preferred ratio of the two dimensions within the quadrant they apply. Each vector will be defined in the perceptual map as a line from the origin to an arrow indicating the direction in which the vector’s attribute is increasing. The longer the line, the greater is the importance of that attribute in explaining the variance. For a better understanding of how this is done and the calculations involved I would suggest you to read the presentation by the Columbia University Marketing Professor Skander Esseghaier here.

1 comments:

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