Multi-stop delivery and stacking economics

We test how far a second order can ride with the first: how much delivery cost falls with each order added, how many minutes it adds for the first customer, where the limit lies and what the group does at each point.

The output is a set of stacking rules and a contribution model for trips of one, two and three orders.

• A stacking model showing cost per drop and contribution per trip at one, two and three orders.
• A delay cost for the first order, set against the saving on the trip.
• Eligibility rules based on distance between drops, merchant, order value and promised window.
• A pay design that rewards stacked trips and pays each minute once.
• A stacking dashboard defined for dispatch and finance, with limits for escalation.

• Stacked trips and orders per trip are tracked, so dispatch knows its stacked share instead of guessing it.
• Cost per drop is compared on stacked and single trips, and the gap is the saving.
• Your board reads the added minutes for the first customer beside the saving on the trip.
• Refund rate on stacked trips is reported, so the price of a late second order shows in the data.
• Contribution per rider hour is read for each stacking rule.

Operators know stacking saves money, yet few know by how much, or what it costs in late deliveries and refunds. Without a limit, dispatch stacks aggressively at peak, the first customer waits and complaints rise. Without a rule at all, riders ride single and the cost stays high.

• Share of stacked trips is unknown, or varies by dispatcher.
• Customers wait longer for food or groceries when a second order is added.
• Refunds and complaints cluster on stacked trips.
• Merchants complain that their orders are held for another merchant's.
• Riders are paid per order, so stacking raises their income and the cost of managing it.

Restaurant groups, quick-commerce and grocery operators, 3PL and courier companies running dense urban routes, and boards that have heard stacking called the main lever of fleet profit and want it measured.

Qasim Abbas set the unit economics behind a blended fleet of about 1,000 vehicles, where a second order on a trip is a margin question before it is a dispatch question.

We write the rules for your dispatch platform, Tookan or another, from a month of your trips rebuilt cost by cost. See how fees work.

How many orders should a rider carry?

As many as the saving still covers the delay. Distance between drops, food or grocery type and the promise made set the point, and the model finds it.

Does stacking suit groceries as well as restaurants?

Yes, often more easily, as groceries tolerate a short wait better than hot food. Zone shape and basket size set the real limit.

A day of trip data is enough to start. Send it to a private briefing and we show you how many of your single trips had room for a second order inside your own promise.