India’s on-demand delivery ecosystem has transformed customer convenience. Behind that speed, however, is a rider operating within a far more complex environment shaped by variable earnings, operating costs, waiting time, road conditions and fragmented access to information and support.

For a customer, a delivery journey is relatively straightforward: an order is placed, a rider is assigned, the delivery is tracked in real time and the product arrives at the doorstep. In quick commerce, this entire experience may be completed within minutes.

For the delivery partner, however, the transaction represents only a small part of the working day. Between two completed orders are periods of waiting, travel, route decisions, operational issues and costs that remain largely invisible to the end customer.

As India’s on-demand economy continues to expand, understanding these underlying realities will become increasingly important for platforms, ecosystem partners and service providers designing solutions for the delivery workforce.

Earnings need to be viewed alongside the cost of earning

The earnings displayed on a delivery platform do not necessarily represent a rider’s effective take-home income. Fuel, vehicle maintenance, tyres, mobile connectivity and unplanned repairs are recurring operating expenses borne by riders.

Time is another significant factor. A delay at a restaurant, waiting outside a dark store, travelling back towards a high-demand zone or locating an incorrect customer address can reduce the number of productive deliveries completed within a shift.

Research by NCAER illustrates this distinction. Its study of food-delivery platform workers found that workers in the sample spent substantially more time working than comparable urban workers. While their gross earnings appeared higher, the difference narrowed considerably once fuel expenses were incorporated. [Source]

Rider performance cannot be understood only through the value of each completed order. The combination of earnings, operating costs and productive time ultimately determines the economics of a working day.

A significant portion of the rider experience remains outside the rider’s control

Delivery operations are highly dynamic. Restaurant preparation times, customer availability, demand fluctuations, order cancellations, traffic conditions and platform processes can all influence a rider’s productivity.

A rider may therefore need to make continuous decisions throughout the day—whether to remain in a particular zone, move to another location, continue during a low-demand period or stay online longer to achieve an incentive threshold.

This creates a degree of income unpredictability. Even when riders have flexibility over when they log in, their ability to generate adequate earnings may still depend heavily on peak-hour demand, incentives and platform-specific conditions.

The distinction between flexibility of working hours and predictability of earnings is therefore important when assessing the rider experience.

The road is also the workplace

Unlike traditional employees, delivery partners operate primarily in public spaces. Their working environment includes traffic, extreme weather, pollution and long periods on two-wheelers.

Access to basic infrastructure can also vary considerably during a shift. Rest areas, drinking water, washrooms, safe waiting locations and reliable vehicle-support services may not always be readily available.

A minor operational event can consequently have a disproportionate effect on the day. A puncture, heavy rainfall, an unexpected road closure or a vehicle breakdown can mean lost delivery time as well as an additional financial cost.

As delivery volumes increase, rider infrastructure may therefore require as much attention as improvements in routing and fulfilment technology.

Support requirements often extend beyond formal processes

Platforms have invested considerably in digital support mechanisms, automated workflows and self-service tools. However, many rider issues are situational and may not fit neatly within a standard support journey.

For example, a rider may want to understand whether a particular pickup location is experiencing delays, whether other riders have encountered the same application issue, how an incentive mechanism has worked in practice or where an emergency repair service is available nearby.

In such situations, peer experience can become highly valuable.

Research by the International Labour Organization has shown that delivery workers already use WhatsApp, Facebook and other informal communities to exchange information relating to traffic, routes, weather, vehicle repairs, incentives, high-demand areas and technical issues. [Source]

The behaviour therefore already exists. What remains fragmented is the infrastructure supporting it.

Rider knowledge remains highly distributed

Every experienced delivery partner develops a substantial amount of local operational knowledge.

They learn which roads become congested at particular times, which pickup locations typically experience delays, how demand shifts across neighbourhoods and where reliable support services are available.

Much of this information, however, remains within individual networks, temporary conversations and closed messaging groups.

This creates an information gap. A rider facing a specific issue may be only a few kilometres away from another rider who has already solved it, yet there may be no efficient mechanism connecting the two.

In a hyperlocal industry, local knowledge can itself become an important operating asset.

The next phase of rider experience may extend beyond order fulfilment

India’s delivery ecosystem has become highly sophisticated in coordinating customers, merchants, inventory, payments, routing and fulfilment. Significant investments continue to improve the speed and efficiency of the transaction.

The next opportunity may be to apply the same level of thinking to the broader rider experience.

This includes improving access to relevant information, strengthening peer knowledge networks, reducing avoidable operational friction, enabling better support services and helping riders navigate the financial and practical realities of platform work.

The industry has spent years optimising the question:

How can an order reach the customer faster?

The next stage may require an equally important question:

How can the ecosystem enable the rider to work more effectively, sustainably and with better access to information and support?

A 10-minute delivery may represent a few minutes of convenience for the customer. For the rider, it forms part of a considerably more complex working day.

Editorial sources