Read time 2 minCustomized solutions are the way forward in the world of business, and e-commerce is no exception to this. Machine learning, artificial intelligence (AI), and data annotation have come together to benefit customers and sellers alike. In this scenario, computer vision models have come to the forefront to simplify the process of choosing from huge online shopping catalogs.
When there is a wide range of choices available, it can be difficult for the customer to find the specific item quickly and easily. The amount of time and effort required to track down the particular product can prove frustrating and dissuade the shopper from proceeding further. For sellers, challenges include creating new listings controlling price inflation, and identifying fraudulent practices.
This is where computer vision AI models that make use of data annotation come in. Data annotation can streamline the process of online shopping in the following ways:
Simplify Searches – When words are used to conduct searches while shopping online, they might not always show the exact matches. Using images instead of searches can prove much more efficient here. Computer vision lets customers choose from a wide range of options by analyzing images at the pixel level. With AI, it is possible to match the images taken by customers with products in online inventories. This speeds up the process while helping customers get what they want.
Personalization – Data annotation can help enhance the shopping experience for buyers and sellers equally by targeting each customer with the right campaigns. AI techniques make it possible to offer product recommendations based on prior purchases or browsing history. Data annotation and labeling can help customize marketing campaigns on a large scale to sustain greater productivity and profitability. Automation also ensures higher efficiency all around.
Product Classification and Listing – Listing products and categorization is at the heart of every e-commerce business. Appropriate classification and accurate listing of products can help customers find what they are looking for quite easily. AI applications backed by machine learning techniques such as object recognition enable online shopping apps to identify items and create automated lists.
Elimination of Fraudulent Selling Practices – Data annotation can help cut down on exploitative and fraudulent selling practices in the e-commerce segment. For instance, computer vision models can help pinpoint products priced higher on purpose. This can help identify problem sellers and boot them off the platform to promote fair practices.
If you want to help your customers find everything they want with ease and ensure a superior shopping experience that will have them coming back, data annotation can be of help. Springbord helps you bridge the gap between machines and humans with our professional expertise in data annotation and labeling. We offer tailor-made solutions to meet all your data processing needs and help reduce your workload.
