Deep dive
Pick a metro and a wedge
Delivery networks are local. A new platform competing with national players needs a reason to exist: a suburb or college town the big apps underserve, a category such as grocery or alcohol, a merchant-friendly fee model or a community angle. Choose one metro, recruit merchants and drivers there first, and keep the MVP focused on the order loop.
Launching small also lets you validate unit economics. Average order value, delivery cost, commission and fees decide whether the business works, and the software should report them per order from day one. Our startup solutions and MVP development teams plan scope around exactly those numbers. A dashboard that shows contribution margin per order, per merchant and per zone tells you within weeks where the model works and where it needs a fee change.
Checkout: fees, tips and tax
Customers expect a transparent breakdown: subtotal, delivery fee, service fee, tax and tip. Several US cities and states have rules about how fees are disclosed and capped, so build the fee calculation as configurable rules rather than hard-coded numbers. Sales tax depends on what is sold and where it is delivered; a tax API returns the right rate for each address and keeps up with changes.
Tips belong to drivers. The ledger should track tips separately from base pay, show drivers exactly what they earned per order and support tip changes after delivery within a time window. Payment products such as Stripe Connect or Adyen for Platforms handle payouts, including instant cash-out for a fee.
- Show the total including all fees before the customer taps Place order.
- Separate food tax, fee tax and tips in your data model.
- Keep an audit trail for every fee rule change.
Dispatch and the driver experience
The dispatcher offers each order to a driver with estimated pay, distance and pickup location. Drivers accept or decline, and the system moves to the next candidate after a timeout. Good dispatch reduces both customer wait and driver idle time; at the start a rule-based system is enough, and predictive models come in the scale tier.
Merchant wait time is the hidden cost in most delivery networks. If drivers arrive early and stand at the counter, they earn less per hour and decline more offers. Ask merchants for a preparation estimate on every order, let drivers report long waits, and use those signals to time dispatch better. Over a few months this data becomes the most valuable input for the scale-tier prediction models.
The driver app is a work tool. It must be fast, readable in a car mount, reliable on poor connections and honest about pay. Background location, navigation hand-off to Google Maps or Apple Maps, photo proof of delivery and quick contact with support are core features, not polish.
Compliance and trust
Expect to handle driver background checks with consent, data privacy rules such as the CCPA in California and the GDPR if you expand to Europe, card industry rules (keep card data with your payment provider) and accessibility expectations for consumer apps. Age-restricted deliveries need ID scanning at the door and rules per jurisdiction.
Contractor classification and minimum pay rules vary by state and city and continue to change. Build pay rules as configuration, keep statements per order, and review the rules for each market with a lawyer before launch. Our security testing and application security work covers the technical side.
Growing beyond restaurants
Once the network has drivers and merchants, the same infrastructure can carry groceries, convenience items, retail and delivery requests from merchants' own channels. Each brings new product work: large catalogues with substitutions, shopper picking flows, cold-chain handling or an API for merchants. These are scale-tier investments that only make sense once the core order loop is efficient.
Running costs grow with volume: cloud, maps, SMS, payment processing, background checks and tax API calls. Budget roughly 15-20% of the build cost per year for maintenance and support, and plan a cloud cost optimization review after the first busy season.