Operations Guide
If you use third-party fleets for delivery, you already know the problems: drivers who don't know your store's pickup process, who can't find the loading dock, who no-show or go dark mid-route. It's not the drivers' fault — they handle hundreds of deliveries a day across dozens of businesses. They can't be set up perfectly for every store. This guide breaks down the 9 most common driver issues and how AI-powered delivery orchestration solves each one without adding headcount.
Issue #1
This is the single most common driver issue businesses deal with. Third-party fleet drivers handle hundreds of deliveries a day across dozens of different businesses. They aren't going to know your specific store layout, your pickup process, or where you stage orders — and that's completely reasonable given the volume they handle.
At pickup: The driver arrives and doesn't know where to go, who to ask for, or where the order is staged. Your staff has to stop what they're doing, figure out which order the driver is there for, and walk them through the process. What should take 2 minutes turns into 15. Multiply that across every pickup, every day.
At dropoff: The driver may not have seen the delivery notes, doesn't know which entrance to use, and can't find the apartment. The delivery gets left in the wrong spot, the customer is frustrated, and your team fields the complaint.
AI Voice Agents proactively call drivers with clear, specific instructions for your store — where to go, what to pick up, where to deliver, and any special notes. The driver gets everything they need before they even arrive, in their preferred language. Your staff doesn't have to explain the process to every new driver. The AI handles it.
Issue #2
This one is just as frequent as pickup coordination issues and makes them worse. Third-party fleet drivers handle tens — sometimes hundreds — of pickups per day across many different businesses. Every single store has a different process.
One store wants them at the back door. Another has a dedicated pickup counter. Another needs them to check in with a specific person. Some stores package orders in advance; others need the driver to wait. Some have loading docks; others expect a driver to walk through the retail floor.
Drivers can't memorize all of this. They're doing too many pickups at too many locations. So they walk in the front door, ask the first employee they see, and hope for the best. Your staff has to stop what they're doing, figure out which order the driver is there for, and walk them through the process from scratch. Every time.
AI agents proactively call or text the driver before they arrive with your store's exact pickup instructions — which door to use, where to park, who to ask for, where the order is staged. The agent is there for the driver throughout the pickup, available to answer questions in real time. Your staff doesn't have to explain the process to every new driver. The AI does it for them, every time.
Issue #3
A driver is assigned to a pickup. The pickup window comes and goes. No driver. No update. No ETA. Your team starts calling the fleet provider, trying to figure out what happened. Meanwhile, the customer is waiting, the order is sitting on the counter, and your staff is burning time on something that should have been automatic.
Late pickups are even more common than no-shows. The driver is technically coming, but they're 30 minutes late, then 45, then an hour — and nobody knows because nobody is actively tracking them.
AI agents automatically call drivers to confirm ETAs as the pickup window approaches. It's interesting how much faster drivers move when they know someone is actively monitoring them. The simple act of a call asking "what's your ETA?" gets drivers to prioritize your pickup, communicate if there's a real delay, and show up on time. If a driver still no-shows, the delivery orchestration platform automatically re-dispatches to a different fleet.
Issue #4
Most deliveries come with dropoff notes — apartment numbers, gate codes, "use the side entrance," "leave with the doorman," "ring buzzer #3." These notes exist because the customer took time to write them. And drivers miss them constantly.
The result: packages left at the wrong door, deliveries marked as complete when the customer never got them, drivers standing outside an apartment building with no idea how to get in. The customer calls your team, your team calls the fleet, and everyone wastes time on something that was already written in the delivery notes.
AI agents proactively communicate dropoff instructions to the driver — and can answer basic questions in real time. Which entrance? Apartment number? Gate code? Where to leave the package? The agent has all the delivery notes and relays them clearly. The driver doesn't need to dig through an app or interpret notes they may not even be able to read.
Issue #5
When a driver texts or calls your customer directly, you have zero control over that interaction. Some drivers are perfectly professional. Others send curt, confusing, or outright rude messages. The customer doesn't distinguish between the driver and your brand — as far as they're concerned, that message came from your business.
A single unprofessional message can undo a great product experience. And you don't even know it happened until the customer complains — or quietly never orders again.
AI agents filter and polish driver messages before they reach the customer. If a driver sends something rude, curt, or unprofessional, the AI intercepts it, cleans up the tone and language, and delivers a polished, brand-appropriate version to the customer. The customer only ever sees professional communication — regardless of what the driver actually wrote.
Issue #6
Sometimes a driver just won't cooperate. They won't follow pickup instructions, they won't respond to calls, they won't follow the delivery notes. You've tried communicating, but the driver isn't interested in doing the job the way it needs to be done.
With a single-carrier setup, you're stuck. You either deal with the bad driver or cancel the delivery entirely and start over from scratch. Neither option is acceptable when a customer is waiting.
Some fleet providers allow unassignment — and a delivery orchestration platform uses it. If a driver is uncooperative or unresponsive, the platform pulls them off the order and re-assigns to a different driver. The customer doesn't know anything changed. The delivery still gets made. One bad driver doesn't ruin the experience.
Issue #7
Proof-of-delivery photos are supposed to verify that the right items were picked up and delivered to the right place. In practice, drivers snap blurry photos of the wrong thing, take a picture of a random doorstep that could be anywhere, or skip the photo entirely.
When a customer says "I never got my order" and the only proof you have is a blurry photo of a brown door, you have nothing. You eat the cost, re-send the order, and hope it doesn't happen again.
AI agents call the driver to confirm the right items were picked up, that the delivery was made to the correct location, and who received it if applicable. Instead of relying on a photo alone, the platform verifies the delivery through direct communication — creating an additional confirmation layer that protects both you and the customer.
Issue #8
A driver shows up in a compact sedan for a delivery that needs a cargo van. Or they arrive on a bike when the order is three cases of wine. The vehicle doesn't match the profile, doesn't have enough space, or can't handle the payload. You can always re-dispatch to a different driver — but now you've wasted 20 minutes, the order is sitting there, the customer's window is tighter, and you're starting the process from scratch. The annoying part isn't that it's unsolvable — it's that you didn't catch it before the driver showed up.
AI agents call the driver before pickup to confirm their vehicle matches the profile and can handle the payload. Some businesses create custom AI agents that walk drivers through the specific requirements — size, weight, item count, anything that matters for that order. If the vehicle doesn't match, the delivery gets re-assigned before the driver even shows up at your store. No wasted trip, no wasted time.
Issue #9
Third-party fleet drivers don't work exclusively for you. They're juggling multiple pickups and deliveries from different businesses on the same route. Your delivery is one of several, and if their other stops run long, your customer's delivery window gets blown — and nobody tells you until it's too late.
AI agents call the driver to confirm ETAs and check whether other stops on their route will affect your delivery window. If the driver has too many stops and can't make the window, the platform doesn't wait and hope — it re-dispatches to a different fleet provider that can meet the timeline. Your customer still gets their delivery on time.
The Pattern
Look at the list above. Pickup coordination, store process confusion, no-shows, dropoff problems, rude messages, uncooperative drivers, bad photos, wrong vehicles, multi-stop conflicts — they all come down to the same root cause: drivers handle too many deliveries across too many businesses to be perfectly set up for yours.
The traditional fix is to throw people at it. Hire someone to call drivers. Train staff to guide pickups. Field customer complaints. But that doesn't scale — and it certainly doesn't work when you're doing 50, 100, or 200+ deliveries a day across multiple fleet providers.
Getcho, a delivery orchestration platform, puts AI agents on every single delivery. They call drivers with your store's specific instructions, guide them through your pickup process, confirm ETAs, verify vehicles, relay dropoff details, filter rude messages, verify photos, and escalate to your team only when human judgment is actually needed. And businesses can create their own custom agents with instructions specific to their workflows — because every operation is different. Your ops team manages by exception — not by babysitting every delivery.
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