The hoo-ha around this week’s launch of Murdoch’s The Daily in New York has largely drowned out an even more significant unveiling – that of the New York Times’ Recommendation engine which seeks to deepen reader engagement with its content.
Last August I posed the question What Would Tesco Do? If it moved into the news business and started to mine data about readers in the way that it currently does with its supermarket Clubcard customers.
Offering people individual cuts of news based around what they regularly read, the genres that interest them, the people they follow and the themes they track seems so obvious you’d think all news organisations would be well advanced in their thinking on this. They’re not.
On its own, of course, even intelligently filtered material isn’t sophisticated enough to fulfil our information needs.
Serendipitous discovery – I-didn’t-know-I-was-interested-in-that-until-I-read-it – is a significant factor in how we consume material. Being walled in by existing preferences would be like eating the same few favourite meals day-in and day-out – ultimately not very satisfying.
So this isn’t a trivial undertaking. The Times is competing for people’s time in a world where they already feel crushed under the weight of information overload (or filter failure, as Clay Shirky would have it).
The idea isn’t necessarily to make you read more – though there’s not an editor alive who wouldn’t want you to – it’s to get you to feel that you’ve come away with something new and useful that you wouldn’t have chosen yourself, that has enriched your understanding and, crucially, that your time has been well spent.
That kind of engagement brings people back and builds loyalty, the antithesis of the click-whoring treatments so often deployed to pump-up page impression stats and extract money from advertisers who, by now, really should know better.
If The Times engine can pass this test and add value by exposing stories you might never have seen – that are tangentially connected through interests and not just by what you last read – then it will be a triumph.
Given that it’s only been up and running for a couple of days it’s too soon to make a judgment. The more stories you read and the more the engine has to work with, the better and more nuanced the results should be.
But however it pans out they should be applauded for their ambition in attempting to open a new route to a richer, more relevant, consumption experience.
- Paper.li, or fixing the filter failure (paper.li)