How to use image recognition to detect damaged products
16 Jul 2025
3 min read
It’s terrible when a customer has a damaged or defective product. It can also be time-consuming for agents to address. There can be a back and forth to get customers to share the right images, and then an agent has to review the images to check whether a refund is due.
The good news if these issues are consuming a lot of your agents’ time is that they can be sped up and even automated entirely. Welcome to the world of Visual AI.
How to speed up “Damaged Product” workflows
As a platform building AI Agents for ecommerce businesses we talk a lot about resolving customer issues. While there is obvious value in fully automating a customer service interaction, there can be a lot of value in just partially automating it. Here’s why:
If a customer has an issue with a damaged product and wants a refund, then a customer service agent needs some information in order to action this. This could be images or videos of the damage, proof of purchase, warranty information, serial numbers, and proof of identity.
Then there might need to be a follow up because one of the images is blurry, or the customer has missed one of the crucial pieces of information, or so on.
If you fire off an email one evening about a damaged product, the agent may ask for all of this information the next day while you are in the office without access to all this information. Suddenly this simple request has lasted days – the customer is starting to get impatient, and it’s no one’s fault.
Now, imagine that instead of having to wait for an agent to come online to ask for all of this, you had an automated response that would ask for all the necessary information. Suddenly you’ve eliminated that lengthy back and forth, and the whole process is massively sped up.
The goal here is to ensure that the customer service agent has everything at her fingertips to quickly assess the situation and then close things off. If you can validate, using AI, that the files the customer has sent are valid and appropriate then you can save even more time.
But what about using AI the whole way through. This is where Visual AI really comes into its own.
Using Visual AI for Image Recognition
Using the power of AI platforms’ ability to recognise images, now you can even check the images that customers send for defects or damage. By uploading pictures of common issues with your products you can train an AI Agent to be able to recognise those issues when they occur.
This means that your AI Agent can already make a call about whether a refund or replacement is needed, or some other action is required. You could even fully automate this and have the AI process it immediately.
Similarly you could use it to check serial numbers are valid, or that the item itself is authentic based on certain brand specifications.
Not all “damaged” items require replacement. Sometimes the customer needs to be educated on how to care for their product. Let’s give an example.
Online florists and plant suppliers need customers to put their products in water straight away but sometimes the plant doesn’t seem to come to life.
Time is a crucial factor here, so it’s important that customer service teams are able to jump on these issues quickly. Visual AI can detect the plant and then be trained to give the appropriate advice considering the plant, the condition it is in, and how long it has been since the plant arrived.
If it has only been 24 hours, the advice might be to wait another day or so. If there are signs of damage or mold, then the brand can ship some replacements or offer a refund. And so on.
Here is our case study with Bloom & Wild which explains this exact use case.
How to get started with Visual AI
To get started, you will need enough images to train a model in order to successfully detect products and defects. If you sell something that is generic, such as a plant or flower, then you may be able to find data from elsewhere. If everything is very branded, then you may need to go back through your tickets and look for images that customers have sent you.
If you have a cache of data, we can help to assess if it’s enough to be confident about Visual AI’s ability to detect faults.
So if you want to start automating for damaged and defective products, speak to us today.