Youtube, world’s leading video platform is greatly popular amongst businesses, online marketers, media companies or digital agencies. However, unlike other products from the Google family, YouTube does not provide data analytics capability. So, I case you wanted to get more insight than those provided in standard interface, you had to build your own analytics solution based on robust YouTube API, or to use some 3rd party solution, however, these are usually hard to be integrated with your existing analytics. Having substantial experience in delivering advanced analytics capabilities for other popular tools and services such as Facebook Insights or Google Analytics and integrating them to various IT stacks, Dataddo increased the capabilities of its platform by ingesting and processing YouTube analytics data.
Automated data extraction, integration and transformation
Being directly integrated with YouTube, the solution provides advanced data analytics capabilities, targeted especially for online marketers and data analysts, such as automated data extraction and delivery, custom metrics definition, data integration of multiple YouTube accounts as well as with other data sources such as Google Analytics, Facebook, Twitter, Instagram or Pinterest.
Metrics for deeper insights
Dataddo currently supports more than 40 different metrics, ranging from engagement (likes, dislikes, comments, shares…) through watch time metrics (view duration, view percentage, minutes watched, watch ration…) to ad performance (gross revenue, CPM, ad impressions, monetized playbacks, estimated revenue…) providing deep insights of your video content.
Dataddo is complex data automation, transformation, integration and analytics platform, build for online marketers, data analysts and others who do not want to waste time by coding and API integration but rather get straight to insights. With Dataddo you can easily deliver Instagram data to your existing data warehouse, define custom metrics, give business value to your Instagram campaign data by integrating them with your financial or e-commerce metrics or simply off-load your data analysts from routine, boring and laborious tasks by automating the data extraction and transformation tasks.