How Xpert Helped Arvind Mills Decode Store Catchments in Surat and Pune to Drive Higher Footfalls
Background
Arvind Limited, formerly Arvind Mills, is one of India's largest textile and branded apparel conglomerates. Founded in 1931 and headquartered in Ahmedabad, the company is the flagship entity of the Lalbhai Group and India's largest producer of denim. Arvind retails a portfolio of iconic brands — including Arrow, US Polo Assn., Tommy Hilfiger, Calvin Klein, and Flying Machine — through over 1,300 standalone stores and 5,000 multi-brand outlets across 192 cities in India. The company also operates dedicated retail formats such as The Arvind Store and Megamart. With a strong omnichannel presence spanning fabric, garments, and fashion retail, Arvind has been a defining force in India's apparel industry for nearly a century. As it expanded its retail footprint into high-potential tier-2 markets, driving consistent store-level demand became a strategic priority.
Challenge Faced
Despite its vast retail network, Arvind was facing persistently low footfalls at its stores in Surat and Pune. Traditional approaches to driving store visits — city-level advertising, broad demographic targeting, and proximity-based promotions — were not translating into meaningful walk-ins. The brand lacked a granular understanding of who the actual buyers in its store catchments were, where they lived at a pincode and locality level, what their purchasing preferences looked like, and which communities dominated the surrounding areas. Without this intelligence, marketing budgets were being spread thin across entire cities, reaching large populations of non-buyers instead of concentrating on high-intent consumers living near the stores. Arvind needed a data-driven approach to understand its store catchments deeply and design hyperlocal campaigns that could convert nearby buyers into regular store visitors.
Audience Strategy Undertaken
Xpert deployed its buyer intelligence platform to conduct a detailed catchment analysis for Arvind's stores in both Surat and Pune. By analysing verified purchase data from over 800 brands, Xpert tracked 137K+ buyers across 70+ pincodes in Surat and 506K+ buyers across 140+ pincodes in Pune. For each store, Xpert drew a 30-minute driving radius to define the catchment area and mapped buyer density down to the pincode, locality, and individual housing society level. The analysis went beyond location — Xpert profiled the catchment buyers by community composition, lifestyle identities, purchase motivations, and cross-category buying behaviour. This gave Arvind a complete picture of who their buyers were, where they resided, what they cared about, and how to reach them through targeted digital ads, BTL activations, and language-specific creatives.
Inferences & Insights
This engagement demonstrates that even for established retail brands with extensive distribution, the gap between store presence and local buyer awareness can be enormous. A store's physical catchment rarely reflects where actual buying demand resides — in Arvind's case, the vast majority of target buyers were living well beyond the 30-minute driving radius. The ability to map buyers by pincode, housing society, community, and lifestyle identity transforms how a brand plans everything from digital targeting to on-ground activations and even in-store assortments. For apparel and fashion retail brands operating multi-city store networks, this case proves that hyperlocal buyer intelligence is not just a marketing optimisation tool — it is a strategic input for store planning, campaign localisation, and catchment expansion. Brands that invest in understanding their buyers at this granularity will consistently outperform those relying on broad, city-level assumptions.
Results Achieved
The catchment analysis revealed that Arvind's Surat store covered just 8% of all target buyers in the city, while the Pune store reached only 4% — meaning over 90% of potential buyers lived outside the immediate catchment. Xpert identified the top buyer-dense pincodes for digital ad targeting — 20 high-density pincodes in Surat and 10 in Pune — along with specific housing societies prioritised for BTL activations based on verified buying demand, not population estimates. The profiling uncovered that 58–62% of target buyers identified as appearance-conscious and over 46% as health-conscious, enabling Arvind to align campaign messaging with these identities. Community analysis further revealed the dominant languages for creative localisation — Hindi, Gujarati, and Marathi in Surat; Hindi, Punjabi, and Marathi in Pune — allowing Arvind to build culturally resonant, hyperlocal campaigns.
Xpert's detailed catchment analysis revealed that over 90% of Arvind's target buyers lived outside their store catchments, unlocking precise pincode-level targeting, housing society activations, and culturally localised campaigns across cities.
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