Returns Management: An Instrument for Enhancing Customer Service for the Indian E-Retail Industry

Introduction

The e-retail sector has witnessed big mergers of Jabong and Myntra, a failed merger of Snapdeal and Flipkart and latest one is of Flipkart itself which has been acquired by Walmart for a big billion deal of $16 billion for 77% stake in 2019. To expand their respective portfolios, the organizations have entered in the e-grocery market, with Amazon acquiring Aditya Birla’s ‘more’ and Flipkart planning to follow the trend to sustain in competition. There is cost associated with customer acquisition which the organizations are not able to recover despite having high growth rate because of low average gross merchandise value (GMV) and high logistics cost to serve the customer which is around $2 for an average GMV of around $24 as compared to China where the figures are $2.2 for an average GMV nearly three times to that Indian market. The computation further gets affected with the delay in cash flow as around 60% -70% of the customers in India prefer cash on delivery on products. The current market curve is in growing stage but the investors like Goldman Sachs, Softbank are eagerly eyeing upon the break-even point and profits to be posted for their huge investment in the e-retail sector.

The major cost parameters involve marketing, forward logistics, inventory and reverse logistics. While first two parameters are inevitable and are directly linked with customer acquisition and service levels. The third aspect of inventory optimization is dealt through marketplace model¹ to avoid cost of obsolete products and reducing carrying cost by e-retail organizations. Reverse Logistics, the fourth parameter is a grey area and the returns process is also an unorganized and unstructured part of the whole supply chain. The resultant increase in the cost of reverse logistics is due to various factors like lose control over quality of products; high quantity of returns and some other inherited traits like absence of physical verification of products on virtual platforms elaborated under the limitation of marketplace model.

The rate of goods or merchandise returns on an average is 15% compared to the total forward shipments but can be as high as 40% in apparel category (KPMG, 2018). The organizations where monthly transaction is in millions, managing and controlling the reverse logistics cost itself is massive area which needs recovery on immediate basis to push down the operational cost and squeeze the incurring losses to a minimum level. One of the drawbacks of the current reverse logistics involves place and time restriction for customers to be available at their respective premises and delays in replacement or monetary refund processes of over 30 hours which hampers the customer retention(Bureau F, 2016).To improve visibility of inventory of the returned products, e- retailers are opting to reduce the replacement or return tenure to a specific amount, which is adversely affecting the preference to be a top choice for customers. In fact, 92% of customers have reported that they would shop on virtual platforms if the return processes are flexible and agile (Saleh K, 2018). The other side of the bottleneck is the cost involved, borne either by the customer or the seller, which both the parties are not in support to pay for the logistics.

This chapter depicts the management & process of product return system in Indian market by application of a solution which while integrating the forward and the reverse logistics in a supply chain is also productive both financially and logistically. The solution is akin to introducing the brick and motor model (B & M) facility in the supply chain of the e- retail segment of the eCommerce industry.

A B & M facility that would be easily accessible to the customers and can be aligned with their respective daily commutation or travel track to return or replace the product is the need of the hour. The location for the facility can be identified based on analysis of transportation zones of a study area and examining the mass movement patterns. The deployment of such model will not only eliminate the restriction of customers to be present on their premises but also create a responsive return or refund management process to cater to the demand of customers. Since the Indian demographic conditions are much oriented towards brick and mortar model involving the trust factor as a major parameter, the success of attaining an organized management system to effectively manage returns are on higher side.