How Data Science is Guiding Brands and Publishers
Data is omnipresent. It includes search queries, credit card spend, social media use, mobile/geo location and everything in between. All kinds of data can be collected and analyzed to drive future decisions – especially in the realm of digital publishing.1
The variety of data available has allowed publishers and advertisers to actively listen to their audience. “Consumers produce incredible amounts of social data every day, and the data can help marketers talk to the people who want to hear from them with the right type of messaging,” says Giselle Abramovich, a senior editor for brands at Digiday.2
Learning how to interpret and use various forms of data has become more of a priority than ever before. “Publishers and advertisers are hiring experts to help with everything from storytelling to subscriber retention to online engagement,” says Lucia Moses, also of Digiday.3
Here’s how publishers and brands are taking advantage of data science.
Data Science Informs Content
The insights derived from data can help publishers and advertisers determine what kind of content to create.
The Wall Street Journal, for example, is expanding its data team to help keep its newsroom informed.4
Almar Latour, an executive editor at the Wall Street Journal, says, “Dow Jones has a team of data scientists that is slated to start working closely with the newsroom to analyze data for news stories, develop new ways of storytelling, and strengthen the Journal’s investigative journalism.”5
Along with scouting employees that specialize in data, publishers are also cultivating technologies to support data driven decisions when creating and even distributing content.
“At BuzzFeed, anybody on staff can query the massive pile of data they’re aggregating from the dozens of platforms and syndication partners they use to distribute content, and nearly half the company’s employees now pull data on a monthly basis,” says Digiday editor Max Willens.6
BuzzFeed uses a data management platform called Looker to compile information regarding content and ad performance. Employees use this data to generate insight and make content decisions – ranging from the launch of a new kind of branded content, to deciding the platforms on which specific content performs best.7
“Big data is changing the world, and it will also change journalism and news-gathering,” says Scott Cohen, previous CEO at digital publisher Vocativ, “data helps us cover subjects with speed and scale.”8
Data Science Boosts Customer Retention, Loyalty and Renewal Rates
Customer loyalty and retention can also be enhanced with audience-centered data-driven approaches.
“Subscribers are telling you what they like about the content — you just have to listen,” says Chris Wiggins, The New York Times’ chief data scientist.9
Wiggins and his team are applying machine learning to determine what makes customers loyal. The insights from the data collected will help the Times with their subscription strategy and increase renewal rates.10
Likewise, Apex Decisions, a data science company, helped financial publisher TheStreet significantly improve its retention rates and pricing by offering personalized price points that made sense to TheStreet’s customers. These points were determined through a thorough analysis of detailed customer information and A/B testing tactics.12
“The only reason Apex was able to apply its very sophisticated data model in first place was because TheStreet had that data aggregated,” says Jill Marchisotto, a marketing consultant brought in to work with TheStreet.13
Data Science Aligns Publishers and Advertisers with Target Audiences
Additionally, publishers and advertisers are using data together to more effectively identify and target key audiences.
“As we look toward our digital audiences across multiple platforms … we’re able to recognize usage patterns, how consumers are absorbing our content, and then translate that information back to advertisers,” says Scott Laine, executive director, digital sales and marketing at culinary publication Bon Appétit.13
Understanding consumer behavior data helps with programmatic targeting and ad placement. “Most advertisers use some type of online data to target their ads, whether it’s based on behavior, demographic, interest or location,” says Digiday editor Jessica Davies.14
“Unsurprisingly, the markets that spend the most on programmatic and general display advertising also spend the most on audience data,” adds Davies.15
One thing is clearly evident: publishers and advertisers alike are seeing the value of data science, and are taking advantage.
1. “Advertisers and Marketers Talk: Tech, Programming and Expectations.” Centro. Jan 2018.
2. Abramovich, Giselle, et al. “The Science of Mining Social Media Data.” Digiday, 11 Apr 2012.
3. Weiss, Mark, et al. “Why Newsrooms Are Enlisting Data Scientists.” Digiday, 2 Apr 2014.
6. Willens, Max, et al. “How BuzzFeed Gets Its Employees Data-Focused.” Digiday, 27 Mar. 2017.
8. Bilton, Ricardo, et al. “Can Vocativ Crack the Data-Journalism Code?” Digiday, 25 Feb 2014.
9. Weiss, Mark, et al. “Why Newsrooms Are Enlisting Data Scientists.” Digiday, 2 Apr 2014.
11. Eldridge, Dan. “How TheStreet.com Used Data Modeling to Boost Renewal Rates and Price.”The Publishing Executive, 1 Mar. 2018.
13. Ember, Sydney. “New York Times Co. Reports Solid Digital Growth as Print Slides.” The New York Times, The New York Times, 1 Nov. 2017.
14. Davies, Jessica, et al. “The Current State of Advertising Data, in 5 Charts.” Digiday, 16 Feb. 2018.