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TRA’s Most Desired Brands: Understanding Methodology

By N. Chandramouli
TRA’s Most Desired Brands 2023 list is the result of a meticulous research and analysis process carried out using our proprietary Brand Desire Matrix. The methodology delves into the intangible elements of brand desirability, understanding that the allure and magnetism of a brand extend beyond superficial attributes. The study engaged with over 2500 consumer-influencers from 16 different cities, ensuring a broad and comprehensive representation of consumer preferences.
The Brand Desire Matrix, developed over a three-year period, comprises 36 intangible attributes organized into 12 behavioral categories and 4 foundational aspects of desire. This sophisticated model enables brands to evaluate their relative standing in the market, shedding light on how their actions, communication strategies, and products or services impact the minds of consumers. Unlike conventional metrics such as market share and growth, our model accentuates the unseen and intangible facets of brand desirability, offering invaluable insights to organizations and empowering them to remain competitive in a rapidly evolving marketplace.
To guarantee the accuracy of the data, we adopted a rigorous approach by employing Computer-Aided-Personal-Interviews (CAPI) conducted via smartphones. Multiple verification methods, including geo-location tracking, voice recording, and personal verification calls, were utilized to ensure the authenticity of the respondents. It was a prerequisite for respondents to be fluent in English and proficient in two other Indian languages, thus facilitating diverse perspectives and a more expansive sphere of influence.
The survey questionnaire was meticulously crafted and encompassed three critical components: respondents were tasked with recalling the names of five brands each for local, national, and multinational brands (resulting in 15 responses); identifying three brand names associated with each of TRA’s 36 desire attributes (yielding 108 responses for each attribute); and naming five brands deemed the ‘Most Desired,’ along with rating their suitability on a 5-point scale for each attribute. This comprehensive approach yielded a nuanced comprehension of consumer preferences.
The next crucial step is actually calculating the Desire Index. The statistical analysis of the big dataset has been no small task. To understand how the statistical analysis was done, deconstructing the Brand Desire Index is the first step. By collating the data and then using the Brand Desire Index, we are able to gain a point-of-vision for the rest of the data.
Over the years, the index calculation has been continuously fine-tuned to have greater sensitivity and relevance. TRA’s Indices are a subtle measurement and take into account the visible and invisible Brand Desire influences. Our research necessitated detailed primary research among consumer-influencers to understand their brand associations with the Brand Desire attributes. This had two parts – the first was created using the four most necessary variables arising from the 36 primary components of Brand Attractiveness. The four parameters were – standard deviation of suitability, position average (whether it was mentioned as the first, second, or third choice for the specific primary component), the suitability average score of the brand, and the number of occurrences.
The other direct and visible influence on Brand Desire was the brand’s frequency (how many times a brand name occurred), position (whether it was stated first, second or, third among the three brands mentioned) and, weighted suitability (how relevant the brand was to the attribute on a scale of the first influence on Buying Propensity. The step-by-step process of measuring the index along with relevant formulas is available on our website TrustAdvisory.info.
Furthermore, TRA extended the scope of the survey by adding an additional layer, wherein respondents specified the category of the brands they mentioned, mitigating subjectivity in brand categorization. The study also acknowledged the influence of home-influencers, recognizing their substantial role in purchase decisions. This inclusion ensured a more representative and inclusive dataset, enhancing the accuracy and comprehensiveness of the findings.
(The author is N. Chandramouli, CEO, TRA Research, and the views expressed in this

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