Newssift by Financial Times

Charge premium rates for contextually relevant ads

In 2007, Financial Times was looking for a way to further engage its international business readers – mainly senior level executives. The trend was for readers to land on Financial Times, nibble on 1.2 pages, then leave. By contextually grouping stories FT was able to increase pages views to 4.5 per reader.

Contextually relevant ads can realize 10x more than run-of-site ads

Semantic metadata lets volumes of information be catalogued  - so people can FIND easily

The next step was to take Financial Times’ archives along with the FT brand, and mix it with news from more than 4,000 business titles to create FT Search’s Newssift. But unlike any other search engine, FT Search wanted an interface that invited engagement – a blank search box if the reader so desired, or hot news of the day broken down by categories, topics, organizations, people and places. No matter the search, readers would be given cues on how to narrow it – until they found what they want.

By leveraging Nstein's Text Mining Engine, it was able to add a layer of semantic metadata on the ingested content, so that Newssift's search engine could expose categories, people, topics, organizations and places, allowing a unique and intuitive browsing experience to its visitors.

Making for more qualified audiences, and happy advertisers

Newssift officially launches in Summer 2009, and CEO Robin Johnson is anticipating being able to sell sponsorships for given categories at premium rates because of the highly targeted nature of the news. At the parent company Financial Times, premium ad rates on targeted content are 10x usual CPMs.