Twiggle: E-commerce with Semantic Search

Four years after being founded, in 2014, by former Google executives Amir Konigsberg (CEO) and Adi Avidor (CTO), Twiggle had developed a search enhancement that plugged into an online merchant’s existing framework. The company utilized advanced structuring and linguistic tools to build search technology that understood shopper intent and matched it with the right products. Konigsberg and Avidor believed e-tailers were losing enormous revenue due to poor search results. The team built a set of proprietary tools that created a human-like understanding of customer queries in the e-commerce search experience, using natural language processing that translated text into meaning. The team also constructed a semantic model of the e-commerce world for three product domains: fashion, home and electronics. The resulting “ontology” was a set of concepts and categories in a subject area that showed their properties and the relations between them. Twiggle’s tools could also unlock significant online sales revenue by increasing click-through and add-to-cart rates, ultimately improving sales conversions. So far, the company had secured deals with more than half a dozen large e-commerce retailers, and could improve search results in three product categories: fashion, home, and electronics.
The company initially targeted large direct-to-consumer e-commerce players. Yet the cofounders encountered challenges pursuing this type of customer. The customer acquisition process included lengthy, intensive face-to-face sales cycles, expensive and technologically complex proof-of-concept testing, and requests for customization. Konigsberg and Avidor wondered if they should expand their customer focus to target a wider set of smaller e-tailers that still had significant volumes of online search queries, but whose search quality tended to be less robust and might be easier to improve. They also contemplated a variety of growth opportunities.