Client

A leading retail chain in India, known for its extensive footprint and focus on providing a wide range of grocery, home, and kitchen products to its consumers.

Objective

The primary objective was to conduct a catchment area analysis to evaluate the viability of opening a new store in a pre-decided location. The study aimed to understand consumer behavior in retail, consumer preferences, consumer spending patterns and geo-mapping analysis for retail within the catchment area, enabling the client to make data-driven decisions.

Methodology

To achieve the objective, a robust research approach was implemented:

1. Quantitative Surveys

   A structured questionnaire was developed and administered to consumers within the catchment area to capture:

   • Demographic details

   • Household income levels

   • Spending patterns

   • Shopping preferences

   • Perceived gaps in their current shopping experience.

2. In-Depth Consumer Interviews

   To gain deeper insights into preferences and unmet needs, a subset of respondents participated in qualitative interviews.

3. Competitor Mapping

   A detailed competitor analysis was conducted to identify:

   • Existing stores in the vicinity

   • Their product offerings

   • Value propositions that attracted consumers.

4. Geo-Mapping and Footfall Analysis for stores

   The team assessed retail traffic and footfall patterns around the location to estimate potential customer inflow.

Challenges

1. Consumer Diversity: The catchment area encompassed diverse income groups and preferences, necessitating a tailored survey approach.

2. Competition Intensity: The presence of established competitors made it critical to uncover unique consumer pain points and untapped opportunities.

3. Data Volume: Collecting and analyzing data from over 50 studies conducted pan-India required efficient tools and coordination.

Findings

The study revealed key insights about the consumers in the target catchment area:

• Monthly Household Income:

  • Identified income brackets of households, providing a clear segmentation of potential customers.

• Monthly Spending Patterns:

  • Grocery: ₹X per month

  • Milk: ₹Y per month

  • Fruits & Vegetables: ₹Z per month

  • Grocery Non-food items and Home & Kitchen needs: ₹A per month

• Shopping Preferences:

  • Stores frequented by consumers and reasons for their preference, such as pricing, variety, or location.

• Consumer Pain Points:

  • Benefits their current vendors failed to provide, such as better quality, discounts, or additional services.

• Reasons for Vendor Loyalty:

  • Convenience, product range, trust, and promotional offers emerged as the primary drivers.

Outcome

The findings enabled the retail chain to:

• Determine the demand potential in the area.

• Identify the product categories to prioritize based on consumer spending patterns.

• Create a unique value proposition to differentiate from competitors.

• Develop targeted marketing and promotional strategies tailored to local consumer needs.

The study also provided actionable insights into pricing strategies, product assortment, and retail store location analysis to maximize consumer satisfaction and sales.

Conclusion

The catchment analysis proved instrumental in equipping the retail chain with the necessary insights to confidently proceed with their new store launch. By understanding the local consumer landscape, unmet needs, and competitive dynamics, the client was well-prepared to establish a store that resonated with the target audience. This study exemplifies the importance of data-driven retail decision-making in retail store expansion strategies.

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