
India’s retail landscape is undergoing a structural shift, and a new report by Knight Frank India makes one thing clear: the next phase of growth will not be driven by metros alone. Instead, smaller cities are rapidly emerging as powerful consumption and investment hubs.
The report highlights a fundamental transformation—India is now witnessing two parallel retail economies. Tier-1 cities, long considered the backbone of organised retail, are grappling with ageing infrastructure and rising vacancies. Meanwhile, Tier-2 cities are benefiting from newer developments, better planning, and faster expansion.
This divergence is not just about geography but also about timing. Much of the retail infrastructure in smaller cities has been built after 2010, making it more aligned with modern consumer expectations.
Some Tier-2 cities are outperforming much larger urban centres in surprising ways.
Chandigarh has topped the International Brand Penetration Rankings 2026, despite its relatively small population of 1.3 million. The city stands out for its strong consumption power, high-quality retail spaces, and dense presence of global brands.
Mangaluru has emerged as the most brand-dense Tier-2 market, boasting more than 102 international brand stores per million people. Meanwhile, Lucknow leads in absolute diversity, hosting 112 international brands across 5.6 million square feet of retail space.
Other cities such as Surat, Jaipur and Nagpur show strong consumption potential but lag in attracting global brands due to limited Grade A retail infrastructure.
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The answer lies in infrastructure and opportunity. Tier-2 cities now have 61 per cent Grade A retail stock, compared to just 45 per cent in Tier-1 cities. Since 2020, these cities have added 5.9 million square feet of premium retail space—more than three times the expansion seen in metros.
The report also reveals the dominance of global players. American brands account for 46 per cent of all international stores in Tier-2 India and a staggering 91 per cent of international food and beverage outlets, largely driven by quick-service restaurant chains. Meanwhile, retail groups from the UAE control nearly 79 per cent of department store space in these cities.
Not entirely, but they are facing growing challenges. Tier-1 cities still hold 98 million square feet of organised retail stock, far more than Tier-2 cities’ 36 million square feet. However, much of this older stock is struggling.
The report points to around 60 “ghost malls” in metros, each operating with vacancy levels above 40 per cent. Ageing Grade C malls and high vacancy rates are dampening growth prospects.
In contrast, Tier-2 retail spaces are newer, more efficient, and experiencing lower vacancy rates.
The report argues that this assumption is outdated. Consumption power is now a more reliable indicator than sheer population size.
For instance, monthly urban per capita consumption expenditure varies widely—from Rs 13,425 in Chandigarh to Rs 5,114 in Chhattisgarh—highlighting that spending capacity matters more than headcount.
Digital adoption is playing a critical role in bridging the urban divide. Increased smartphone usage, widespread UPI adoption, and easier access to digital content have significantly reduced the gap in brand awareness between metro and non-metro consumers.
This has made Tier-2 consumers more aspirational, informed, and willing to engage with international brands.
Shishir Baijal, International Partner, Chairman and Managing Director of Knight Frank India, summed up the shift, saying:
“India's next phase of organised retail expansion will not be led by the metros alone, we are witnessing the emergence of a parallel retail economy across Tier 2 India -- one that is younger, more aspirational, digitally connected and increasingly capable of supporting international brands at scale.”
He added that population size is no longer the defining factor, noting that cities like Chandigarh and Mangaluru are outperforming larger urban centres due to stronger consumption, better infrastructure, and higher brand absorption.
(With inputs from ANI)