In today's digital age, businesses strive to ensure that they offer their customers a seamless experience that is personalized and optimized to fulfil specific demands.
Understanding customers' pain points and finding fitting solutions are paramount to satisfying end customers. For the economic development of a company, gaining insight into how customers perceive their products will help them improve their offers and the product itself.
In this case study, we focus on our AI-based solution “Product sales feedback analyzer” for an e-commerce website, which examines bulk feedback data from customers and vendors to understand and interpret product information.
Our client is a leading manufacturer and distributor of computer hardware products, laptops, desktops, servers, monitors, etc. With a solid market reputation in Australia and New Zealand, our client channels its products through partners, including retailers, educational institutions, government agencies, and other business entities that purchased computer products in bulk.
The client implemented our AI-based product feedback analyzer on multiple platforms to generate meaningful insights from the feedback data from vendors and customers. We continue to work alongside them as their reliable partner.
The business approached Zlabs to build an application powered by AI, which would offer insight into customer feedback while eliminating all the possibilities of error arising from manual work.
We developed an AI-based server-side and web application to enable an accurate and timely understanding of bulk feedback data from customers and vendors.
Through our customized AI model, we could determine business priorities and desired outcomes from a large amount of feedback data. Using our AI customer analytics tools, we were able to derive insights to understand market positioning and achieve continuous business improvement.
By leveraging our sales feedback analyzer, our customer was able to:
Different insight reports are generated for management to make informed decisions. Our AI systems organized and classified a large amount of feedback data for efficient interpretation.
The AI-based application analyzes each feedback and email submitted by customers and vendors. Our feedback analyzer identified keywords and product details from bulk feedback data and stores them in a database.
Using our AI-powered feedback analyzer, the application was able to identify the positive or negative emotions of customers and vendors.
Performed in-depth analysis of clients' e-commerce feedback data with precision to reduce human error and improve the quality of insights derived from feedback data.
Concise summaries for each product are created from feedback data and presented using interactive dashboards to make it easy to understand.