How Tech Mahindra’s Analytics Are Cutting E-Commerce Returns in India
India’s e-commerce market is growing fast, but it comes with a hidden cost: high return rates. Online shoppers frequently order multiple sizes, return items after delivery, or send back products due to mismatched expectations. For every 100 orders, 30 or more may end up back in warehouses. This isn’t just inconvenient—it’s expensive.
Logistics costs rise, profits shrink, and customer trust can erode if returns aren’t handled smoothly. As a result, companies are searching for smarter ways to manage returns without sacrificing service quality. One solution gaining attention is the use of advanced analytics to predict which orders are likely to be returned—before they’re even shipped.
The Real Cost of Returns in Indian E-Commerce
Returns are especially common in fashion and electronics. In many cases, customers order with the intent to return what doesn’t work, knowing they can do so easily. Cash-on-delivery, still widely used, encourages trial but increases return risk. Poor product images or unclear descriptions also lead to mismatches between expectations and reality.
Each return involves multiple steps: pickup, transport, inspection, and restocking. For smaller sellers, these costs can exceed the original profit margin. Over time, the cumulative effect strains warehouse capacity and slows down delivery networks. Addressing returns isn’t just about customer convenience—it’s a critical factor in maintaining healthy operations.
Predicting Returns Before They Happen
Tech Mahindra’s solution uses machine learning to analyze customer behavior patterns across millions of transactions. By identifying signals such as frequent size variations, return history, or product category trends, the system flags high-risk orders early in the process.
For example, if a customer often orders the same shirt in multiple sizes, the system might suggest a size recommendation tool or prompt them to confirm their choice. In some cases, it triggers a message highlighting restocking fees or encouraging careful review of product details. These small interventions can significantly reduce avoidable returns.
The model adapts to regional differences. Shopping habits in urban centers like Delhi may differ from those in smaller towns, where internet access or product knowledge may be more limited. By tailoring predictions to local behaviors, the system becomes more accurate and effective across diverse markets.
Why FICO’s Recognition Matters
FICO, best known for credit scoring, has expanded into enterprise AI and decision intelligence. Its recent recognition of Tech Mahindra’s work highlights the growing importance of data-driven innovation in solving real-world business challenges.
The collaboration likely strengthened the solution’s reliability, using FICO’s proven frameworks in predictive analytics. This validation ensures the model isn’t just innovative in theory but performs consistently in live environments. It also brings visibility to Indian tech expertise on a global stage, showing that homegrown solutions can meet international standards.
A Smarter Future for E-Commerce
As India’s e-commerce market expands, managing returns efficiently will become even more crucial. Solutions like Tech Mahindra’s offer a path forward that benefits both businesses and consumers.
Beyond reducing returns, the same analytics can improve inventory planning, personalize marketing, and enhance customer experience. Every percentage point saved in reverse logistics can lead to significant cost savings and faster delivery times.
The recognition from FICO signals a broader shift: e-commerce in India is maturing. Instead of focusing only on growth, companies are now investing in smarter, more sustainable operations. By using data to understand customer behavior, platforms can turn a persistent challenge into a competitive advantage.