Data is the fuel that’s going to power publishers’ revenues and overall growth in the coming years. It’s importance has increased with the decline in advertising and shift to reader revenues, and the impending phase-out of third party cookies.
“When Google announced the cookie apocalypse in early 2020, they accelerated the preparations for many publishers because suddenly they were facing the loss of a big chunk of their advertising revenue that was reliant on third-party cookies,” says Greg Piechota, Smart Data Initiative Lead, INMA. “And some of them recognised that in the new world, first-party data would be much more valuable.”
“Fuel the growth engine for both revenue models”
There’s also been significant progress in the technology available. More publishers than ever before are using data to grow traffic and revenue. INMA has published a new report featuring 13 case studies. It explores how publishers are developing data strategies and applying those strategies to key areas of their business. The report, “The Guide to Smart Data Strategy in Media,” written by INMA blog editor Paula Felps, also looks into how artificial Intelligence and machine learning help harness the power of data.
First-party user and content data analytics has become a common resource helping fuel the growth engine for both revenue models.Greg Piechota, Smart Data Initiative Lead, INMA, The Guide to Smart Data Strategy in Media
“Data basically is a way for companies to become customer-centric,” notes Piechota. “It’s a tool. Data is basically feedback about how customers are using your product. If we want to know our customers so we can better serve their needs with products and services, we collect data and analyse it.”
“When companies put data technology at the centre of their ecosystem, it provides the backbone for a digital business to emerge,” writes Felps. Focusing on data has helped many publishers grow. The New York Times, refocused on end consumers and saw subscriptions lift to historic numbers, says Piechota.
Publishers today are primarily using data for 3 purposes:
- Identifying audiences so that they can improve content and user experience, as well as create attractive advertiser segments.
- Enriching profiles of identified audiences.
- Activating the data for advertisers
“Data should underpin the organisation’s vision”
To begin with, publishers need a clear vision of what they want to achieve with data, suggests Felps. The goals can include producing better content, creating better user experiences, or growing advertising revenue.
With so much data being generated, being clear about what they want from the data is key, according to Piechota. He recommends publishers “start at the end” and then create a system designed to reach that endpoint. “Knowing what the end goal is — whether that means producing better content, creating better user experiences, or growing advertising revenue — will inform what infrastructure needs to be created,” explains Felps.
“If you’re not focusing on the use cases, you may end up with a big infrastructure with a lot of data that you are not using,” adds Piechota. “You are not monetising the data; you are monetising the insight.”
Data should underpin the organisation’s vision. Data strategy cannot be about hoarding data for the sake of it. It’s about thinking of the purpose, or the outcome, of using data.Caroline Carruthers, Co-author, The Chief Data Officer’s Playbook
Hearst’s data strategy is based on a combination of offense and defence measures, according to Daniel Hallac, Chief Product Officer, Hearst Newspapers, US.
The defence part is based on the knowledge that third party cookies are dying. This has lead the publisher to focus on building user profiles over the past several years and categorize them into five groups:
- Newsletter subscribers
- Anonymous users
- Repeat visitors (“known anonymous”)
- Registered users
- Paying subscribers
“We group these users and try to identify them across our properties,” says Hallac. These identities that live in multiple systems are then gathered in one place so that they can be tracked across domains. The publisher also works at enriching the data profiles parallely.
“There’s a lot we know about our users, such as their reading habits, devices, time of day that they engage with us,” explains Hallac. “But really what we’re missing is what are their interests, who they are demographically, what are their lifestyles? What are their purchase intentions?”
By using the data and applying look-alike capabilities, Hearst can find more people who might be interested in the same things. That helps its advertising business.
We may know that we have 10,000 users who are interested in, let’s say buying a car. But by developing look-alike capabilities, we obviously can find more people who are like them and infer that they also could be potential car buyers. And that’s a big part of helping our advertising business.Daniel Hallac, Chief Product Officer, Hearst Newspapers, US
The publisher activates its data strategy through what it calls a dynamic template. This enables it to optimize the experience for the user. “The goal is to get the right content marketing and advertising message to the right person at the right time,” Hallac says.
“Insights to create better products and services”
“Understanding how to gather data is one thing,” writes Felps, “but knowing how to apply it is often a different challenge entirely.” It entails, among other things, developing the right kind of dashboards which enable all stakeholders to interpret the data. “Academic studies show that high-performing firms know their customers better. They have deeper insights, and they use these insights to create better products and services that out-compete others,” says Piechota.
Austrian newspaper Die Presse introduced its paywall in 2017 and found immediate success. The publisher analyzed its strategy as it continued with its digital transformation and found that it was making several mistakes.
- Collecting the wrong data
- Reporting data that was not a beneficial analysis
- Avoiding analysis
- Postponing action
The company calls this model CRAP analytics. To address the problem it has created CARE analytics which includes:
- Collecting the correct data
- Analysing it
- Recommending action
- Executing and experimenting
The CARE approach has five key elements:
- Actionable dashboards that track segmentation, engagement, and conversion
- Reporting for the entire newsroom that allows journalists to see how stories are performing
- Performance prediction analytics that ranks stories according to their engagement.
- Fitness monitoring to indicate the “health” of each piece of content and determine whether it is meeting performance goals.
- Data talks between different stakeholders to provide deep-dive analysis and experiments.
The South China Morning Post has built its own first-party data platform, called Lighthouse. It’s available to every employee of the company and provides the following user insights:
- Preference: A long-term attribute unlikely to change.
- Opinion: Current way of thinking, which might change based on circumstances.
- Sentiment: The positive, neutral, or negative feeling about an article.
- Intent: Declared action to do something.
- Behavioural: A predictable, usual way of being.
- Interest: Declared passion for something.
“When we put all of that together in a profile, we start to build what we think looks much more like a person,” says Ian Hocking, VP of Digital, South China Morning Post.
I think publishers that have a great, ongoing relationship with audiences to really benefit and present something interesting [comes from] building out not just an ID with an attribute attached to it, but a broad profile that really talks to them as individuals.Ian Hocking, VP of Digital, South China Morning Post
“It’s designed for us to create a space to understand our users,” adds Hocking. It helps with advertising as well. “You get to add value as a publisher by demonstrating to a client where you can find them prospects. They want to understand how you can find them new customers, and by having really great in-depth profiles that aren’t just a data point, you can do that very well.”
“Publishers are dreaming again”
Mediahuis which reaches 2.1M people a day through its four national news titles in Belgium segments readers into four groups — fan, discoverer, strayed, and lost. It has developed KPIs for each group that indicate what to focus upon to improve engagement for different users.
The publisher has a multidisciplinary engagement team that looks at the four different groups of customers. It crafts different ways to help engage each group. For example, readers in the “lost” group are guided by an onboarding process. Those in the “discoverer” or “strayed” groups are encouraged to take advantage of all their subscription offers and consume content more often.
“We use different tools such as newsletters, social campaigns, and pushes,” says Hanne Hendrikx, Manager/Customer Retention, Mediahuis. “We try to get the e-paper more into their attention. And also we try to serve them podcasts or puzzles just to make them use their subscription more often.”
Within Mediahuis, the voice of the customer gets louder and louder each year. But we also learn and change things every week. So, every week we get new insights and we make new decisions.Hanne Hendrikx, Manager/Customer retention, Mediahuis
“Many publishers are still early in their journey and have much to learn from data,” writes Felps. “The rise of platforms like Google and Facebook, which could track users’ behaviour and target them with ads, has forced them to refocus their relationship with readers and rebalance the revenue model.”
“The transformation we are observing in the news media and described in this report is not about digital, nor technology, nor even data,” adds Piechota. “It is about our business transformation to being customer-centric.”
Almost 30 years since the emergence of the Web, having been severely disrupted and then rebounded, publishers finally are cracking it and getting excited about the future. News publishers are dreaming again, seeing opportunities to become disruptors themselves.Greg Piechota, Smart Data Initiative Lead, INMA
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