Merchandizing for fashion retailer

CATI interviews.
In-person interviews.
Online/web surveys.


A US-based fashion retailer with physical and online stores.


The client was looking to establish a new collection across their brick and mortar stores to increase their market share in a specific target segment in Millennials. However, the client was traditionally focused on Generation X customers and replicating their existing business rules would have been ineffective.


SG Analytics leveraged different methodologies to capture all relevant and available data points and ensure holistic insights. A specialist team comprising of data processing specialists, data scientists, survey programmers, and primary research analysts conducted the following exercise:

Primary Research:
  • 200+ Computer Aided Telephonic Interviews (CATI) with respondents representing the target customers.
  • 50+ in-person interviews (IPI) at targeted mall intercepts and shopping centers with appropriate respondents.
  • Conducted 200 online/web surveys across 6 the target geography.

  • SG Analytics analyzed the survey data using a maxdiff analysis technique to gauge the attributes that drive the target group’s purchase decisions.
  • The team conducted a factor analysis study to derive the factors covering both emotional and functional attributes that appeal to the consumers.
  • SG Analytics' data scientists used the obtained factor scores along with the contextual variables to identify the statistically best-fit discriminating variable using a clustering analysis. The team further iterated the process to identify multiple descriptors that fully segmented the survey data to create a driver tree.
  • Based on the driver tree SG Analytics created a model to support the client in their merchandise decisions.


SG Analytics delivered a model that enabled the client to understand purchase decision drivers in their targeted consumer segment.
The model provided an improved understanding of consumer tastes, leading to better consumer targeting.