India's e-Commerce: From Discounting Nightmare to Profitability

By Anand Katakwar, Founder & CEO, Retail Automata Analytics Inc.

Anand Katakwar, Founder & CEO, Retail Automata Analytics Inc.

Retail Automata Analytics Inc. is a Big Data Predictive Analytics Company established in the year 2012. The Omni-Channel Personalization Product suite is extremely well received in the U.S.A and Indian marketplace. 

In next five year projections of global e-Commerce B2C sector shows an expected CAGR of around 18 percent. Top 1 percent of world's e-Commerce retailers, account for 34 percent of all the sales. In India, the top 1 percent players like Flipkart, Snapdeal and Amazon probably account for even a larger share of the overall market. The market place model fuelled by easy availability of capital, chasing growth is the key reason behind the growth & stratospheric valuations of these players. In the fiscal year of 2014, the combined losses of these players were $160 million.

There is no doubt that India’s growing middle class, increasing disposable incomes; penetration of smart phones, along with inherent demographic and economic growth will result in an expansion of e-Commerce sector in upcoming years. With expected growth of 13 percent CAGR to 2025, retail sector can be estimated to be $1.5 trillion. On the other hand, e-Commerce, accounting for 10 percent will put the online retail to be around $150 billion range. The growth of e-Commerce worldwide and rapid growth in India is a well accepted reality. The question is about the sustainability of loss making business models of top players. There have been lot of discussions related to this.

“Is Indian e-Commerce sector a Bubble?” has become a hot topic of discussions. Flipkart and Snapdeal alone are valued much higher than the total market capitalisation of India’s major brick and mortar retailers.

According to a recent report by UBS titled “Is India in an e-Commerce bubble? A framework for assessing emerging markets’ e-Commerce”, investor concern about e-Commerce being a bubble in India is misplaced. The key argument for the sustainability is that lower discounting should lead to operating profits in 2020. After discussing the top 1 percent players, let us also look at the rest of 99 percent of e-Commerce retailers. There are a significant number of online retailers in India who are NOT funded externally. They do not have the luxury of making losses till 2020.

They have realized the hard way that sheer mainstream advertisement & deep discounting does not result in sustained profits. While it increases revenue it kills profits. For surviving and flourishing in online retail, a consistent branding and repeat business earned from satisfied customer base is a must.

The Indian consumer is very frugal. Today, it is entirely common to see a customer choosing one market place over another just to get that additional INR 50 discount on a Mobile Phone worth INR 10000. The value of such a customer and how much that sale should contribute to the valuation of organization is a good question to ask.

Application of business intelligence technologies and analytics should result into the evaluation of quantifiable measures of how much business revenues will be generated if the discounting is reduced. What is the strength of branding of a particular retailer and how loyal are the customers?

For higher per customer sales and increased profitability, attractions other than deep discounting must be there. Consumer experience should be enhanced. Personal attention is the single most qualitative important factor for customer satisfaction. If we can generate accurate predictions of future buys of customers, repeat customers can be presented with the dynamic coupons of say 30 percent off instead of offering store wide 50 percent off discounting. In this hypothetical example, the discounting percentage will get reduced effectively by 200 basis points.

For effective campaigning importance of customer segmentation is well accepted. Customer segmentation on the basis of geographical, economical and demographic factors yields a better open ratio and conversion to sale, compared to generic offers. Predictive analytics can achieve the customer segmentation of one, where a different offer can be generated for every customer, as per the customer’s predicted buys.

A personalized Omni-Channel world can be created for every customer where every customer would receive consistent personal offers on-site; email/SMS and mobile application push notifications. Customers presented with exactly what they want to buy tend to buy much more. A personal coupon and discounting offer of a lesser extent than store wide discounting can be more effective. Of course, there are various challenges for such an approach to work. The quality of recommendations is of highest importance along with coverage of customers and products.

In fact, because of lack of availability of the repeat sales history of the same product, the predictive analytic problem for 99 percent of retailers is much tougher, than for the top 1 percent of easy access to funding retailers. This is the problem we have solved and our predictive analytics engine can generate most accurate recommendations, even for the smallest and one of a kind retailer like jewellers.

Worldwide growth of e-Commerce and explosive growth in India from the current $16 billion to $100 billion or more by 2025 will happen. Predictive analytics and Big Data Technologies will play a crucial role in journey of e-Commerce sector to profitability.

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