How can improve the efficiency of a e-commerce business reliant on specialized parts replacement?
Identification of the correct replacement parts was forming a bottle neck in the process and often resulted in missidentified items. The existing process was a very time consuming and manual one invlolving discussion with the customer, browsing through thick spare part catalogues, and always carrying the risk of ordering a wrong component. We automated this entire process with machine vision technology and integrated the identification process directly into a new e-commerce platform.
Through a WhatsApp integrated service, you can quickly and easily take a photo of the broken component and send it directly to Green Master. Once in our system, our machine vision application uses identifiable data points from the submitted imagery to match it to an item in the Green Master catalog of parts with a far higher degree of confidence than the manual process.
Once an item is identified the system will automatically reply with a link to the identified part within the Green Master e-commerce platform, where you a user can directly purchase their replacement or new component in confidence that their order will match their need.
The efficiencies created by the system impacted not just Green Master as a company, but also their customers. The reduction of manual consultation and resolving ordering issues meant vast time savings at Green Master. The reduction in miss-identified parts meant more satisfaction for their customers who’s confidence in the product, and Green Master, greatly improved as a result.
We don’t mean to be aggressive. We’re just enthusiastic about solving problems. Challenges fuel us.
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