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For traditional publishers trying to find their place in the 21st century, digital media is both a blessing and a curse.
The blessing: incredible opportunities to reach their audiences across channels, building stronger relationships in the process. The curse: digital has upended huge parts of the revenue models that kept them flush with cash in the past.
According to David Soloff, CEO of predictive analytics vendor Metamarkets, there is a panacea for publishers struggling with the curse: big data analytics.
In an AdAge piece, he argues that "publishers of high-quality content with large, desirable audiences need to reclaim their online ads inventory". How? By coupling private ad exchanges with their analytics data:
Only big data tools can dig them out of the undifferentiated, over-supplied, machine- driven nightmare of the sell side by enabling publishers to scalably and cost-effectively analyze, price and allocate inventory in the new environment.
As an example, Soloff points to one of his company's clients, The Financial Times:
The Financial Times...uses big data analytics to optimize pricing on ads by section, audience, targeting parameters, geography, and time of day. Our friends at the FT sell more inventory because the team knows what they have, where it is and how it should be priced to capture the opportunity at hand.
To boot, analytics reveal previously undersold areas of the publication, enabling premium pricing and resulting in found margin falling straight to the bottom line.
The idea that publishers should use the tools at their disposal to optimize price and stop selling their ads like they're about to go out of style seems like a perfectly sensible one. But is it really a panacea?
The problem for many traditional publishers is that their cost structures were (and still are) based on large amounts of non-digital revenue that has disappeared much faster than digital revenue has appeared to replace it.
For at least some publishers, it's not entirely clear that digital revenue can ever even come close to replacing the lost non-digital revenue. The fact that some publishers are able to realize ad rate increases of up to 50% through their own private exchanges isn't going to change this.
All of this makes the challenge clear: publishers not only need to optimize how much they sell their ads for, they need to optimize how efficiently they can produce the high-quality content that enables them to sell those ads at a premium in the first place.
Big data may have a big role to play in the former, but it won't save them if they can't figure out the latter. In effect, publishers are stuck with a Catch 22 they've been grappling with for years: producing high-quality content isn't cheap, but you probably don't have a business without it.
So what happens? The rich get richer. While publications like The Financial Times will manage to thrive on multiple platforms, and reap the rewards from optimizing their ad sales, struggling publications that haven't figured out the big picture will probably find that 'big data' can be a big distraction.