A glimpse of India’s offline retail landscape, how consumers shop offline, and the role data plays in connecting the dots for retail brands
The biggest aid for retail brands in optimizing online commerce channels is the data generated with each order and sale. The data generated by e-commerce and D2C brands also helps understand at a macro level how people shop online. But what about the offline space? Most data generated online cannot be directly applied to take actions and decisions in the offline retail space. The growing omnichannel trend across the global retail landscape is also witnessing the advent of location intelligence within retail tech. Profitable offline expansions can now be calibrated with predictive analysis and machine learning to reach the most optimal revenue timeline.
In this article, we give you a glimpse of India’s offline retail landscape, how consumers shop offline, and the role data plays in connecting the dots for retail brands.
Retail Landscape: High streets, malls, and neighbourhood markets
India’s offline retail landscape is defined by a strategic mix of high streets, malls, and neighbourhood markets, each serving distinct segments of consumers based on their characteristics and spending behaviours. High streets, typically located in central business districts, attract affluent consumers with higher household incomes and significant spending capacity. These areas feature flagship stores and exclusive brand showrooms catering to customers seeking high-value purchases and bespoke items. The visibility and accessibility of high streets make them prime locations for luxury labels and popular fast-fashion brands, alike.
Malls provide a more curated shopping experience and are accessible to a broader demographic within a reasonable drive time. They cater to families and young professionals who value convenience and a comprehensive mix of retail, dining, and entertainment options. The presence of international and national brands in malls, along with lifestyle and electronics stores, reflects the higher spending capacity of this segment. Malls also feature health and beauty outlets, food courts, and multiplexes, creating a one-stop destination that appeals to consumers looking for a variety of experiences under one roof.
Neighbourhood markets emphasize convenience and personalized shopping experiences, attracting a diverse range of customers. These markets serve local communities, with accessibility being a key factor for consumers who prefer quick and easy shopping trips. Customers in these markets often have varied household incomes, and the presence of local and artisanal brands caters to those seeking unique, region-specific products. Furniture and home decor shops are common, along with vendors offering everyday essentials. The trend of pop-up shops and street vendors offering trendy and affordable fashion highlights the evolving preferences and budget-conscious nature of many consumers in these markets.
This diverse mix of retail formats ensures that the needs and preferences of Indian consumers are met across different shopping environments, taking into account factors such as affluence, spending capacity, drive time, accessibility, and more.
The Footfall metric
Assessing footfall is a complex yet crucial task for retailers aiming to make informed decisions about store locations, product offerings, and marketing strategies. A bird’s eye view of footfall at the street level reveals vital patterns and trends in customer behaviour, providing insights that can significantly impact a retailer’s success.
In India, highstreet retail locations remain dominant, with an occupied stock of 13.2 million sq. ft. across the top eight markets. The National Capital Region (NCR) alone holds 39% of this total stock, indicating high customer density and potential foot traffic. Additionally, Bengaluru and Chennai exhibit high concentrations of modern retail areas, with shares of 67% and 66%, respectively​ (Knight Frank)​​ (India Retailing)​.
Understanding these footfall trends helps retailers determine the most strategic locations for new stores, optimize their product mix, and tailor marketing campaigns to the specific demographics of an area. For instance, high streets like MG Road in Bengaluru, which ranks top in performance, attract affluent customers with higher spending capacity, making it ideal for premium brands. On the other hand, areas with high footfall but lower rental costs, like those in parts of NCR, might be more suitable for mid-range or value-oriented retailers.
By leveraging detailed footfall data and customer behaviour insights, retailers can enhance their site selection process, improve operational efficiencies, and ultimately increase profitability in the competitive Indian retail market.
Branded vs Non-branded stores
In the current Indian retail landscape, there is a coexistence of both branded and non-branded stores. While branded stores have seen significant growth, especially in urban areas and across categories like fashion, electronics, and food and beverages (F&B), non-branded stores continue to thrive, particularly in rural areas and segments like groceries, apparel, and local handicrafts.
While the traditional wisdom correlates affluent areas with branded stores, data can show the beautiful dichotomy of Indian diversity where branded and non-branded often coexist with customer nuances attached to both. Take Khan Market in New Delhi for instance. One of the oldest and most popular high streets in India, is home to some of the most high-end brands while also being known for its street vendors who sell anything from kurtas, and juttis, to phone covers and artefacts, and more. Another interesting case study is Mehrauli in New Delhi, which has steadily become the couture hub in the national capital, also making way for the hottest restaurants in the city.
The point remains that studying these intricate nuances of offline retail is the doorway to knowing your customer at the street level as a brand.
Moving the needle from reactive to proactive retail expansions
What we explored in this article leads us to an important conclusion. Retail brands no longer have to shoot in the dark when it comes to offline retail. Much like online commerce, with the advent of artificial intelligence (AI) and machine learning (ML), retail tech today has unlocked the wealth of offline retail data. Not only are we able to ascertain the viability and potential of a retail location, but we are also able to generate a revenue timeline, determine rent optimisation, and locate the next promising location among other things. Brands no longer have to be reactive in their retail growth story and can proactively craft one based on astute data insights. Retail has been due for disruption for decades now and as much as we love our highstreets and neighbourhood markets history, it appears that the transformation era is finally here.
