Zebra Medical Vision

Shane  Greenstein; Sarah  Gulick

Teaching Note | HBS Case Collection | June 2019

Zebra Medical Vision

Abstract

Teaching note is meant to accompany Zebra Medical Vision case, which offers a look at a company’s decisions as a small startup competing with other startups and major technology companies. It also demonstrates the challenges faced by a machine learning company working on brand-new technology, including difficulties finding training data, hiring competition, and negotiating FDA approvals and other government regulations. Teaching Note for HBS No. 619-014.

Keywords: Business Startups; Science-Based Business; Software; Patents; Cross-Cultural and Cross-Border Issues; Health Care and Treatment; Health Industry; Medical Devices and Supplies Industry; Technology Industry; Israel;

Language: English

Format: Print

12 pages

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Citation:

Greenstein, Shane, and Sarah Gulick. "Zebra Medical Vision." Harvard Business School Teaching Note 619-053, June 2019.

The President of Harvard University is facing growing pressure from students, alumni, and other climate change activists that are urging the university to divest its multi-billion dollar endowment from fossil fuel companies. The case summarizes the arguments for and against Harvard divesting, examining past examples of Harvard’s investment decisions and the financial implications of divestment.

Case | HBS Case Collection | August 2019

Twiggle: E-commerce with Semantic Search

Shane Greenstein and Danielle Golan

By 2018, Twiggle, e-commerce search enhancement API, utilized advanced structuring and linguistic tools that understood shoppers’ intent and matched it with the right products. Four years after being founded by Amir Konigsberg (CEO) and Adi Avidor (CTO), Twiggle had developed a search enhancement that plugged into the online merchants’ 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. Twiggle was founded in 2014 by former Google executives Amir Konigsberg (CEO) and Adi Avidor (CTO), who 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 buyer/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 their search quality tended to be less robust and might be easier to improve. They also contemplated a variety of growth opportunities.

Keywords: e-commerce; search technology; customer acquisition; Online Technology; Technological Innovation; Commercialization; Growth and Development Strategy; Technology Industry; Israel;

Citation:

Greenstein, Shane, and Danielle Golan. "Twiggle: E-commerce with Semantic Search." Harvard Business School Case 620-025, August 2019. View Details

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