MAM
GoKwik saves eCommerce brands Rs 130 Cr in RTO losses for 2023
Mumbai: Brands on the network of eCommerce enabler GoKwik have saved up to Rs 130 Cr in losses from return to origin orders (RTO) in 2023 so far.
According to data released by GoKwik, direct-to-customer (D2C) brands on its network benefited from its interventions to arrest RTO occurrences. Brands saved over 16 lac orders from being returned to origin. As a result, they also saved over Rs 24 Cr in reverse logistics costs owing to orders being returned while in transit.
“We are constantly building deep-rooted intelligence & interventions that will help brands cater to the cash-on-delivery-loving shoppers while also mitigating RTO losses smartly. Our solutions are constantly committed to solving deep-rooted problems of the eCommerce industry at the source while also ensuring we contribute to becoming the eCommerce gateway of India. By seeing success stories of merchants, we are rest assured that we are heading in the right direction” said GoKwik co-founder and CEO Chirag Taneja.
RTO or return to origin is when undelivered orders are returned before delivery causing a major setback to operations for e-commerce brands as they add to logistics costs, inventory blockage, loss of true conversions and leaking profitability.
The chances of RTO are significantly higher in cash-on-delivery (COD) orders than in prepaid orders. GoKwik offers a range of solutions backed by data and analytics that can predict customer behaviour and help sellers prevent RTOs while ensuring expansive COD serviceability across regions.
Through GoKwik-led interventions, brands also had over 16 lac products readily available to be shipped which would have otherwise been in transit for 20-30 days leading to inventory blockage and damage, data released by GoKwik shows.
Fashion brands saved around Rs 15 Cr, electronics brands around Rs 61.7 Cr, beauty brands around Rs 2.75Cr, and footwear brands around Rs 5.5Cr in inventory blockage owing to GoKwik interventions. Moreover, among these categories, electronics saw the highest reduction in COD RTOs with 28 per cent. Fashion brands recorded an 11 per cent drop in COD RTOs, footwear recorded a 16.6 per cent drop, and beauty and personal care saw 10 per cent.
Around 40 per cent of the brands in the GoKwik network continued to increase their COD share by 16 per cent and reduced COD RTO by up to 18 per cent.
Homegrown consumer electronics brand boAt saw up to a 32 per cent drop in RTO rate and a four times increase in COD gross merchandise value with the help of GoKwik’s interventions. Footwear brand Attitudist also recorded a 15 per cent reduction in RTOs with these interventions. Boult Audio further brought down RTOs by 40 per cent and Fireboltt by 30 per cent respectively.
Many other brands including Swiss Beauty, The Man Company, Neeman’s, Wallmantra, and Lenskart were able to expand their COD serviceability pan India while containing RTO rate.
GoKwik’s smart suite of solutions helps brands start COD, expand COD, reduce return to origin and contain return to origin depending on the stage of COD serviceability their brand is in. GoKwik is committed to solving these problems at the source by risk-based interventions such as adding extra layers to order completion to avoid RTO, behavioural analysis of the shoppers, risk profiling and placing pre-order interventions such as COD captcha, COD confirmation prompts, prepaid discounts and more.
Risk and return maintain inverse proportionality within mutual funds – higher potential rewards accompany elevated volatility, while stability demands lower expectations. SEBI’s Riskometer (1-5 scale) standardizes visualization, but quantitative metrics reveal nuanced relationships across categories and market cycles.
Fundamental Risk-Return Relationship
Equity funds (Riskometer 4-5) deliver historical 12-16% CAGR alongside 18-25% standard deviation—large-cap 15% volatility, small-cap 30%+. Debt funds (1-2) yield 6-8% with 2-6% volatility. Hybrids (3) average 9-12% returns, 10-14% volatility.
Sharpe ratio measures return per risk unit – equity 0.7-0.9, debt 0.5-0.7 over complete cycles. Higher risk categories compensate through return premium capturing economic growth.
Volatility Metrics Explained
Standard Deviation: Annual NAV return dispersion—equity 18-22%, debt 4-6%.
Maximum Drawdown: Peak-to-trough losses – equity 50%+ (2008), debt 8-12%.
Beta: Market sensitivity – equity 0.9-1.1, debt 0.1-0.3.
Sortino Ratio focuses downside volatility—equity 1.0-1.3 favoring recoveries.
Value at Risk (VaR) estimates 95% confidence, worst 1-month loss: equity 10-15%, debt 1-2%.
Category Risk-Return Profiles
Large-cap equity: 12-14% CAGR, 15% volatility, Sharpe 0.8.
Mid/small-cap: 15-18%, 22-30% volatility, Sharpe 0.7.
Corporate bond debt: 7-8%, 4% volatility, Sharpe 0.6.
Liquid funds: 6.5%, <1% volatility—capital preservation.
Credit risk debt: 8.5%, 6% volatility—yield pickup.
Hybrids: 10-12%, 12% volatility—balanced exposure.
Review types of mutual funds specifications confirming mandated asset allocations driving profiles.
Historical Risk-Return Tradeoffs (2000-2025)
Complete cycles: Equity 14% CAGR/18% volatility; 60/40 equity/debt 11%/11% volatility; debt 7.5%/5% volatility. Bull phases (2013-2021): equity 18%, debt 8%. Bear markets (2008, 2020): equity -50%/+80% swings, debt -10%/+10%.
Inflation-adjusted: Equity 8% real CAGR; debt 1.5% real—growth funding requires equity allocation.
Risk Capacity Assessment Framework
Short-term goals (1-3 years): Riskometer 1-2 (liquid/debt), 2-4% real returns. Medium-term (5-7 years): Level 3 (hybrid), 4-6% real. Long-term (10+ years): Level 4-5 (equity), 6-9% real.
Personal factors: Age (younger = higher risk), income stability, emergency fund coverage, other assets. Drawdown tolerance—20% comfortable vs 40% discomfort signals capacity limits.
Portfolio Construction Principles
Diversification: 60/40 equity/debt reduces volatility 40% versus equity-only while capturing 80% returns.
Correlation: Equity/debt 0.3 average enables smoothing.
Rebalancing: Annual drift correction sells outperformers (equity +25%), buys underperformers (debt -5%).
Style balance: Large-cap stability offsets mid-cap growth volatility.
Quantitative Risk Management Tools
Sharpe Ratio: >1.0 indicates efficient risk-taking.
Information Ratio: Alpha per tracking error.
Downside Deviation: Focuses losses only.
Stress Testing: 2008 scenario simulations reveal portfolio behavior extremes.
Conclusion
Higher mutual fund risk levels correlate with elevated return potential – equity 12-16% amid 18-25% volatility versus debt 6-8%/4-6%. Risk capacity matching, category diversification, rebalancing discipline, and quantitative metric interpretation align portfolios with personal tolerance across economic cycles.
Disclaimer: Investments in the securities market are subject to market risk, read all related documents carefully before investing.
