Product Advisor is a top-level affiliate web app, which delivers support to advanced API services like Amazon, Walmart, eBay, Best Buy, etc. If you are looking for a useful product at the most affordable price, Product Advisor can be the best alternative for you.
This amazing tool can help you to find out the perfect product from Amazon, Walmart, eBay, Best Buy etc. so that you can get the products that are perfectly in line with your requirements. We believe this next-generation software will play a significant role to improve customer experience in the future.
Some Advanced Features of Product Advisor:
- Regular price update facility for the products of Amazon, Walmart, eBay, Best Buy, and other eCommerce websites
- Analyzes the total products, and gives genuine reviews for them
- Detects scams and fraud seller
- Uses an intelligent algorithm to ensure real and scam free products
- API: Amazon, eBay, Walmart, Best Buy, Proxy Crawl, Papi, Algolia search, review meta
- Server Side Details: PHP 7.4 ,MySql,Ubuntu, Composer, Node
- Frontend Technologies: Tailwind css,scss,Vue JS,Tiptap, Bootstrap
- Framework: Laravel 8, Vue JS,Nova etc
- Management Tools: Github, Slack, Skype, Agile methodology
The demand of our partners was to provide a next-generation product advisor algorithm to them. At the initial state, our partner came to us with a basic Laravel Nova Admin Panel having some fundamental CRUDS. They were looking for a team they can depend on, and ultimately they found us and trusted us enough to hand-over the project.
Challenges we faced:
- We were in need of a package that will fetch Amazon related data to us, but sadly we did not find a good enough package to support this
- We needed some additional information That we were not getting from amazon API
- We needed a smart algorithm to get some genuine review of the products
- Handling a very large data by job schedule
- Memory Usages
- Image rendering & merging.
How we overcome the challenges:
- To get data from amazon, We created our own version API and released a package for it. Thanks to our dedicated engineers, the effort became successful and it worked like a charm.
- We used proxy crawl on demands, which gave us exact information regarding the things we needed
- We spent several weeks making this algorithm & put our level best, which helped to ensure an optimum quality
- Optimization is the only way to reduce memory usages. We optimized every possible query and situation to handle things perfectly.
- We used image intervention for image rendering and merging, which can compress 8 images into 1.
This project was one of our best works ever. The project delivered a huge success to us and led us to a huge boost.