By Ankita Thakur and Tusheet Shrivastava
Online retail brands in India are on the cusp of a transition. After making their mark in the digital world, an increasing number of direct-to-customer (D2C) businesses are realizing that the offline market cannot be ignored. With competition on the rise and urban markets hitting saturation, it is becoming increasingly expensive to attain customers in the cyber domain.
Rather than over-index on digital play, online startups need an omnichannel approach, which leverages both online and offline channels to maximize market reach and customer engagement. Mamaearth, for instance, now earns 35% of its revenue from offline channels The startup is planning to expand its offline retail further claiming that it helps improve its overall margin profile.
The silver lining lies in the fact that these businesses, being inherently digital and adept at harnessing vast data reserves, can venture into the offline domain, armed with data-driven insights, rather than depending on intuition-driven approaches. Recent advancements in the utilization of artificial intelligence (AI) and machine learning (ML) to amalgamate customer data and uncover concealed patterns can transform how online retail startups in India structure their business growth and strategies.
Looking beyond urban India
India is a country of 1.4 billion people. Only one-third of this resides in urban cities with unfettered access to the internet and even fewer have the technological know-how to conduct transactions online. Online startups, especially those catering directly to the customer, can only expand so far if they limit themselves to this target audience.
However, beyond the boundaries of Mumbai, Delhi, Kolkata and other metropolitan areas, demand as well as digital literacy is on the rise. Consumers are looking for more options, but they’re primarily still searching offline. Some even travel to the nearest tier-I city in order to shop for luxury and high-end brands because that’s where quality malls are located.
This ‘Halo Effect’ demonstrates that even though they have disposable income to spare, trust is still key before they open their wallets.
The keyword is ‘trust’
In offline stores, especially innovative ones, direct contact with products builds brand trust and loyalty. Instead of just making the one-off purchase, they’re more likely to return if they have a physical touch point. Being able to hear, see, touch, smell, and taste their options not only gives consumers a happy experience but also helps them form cognition and judgment about products.
This is one of the reasons that while India’s e-commerce sector was on the rise well before the pandemic hit, 90% of retail shopping was still happening offline. Once COVID hit, there was another boom in online shopping with people having no other option but to shop online in the face of lockdowns and restricted access to offline markets. Even then, retailers like Reliance Brands were looking for ways to engage with consumers and build trust with Zoom calls and WhatsApp chats, emphasizing the need for retail brands to leverage the respective advantages and synergies of online and offline channels to retain customers for longer periods.
Studies show that direct product experience, sales-staff assistance and store ambience are key advantages of having an offline retail avenue. Personalized sales assistance boots information quality and shopping satisfaction. A visually appealing shopping environment reduces customer costs and signals high service quality. These benefits lower transaction costs, elevate the shopping experience, and enhance perceived value for consumers.
While the pandemic rollercoaster created many opportunities and challenges for entrepreneurs, it has also exposed the need for a more balanced and mature approach to building a resilient business. Rajan Anandan, the Managing Director of PeakXV Partners, shared in a recent podcast that the odds of a startup reaching scale are significantly higher if you combine the online and offline components.
The advantages of going offline
Omnichannel shopping behavior is growing in India. By honing into the key advantages of online and offline channels influencing the omnichannel shopping experience, retail brands can reduce their costs, thus expanding margins and improving their profitability.
Traditional business wisdom has always emphasized profitability and efficient resource management for growing companies. But in India, according to a report by VCCircle, the top technology startups in the country doubled their cash burn in FY22 from $2.5 billion to $5 billion even though revenue growth continued to lag behind. This has made an omni-channel approach imperative for startups.
Nykaa, for instance, opened up 141 physical stores across 56 Indian cities by the end of December 2022 resulting in 33% growth of its operating revenue. Lenskart, the 13-year old homegrown multinational eyewear retail chain, now operates more than 1,000 offline stores and registered a 66% increase in operating revenue in FY22. Furlenco, Pepperfry, Wakefit and others are following suit with an omnichannel approach targeting profitability in FY23.
A customer with a budget of ₹10,000 may consider spending ₹15,000 instead, just because they are in a store and the difference in quality is apparent and tangible in front of them. Not only is this great for the brand, but it’s also beneficial for the customer who’s walking away with a better product that has more value-for-money for them.
The role of AI and ML
Sales data empowers online retail brands to locate their current customers, yet this is merely a fraction of the untapped market potential. Identifying other areas that are similar, with comparable customer profiles, can open up new markets where demand is yet to be captured.
This task is best executed with the help of AI. By scrutinizing anonymized data and conducting street-level customer analysis, AI extracts intricate customer profiles encompassing spending habits, expenditure priorities, and behavioral insights. For brands venturing offline, crucial insights include customers’ shopping preferences and ideal locations for investment, enhancing the likelihood of success.
This is especially important for expansion in non-metro regions where malls are not the primary shopping destination. Consumers in tier-II, tier-III and tier-IV cities are more likely to shop at already established high-streets, generally located in the heart of the city, or at upcoming areas in residentials sectors.
This kind of location intelligence becomes even more powerful with ML to create predictive models. Building on the former example, ML can help brands decide whether it makes more sense for them to open a store in a high-street or if an emerging shopping area has more potential for them to tap into their target audience. It allows businesses to move from a reactive approach to a proactive one. ML models can identify areas with high potential for the brand by looking at hidden patterns within data.
Once these areas are identified, ML can also estimate the kind of revenue retail brands can expect to generate from them. Predictive modeling offers forecasts about changing market trends, evolving consumer behaviors, and shifts in competitive activity further reducing the risk of expanding offline and protecting one’s margins.
An omnichannel approach hones in on the respective advantages of online and offline shopping cultivating positive brand relationship outcomes. Online channels are great for consumers to search, evaluate and meet consumer demand. Offline channels, on the other hand, leave consumers with more satisfaction about their purchase and create an experience around the product.
Combining the complementary advantages of both using technology is key for a brand to not just survive, but thrive in the post-pandemic retail segment and build a business that’s sustainable.
(The authors are By Ankita Thakur and Tusheet Shrivastava, co-founders of GeoIQ, and the views expressed in this article are their own)
