We look at three ways that publishers should be rethinking how they use social metrics in their workflows.
We’re in an age where people across the world find social media to be their number one source of information each day.
This week, new research surveying 13,000 people in 13 countries found that social media is now judged to be the most relevant source of information worldwide. 59% cite it as important to their ‘personal understanding’ – ahead of television (57%), “word of mouth from friends and family” (45%), and online news (41%).
For most editors, journalists and content creators generally, this will not be majorly surprising. Reliance on social media as a means of content distribution has become steadily more important, as audiences turn to their smartphones and news feeds in increasing numbers.
Less talked about are the possibilities that this behaviour shift has had on content creation itself.
Every day, there are billions of social interactions on content around the world. Through commenting on interesting stories, sharing posts that they find worth passing on, and liking videos worth responding to, social media users leave a trail of their interests on different networks. This is richly insightful data, the type which any modern data-informed newsroom should be happily integrating into their content workflow.
At the moment however, the way that social data is utilised by content creators is largely two-dimensional. Shares and likes are measured as a means of seeing how far stories travelled on the social web. They’re purely distributive metrics that are used retroactively once the content has been created and pushed out.
This is important to track engagement growth and audience development, but too much of a focus on this aspect of social analytics means that there’s little thought put into how the data can lend to the creative process itself. Newsrooms have to understand that social data can be used as an input in their editorial process, rather than just a measuring stick for how viral individual posts go.
In other words, social data shouldn’t just be about measuring content distribution – it can also be used in the editorial process itself, right at the ideation stage.
Many newsrooms already have particular ways of integrating social analytics and metrics into their workflows. Morning editors will keep a close eye on the stories that saw heavy engagement overnight as a means of informing their coverage in the early part of the day.
But in a digital publishing space that is more competitive, where publishers have to fight hard to gain attention in news feeds, there’s room for much more creativity and with the data. We look at three ways that newsrooms can look at harnessing social data to improve their content and storytelling.
Editorial strategy: Using social data to figure out what stories are resonating
One unique aspect of social engagement data is that it provides a full picture of what audiences are engaging with across the board, rather than simply what worked for your own site. The possibilities for the audience development and editorial sides of the house to work together here are significant.
Many newsrooms are already turning to social analytics to help inform what their readers and viewers are interested in learning about. While content discovery tools and social media lists help show stories and trends that are worth covering in real time, there’s place here for editors to delve into the data and think a bit more long-term about how social data can help them tune in to the interests of their audience.
This can be particularly useful in covering big events that attract mass coverage from competitor media. Being able to spot unusual headlines or story themes that are getting high engagement informs the editorial team that something is really happening. For events like the upcoming UK election, UK newsrooms will be looking to see what themes readers have been responding to on Facebook and other platforms. Being able to see engagement data representing interest graphs can be hugely beneficial here.
For example, here’s how average engagement with coverage of stories about ‘climate change’ or ‘environment’ played out on stories over the last month, allowing editors to quickly see if readers are responding to the coverage. Here’s how social media engagement with articles about the Paris Agreement steadily increased over the last 30 days.
This could prompt articles about what the agreement is, and what it means, helping SEO and allowing the publisher to keep its readers informed.
2. Benchmarking: Seeing what works, so you can reiterate, fast
An obvious use case for social data in the newsroom: seeing what’s working in terms of platforms and content formats, and making improvements, fast.
As social content formats evolve rapidly, it’s important for newsrooms to be able to measure audience reaction to new videos, articles, headline formats, and more. Every output demands rigorous testing. When weighing up each new format, investment in time, resources and money are at stake, so having data to back up decisions around coverage and format experimentation is critical.
Social data allows newsrooms to see not only how their own output is performing, but also allows for easy use of comparison for best practice against others. For example, NewsWhip Analytics users interested in the characteristics of the most engaged food videos on Facebook can look at a spreadsheet of the most popular clips over the last 30 days, allowing their data team to take learnings from successful clips on that theme.
At a domain level, it’s also possible to set realistic benchmarks for social engagement with other sites. This helps social media teams get an idea of what social engagement numbers they should be expecting daily, weekly and monthly, to ensure continued audience growth.
Here’s how the Washington Post and the New York Times duked it out for engagements on social media following a month of scoops and reporting that was widely shared on social media.
3. Spotting the ‘white space’ – the stories that your readers aren’t seeing.
While social data can be fairly quickly used to see the stories that your readers are seeing in their feeds, being aware of the stories that they aren’t seeing can be just as important.
Imagine your content and audience existing in one bubble. If your readers are interested in entertainment or business news, for instance, they probably see a lot of similar content themes from competitor sites that they’ve also subscribed to in their feeds. In another bubble exist readers interested in technology news, subscribed to a bunch of different niche sites, and seeing a dramatically different news feed. The nature of social algorithms means that expressions of approval and interest are rewarded with further posts from that source. While this ensures that the reader stays interested in their feed, it also lessens their chance of serendipitously spotting stories that they might find fascinating. The business readers will be less likely to see tech stories that they might find interesting.
This is where social data gives editors the chance to bring new stories and ideas to audiences. By monitoring the stories rising from non-competitor sites and pages, editors have the option of adapting different stories to their coverage. Another way that newsrooms can use this is by monitoring niche coverage and local news to bring ‘small’ stories to a wider audience, first. Social data analysis makes that process much simpler than ever before.
When you consider the filter bubble experience that many readers now exist within online, the possibilities with this ‘white space’ approach are exciting.
Newsrooms, communicators, and generally anyone who wants their content to be seen by more people, have much to gain from taking a different look at how they use social metrics.
Try NewsWhip Analytics to leverage social analytics in your workflow today.