AfterShip EDD - helps you provide customers with the same EDD prediction experience as other prominent third-party platforms

The EDD (Estimated Delivery Date) function has become a standard feature in China's e-commerce industry, but why are so many overseas customers still willing to pay for our AEDD, and even accept a premium price of 30% for it?
In today’s article, let us unveil the mystery of AEDD, including:
- What is AEDD ? How does it relate to AI EDD?
- What value can AEDD provide to customers, and why are customers willing to pay for AEDD ?
- Why can AEDD products have higher coverage and accuracy than the EDD provided by 99% of carriers?
I hope this article can help everyone understand the value and working principle of AEDD and the direction in which efforts and improvements are needed so that together we can provide products and services that create greater value for customers.
What is AEDD? What is AI EDD?
In daily life, we often see estimated delivery time indications on shopping interfaces, which will be used to understand when we expect to receive the package. This time is what we refer to as EDD.
EDD stands for Estimated Delivery Date. Strictly speaking, it represents the time when the package is first attempted to be delivered.
AEDD is AfterShip’s EDD product, which mainly serves customers who prioritize enhancing the shopping experience for their customers and operational efficiency but have weak control over the logistics operations.
For this group of customers, AEDD offers a variety of options, either relying on carriers to provide an estimated delivery time, clients providing the estimated delivery time by themselves, or even just handing it over to AI-powered predictions offered by our AI EDD.
AI EDD is a set of EDD prediction AI models built by AfterShip. Leveraging its huge database and meticulous model tuning, AI EDD not only supports post-purchase scenarios but also provides delivery time estimation for pre-purchase scenarios. It dynamically updates the prediction in case of unexpected circumstances.
Generally speaking, if the predicted value of the EDD is consistent with the final delivery time, it signifies accurate EDD prediction. The earlier the prediction of the EDD value, the higher the likelihood of inaccuracy due to insufficient information. Currently, our AI EDD can achieve an accuracy of close to 90% in the first prediction after the tracking is created. This is undoubtedly a breakthrough in the industry.
So overall, we can say AI EDD is the AEDD product’s core data engine。
After understanding AI EDD and AEDD, you may be curious, how do AEDD products bring value to customers? We will explore the application in two scenarios: pre-purchase and post-purchase:
1. Pre-purchase AEDD
In one sentence, customers who use pre-purchase AEDD can provide their shoppers with an EDD experience equal to that of other major e-commerce platforms!
The two images below demonstrate the implementation of AEDD in pre-purchase scenarios, including EDD display on the product page and checkout page.
Some studies show displaying the clear delivery time of the product and combining it with tools such as order countdown can effectively reduce shoppers' information uncertainty during the shopping process and enable faster purchasing decisions, at least improving the 20% store conversion rate.
Additionally, displaying the corresponding estimated delivery time for different shipping options on the checkout page can help customers more intuitively feel the differences to make better choices of shipping options.
Large e-commerce platforms such as Amazon and Temu have already improved their conversion rates by displaying EDD in pre-purchase scenarios. However, many DTC customers or emerging shopping platforms currently rely on third-party carriers. The customer has limited control over the logistics process, and cannot obtain the EDD of the logistics provider for reference before creating a tracking. Therefore, it is challenging for them to demonstrate an accurate EDD value in pre-purchase scenarios.
The AEDD pre-purchase product created by AfterShip is based on the powerful prediction capabilities of the AI EDD model. It can support EDD value prediction in pre-purchase scenarios without relying on data references from carriers. It effectively addresses the pain point for this group of customers.
Furthermore, we also provide services for Shopify customers who have restricted R&D resources. Integrated one-stop EDD plug-in, customers only need a few simple configuration steps to install and display, providing customers the same EDD prediction experience as other prominent third-party platforms!
2. Post-purchase AEDD
In addition to the pre-purchase scenario, AEDD also plays an important role in the post-purchase scenario. You may have encountered a similar frustrating situation - gifting a birthday to a friend, only to have the transportation delayed due to bad weather or accidents. However, the merchant failed to provide any notice of delivery delay during the entire process, resulting in the gift arriving late for your friend’s birthday.
To avoid encountering similar unfortunate situations, we can keep customers informed of the status of the package at any time through the display of post-purchase EDD, alleviating unnecessary anxiety and waiting. This not only helps to build trust between merchants and shoppers but also improves the satisfaction of the shopping experience.
There is even more data proving that post-purchase EDD display can effectively reduce WISMO tickets by 70%, Therefore, EDD in post-purchase scenarios is widely used by customers in notification emails and tracking pages.
As mentioned before, AI EDD is one of the data sources of post-purchase AEDD. Although customers have access to EDD from other sources, why do we still recommend enabling AI EDD?
We use the following three keywords to answer this question:
- High accuracy: Up to now, the AI EDD model has been trained using 4.4 billion tracking data, with the training data continuously growing at a rapid rate. With the massive training dataset surpassing our competitors, AI EDD can provide more accurate predictions earlier than carriers. This undeniably appeals to customers who prioritize efficiency and accuracy.
- Dynamic updates: On average, AI EDD updates 2-3 times during transit. Dynamic update is the unique capability of AI EDD, which can effectively improve the real-time accuracy of prediction results. In contrast, EDD from other sources lacks this capability. Especially in the face of logistics events such as extreme weather and strikes, AI EDD can trigger dynamic updates, promptly adjust predictions, reduce order cancellation rates, and improve shoppers' satisfaction.
- High coverage: At present 80% of AfterShip trackings can be predicted by AI EDD. This coverage is 3 times that of carrier EDD. In comparison to carriers’ EDD, AI EDD can provide effective prediction services to more customers, ensuring that customers can access comprehensive logistics information.
How does AEDD make accurate predictions?
After understanding the basic content and practice of the AEDD product, it's important to delve into the powerhouse behind this product - the AI prediction model.
First, let’s take a look at how AI predicts delivery times.
For example, let’s consider Yoyo bought a mobile phone case in Temu on Monday. After receiving the order, the merchant started sorting and packaging and contacted the carriers to schedule parcel pickup from their warehouse at 8 a.m. on Tuesday. Once the carriers picked up the parcels on Tuesday, they attempted the first delivery to Yoyo on Friday. However, Yoyo was not at home, so the carrier made another attempt on Saturday and successfully delivered the package.
The example above illustrates a typical shopping process, where the AI EDD model only predicts logistics behavior, which is the time from picking up the parcels on Tuesday to the first delivery on Friday. The customer is responsible for providing the processing time required to prepare the parcel before carrier pickup. Additionally, the EDD value does not account for the time taken for re-delivery.
What factors does the AI EDD model take into account when predicting the transportation time of carriers?
Take a moment to consider if your ideas align with the current AI EDD practices.
1. Logistics information:
During the training process, the AI EDD model utilizes the logistics data provided by the Courier team.
These data cover core elements such as the carrier, the type of logistics service, the origin and destination address, the transportation route, and the mode.
Importantly, the model incorporates checkpoint messages during transportation to support the EDD dynamic update function to ensure the accuracy and timeliness of predictions.
2. Other external events:
Apart from the aforementioned common logistics information, the model will also consider traffic conditions, weather conditions, and any major social events that may impact the shipping process.
For example, in July last year, there was a serious strike at UPS, which resulted in a shortage of delivery manpower and many delayed trackings. The AI model promptly considered the impact of the incident and adjusted the estimated delivery time.
In addition, during major promotions and holidays, logistics companies usually experience slower operations due to a surge in parcel volume. The AI model will also make corresponding adjustments based on such events to ensure more accurate prediction results
Now, I would like to summarize the main competitive advantages of AEDD products compared to other EDD products in the market:
1. Powerful AI algorithm capabilities: Leveraging a huge training database, we provide more accurate and timely estimated delivery time predictions.
2. Integrate with Shopify for a one-stop EDD plug-in: Offered to Shopify customers who currently do not have enough R&D resources.
Summarize
AEDD aims to improve the shopper experience by offering Estimated Delivery Date (EDD) prediction capabilities that rival those of world-class e-commerce platforms.
This capability helps give shoppers more certainty in pre-purchase scenarios and improves deal completion rate;
In the post-purchase scenario, timely feedback on the estimated delivery time can be provided to optimize customers’ shopping experience and to foster customer repurchase and excellent word-of-mouth.
If you want to provide customers with the same EDD prediction experience as other prominent third-party platforms, feel free to contact us!
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