Lily AI secures funding to expand personal recommendation tech

Dive Brief:

Lily AI, a startup that bases product recommendations on the emotional context of customers, announced that it has secured $12.5 million in Series A funding, according to a company blog post.
The funding round was led by Canaan with support from existing investors NEA, Fernbrook Management and Unshackled Ventures.
Lily AI utilizes "deep product data and anonymized customer behavior data" to present personalized e-commerce experiences, according to the company.

Dive Insight:

Discussion regarding e-commerce personalization has always been tied to algorithms and data analysis, but has yet to fully incorporate the emotional elements of shopping. Lily AI touts that it focuses on how to communicate the fit and feel of products while digging into the emotional context of shopping decisions.

"Most personalization technologies are segment-based because neither the insight about the product nor the customer is rich enough," the company said, stating that customers that have similar profiles when it comes to body shape, location and brand preferences may have vastly different tastes. Additionally, Lily AI focuses on improving site search, enhancing filters and providing product recommendations.

Depth of understanding of who a consumer is can potentially mean a big payout for companies. A study from Monetate and WBR Research found that 93% of businesses with advanced personalization strategies increased revenues. Additionally, 77% of businesses that exceeded their revenue goals in 2018 had a documented personalization strategy, while 74% had a dedicated budget for those efforts.

Other retailers are also researching and implementing means of further customizing shopping experiences. Last summer, eBay rolled out a series of personalization features aimed at showing products to users that suit their interests and shopping habits. For consumers who can't describe the item they're trying to purchase, the site has an image search function that is enabled by artificial intelligence and machine learning to better recognize objects.