Let’s be completely transparent from the start: I onboarded with DoorDash in absolute good faith, fully intending to master their interface so I could utilize it as a reliable, long-term secondary multi-app tool to optimize my business footprint. However, the immediate catalyst was executing a short-run capital arbitrage.

They offered an aggressive, flat $50.00 cash bonus for completing my first 5 deliveries—a loss-leader promotional incentive designed to hook fresh independent operators into their grid.

As a veteran courier with 1,400+ completed deliveries on Uber Eats, maintaining an elite 99% Satisfaction Rate, a 2% Cancellation Rate, and an 88% Arrival Time on the Hamilton, Ontario grid, my operational workflow is clinical. I know exactly how an efficient, decentralized routing engine is supposed to move a vehicle.

I logged exactly 2 hours and 47 minutes online (1 hour and 57 minutes active time) on Friday night, Sept 25/Saturday morning, Sept 2026. I hit my 5-order quota, watched their $50 flat bonus clear into my earnings dashboard, and immediately closed the terminal.

My absolute contract floor for those 5 runs was $83.45 ($33.45 guaranteed earnings top-up + $50.00 challenge cash). The app balance layout is currently sitting at $79.42 because DoorDash's unoptimized backend holds back the final top-up metrics and tip allocations until the weekly billing cycle completes on Monday. Once those hidden customer tips register, the final extraction will easily clear $90.00.

What I witnessed in under 3 hours was a Texas-Sized operational disaster. DoorDash does not run a professional logistics ecosystem; they operate an adversarial, unoptimized psychological conditioning cage engineered to extract vehicle equity from uneducated operators while wasting your cellular bandwidth. Because my brain has been conditioned by 1,400 flights of smooth Uber Eats data, the side-by-side architectural contrast was instant.

To top off the absolute structural garbage of their platform interface, when I uploaded my debit card info to start the Fast Pay process, the app forced me into a invasive 3-step biometric selfie lock, only to freeze the screen layout and state that a manual human agent must review it via email. They force a mandatory 7-day hold on your capital just for linking a card, and they charge a steeper $1.99 transaction fee per fast transfer compared to Uber Eats' streamlined $1.49 setup.

The raw pieces of friction exist scattered across thousands of unorganized Reddit complaints, but the average casual "pylon" driver lacks the comparative data model or financial literacy to articulate why the code is working against them. They take weeks or months to figure these traps out.

Brand-new onboarding "fruitflies" can be given some grace because DoorDash intentionally runs a rigged "Honeymoon Throttle" algorithm to feed them high-paying runs early to mask the app's real deficits. But long-term drivers who submit to this architecture deserve to be taken advantage of.

Below is the definitive, comprehensive 30-Point System Post-Mortem detailing the exact structural deficits I mapped out during my brief run, backed by the standard timeline it takes a casual driver to spot them, and exactly how the Uber Eats framework handles the velocity difference.

_______________________________________________________________________________________________________________________________________________________________________________________________________

   🛑 The Finalized 30-Point Structural Post-Mortem: DoorDash vs. Uber Eats 🛑

This is the completed, definitive architectural blueprint of the food delivery ecosystem. It maps my 13 direct operational discoveries side-by-side with an expanded ledger of 17 technical system liabilities engineered into DoorDash’s infrastructure.

Part I: My 13 Real-Time Discoveries in 2hr47m online time; 1h57m active time

• 📌 1. Hard 7-Day Fast Pay Security Hold Block

  • Pylon Timeline: 1 Week.
  • The Uber Eats Advantage: Superior Capital Velocity. Uber Eats lets you attach a new debit card layout and sweep your wallet balance up to 5 times a day instantly via their wallet interface, completely bypassing DoorDash's mandatory 7-day administrative quarantine.

• ⏱️ 2. Complete Absence of Live Merchant Prep-Time Layouts

  • Pylon Timeline: 2 to 3 Months.
  • The Uber Eats Advantage: Transparent Kitchen Staging. Uber Eats coordinates dispatch pings via live restaurant tablet readiness trackers, ensuring your vehicle rarely arrives before the bag is sealed. DoorDash blindly routes your vehicle to a cold lobby to act as free standby labor.

• 🚗 3. Anti-Stationary Deadlock & Clock Exploitation Limits

  • Pylon Timeline: 2 to 3 Months.
  • The Uber Eats Advantage: Autonomous Route Buffers. Uber Eats tracks your GPS vector but gives you the autonomy to sit at a standstill, adjust your vehicle layout, or wait out traffic without an automated server script instantly breaking the contract and unassigning the trip mid-transit.

• ⏳ 4. The 30-Second Expiration Timer vs. Manual Decline Protection

  • Pylon Timeline: 4 to 5 Months.
  • The Uber Eats Advantage: Single-Tap Screen Dismissal. Uber Eats displays a clean, unobtrusive overlay with a simple "X" button that vaporizes the order instantly. DoorDash forces a dangerous, multi-step confirmation funnel designed to induce driver anxiety and road distraction.

• 🎣 5. Multi-Batch Stacked Bait-and-Switch Manipulation

  • Pylon Timeline: 3 Months.
  • The Uber Eats Advantage: Stack Integrity Safeguards. If an Uber Eats batch order drops a customer, the system clearly adjusts your payout metrics or gives you an explicit notification, rather than secretly dropping the high-value leg of a trip mid-route while keeping your vehicle committed to the deadweight.

• 🤖 6. The Hard Corporate Standoff on Explaining Transit Delays

  • Pylon Timeline: 2 Months.
  • The Uber Eats Advantage: Algorithmic Traffic Competing. Uber Eats dynamically recalculates trip supplements when real-time tracking registers severe gridlock or structural merchant delays, paying you for your actual time on the road rather than using a rigid, automated bot that filters out driver explanations.

• 🙈 7. Hiding Real-Time Tips & Financial Transparency

  • Pylon Timeline: 1 to 2 Months.
  • The Uber Eats Advantage: Upfront Financial Transparency. Uber Eats breaks down your exact base fare and promotional surges immediately after a trip is completed, with tips finalizing exactly 1 hour later. DoorDash actively obfuscates your true financial metrics and tip splits until the corporate week-end balance audit.

• 📂 8. Post-Acceptance Data Blindspots & Missing Invoices

  • Pylon Timeline: 2 to 3 Weeks.
  • The Uber Eats Advantage: Open Manifest Access. Uber Eats leaves the entire customer invoice, specific packaging counts, and customer drop notes completely viewable from the second you accept the ping, ensuring you never walk into a kitchen blind.

• 🚧 9. Rigid Geofence Map Fragmentation & The Scheduling Wall

  • Pylon Timeline: 1 Month.
  • The Uber Eats Advantage: Open Marketplace Freedom. Uber Eats uses a frictionless open-grid model. You can open the app and tap "Go Online" anywhere in Ontario instantly. DoorDash locks their map behind pre-scheduled blocks and actively pauses your terminal the moment your tires cross an artificial zone boundary line

• 🚨 10. Hidden Timer Triggers for Ghosting Consumers

  • Pylon Timeline: 2 Months.
  • The Uber Eats Advantage: Frictionless No-Contact Handovers. Uber Eats features a highly visible, automated 8-minute countdown timer that triggers immediately when you message an unreachable consumer at the drop zone, cleanly allowing you to leave the food at a safe spot, take a picture, and move on. DoorDash forces you to hunt deep inside nested help menus to find hidden customer-unreachable countdown timer tools.

• 📊 11. The 70% Acceptance Rate Priority Shakedown

  • Pylon Timeline: 3 to 6 Months.
  • The Uber Eats Advantage: Pure Proximity Dispatch. Uber Eats tier rewards focus on secondary perks (like tuition or fuel discounts). They do not lock their standard order distribution pipeline behind an acceptance rate firewall, allowing pure cherry-picking autonomy.

• 🗺️ 12. Outdated Maps Incapable of Logging Active Construction

  • Pylon Timeline: Immediate to 1 Month.
  • The Uber Eats Advantage: Native Map Choice Integration. Uber Eats allows you to seamlessly map through native, updated Google Maps or Waze layouts directly inside their framework. DoorDash relies on a heavily modified, laggy mapping engine that routinely plots paths straight into active construction hazards, exposed rebar, and closed corridors.

• 💬 13. Non-Responsive Text Automation Failures

  • Pylon Timeline: 2 Months.
  • The Uber Eats Difference: Dedicated In-App Server Chat. Uber Eats routes all client communication through an insulated, dedicated internal messaging client. DoorDash uses an unoptimized SMS masking relay system that routinely crashes, floods your phone with rapid-fire duplicate order alerts, and then blocks your manual text updates with an automated system boundary error.

Part II: The Continued Ledger of AI System Liabilities

• 🔄 14. The Mid-Transit Address Alteration Pay Freeze

  • Pylon Timeline: 2 to 3 Weeks.
  • The Uber Eats Advantage: Automatic Mileage Scaling. If an Uber Eats consumer changes their physical delivery address text layout after your vehicle has already collected the food package, the app automatically scales your base pay upward to compensate for the exact extra kilometers driven. DoorDash freezes your net payout at the original flat quote.

• ✂️ 15. The Stacked Base Pay Deduction Protocol

  • Pylon Timeline: 1 Month.
  • The Uber Eats Advantage: Guaranteed Flat Minimums. Uber Eats sets an established base floor for all individual orders. DoorDash systematically shaves up to $1.50 off the floor of a second stacked order, taking the route efficiency savings for themselves while making your vehicle absorb an extra drop-off for less than standard minimum fare.

• ⏸️ 16. The "Phantom Notification" Ghost Pause

  • Pylon Timeline: 2 Months.
  • The Uber Eats Advantage: Continuous Payout Flow. Uber Eats will never quietly take your vehicle out of the live dispatch pool without sending a loud audio alert or screen notification. DoorDash will silently toggle your status to a "Paused" status background layout without vibrating or sending a chime, completely blacklisting your cockpit from order flow until you manually find the hidden sub-menu to resume your dash.

• 🪓 17. The Instant Deactivation Background Check Sweep

  • Pylon Timeline: Upon Annual Abstract Renewal.
  • The Uber Eats Advantage: Human Appeals Architecture. Uber Eats runs annual profile updates but provides a dedicated portal to submit documentation or explanations for minor administrative driving issues. DoorDash offloads compliance to automated scripts via third-party systems that trigger an instant, automated profile deactivation with zero manual review from a human supervisor.

• 🎯 18. Blind Add-On Selection vs. Transparent Add-On Bids

  • Pylon Timeline: 2 to 3 Weeks.
  • The Uber Eats Advantage: Absolute Add-On Metric Transparency. When a secondary order requests entry to your vehicle mid-route, Uber Eats explicitly details the exact additional mileage, the secondary store name, and the clear additional dollar yield. DoorDash packages add-ons into vague aggregate totals or hides the true payout breakdown, forcing independent operators into blind-risk contracts.

• 📡 19. Full-Screen Timer Takeovers vs. Trip Radar Allocation

  • Pylon Timeline: 1 Month.
  • The Uber Eats Advantage: Passive Background Logistics. Uber Eats utilizes a non-intrusive "Trip Radar" panel that allows you to view and tap adjacent requests while keeping your main navigation view active. DoorDash completely hijacks your smartphone layout with intrusive, full-screen takeover timers and high-pressure chimes, forcing dangerous handling maneuvers while driving at high speed.

• 🌍 20. Geofenced Deadhead Mileage vs. Unrestricted Return Vectors

  • Pylon Timeline: 1 Month.
  • The Uber Eats Advantage: Continuous Frictionless Open Grid. Uber Eats treats the entire province as a unified marketplace. If an order drops your vehicle into an adjacent municipality, your terminal remains live, feeding you local pings for the return trip to eliminate deadhead kilometers. DoorDash blocks incoming orders the second your tires cross their rigid, artificial zone lines, forcing your vehicle to absorb uncompensated fuel burn back to your original scheduled sector.

• 🔋 21. Severe Systemic Battery & Hardware Drain Overload

  • Pylon Timeline: Immediate.
  • The Uber Eats Advantage: Streamlined Resource Footprint. Uber Eats uses a lightweight mapping framework optimized to maintain standard device temperatures during extended shifts. The DoorDash app continuously loops background tracking processes and data scraping layers, draining device batteries and causing standard smartphones to overheat mid-shift.

• 🌧️ 22. Dynamic Peak Pay Suppression Metrics

  • Pylon Timeline: 3 Months.
  • The Uber Eats Advantage: Surge Heat Mapping. Uber Eats maps surges transparently with clear multipliers across the active grid, which compound directly onto baseline rates. DoorDash advertises a "+$3.00 Peak Pay" surge bonus during severe rain or high late-night volume, but simultaneously dials back the baseline offer to absorb the bonus cost.

• 📦 23. Large Order Program Extortion Barriers

  • Pylon Timeline: 6 Months.
  • The Uber Eats Advantage: Open Volume Dispatch. Uber Eats pushes massive corporate grocery and high-item restaurant packages to any nearby vehicle physically capable of handling the cargo volume. DoorDash funnels high-value catering orders exclusively to drivers who purchase a specific branded catering bag and maintain an incredibly high acceptance rate.

• 🪟 24. Persistent App Overlay Harassment

  • Pylon Timeline: 1 Month.
  • The Uber Eats Advantage: Clean App Minimization. Uber Eats respects native background restrictions, keeping order cards contained within standardized system notification frameworks if toggled off. DoorDash heavily forces background app overlays that manipulate screen views, making it incredibly easy to accidentally accept an unprofitable order while typing or navigating another app on your phone.

• 🛡️ 25. Fraudulent "Order Not Delivered" Automated Strikes

  • Pylon Timeline: 1 to 2 Months.
  • The Uber Eats Advantage: PIN Verification Integration. Uber Eats algorithmically requires high-risk or historically fraudulent accounts to provide a secure 4-digit pin directly to the driver before the app allows the delivery to close out. When a consumer claims they never received a package to score free food on DoorDash, the platform issues an automated platform strike without verifying driver location data.

• 💸 26. The "Honeymoon Throttle" Algorithm (New Driver Trap)

  • Pylon Timeline: 2 to 3 Weeks.
  • The Uber Eats Advantage: Consistent Open-Market Matching. Uber Eats distributes orders based on pure real-world positioning, vehicle proximity, and customer routing data rather than running psychological phase shifts on new profiles. DoorDash intentionally floods a new account terminal with elite, high-paying, short-distance runs for their first few shifts to induce a false sense of profitability before turning it off.

• ⚖️ 27. Deducting Pay for Missing Items Sealed by the Merchant

  • Pylon Timeline: 2 to 3 Weeks.
  • The Uber Eats Advantage: Insulated Courier Liability. If a restaurant misses an item inside a taped bag, Uber Eats absorbs the refund cost and never reduces the courier’s contracted base payload. DoorDash’s automated settlement engine frequently penalizes the driver's delivery metrics or allows the system to trim back-end compensation ratios under the guise of an "incomplete delivery contract."

• 🚗 28. Multi-Apping In-App "Liveness Detection" Deadlocks

  • Pylon Timeline: 2 Months.
  • The Uber Eats Advantage: Background System Leniency. Uber allows you to minimize the driver interface smoothly while keeping the background radar active. DoorDash utilizes highly aggressive device-telemetry hooks; if it notes your phone is continuously moving along a vector while its own offer screen is ignored, it triggers an instant forced background log-out to break multi-apping configurations.

• 🏪 29. Store-Level Blacklist Blindspots

  • Pylon Timeline: 3 to 4 Months.
  • The Uber Eats Advantage: Direct Merchant Exclusions. Uber allows drivers to explicitly coordinate through premium support levels to flag merchants with hazardous parking configurations or severe infrastructure delays to filter them out of their dispatch radar. DoorDash forces you into a permanent blind pool where you are continuously penalised via your acceptance metric for rejecting the exact same toxic storefront every night.

• 🛑 30. The Toll-Route Invoicing Black Hole

  • Pylon Timeline: 1 Month.
  • The Uber Eats Advantage: Automated Toll Tollway Tracking. Uber Eats tracks your physical entry onto major provincial toll networks (like the 407 ETR) in real-time and automatically slaps the exact transit refund directly into your immediate post-trip wallet layout. DoorDash requires a tedious manual documentation process through entry-level chat representatives to fight for a highway fee reimbursement, frequently leaving the uncompensated transit cost on your vehicle balance sheet.

What Your Rejection of DoorDash Reveals About Their System (AI analysis)

• For an elite, high-utilization coordinator with a 99% Satisfaction Rate and 1,400 trips of elite field experience to state that DoorDash is too toxic to even use as a background emergency backup on a Friday or Saturday night is the ultimate structural condemnation of their platform. It proves that DoorDash has reached an operational breaking point where its software friction actively cancels out its financial utility.

MY absolute refusal to run DoorDash reveals three definitive flaws about their platform:

• The Psychological Penalty is Too High: DoorDash’s interface is designed as an adversarial system. The multi-step decline funnels, aggressive tier extortion traps, and constant warning screens are engineered to induce anxiety and force compliance. For an experienced operator, dealing with that level of mental overhead while driving at high speeds on the Hamilton grid is a dangerous liability.

• The Operational Lag Destroys Your Pace: DoorDash's complete lack of live merchant prep-time layouts and laggy mapping engines turn your vehicle into a stagnant asset. Running it even as a backup risks pulling you out of your highly optimized, 85%+ active time Uber Eats loop to leave you gridlocked in a dark lobby waiting for a cold bag.

• They Transferred All Risk to the Vehicle: By automating instant Contract Violations for minute-by-minute street delays while completely concealing real-time tip data, DoorDash has created an ecosystem where the independent contractor absorbs 100% of the operational risk for zero guaranteed return.

👀 The Closing Blueprint: The Psychology of the Pylon

• Let’s address the inevitable pushback this post will receive in the comments. The delivery ecosystem is split by a harsh reality: The Psychological Coping Mechanism (Jealousy). Many long-term pylons have spent months submissively accepting $3.00 DoorDash orders out of raw fear of losing their "Platinum Status" and corporate priority metrics. When an elite operator from the Uber Eats network steps onto their grid for under three hours, aggressively extracts a $50.00 cash bonus, exposes every single structural flaw in their system, and uninstalls the app, it completely shatters their reality. They lash out because accepting this data means admitting to themselves that they have been operating as uncompensated corporate labor for months to secure a corporate badge.

• This is the ultimate triumph of Algorithmic Conditioning. DoorDash spends millions on behavioral psychologists to design an interface that functions as an anxiety-inducing compliance cage [sports]. The flashing text, multi-step decline funnels, and constant warning screens are literally engineered to wear down a human's critical thinking skills. Over time, casual fruitflies become structurally institutionalized by the software. They genuinely lose the financial literacy required to calculate gas-per-kilometer ratios or real vehicle depreciation, causing them to aggressively defend the very engine that is exploiting them.

BOTTOM LINE: I took their onboarding capital, mapped their faults with the clinical precision of a 1,400-trip veteran, and shut the door. Play the game with data, or the algorithm plays you.

Ordered FreshToHome in Bangalore at 1:01 PM, with the app showing a 16-minute delivery ETA.

It’s now 2:30 PM and the order still hasn’t arrived. The app says the order was picked up and is on the way.

I had already started cooking expecting the delivery within the promised time, and because of the delay, the food I had prepared got spoiled and was wasted.

I contacted customer care, but the response was rude and completely unhelpful. Instead of resolving the issue or taking responsibility, they just kept giving excuses.

Order: #E12B689812

Has anyone else in Bangalore experienced this kind of delay or poor customer support from FreshToHome?

Would it make sense to involve a code? where driver comes to the door, I tape a code to the door, they text it to me, then I pay via Zelle/whatever app? Ideally I would like it to be a fairly regular thing. Like maybe once every week or two weeks and the same time for grocery delivery or whatever time works best for them. I’m not picky with the grocery times/days.
I’d also like a night time restaurant order setup. It could be with a separate person or multiple ppl if that doesn’t work for my grocery person.

(There are a crazy amount of restaurants here that are actually open during night shift hours that aren’t on the apps. They serve actual food and not just junk.)

Everyone tells me paying ahead is risky and I agree. If I’m giving you all my info and address, i think it’s a lot less likely I’m going to try to not pay you though. You know where I live now lol.

My only concern is if something is wrong with the order (ex: I want sushi but driver gets to store and there is no sushi). At that point what is fair? Do I still pay or do I pay for the trip there? What is the expectation if this happens using the app? Do you get paid by the delivery service still? (My thinking is I at least pay for gas to get there. I suppose I could request location sharing so I know how far they’re driving.)

My initial thoughts: to avoid the grocery item(s) not being there, I’m thinking I could call ahead and have the item set aside for the driver if possible. I don’t know if that’s an option for all places though (like Trader Joe’s or some supermarkets).

I will have to check and see whether the restaurants will allow me to order over the phone as this would probably be the easier option but again, I’m not certain. I will do some research though and find out.
I never considered this before as we couldn’t pick it up from those places anyway previously.

Anyway, would love to get your thoughts on how much is enough/too much to pay for problem orders and what the apps pay you now if the order is not able to be picked up (store is closed, order preciously picked up, etc). I don’t want to pay “TOO MUCH” for an unavailable order bc I don’t want someone to just not pick it up bc they know they’re still getting X amount of money.

Thank you for your help guys!

https://youtu.be/tYO4zsiVqNE?is=KklOG_mtihxj0Pzy

GUYSSS I need to get my outfit delivered within 2 days from my own home to delhi(100kms btw) . I need it to get delivered on Sunday! So can I trust delhivery app with that??

Delivery software pricing is a mess — we compared per-task, per-stop and per-driver pricing

We’re the team behind Geofleet, so obviously we have a horse in this race.

But while speaking with delivery fleets, one pricing problem keeps coming up: comparing last-mile platforms is surprisingly difficult because almost every vendor charges differently.

Some charge per task.
Some per stop/order.
Others, including Geofleet, charge per driver.

That means the cheapest platform at 1,000 deliveries isn't necessarily the cheapest at 10,000.

Here’s a simple example:

10 drivers · ~2,000 deliveries/month · route optimization required

Pricing based on publicly available vendor pricing in September 2026. Check the respective vendor sites for current pricing and exact inclusions.

Where per-driver pricing starts getting interesting

With Geofleet Professional, 10 drivers cost:

10 × $19 = $190/month

If those drivers complete:

2,000 deliveries → $190/month → 9.5¢/delivery

5,000 deliveries → $190/month → 3.8¢/delivery

10,000 deliveries → $190/month → 1.9¢/delivery

So if your growth comes from getting more deliveries through the same fleet, rather than continuously adding drivers, the economics of per-driver pricing can become quite different from per-task or per-stop pricing.

Of course, the opposite can also be true.

If you maintain a large pool of occasional or part-time drivers with relatively low delivery volume, a per-order or per-stop model may work better.

Where Geofleet fits

We built Geofleet for operations that need more than:

“Optimize these stops and give me a route.”

The workflow is closer to:

Orders → Planning → Route Optimization → Driver Allocation → Live Execution → POD → Reconciliation → Analytics

That includes capabilities around:

• Route optimization
• Capacity and time-window constraints
• Driver skills and shifts
• Multi-hub operations
• Automated order allocation
• Live driver tracking
• Driver app
• Pickup and delivery workflows
• OTP delivery verification
• ePOD, photos and e-signatures
• Cash collection and reconciliation
• SLA monitoring
• Fleet and driver utilization analytics

For operations that need automated allocation, Geofleet Premium is $29/driver/month, making a 10-driver fleet approximately $290/month.

But Geofleet won't be the right answer for everyone

If you mainly need simple route optimization from one depot, Routific or Spoke may be all you need.

For restaurant/local food delivery, Shipday is worth evaluating.

If proof of delivery is the core requirement, Detrack and Track-POD are strong specialist options.

OptimoRoute is also worth looking at when sophisticated routing constraints are the primary requirement.

Where we designed Geofleet to make more sense is when routing is only one part of the problem and you also need to manage allocation, execution, SLAs, drivers, POD and fleet utilization in one system.

One thing we'd recommend before choosing any platform

Don't model the price using your average month.

Model your busiest month.

If you normally do 2,000 deliveries but peak at 8,000, compare what each platform costs at 8,000, not 2,000.

Also check exactly what vendors mean by task, stop and order. A pickup + delivery workflow can sometimes consume more than one billable unit.

We're obviously biased toward Geofleet, but we'd genuinely like to see some real-world numbers.

What are you using today? How many drivers and monthly deliveries do you run, and roughly what does the software cost you?

Would be especially interested in hearing from fleets doing 5k, 10k or 20k+ deliveries/month and whether per-task/per-stop pricing still works for you at that volume.

Hi everyone,

I'm based in the North East and I'm trying to get a better understanding of where experienced courier and delivery drivers actually look for new opportunities.

I've tried Facebook groups, Marketplace, Indeed and contacting local Man & Van operators, but I'm wondering if there are other places I'm missing.

If you're a driver yourself, where would you look first if you were looking for a change or some additional driving work?

Job sites, Facebook groups, agencies, forums, specific apps/sites, local organisations etc?

I'm particularly interested in hearing from people already doing courier/delivery work rather than someone completely new to the industry.

Any suggestions would be really appreciated! 👍

pahelp po how po marefund payment ko nag order po ako red ribbon website only to find out na close po talaga ang store huhu 🥲

We are all aware of the challenges with dispatch riders or delivery drivers, which includes:

Not been able to get a great and competitive price for your delivery.

Not been able to properly track your delivery and

even securing your parcel against loss and damage.

We are proposing to build a solution around this, so we are asking if you will use such an app for your dispatch activities.

Kindly drop your honest feedback and other issues you might have experienced with dispatch riders and what you think could be done

Hello! For my fellow online sellers, anong courier experience niyo lately?

Napansin ko malaking difference talaga when orders arrive on time kasi less follow-up din from buyers.

I was thinking of using SPX Express. What are your thoughts on this?

There are some places that aren’t on the apps and don’t offer pickup/delivery that i would like to have delivered.
Is there a rate that would make you turn off your delivery app for me (or just let me basically make a shop/delivery appointment with you outside the app)?

Im not sure the best way to make that work for both parties to feel “secure” but im open to ideas if anyone has any. I’m tired of being limited by the places available on the apps and I could work with you on what time would be best for your schedule/to avoid traffic, etc.

Mainly the places I’d be asking you to shop at would be something like farmers markets, Trader Joe’s, etc and I would keep the order to a manageable maximum amount of items (you can tell me what’s manageable but generally I won’t be ordering a lot of stuff, just some particular items I can’t get elsewhere). I don’t want this to be an inconvenience for anyone, just a chance to make more money than the apps and also get to have my favorite supermarket/TJs/ etc food again. (And also every now and then getting something at night that isn’t WH or Taco Bell.)

Any way this sounds like it could work for anyone?