Hearst’s Rob Barrett on The Strategic Use of Big Data

The strategic use of Big Data surely hasn’t rescued the news industry, but its smart application has given some media companies a chance to grow.

At Borrell’s Local Online Advertising Conference 2017 in New York this week, McClatchy SVP of Innovation Chris Hendricks said that the use of data allowed the company to squeeze more revenue from a declining subscriber and advertiser base, allowing its revenues to basically stay even.

Hearst Newspapers Digital President Rob Barrett – a longtime data/content geek with The LA Times, Yahoo and Perfect Market — focused on how data has played a key role in re-orienting Hearst’s market strategy. Indeed, “the data team is the biggest investment I’ve made,” he says.

Barrett emphasizes that the idea is to combine databases from various sources to ask complex questions. “I don’t know the percentage of core paid versus advertising in the future,” he said. “I don’t know the right revenue mix. But data tools will give us the answer.”

The biggest use of data is to determine where consumer loyalty is coming from and to develop paid and free marketing efforts around that. “Loyalty is the growth engine,” says Barrett. “Ten percent of loyal users drive sixty percent of overall page views. Loyal users – those who visit a site 10 x or more a month — drive 15X more impressions than casual users.

It is critical to get the data strategy right, Barrett emphasized. A failed strategy will:

1. Chase reach, not value
2. Make digital products for sponsors, not the audience
3. Let vendors own the data
4. Use legacy tech for digital
5. Pray programmatic is enough

Hearst Newspapers Digital President Robertson Barrett (at a different event)

One thought on “Hearst’s Rob Barrett on The Strategic Use of Big Data

  1. This assumes that the data coalesce around actionable points. I heard a Ted talk recently that challenged executive decision making theory that the data will point the way to a clear decision. Sometimes consumer data results will scatter illustrating that there is not a clear answer. While I am inclined to agree with Rob’s assessment I would not discount that consumer content preferences in the Internet age may not cluster enough to develop actionable profitable content models. I suspect that may be an underlying reason why 20 years into the commercialization of the Internet we still do not have a clear path to content monetization the way that we did with traditional media. I would love to see a snapshot of Rob’s results!

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