Click, Buy, Return: Shipway Unveils Why Online Orders Come Back

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TLDR: Shipway, an Indian logistics management platform, has launched its inaugural ‘ShipNotes’ report, revealing key insights into Return to Origin (RTO) challenges in e-commerce. The report highlights that 26% of Cash-on-Delivery (CoD) orders are returned, compared to less than 2% of prepaid orders. It also identifies factors like delivery speed, order value, and geographic location influencing RTO rates, with Patna having the highest and Vadodara the lowest. Shipway has implemented features like automated CoD confirmation and WhatsApp-based address correction to help D2C brands reduce returns.

Shipway, one of India’s leading logistics management platforms and a subsidiary of Unicommerce eSolutions, today announced the launch of its inaugural e-commerce logistics report, ShipNotes. This edition of ShipNotes offers data-driven insights into one of the most critical challenges facing Indian e-commerce: Return to Origin (RTO). The analysis is based on millions of D2C brands’ shipments processed through Shipway in FY25.

RTO refers to instances where an online order is shipped but fails to reach the customer, resulting in the product being returned to the seller. This phenomenon, often caused by failed delivery attempts, inaccurate addresses, or customer refusal, significantly impacts D2C brands – increasing logistics costs, blocking inventory, and eroding profit margins.

The report highlights that less than 2% of prepaid orders are returned, while nearly 26% of the non-prepaid orders are returned, reinforcing that RTO challenges are overwhelmingly concentrated in non-prepaid transactions. Therefore, this edition of ShipNotes focuses exclusively on the trends and drivers behind RTOs for Cash on Delivery (CoD) orders.

Looking at the percentage of returns across various cities, the report shows that Vadodara recorded the lowest RTOs at 18%, while Patna recorded the highest RTO percentage at 35%. Shipway analysis reports Vadodara, Thrissur, Mumbai, Kolkata, Chandigarh, Ahmedabad, Ernakulam, Nagpur, Chennai and New Delhi as the top 10 cities with least RTO rates. On the other hand, Patna, Srinagar, Jaipur, Varanasi, Ranchi, Jammu, Meerut, Guwahati, Vishakhapatnam and Nasik rank as cities with highest RTO rates. The difference in RTO rates across cities points to the complex interplay of factors such as address accuracy, consumer behavior, and logistical predictability across diverse delivery environments. This analysis includes cities for which Shipway processed a minimum of 5,000 non-prepaid orders in FY25.

Delivery speed emerged as a strong influencing factor. In FY 25, orders attempted within 1–2 days recorded a 22% RTO rate, which rose to 27% when attempted in 3–5 days, and further to 35% when delivery was attempted after more than 5 days. These insights clearly show that slower deliveries contribute to higher RTOs.

The report also highlights an interesting relationship between order value and RTO rates. Orders priced between ₹500 and ₹1,000 saw the highest RTO rate at 28%, while lower-value orders under ₹500 and orders over ₹1,000 experienced lower RTOs of 25% and 24% respectively. These findings suggest that mid-value purchases may be more susceptible to impulse buying and post-purchase regret.

Distance and zone classification also had a measurable effect on RTO outcomes. Intra-city shipments (Zone 1) recorded a 20% RTO rate, followed by metro-to-metro (Zone 3) at 22%. Intra-state deliveries (Zone 2) recorded 23% RTOs. Inter-state, non-metro shipments (Zone 4) reported RTOs of 27%. Special zones (Zone 5) including North East, Jammu & Kashmir reported RTOs of 28%. These trends align with the inherent complexity of longer-distance logistics and localized challenges in certain regions.

Over the years, Shipway has implemented a suite of targeted features aimed at reducing RTOs across its network. These include Automated CoD order and address confirmation to verify customer intent before dispatch. WhatsApp-based address correction and rescheduling tools to enable real-time updates. For high-value or sensitive shipments, where automation alone may not suffice, Shipway has introduced manual calling support to ensure accuracy and reduce failed deliveries.

RTOs have long been an Achilles’ heel for D2C brands. Our data-driven approach for RTO reduction has created a blueprint for the industry. Anchored in intelligent automation and customer-centric verification systems, it has not only reduced operational costs for our partners but also enhanced the delivery experience for millions of customers across the country,” said Saurabh Choudhary, Chief Business Officer, Shipway.

Shipway continues to evolve its technology stack, including AI-driven risk scoring and enhanced customer communication tools in collaboration with the brands to enable them in reducing their RTOs further.

Key Findings from ShipNotes

  • Cash-on-Delivery (CoD) Drives Returns: While less than 2% of prepaid orders are returned, 26% of Cash-on-Delivery orders come back – making CoD the single biggest contributor to RTOs.
  • Speed Reduces Returns: Orders attempted for delivery within 1-2 days recorded a 22% RTO rate, compared to 35% for those attempted after 5 days.
  • City-Level Trends:
    • Lowest RTO rates: Vadodara (18%), Thrissur, Mumbai, Kolkata, Chandigarh
    • Highest RTO rates: Patna (35%), Srinagar, Jaipur, Varanasi, Ranchi
  • Order Value Insight: Mid-range purchases (₹500–₹1,000) saw the highest RTO rate at 28%, suggesting higher impulse-driven returns in this segment.
  • Geographic Complexity: RTOs rose in proportion to delivery distance and complexity – from 20% in intra-city shipments to 28% in remote/special zones like the North East and Jammu & Kashmir.

Shipway has introduced several proactive features to help brands reduce returns:

  • Automated CoD order and address confirmation to verify customer intent before dispatch.
  • WhatsApp-based address correction and rescheduling tools, enabling real-time updates.
  • Manual calling support for high-value shipments to ensure accuracy and reduce failed deliveries.

 

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