We’ve been able to save in research and development, meanwhile, our ability to create topics is faster because your tools are so easy to use. So overall we’re working much more effectively.
Malcolm CasSelle, CEO, Timeline Labs

Case Study

Case Study Highlights

  • TLL uses DataSift to monitor everything that’s relevant to a news organization: from global press, events, incidents, and natural disasters to local and regional news, weather alerts, sports, crime, and even school closings.
  • With DataSift, it’s easier for TLL to find relevant results with higher geographic coverage and custom classifications to subcategorize larger topic feeds.
  • Using DataSift’s platform and data management tools, TLL is more cost effective in their operations, and more efficient in their service delivery.


With offices in Santa Monica and San Francisco, Timeline Labs provides the world’s top media companies and brands with easy to use tools that discover trending social content, display social content in rich and engaging ways on broadcasts or the web, and measure the true impact of social content. Find out more: www.timelinelabs.com

Discover, Display & Measure Social Content

Oriented to the needs of traditional media companies who are seeking to incorporate social media into their operations, Timeline Lab’s application empowers editors to Discover, Display and Measure relevant social media interactions. It allows them to identify stories as they break, track trending news as it develops, and leverage social conversations relevant to their broadcasts for content on video, web, and mobile channels.

  • Discover new, meaningful content more efficiently while reducing costs
  • Display rich content that enhances audience engagement and creates new advertising revenue opportunities
  • Measure in real time the true reach of influential conversations across social media.

Project Requirements

To help their clients discover and track newsworthy content in social media, TLL monitors social content in two ways: filtering by topics via keyword sets, and by social activity in regional geographies for local news customers. Relevance and speed are critical, and as TLL’s business grew, they found they required a more robust data platform to support their needs. Specifically they looked for improvements in:

  • Easy to use topic filtering & categorization tools
  • Data source availability and fidelity of resulting data feed
  • Availability of enriched metadata for link extraction and improved geo coverage
By incorporating VEDO classification features, we can get much more relevant information to our customers because we can create a national topic feed, a mega feed, and then break it down into smaller, local feeds targeted to them.

Malcolm CasSelle, CEO, Timeline Labs

Why Timeline Labs Chose DataSift

With DataSift, TLL gets reliable access to data from sources like Twitter, Facebook, Google+ and NewsCred, as well as, enrichments like demographics that increase their geo data coverage from an average of 20% to closer to 80%. DataSift also delivers key platform benefits that make it easier for TLL to deliver breaking stories to their clients such as:

Advanced Filters

TLL uses DataSift to monitor an expansive list of topic streams ranging from global press, events, incidents, and natural disasters to local and regional news, weather alerts, sports, crime, and even school closings. They’re looking for everything that’s relevant to a news organization. Some of these topics include hundreds, even thousands of keywords for terms like “helicopter,” “gunship,” “swat team,” to “shots fired.” In one case, TLL detected a Tweet from a local TV station in Temple, Texas that reported a shooting incident at Fort Hood shortly after the incident began. TLL was able to provide this alert to its national news partners--beating AP and CNN by 23 minutes and Reuters by 34 minutes.


With all the topic filters, and the increased geographic region coverage, TLL is monitoring billions of social interactions. They’re using DataSift VEDO to add custom classifications to that data which enables them to take a larger feed and break it down into categories. For example, they can start with a global topic and categorize it by region and sub-region, or start with breaking news and categorize it by topic. With these custom tagging hierarchies in place, TLL can optimize how they analyze the incoming data.

By incorporating demographic enriched social data into their app, and utilizing the power of the DataSift platform to handle the heavy lifting of data management, TLL has found they’re able to be more cost effective in their operations, and more efficient in their service delivery.

Example: Discover Dashboard

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