Subject category:
Strategy and General Management
Published by:
Singapore Management University
Version: 2019-05-10
Length: 8 pages
Data source: Published sources
Abstract
June 20, 2016. It was the day Magic Pony Technology galloped to fame after Twitter announced its acquisition of the Artificial Intelligence (AI) start-up for a reported USD150 million. Co-founded by Rob Bishop and Zehan Wang in London in 2014, Magic Pony specialised in using machine learning, a branch of AI, to optimise image-processing technology that greatly enhanced the quality of video streaming over the Internet on mobile devices. Along with a team of highly-skilled computer and neuro-scientists, Magic Pony brought critical technology in video compression to Twitter which would strengthen the microblogging service's live streaming capabilities. To battle against stagnant subscriber growth, one of Twitter's best bets perhaps was to rely on high-quality live video streaming in an attempt to draw a larger user base from a broader cross-section of the society. On the other side of the deal, the successful exit of the 18-month-old start-up was engineered by its founders based on a mix of strategies which included securing investment from venture capitalists and resisting acquisition offers from smaller players while perfecting the technology until a sizeable offer (ie, Twitter) came along. Looking back, was there a better time to sell? Why was Twitter successful in acquiring Magic Pony while others failed? What made Magic Pony a favourite acquisition target? This case may be used in undergraduate business classes to teach topics related to entrepreneurship, start-ups, and merger and acquisition (M&A). Through this case, students can expect to differentiate between M&As of traditional versus technology firms, and discuss how buying and selling decisions are made on both sides of the deal. Students will learn to identify the forces behind the best timing for a start-up's exit and describe the post-acquisition challenges faced by the founders.
Time period
The events covered by this case took place in 2016.Geographical setting
Country:
United States
About
Abstract
June 20, 2016. It was the day Magic Pony Technology galloped to fame after Twitter announced its acquisition of the Artificial Intelligence (AI) start-up for a reported USD150 million. Co-founded by Rob Bishop and Zehan Wang in London in 2014, Magic Pony specialised in using machine learning, a branch of AI, to optimise image-processing technology that greatly enhanced the quality of video streaming over the Internet on mobile devices. Along with a team of highly-skilled computer and neuro-scientists, Magic Pony brought critical technology in video compression to Twitter which would strengthen the microblogging service's live streaming capabilities. To battle against stagnant subscriber growth, one of Twitter's best bets perhaps was to rely on high-quality live video streaming in an attempt to draw a larger user base from a broader cross-section of the society. On the other side of the deal, the successful exit of the 18-month-old start-up was engineered by its founders based on a mix of strategies which included securing investment from venture capitalists and resisting acquisition offers from smaller players while perfecting the technology until a sizeable offer (ie, Twitter) came along. Looking back, was there a better time to sell? Why was Twitter successful in acquiring Magic Pony while others failed? What made Magic Pony a favourite acquisition target? This case may be used in undergraduate business classes to teach topics related to entrepreneurship, start-ups, and merger and acquisition (M&A). Through this case, students can expect to differentiate between M&As of traditional versus technology firms, and discuss how buying and selling decisions are made on both sides of the deal. Students will learn to identify the forces behind the best timing for a start-up's exit and describe the post-acquisition challenges faced by the founders.
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Time period
The events covered by this case took place in 2016.Geographical setting
Country:
United States