Share your ideas with us

As a merchant, I allow shoppers to exchange items for different variants during returns, which may have different prices. For example, a Small size costs $30 while a Large size costs $50.   Currently, Shopify allows me to adjust prices manually only after the Return Merchandise Authorization (RMA) is submitted. If aftership could facilitate charging or refunding price differences for variants during the return request process, it would greatly streamline our operations and enhancing the overall efficiency of RMA management.

Hello to Aftership team, I am from Fabricdekho.com. I am here to write a request for providing a return request  button along with seller approval so that return could be the easy process. As return is a difficult process as of now. Customer need to request again n agian to seller. We should work on this so we can ease the process of return.   Thanks.

We use this to ship to clients it would be nice if we could save clients within the system to send notifications to. 

I see that Aftership is already having public api end points available for tracking and returns. i would like to have similar one for reviews.

Could you please make a slight programming change, could you please allow swipping back to the main list of packages once you looked at a package info    iOs

The background is that I sell my products on multiple marketplaces, and each has different return flows that the aftership Returns page cannot handle. It would be much easier if there is a Returns API that can meet my requirements below.   Need: - I need a Returns API to allow creating RMA/return requests without having to use the Returns Page to file it.  - I can call the API and pass the information regarding the Return Reason Resolution, etc in one go.  - Once I call this API, it will return creation in Pending or Auto-Approved Status.

I work in the furniture industry with thousands of products and continuous new product listings.   Consumers often inquire about variations in materials and sizes between similar pieces of furniture, placing a significant burden on my support team. Generating comparison pages for every query we receive is unfeasible due to the volume of requests.   Given the potential of AI to suggest comparable items, could it also be leveraged to pinpoint disparities among products and present these distinctions to consumers? Such a system can alleviate my workload significantly and potentially reduce bounce rates as well.

The current OpenGraph meta preview generated by AfterShip's referral link system is unacceptable. We run a professional e-commerce business in South Africa selling premium seat covers, yet the influencer link preview looks like a child’s sticker book. Confetti, a USD coupon graphic, and a generic "Get special offers" line? Completely irrelevant, off-brand, and frankly embarrassing when shared by influencers. This isn’t just a design problem. It reflects poorly on our business when our partners share this link on Facebook and social platforms. It gives the impression of an unprofessional or scammy brand — damaging our credibility and costing us leads. We don’t even use USD as our currency. Why are you pushing American coupon-style banners to international stores?

I am utilizing Smile to develop the Reward program for our business. This year, I aim to motivate members to increase their reviews by integrating Reviews into the reward system as bonus incentives. This will allow our members to accumulate extra points by sharing feedback for their purchases.

When a warranty is approved, you can choose to include an label. In the “Warranty claim approved” email, there is no ability to account for this decision. We would need to add an ability to have wording around a label being included as well as a label not being included. Below is an example email we have now.   Two ways this could be addressed: 1. Split this notification into 2 notifications: “Warranty claim approved - with label” and “Warranty claim approved - no label”. 2. Add Flows to Warranties with Split functionality for generated labels.