Last Updated: August 8, 2026 | The platform\u2019s order assignment interface, rewards, and order acceptance rules are subject to change based on your account, city, and time. Please refer to the information currently displayed in the delivery app and official announcements for the most up-to-date details.<\/p>\n
The most common mistake during peak hours isn\u2019t necessarily accepting the wrong order, but accepting every order that comes along. Although orders come in thick and fast during lunch and dinner hours, restaurant preparation times, traffic, parking, and elevator wait times also slow down. If you only look at the pay shown on the screen without factoring in the total time the trip takes, you\u2019ll likely end up working harder than usual, yet your actual hourly earnings won\u2019t be any higher. A more reliable approach is to treat each order as a small decision involving \u201ctime, distance, and risk,\u201d rather than simply focusing on whether the pay is high.<\/p>\n
This article outlines a peak-hour order-acceptance process that you can test for yourself. The focus isn\u2019t on teaching you to aim for a fixed price per kilometer, nor is it a guarantee that a certain driving strategy will always be profitable. Instead, it\u2019s designed to help you quickly assess\u2014in just a few seconds\u2014how much time a ride might take, where it will take you, and whether you\u2019ll be able to accept another ride smoothly after completing it. For new drivers, starting with simple records to establish your own baseline is usually more practical than blindly copying someone else\u2019s standards.<\/p>\n
Estimate the total time first; don't just look at the kilometers displayed on the screen.<\/strong><\/p>\n When evaluating an order, you can break it down into five stages: traveling to the restaurant, waiting for the food inside the restaurant, packing and picking up the order, delivering it to the customer, and returning to the order-acceptance area after completion. The distance displayed by the platform usually reflects only a portion of this process and does not fully account for traffic lights, locating the correct address, community access checks, going up stairs, and the return trip. During peak hours, if the restaurant is swamped with orders, even an order that initially seems very close can end up taking a significant amount of time just to wait.<\/p>\n The simplest way to estimate is to first ask yourself three questions: How long will it take me to get to the store? How long is the current wait time at this store? Are there any follow-up orders at the delivery location after I drop off this one? If you estimate the entire trip will take 25 minutes, divide the pay by 25, then multiply by 60 to get a rough \u201chourly pay for the duration of the trip.\u201d This isn\u2019t your actual hourly wage, since it doesn\u2019t account for gas, maintenance, supplies, or downtime, but it can help you compare which of two orders is more efficient.<\/p>\n For example, suppose two orders both show a fare of 100 yuan: one is estimated to take 20 minutes and is in a high-demand area, while the other is estimated to take 35 minutes and is in a remote residential area. The value of these two orders is not the same. The estimated hourly pay for the former is 300 yuan, while that for the latter is approximately 171 yuan\u2014and the latter may also require a return trip. What really matters is how long it takes to complete an entire cycle, rather than just looking at the order amount.<\/p>\n Include store wait times in your personal database<\/strong><\/p>\n For orders over the same distance, the difference often comes down to the restaurant. Popular restaurants may be handling dine-in, takeout, and multi-platform orders simultaneously during lunch and dinner hours; some restaurants prepare meals on time, while others wait until the delivery driver arrives before starting to prepare them. Instead of complaining based on vague impressions, use your phone\u2019s notes app to record the date, time, arrival time at the restaurant, pickup time, and the reason for any issues. After collecting data for one to two weeks, you can then make an informed judgment.<\/p>\n When keeping records, don\u2019t be quick to assume that a single delay represents a consistent pattern. It could be due to a temporary staff shortage, special meal requests, system delays, or rain that day. Only add a store to your list of high-risk peak hours if it experiences long wait times multiple times during similar time periods. If you\u2019ve already accepted an order and encounter a long wait, first follow the app\u2019s procedures, save a screenshot and record the time, and then decide how to proceed; you can also use this site\u2019sGuide to Recording and Handling Customer Wait Times<\/a>...to avoid making the situation even more tense by letting emotions get in the way of communication.<\/p>\n A restaurant database doesn\u2019t have to be complicated. For each restaurant, it\u2019s enough to record just three items: \u201caverage wait time,\u201d \u201cparking availability,\u201d and \u201cpeak-hour crowding.\u201d Once you\u2019re familiar with the area, you\u2019ll be able to quickly adjust the system\u2019s estimated time just by seeing the restaurant\u2019s name\u2014which is usually more accurate than setting a citywide threshold per kilometer.<\/p>\n When combining orders, first consider the workflow, then how much the commission will increase.<\/strong><\/p>\n Whether combining orders is worth it depends not on delivering two orders at once, but on how much extra time the second order adds. Combining orders can only improve efficiency if the two pickup locations are close to each other, the delivery routes are in the same direction, and the meals can be prepared within a reasonable timeframe; if the route requires crossing major thoroughfares, backtracking, or if one of the restaurants is particularly slow to prepare orders, the additional compensation may not be enough to offset the delay.<\/p>\n When you see a combined order, check the following four things in order: whether the new pickup location is on your route; the risk of delays at both locations; whether the delivery order makes sense; and whether the first customer\u2019s order will sit in the car for too long. You should also take the space in your insulated bag into account\u2014if large drinks, soups, and pizzas are crammed together, the risk of spills or food damage increases significantly. When space is limited, turning down one order is often more time-efficient than having to pay compensation or handle customer complaints afterward.<\/p>\n The information displayed on the platform, the ability to decline additional orders, and the procedures following a cancellation are all subject to change. Do not treat any individual\u2019s order acceptance or cancellation rate thresholds found online as a general rule, and do not assume that skipping a particular order will necessarily affect the next assignment. You can rely on the information currently displayed in the app, your partnership agreement, and official guidelines; it\u2019s best not to base major decisions on unverified rumors about the algorithm.<\/p>\n The delivery location determines the opportunity cost of the next order<\/strong><\/p>\n Long-distance rides during peak hours aren\u2019t necessarily bad; the issue lies in the driver\u2019s location after dropping off the passenger. If the destination is near a commercial district, a train station, or a popular dinner spot, the driver may be able to pick up the next ride quickly after completing the trip. However, if the destination is in a mountainous area, an industrial zone, or on the outskirts of a large residential area\u2014where orders are scarce\u2014the time spent returning must be factored into the cost. This revenue-free travel time is often the reason why reported earnings look good on paper, but actual hourly earnings end up being lower.<\/p>\n In familiar areas, you can identify three types of locations: spots where orders come in consistently, spots prone to traffic jams, and spots where it\u2019s difficult to return after delivery. When you receive a cross-district order, first determine which category the destination falls into, then assess whether the pay is sufficient to cover the return trip. Don\u2019t park illegally or make dangerous U-turns just to stake out the so-called \u201chot spots\u201d; areas where you can find legal places to wait and enter and exit safely usually yield better long-term efficiency.<\/p>\n Weather can also affect location value. During rain, bridges, underpasses, and shopping mall driveways may become congested; in the summer, be sure to schedule time for hydration, cooling off, and rest during midday. If fatigue is already affecting your judgment, it\u2019s not worth the risk\u2014no matter how high the peak-hour bonus. The losses resulting from accidents and injuries far exceed the loss of a single ride; you may want to review your insurance coverage in advance.A Guide to Insurance for Food Delivery Drivers<\/a>...and your own insurance policy and the platform's supporting documents shall prevail.<\/p>\n Use a 7-day tracking exercise to identify your threshold for accepting orders<\/strong><\/p>\n The threshold for accepting rides shouldn\u2019t be based solely on \u201cX yuan per kilometer.\u201d We recommend keeping track of the following for seven consecutive days: hours online, number of completed rides, fare earnings, bonuses, tips, total mileage, fuel or charging costs, parking fees, and any obvious idle time. At the end of each day, calculate two figures: total earnings divided by total online hours, and the net hourly rate after deducting directly identifiable costs. This is the only way to determine whether a particular order-taking strategy actually improves your earnings.<\/p>\n Next, review the low-efficiency orders and briefly note the reasons, such as \u201cwaited more than 15 minutes for the meal,\u201d \u201cdelivered to a remote area,\u201d \u201ctook too long to find the address,\u201d \u201chad to turn back after combining orders,\u201d or \u201crush-hour traffic.\u201d If the same reason recurs frequently, incorporate it into the decision-making criteria for the following week. For example, instead of refusing all long-distance orders outright, raise the acceptance threshold for orders that \u201care delivered to a remote area and require an empty return trip\u201d; instead of rejecting all combined orders, avoid combinations involving two high-risk stores with long wait times.<\/p>\n Under the current law governing food delivery services, the base pay for each order must be calculated proportionally based on the duration of the delivery service, must not be less than 1.25 times the minimum hourly wage, and must not be less than 45 yuan per order; for details on the actual calculation and applicable conditions, please refer toExplanation of Compensation on the Ministry of Labor\u2019s Special Section for the Protection of Food Delivery Riders\u2019 Rights<\/a>. The statutory minimum is not the same as your personal net income goal. You still need to keep track of fuel costs, vehicle depreciation, maintenance, and waiting time yourself, so you don\u2019t mistake revenue for actual profit.<\/p>\n The bottom line for peak efficiency is safety and traceability<\/strong><\/p>\n No matter how refined your order-acceptance strategy is, you must never run red lights, ride against traffic, use your phone while riding, or park illegally to save time. During peak hours, when there\u2019s a lot of information to process and pressure is high, you should secure your phone, adjust the navigation volume, and stop in a safe location before confirming a new order. If disputes arise regarding meal delivery, house numbers, customer instructions, or waiting at a restaurant, saving the necessary screenshots, communication records, and timestamps will be more helpful than relying on memory to explain the situation afterward.<\/p>\n If you encounter issues such as incorrect deliveries, damaged food, customers who cannot be contacted, or billing disputes, first follow the platform\u2019s customer service and appeal procedures. Do not make compensation promises on your own that exceed your capabilities, and avoid posting customers\u2019 personal information on public social media platforms. This site\u2019sGuide to Resolving Food Delivery Disputes<\/a>I've organized the records in chronological order; if there are any issues related to suspensions, contracts, or compensation, they can also be tracked.Food Delivery News and Policy Updates<\/a>...Subject to government announcements and official notices from the platform.<\/p>\n During peak hours, what really makes the difference isn\u2019t how fast you tap, but whether your time estimates are close to reality. First, look at the total trip time; then examine the pickup location and destination; next, assess the increased risk of combining orders; and finally, adjust your threshold based on your own seven-day records. When you can clearly explain why you accepted a particular order and whether the outcome met your expectations, you\u2019ve moved beyond relying on gut instinct and toward a sustainable, adaptable approach to accepting orders.<\/p>\n This article is a compilation of general experiences and information and does not constitute a guarantee of platform earnings, legal advice, or insurance advice. The rules, order-assignment screens, and rewards for each platform are subject to change at any time; please refer to the app, partnership agreements, announcements from regulatory authorities, and your own actual records for details.<\/p>","protected":false},"excerpt":{"rendered":" Taking every order during peak hours may actually lower your hourly wage. This article outlines how to assess pickup, delivery, waiting times, route optimization for combined orders, and return trip costs, helping delivery riders set their own order acceptance thresholds based on their schedules and performance data\u2014rather than relying on a single route as a guarantee of income.<\/p>","protected":false},"author":3,"featured_media":1587,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":false,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[65],"tags":[23,43],"class_list":["post-1330","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-65","tag-23","tag-43"],"yoast_head":"\n