How AI & Data-Backed Insights Are Changing The Pace Of Offline Retail Growth

As the third largest contributor to the Indian economy, growth of Indian retail is deeply tied with the ambitions of the country. It stands at $500 Bn today, and continues to grow. 

While much of the technology development has gone into the growth of online retail which contributes 8% of the total retail market, real growth is being achieved in the offline world. Think Reliance Retail. Think Tata’s Zudio. Think Lenskart. 

For modern companies, online growth comes at a cost. What they have learnt is that for profitable growth, they need to step out of the online world – to the sizable number of consumers who shop in malls, high streets in major metros, to new centres in tier 1, tier 2 or tier 3 cities, which is booming with increased disposable incomes. 

Navigating the world of offline growth isn’t easy. It’s just a different business model and the rules of online growth either do not apply or do not translate.

The Next Era Of India’s Retail Growth

The introduction of technology and India becoming the world’s second largest user base of the Internet has helped propel the country’s retail sector to new heights. Cheap data and widespread connectivity have fueled the growth of ecommerce platforms and mobile apps, fostering online shopping habits thus far. 

The online retail sector has expanded by $8-12 Bn annually since 2020, with categories like fashion, beauty and personal care, electronics and food leading the way. 

Despite the rapid growth of online retail in India, online penetration is still only 8% with 92% of retail sales happening offline. There is a lack of trust when making an online purchase due to, in some part, lack of awareness but also the uncertainty that comes with spending money on something you haven’t physically touched and felt. 

60% of Indian consumers trust physical stores more than online platforms and 80% of them value the ability to touch and feel products before buying them. 

India’s homegrown eyewear brand, Lenskart, for instance, successfully leverages offline stores to build trust by offering eye tests and consultations. While online sales still dominate its revenue, most of its customers use both online and offline channels during their purchase journey. 

The brand claims that having an omnichannel presence has helped increase their brand awareness by 50% and the customer conversion rate in stores is 30% higher as compared to online channels, the halo effect of brick and mortar. 

Lenskart’s offline expansion has been successful primarily due to its data-driven strategy for opening physical stores. Rather than depend on old school methods, which are largely subjective and prone to human bias, the brand uses data-backed insights & analysis to estimate revenue and footfall when selecting new locations. 

While Lenskart’s story exemplifies the synergy between online and offline channels, it’s not alone in recognising the untapped potential of India’s offline retail market. A growing number of brands are embracing technology and, more specifically, data-backed decision making to navigate the complexities of physical markets in Tier-II and Tier-III cities, where the data drought has been a persistent blocker. 

Technology: A Unifying Force Rather Than A Dividing Factor

While ‘expanding offline’ seems to be the buzzword for retail in 2023, the sector faces challenges such as infrastructure limitations and logistical complexities when looking to set up physical stores in tier 2 towns and beyond. 

However, data-backed decision making can significantly reduce the amount of effort and man hours required to understand these areas by filtering through potential sites using thousands of  location attributes depending on the brand and its requirements. 

This can include demographic parameters like population, age and income. Some brands also filter locations by the retail presence in the area which can be ascertained by attributes like luxury brand count, value brand count and competitor density. Most focus on commercial indicators like rents, average spending on food, affluence level and other factors to attract the ideal target consumer. 

Using data-backed insights, many online retail brands have been able to enhance and double down on their initial offline expansion plans since site selection errors are greatly reduced. Instead of standing on a corner of a street counting cars, as one business owner recounted to me, data-backed decision making is able to unlock far more relevant, accurate and predictive statistics. 

Brands are able to reduce the risk of operating in low revenue-generating areas, identify high-performing sites that could benefit from a nearby store, and understand spending patterns to make informed decisions. Data can also be used to optimise product offerings and tweak pricing strategies based on local demand and preferences. 

Street-level Data Trumps Pincode Analysis

The advantage of data-backed decision making over existing data analysis solutions is that it can give a brand street-by-street insights rather than an overarching view of which pincodes are ideal. Just because a locality like Sector-17 in Chandigarh or the Sarafa Bazaar in Indore are shopping hubs, that doesn’t necessarily mean that all corners of the market are ideal for opening a store. 

Brands are able to reduce the risk of operating in low revenue-generating areas, identify high-performing sites that could benefit from a nearby store, and understand spending patterns to make informed decisions. Data can also be used to optimise product offerings and tweak pricing strategies based on local demand and preferences

Having a more accurate method of identifying high performing locations correctly has a direct impact on a company’s bottom line. Not just because using technology makes the process more efficient, but also because high performing locations imply that the average time for a store to turn profitable is as low as possible.

Cultfit’s Cultsport, for instance, is planning on opening a new exclusive brand outlet in the country every month. According to the company, there’s untapped market potential in the lack of penetration of sports retail shops in India. Cultsport currently contributes to around one-third of Cultfit’s revenue and the company is banking on data-backed brick-and-mortar expansion to bring that up to 50%.

The paradigm shift from brands exclusively existing online to a harmonious blend of online and offline strategies marks the next era of India’s retail growth. Data-driven expansion offline expansion plans and the adoption of data-backed decisioning is emblematic of a broader trend among forward-thinking brands. It’s a tool that not only helps brands navigate the challenges of tier 2 and tier 3 markets, but also streamlines the site selection process by minimising risk and increasing efficiency. 

The reliance on technology to enable that shift is not a mere trend – it’s a transformative shift that enables brands to enter any market they choose with precision. In this new era, data-backed decisioning is proving to be a compass guiding brands towards untapped market potential. 

The goal isn’t just to grow and provide expansion opportunities, but to do so in a sustainable way that can preserve through the dynamic and ever changing habits of Indian retail.

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