October 1, 2019

Moving Beyond Age and Gender: Syndicated Data Sources

With advertisers increasingly turning to data-driven linear TV, moving beyond traditional age/gender targets, we’ve also seen a proliferation of data sources. How do you know which […]
April 11, 2019

SpotX and clypd Bridge Audiences between National Linear TV and OTT

Discovery and Fox among the first partners to deploy new data-driven cross-platform advertising solution BOSTON and DENVER — April 11, 2019 — SpotX, the leading global […]
October 17, 2018

clypd to Optimize TV Campaigns for Viewer Attention using TVision Data

New York – October 17, 2018 – clypd, the leading audience-based sales platform for television advertising, today announced the integration of TVision attention data into its […]
September 13, 2018

clypd Collaborates with Industry Consortium ATSG to Define Standards for Advanced Audience Targeting in TV; Nielsen Among First to Adopt

The Advanced Targets Standards Group (ATSG), whose members include Disney|ABC and ESPN, AMC Networks, A+E, CBS, CIMM, and Discovery, announced significant progress in bringing advanced audiences […]
February 27, 2018

The Amazing Race of Forecast Models

Deal or No Deal To plan for a TV advertising campaign, it is important to have a good understanding of the trend in TV audiences: who […]
January 18, 2018

New Report: Unlocking the Data Behind Targeted Linear TV

Linear TV remains the primary way of reaching mass audiences effectively. According to Nielsen, in Q1 2017, Americans spent over 11 hours per day interacting with electronic media (including TV, radio and digital). The single largest piece of that was linear TV, accounting for nearly five hours. So, if you’re a beer brand, why advertise to Men 21-34 when you can advertise to all beer drinkers 21+? Making TV advertising better using data is to everyone’s advantage: advertisers get a better return, media owners use their inventory more efficiently, and viewers get more relevant ads.
January 10, 2018

Using Algorithms to Improve TV Audience Forecasting

This is the first of a series of blogs around building time-series forecasting models. At clypd, we use forecasting models to help media owners and buyers forecast future TV audiences. A successful forecasting model depends on many factors. In this blog, we focus on algorithms, and how we tap into both modern Machine Learning (ML) models and classical statistics models to take advantage of what both offer. The advancement of Machine Learning and Artificial Intelligence has been creating amazing stories everyday, from the AI assistant and self-driving vehicles to computer programs beating professional Go players. At clypd, we also have lots of success stories of using ML models. With the benefits of better accuracy and better automation, these ML models are an integral part of our forecasting models. At the same time, we also continue to find great value in “conventional” statistics models. So, instead of pitching Data Scientist vs. Statistician, let us look at ML models vs. statistical models, and how we can leverage both types of approaches in building a TV audience forecasting model.
December 5, 2017

eMarketer Interviews clypd CEO Joshua Summers

eMarketer recently released a new report on “The Opportunity for OTT Advertising and Programmatic Connected TV.” In the report, eMarketer analyst Lauren Fisher discusses the future […]
September 7, 2017

Standards Group Led by clypd Shares Industry Progress for Advanced Target Transactions

Recommendations Expand on Recently Published Guidelines New York, NY, September 7, 2017 – The Advanced Target Standards Group (ATSG), a consortium of leading network TV programmers, […]