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The Analyst Team
Kia Ling Teoh
Follow AnalystSenior Analyst, Advertising
As part of Omdia's media and entertainment team, Kia Ling Teoh covers global advertising, channels, and programming research, with specific interests in traditional TV’s digital extensions and content strategies. Her research focuses on the development of the advertising and television programming markets including, but not limited to, key markets in Asia Pacific.
Kia Ling provides analysis and forecasts on subjects such as TV broadcasters’ advertising revenues, including those from linear TV and ad-supported online video, and programming spend. She is widely quoted in media publications and has authored topical reports covering advertising M&A and TV and online video markets in China, Indonesia, and India. She is based in Penang, Malaysia, and joined Omdia in April 2014. Prior to joining Omdia, Kia Ling was a lead analyst at the Governance, Risk, and Compliance division of Thomson Reuters. She holds a Master of Science in international business management from University of Kent, UK. She is fluent in English, Chinese Mandarin, and Malay.
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Rob Moyser
Follow AnalystSenior Analyst, TV & Online Video
Rob covers the television market in Western Europe, tracking key developments in the pay-TV and free-TV industries from cable, satellite, terrestrial, and telco perspectives. His work also focuses on cross-platform TV viewing time in the US and Europe.
Rob holds a Bachelor of Arts (Hons.) in history from Anglia Ruskin University in Cambridge, England.
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Matthew Evenson
Follow AnalystSenior Analyst, Media and Entertainment
Matthew tracks the content strategies of TV and streaming groups across the world, analyzes trends in individual title viewing on streaming platforms such as Netflix, and contributes to Omdia’s wider coverage in the Digital Content & Channels Intelligence service. He also leads much of Omdia’s coverage on Netflix and the French pay-TV and streaming market as part of Omdia’s TV & Online Video Intelligence service.
Prior to joining Omdia, Matthew worked as an analyst for Broadcast Intelligence and previously worked on scripted television productions in the UK. He holds a Bachelor of Science (Hons.) in cell biology from Durham University and a master’s degree in forensic science from the University of Central Lancashire (UCLAN).
Juan Villegas
Follow AnalystResearch Analyst
As part of the media and entertainment team, Juan’s main areas of research are TV & Online Video, covering the Latin American markets.
Juan joined Omdia in July 2021 after two years working at Futuresource Consulting as a research analyst in the Home Electronics team covering devices such as TV sets, media streamers, and home video players. Before entering the market research industry, he worked in the corporate communications sector and politics in his native Venezuela along with freelance content contributions in the music business. Juan holds a licentiate degree in sociology from Andres Bello Catholic University in Venezuela and a master’s degree in marketing from the University of Manchester, UK.
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Daoud Jackson
Follow AnalystSenior Analyst
Daoud Jackson leads Omdia's research on pay-TV and online video markets across the Middle East, Africa, Turkey, and India as part of the media and entertainment team. He also oversees advertising market coverage in MENA and India. Daoud delivers analysis of key regional and global developments through research interviews, financial modelling, and industry analysis.
Since joining Omdia in 2022, Daoud has presented at numerous industry events and received citations in international news coverage about the evolving media landscape. His research spans SVOD and social video platforms, changing seasonality patterns in MENA, emerging content trends, and successful monetization strategies for developing markets.
Daoud holds a master’s degree in global history from the University of Oxford. Before Omdia, he worked as an analyst at social listening company Brandwatch and as a research analyst at Nielsen covering the global publishing industry.
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These are Omdia driven recommendations based on content that is both similar, and has been frequently visited by other users in combination with the content you are currently viewing.
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