Client: A global fast food restaurant chain

Objective

The client intended to find the performance attributes driving the “Favourite brand” of the category where the population is more heterogeneous.

Approach

Since the population was heterogeneous in nature, merely aggregating the data and deriving the set of drivers (factors driving the brand’s success) would not have been effective. Hence, we had to look at drivers within homogeneous groups. Using this technique would have allowed the client draw out different action plans for each segment.

For the analysis, we used the Latent Class Regression approach, in which, we first segmented the population based on various characteristics (demographic, socio-graphic, etc.) and then, determined the drivers that contributed to the brand featuring as the ‘Favourite Brand’.

Impact

The analysis helped the client gauge the drivers that worked best for each segment enabling it to draw out segment-specific strategies.

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Understanding the factors that make a brand a ‘favourite brand’

Venugopal Manneni


A doctor in statistics from Osmania University. I have been working in the fields of Analytics and research for the last 15 years. My expertise is to architecting the solutions for the data driven problems using statistical methods, Machine Learning and deep learning algorithms for both structured and unstructured data. In these fields I’ve also published papers. I love to play cricket and badminton.


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