Merchandizing for fashion retailer

CLIENT

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

OPPORTUNITY

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.

SOLUTION

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.
Analytics:
  • 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.

VALUE DELIVERED

  1. SG Analytics delivered a model that enabled the client to understand purchase decision drivers in their targeted consumer segment.
  2. The model provided an improved understanding of consumer tastes, leading to better consumer targeting.
200+
CATI interviews.
50+
In-person interviews.
200
Online/web surveys.

Client

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

OPPORTUNITY

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.

SOLUTION

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.

Analytics:
  • 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.

VALUE DELIVERED

►
1
SG Analytics delivered a model that enabled the client to understand purchase decision drivers in their targeted consumer segment.
►
2
The model provided an improved understanding of consumer tastes, leading to better consumer targeting.