[ad_1]
During the pandemic, retailers were forced to embrace e-commerce. But some have found they struggle to maintain customer loyalty as consumer needs change and shopping patterns change. With fierce competition from the likes of Amazon, customers have proven to have little patience for websites that don’t deliver what they want. According to Baymard Institute research, for every 100 potential customers, 70 leave without making a purchase.
That’s why Purva Gupta started Lily AI, one An AI-powered platform that connects retailers or brand consumers with the products they want to buy. Co-founded by Sowmiya Narayanan, Lilly provides algorithms designed to power web store components such as search engines and product discovery carousels.
Lilly today announced it has raised $25 million in Series B funding led by Canaan, bringing its total funding to $41 million.
“Different consumers search in unique ways, making it important to create common and long-tail searches to build the right product taxonomy for retail ecommerce products,” Gupta told TechCrunch in an email. “About the frustrating experiences you’ve had on retail ecommerce sites and irrelevant results, or worse, no results at all, even though the retailer clearly carries the product you’re looking for.”
Prior to co-founding Lilly, Gupta held various roles at Eco India and UNICEF. Narayanan at Texas Instruments Yahoo! (Full disclosure: TechCrunch’s parent company) and Box, she was a full-stack web dev for the product Box Notes.
Lilly started life as an app for retailers to understand the personal preferences of women shoppers around fashion. But when traction is hard to come by, Gupta and It inspired Narayanan to build a more enterprise-focused solution packaged as a plug-in, software-as-a-service subscription product.
Lilly now maintains a team of fashion, home and beauty “experts” who help refine product taxonomies, which are then used to train algorithms for product discovery and recommendations. (The team researched and developed ways to convert things like “ribbed fabric” and “minimal clothing style” into a mathematical “language” so the algorithms could help.) Basically, Lily stores detailed information on products based on attributes (eg, “style,” “fit,” and “coincidence”) and uses customer data derived from product names associated with the item’s attribute data to predict each customer’s affinity for product attributes in the catalog.
Image Credits: Lily A.I
Gupta acknowledged that there are other companies in the product labeling and automated product labeling areas that rely on automation and AI. For example, Depict.ai offers a product recommendation tool that pulls from data from across the internet. Black Crow AI is developing a platform to predict which products e-commerce customers will buy, while Constructor sells a framework that powers the search and discovery of digital retail markets.
Meta also experimented with clothing feature prediction on Facebook’s marketplace, two years ago it demonstrated a system that could extract clothing features and fashion styles from photos of models on Instagram and Flickr.
But she argues that Lily is one of the most powerful options in setting up. Gupta also stressed that the platform is as privacy-friendly as possible, not using customer names, addresses or financial transaction information to enable anonymous user interactions on its customers’ ecommerce sites.
“The IT decision makers we work with are focused on a more realistic and realistic application of Lilly and being on the strategic front. They are interested in the depth and accuracy of the information that Lilly can provide; how we train the models; and the accuracy of the results and confidence levels,” she said. “We win by customizing our product to meet their needs and have a dedicated customer success team available to take into account changes in goals or outcomes over time.”
Either way, big-name clients have signed up for Lilly’s services to date, including Macy’s, The Gap and its various brands, Bloomingdale’s and thredUP.
Lilly is loathe to release its revenue figures publicly, and the 87-employee company said it does not have a headcount forecast for the end of the year. Gupta brushed aside questions about the volatility, saying Lilly was “well positioned” to take advantage of new retail assets in the coming months, even as macroeconomic headwinds emerged.
“Lily AI has grown exponentially. Since the start of the pandemic, health crises have accelerated retail’s shift to e-commerce and digital transformation,” Gupta said. “We will use the new funding to further expand our enterprise and mid-market retail e-commerce brands in home, beauty and fashion. A rich set of analytics for our clients.
[ad_2]
Source link