Infosearch provides the best image classification services for all industries. In this article lets see a case study of how a retail brand increased sales through effective image classification services. Contact Infosearch for your outsourced image classification services.
Background:
A well-known fashion
retail company was looking for ways to improve the user experience of its
e-commerce website for sales to be improved. The brand’s online store lists tons of products, with little chance for customers to come across relevant
items within the shortest time. The retailer also acknowledged that better
image classification could help the customers find the products that they are
looking for hence enhancing the image and increasing sales.
Challenge:
The first difficulty
was tired categorization and organization of hundreds if not thousands of
products that constantly arrived. The process of manual tagging and
categorization was time-intensive, and often inaccurate resulting in the production of inconsistent results in displaying and searching through products
suitable for customers.
Solution:
To overcome this
issue, the brand established an image classification system using Artificial
Intelligence which pools the type of product by analyzing the pictures. It
utilised CNN-based approaches to categorise the product images, which could be
anything from “dresses,” “shoes,” “accessories,” etc. The AI model was trained
with a large set of labeled product images allowing it to identify certain
features and style assignments relevant to each category.
Apart from basic
separation based on the categories provided, the AI system might also determine
other characteristics, for instance, colour, texture and type of product (e.g., “flowering dress,” “red sneakers”). This helped in enhancing the digital
tags which in turn enhanced the search and the recommendations for the
customers.
Implementation:
1. Data Preparation:
To create the model, the brand accumulated a set of various images of products
and labelled them. This dataset is comprised of images from different classes,
styles and angles to make the model more flexible when dealing with new
products.
2. Model Training: In
training the model, deep learning methods especially CNNs were employed to
identify these patterns and features in clothes product images. The model was
systematically updated and assessed to achieve high levels of accuracy in
guide image classification.
3. Deployment: As
mentioned earlier, the identified AI model trained was embedded in the brand’s
e-commerce platform. When new products were added, the system recognized and
tagged them to the right category thus maintaining uniformity on the site.
4. Search and
Recommendation Optimization: The enhancement of image classification helped the
brand optimize its search capabilities and make recommendation engines
better. Consumers could now search through all available products based on the
desirable qualities or characteristics thus making the shopping experience less
general.
Results:
Increased Sales: This
brought about by the adoption of AI-based image classification improved the
sales. The kind of results that the brand offered to the consumers were
discovered to have enhanced conversion rates by 20% due to enhanced product
visibility and relevant search outcomes.
Enhanced User
Experience: This was not only enjoyed by customers as they were able to acquire the
products which they were looking for faster and this increased their
satisfaction thus increasing the rate at which they could come around to
purchase more products.
Operational
Efficiency: It helped the brand in the automation of processes that enabled
roaming the running scale of the inventory through setting up image
classification.
Conclusion:
Thus, this case
focuses on the effects of adopting image classification through Artificial
Intelligence in the retail sector. As a result of the new LP-telling approach,
the categorization and the subsequent tagging of product images contributed to
enhanced usability of the brand’s e-commerce platform, and thus resulting in
greater sales and a superior customer experience. It shows that the use of AI
is highly beneficial for retail businesses and, particularly, for such stages
as product search and selection.
