Today we’re launching a brand new beta product called NewsWhip Analytics, the biggest repository of human story engagement ever created.
We have something extremely exciting to tell you about at NewsWhip today.
First a little background.
Humans crave these things called stories. They shape our lives and our world – starting religions, electing presidents, shaping personalities. They can even turn a fizzy soda into a symbol of youth.
For as long as we’ve told stories, we’ve struggled to figure out which ones work. Which ones stick in people’s minds, get passed on, or change our beliefs?
Even the experts often get their stories wrong. Book publishers and movie producers push out thousands of duds each year, while even experienced news editors will often not know which of the stories their team publish each day will get the greatest reach.
In the last few years, the need to fully understand stories has been keenly felt by professionals in media and marketing. The reach of many media companies is now dependent on whether consumers share their content. For marketers, advertising is becoming less effective as people tune it out or block it altogether. Brands that used to buy attention must now earn it – by telling good stories.
Introducing NewsWhip Analytics
NewsWhip’s Spike platform helps thousands of journalists and communicators get on the right stories each day, by showing which are trending or about to become big, and surfaces the most important user generated content.
But our customers want to go deeper – and move from real-time trends to fully mapping the genome of exactly what stories, writers and topics really resonate in the world.
So since 2013, we’ve slowly built the biggest social content database yet created. We’ve found scaleable ways of categorising sites, social pages and content based on what they’re about, where they’re from, and how many people signalled their interest on social media. We have all the stories, and all the reactions to the stories.
Today, we’re opening the keys to this kingdom, with our launch of the beta version of NewsWhip Analytics. It opens the biggest repository of human story engagement ever created. It’s also a database of storytellers – authors, influencers – showing who creates important stories in any niche, and who amplifies them.
The data in NewsWhip Analytics is the source of all the research we’ve published on this blog, from the most engaged sites on Facebook, to the average length of the most shared stories on social media. Beyond the numbers, what’s really exciting about this database is the depth of insight it provides into the characteristics of successful stories, videos and sites. In effect, it’s a map of modern content distribution.
Using data to tell stories that resonate
Social data shows us how audiences reacted to some of the biggest news events of recent times. For instance, this chart shows the total social engagement on ‘Trump’ and ‘Clinton’ articles throughout 2016, a year when there were billions of interactions around the US election.
In this graph, we’re looking at aggregate interaction (shares and tweets, mainly) on content about each candidate, aggregated monthly. While interaction with content about both candidates grew over 2016, Trump kept a solid margin ahead, and by October had broken 300 million interactions per month, and 500 million in November.
The November election result was a surprise. But if winning the election was about social engagement with news content, Trump had the lead all year.
Analytics is not just for global political matters. Let’s imagine we’re in the car industry and see if we can learn anything about the stories driving people to talk about Tesla and BMW during 2016.
While there was more engagement around stories about Tesla for most of the year, there’s a particularly notable bump in November. Zooming in, we can analyse the stories responsible for the boost – the announcement of Tesla’s new solar roofs at the end of October. It seems stories with an angle on the broader theme of clean energy drove the engagement.
Looking closer, that’s only part of the story. What really got people sharing that month were pieces combining the theme of clean energy with another immediate feel-good story: the personal financial incentives of using solar panels. The biggest stories said ‘Musk Says Tesla’s Solar Shingles Will Cost Less Than a Dumb Roof’ (66,500 engagements), and ‘Elon Musk says a Tesla solar roof could cost less than your crappy normal roof’ (29,500 engagements).
Readers were impressed by the solar panels, sure, but what really got them sharing was the detail about they could fit them into their own lives. The car company drove engagement through its focus on personal finance.
At a big consumer brand, these insights can guide a campaign or announcement to market with a successful, pre-road tested message, with a pre-built plan of influencers and content, and target publications with the audiences who will share it.
At a newsroom, these insights can help editors to get the most of their editorial resources by showing how audiences responded to different styles of coverage, and to identify the ‘white space’ in wall-to-wall coverage on social media – the angle that’s been missed in the deluge of information.
One of our early users of Analytics is MTV News’ Director of Audience Growth and Engagement, Renan Borelli. Analytics has liberated him from the tighter range of on-site metrics to answer broader questions.
“A lot of the focus on web analytics is self-examination. But I also care about how other publishers may have covered the same topics. If eight websites all covered the release of Beyonce’s surprise album Lemonade, which was the most engaging piece? Which drew the most shares? What had the best distribution?”
The same holds for brands looking to create messages that resonate.
You can pull insights from Analytics quickly. Imagine planning marketing for a chain of coffee shops. Sure, people prefer iced coffee in summer and hot chocolate in winter, but when in the year do they start engaging with content around those beverages on social media? And when does that engagement peak? And what stories about either beverage do they share?
Now, if you are interested in beverage content – hot or cold – you have a media list to target, a schedule for publishing, and inspiring content ideas.
We’ve been learning the strangest things through querying Analytics. Food writers might be interested to find that engagement with Thanksgiving recipes peak very suddenly, while interest in Christmas recipes is much more sustained, rising from mid-November right up to Christmas week.
With this information and some imaginative question asking, editors or marketers can build a far more effective publication schedule.
Reaching the right readers in the social era
In addition to trend analysis, brands want to examine individual publications and influencers to see the sites, authors and platforms that command the greatest reach and have the most impact. Similarly, publications want to benchmark their own performance. Both are possible through Analytics.
Let’s take the example of a food brand looking to identify a suitable site for reaching its target audience. First, we can analyse three relevant sites’ total article engagements on social media to see how much engagement they achieved on the articles that they published over three months.
Here we’re looking at new engagements on new articles, rather than on older stories that suddenly pop up and go viral months after publication. This view helps identify sites that have current and vibrant audience bases. Food & Wine is the clear leader here, with over 400,000 total engagements over the period.
Let’s look deeper at the platform breakdown and article output for each site.
Looking at the “article count” and “total” columns (to the right side of the above graph) we can see that Food & Wine drove almost twice the level of engagement as their nearest competitor. However, Cooking Light published fewer stories and actually had a higher average engagement rate per story published. A Cooking Light story is more likely to reach a wide audience, while Food & Wine produce more content overall.
From here, we can export a list of each site’s top 100 most engaged stories over the period, to see what topics attracted the most interest. This immediately helps a brand sharpen a pitch, or help a writer focus their coverage.
Armed with the knowledge that short visual clips of food preparation see extremely high engagement rates on Facebook, an editor can see where to focus their video resources. In the example above, Bon Appetit’s popular Chicken Adobo story could have been turned into a Facebook video to capitalise on audience interest, furthering the reach of the piece.
A data-driven content strategy helps answer questions about where these editorial resources should be deployed right at the beginning of the creative process.
And of course, social data also provides the ability to perform meticulous benchmarking of how stories are being shared on a site-wide level.
This goes much further than just showing the reach and engagement of your Facebook page versus a competitor’s. It shows how all of the content published on your site performed, combining native engagement on Facebook with other forms, such as share buttons and copy-and-paste shares.
For instance, here’s how three of the top Facebook publishers in December duked it out for engagement throughout that month.
The bars are showing us how many shares, comments, likes and reactions each publisher achieved on new articles posted on their site during the month. This gives audience development teams a single view of their social performance versus competitors, over any time range.
It’s also possible to benchmark the how different sites performed with their coverage of specific events, giving an immediate indication as to the share of voice achieved by each site. Here we see how much engagement five sites achieved for their 2016 Oscars coverage in the weeks before and after the awards:
These are insights that can be parsed and quickly actioned into best practices that make immediate impact on readership and engagement levels at any site or brand.
Inspired decision making
As we continue to develop NewsWhip Analytics with input from our machine learning team, we will help publications understand their audiences better, pick content themes, and produce stories that are on-topic to maximise their reach.
Most technological developments are dismissed as novelties before suddenly reshaping our worlds. “Trends”, “trending” and “going viral” were once marginal things, for marketers and the silly section of news sites. Today, the landscape has changed. Social networks are how information gets around. Our data will help media companies crack the code to this new era. The head of Content at Edelman, Steve Rubel, calls it “moneyball for media”.
Social data can’t and won’t be the only input to creative processes. But it finally gives foundations to test hunches, and data to save fruitless guesswork. After that, every brand and publication must define itself – which means ignoring some of the trends, and embracing others.
Making billions of stories instantly query-able and meaningful is no easy thing – I’d like to thank our amazing R2D2 product team who built the whole platform from scratch and brought our query response time from minutes to microseconds. The rest of NewsWhip is proud of what they built and they should be too. Time for some cans!
We’ve been bowled over at the ideas our alpha customers pulled from Analytics, and we’re eager to see how more brands and publishers can put it into action.