Lookerz provides an AI-powered tool that generates real-time outfit recommendations, tags, and similar items for fashion e-commerce platforms, enhancing product visibility and customer engagement. This solution addresses the challenge of high return rates and unsold inventory by personalizing the shopping experience, leading to a measurable increase in sales.
Funding
$30K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Fashion e-commerce platforms face challenges in visually merchandising products online, leading to low customer engagement, high return rates (up to 30%), and unsold inventory, as customers often miss items buried deep in the catalog. The lack of personalized recommendations and effective product discovery methods contributes to these issues.
Solution
Lookerz provides an AI-powered personalization engine for fashion e-commerce, designed to enhance product visibility and customer engagement. The platform uses machine learning models to generate real-time outfit recommendations, suggest similar items, and create smart tags from flatlay images. By offering dynamic and static outfit suggestions, Lookerz helps customers discover products they might otherwise miss, while smart tags improve search precision and cross-cutting filtration. This leads to increased sales, reduced deadstock concerns, and improved customer loyalty through a more personalized shopping experience.
Target Audience
The primary target audience includes fashion e-commerce businesses with extensive product catalogs seeking to improve product discovery, increase sales, and reduce return rates.
Features
- **Dynamic Outfits ("How to Wear It"):** AI-generated outfits compiled in real-time from flatlay images, displayed on product pages or in a dedicated section.
- **Static Outfits ("Complete the Look"):** Pre-compiled outfits that complement a product page, showcasing a product in various styles.
- **Similar Items ("You May Also Like"):** Product recommendations to facilitate navigation within a category and promote the discovery of older or less-visible items.
- **Smart Tags ("Find Similar"):** AI-driven tags that capture the essence of each product, improving search precision and enabling cross-cutting filtration.
- **Easy Integration:** Widget-based implementation for seamless integration into existing e-commerce platforms.
- **Automated Recommendations:** AI-driven recommendations that automate outfit suggestions, saving time and resources.