Whitepaper
June 20, 2019

Content virality: How to achieve social engagement

Emerge from the flood of online content

The Internet is saturated with content.

Content creators should strive to drive virality to emerge from the flood of online content. Viral content is not merely a popular piece, but it garners excessive engagement to outliers.

This paper explores some common factors of viral content.

If you would like more information about monitoring your content, get in touch with us today.

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A headline might be a reader's first – and only – contact with a brand, and many will keep skimming until they land on something that takes their interest.

If you aren't into the nitty-gritty of headlines, stop reading now. But if you want to be that content creator who writes the runaway headline, here's a snapshot of what some of the research has found.

Between 1 March and 10 May 2017, BuzzSumo analysed 100 million of the most shared article headlines on Facebook and Twitter, the platforms dominated by publisher and consumer content. Then in July, it published its analysis of 10 million B2B headlines – those shared on LinkedIn – and found that the best headline phrases, structures, numbers and lengths differed from the B2C results.

1. What works for B2C content

While previous research suggested that the first three and last three words were the important parts of a headline, the BuzzSumo research highlighted linking phrases as key for headlines targeting B2C audiences.

The three-word phrase – or trigram – that led the engagement charge (likes, shares, comments) was 'will make you'. In fact, on Facebook it had twice as many engagements as the trigram that took second place ('this is why'), followed by 'can we guess', 'only X in' and 'the reason is'.

BuzzSumo determined that the success of the 'will make you' phrase was based on it linking content to the emotional impact it will have on the reader – it sets you up to care ('will make you cry', 'will make you smarter', etc.).

It also found that headlines that provoke curiosity work well when readers are looking to learn something from an article. They are a little like the 'will make you' articles, but they tell you what you'll find out rather than what you'll feel.

The BuzzSumo research found that the top five phrases starting a B2C headline were:

  1. X reasons why…
  2. X things you…
  3. This is what…
  4. This is the…
  5. This is how…

The top five phrases ending a B2C headline were:

  1. …the world
  2. …X years
  3. …goes viral
  4. …to know
  5. …X days

Admittedly, the second-place holder might not rate as well in Australia, but the five top-performing first words were:

  1. This…
  2. Trump…
  3. How…
  4. 10…
  5. Why…

So, what doesn't work for B2C audiences? The five worst-performing frequently used phrases were:

  1. control of your
  2. your own business
  3. work for you
  4. the introduction of
  5. what's new in

Confirming earlier Outbrain research, BuzzSumo found that 12 to 18 words and 80 to 95 characters had the highest engagement on Facebook.

2. What works for B2B content

In BuzzSumo's analysis of 10 million headlines of articles shared on LinkedIn, the practical and informative nature of how-to and list posts (see #3 below) proved to be strong performers in the top five most popular three-word phrases:

  1. X ways to…
  2. The future of…
  3. X things you…
  4. How to get…
  5. How to make…

There was a clear frontrunner in the top two-word phrases starting headlines – 'How to…' was shared almost three times more on average than the second-place holder. The top two-word phrases starting B2B headings were:

  1. How to…
  2. The X…
  3. X things…
  4. X ways…
  5. Top X…

Note that after the 'How to…' phrase, the next four most shared phrases were all forms of list posts, which gained more than double the average shares of ‘what’ or ‘why’ posts.

Celebrity brand names also garnered high levels of engagement. It makes sense that companies influencing the business environment and forging technological and business model innovation – like Uber, Google, Apple, Facebook, Tesla and Amazon – will have strong reader appeal. For example, nib's Ambulance or Uber: Who you gonna call?generated a lot of conversation on its Facebook page due to Uber's topicality.

At seven to 12 words, the optimum headline length for LinkedIn is much shorter than for Facebook.

3. The ongoing power of the list

In July 2017, CoSchedule founder Garrett Moon published results of an analysis that began with close to one million blog headlines – which were then put through various filters. The top takeaway was that list posts or listicles (headlines that start with a number) are "huge". Moon wrote they are "the most likely type of post to be shared 1000 or even 100 times". Interestingly, he also noted that "list posts only made up 5% of the total posts actually written".

The BuzzSumo research, confirming the power of lists and the list post format, found the six most effective numbers (in descending order) in B2C content are 10, 5, 15, 7, 20 and 6. In B2B content, the most shared numbers that start post headlines are 5, 10, 3, 7, 4 and 6, with 5 and 10 performing equally well. Note that how-to posts outstripped list posts in B2B.

CoSchedule's results show that list posts that they identified by the words 'thing', 'should' and 'reasons' – '5 things you can do…', '4 reasons why you should…' – do best on Facebook, Twitter and LinkedIn.

It's possible that this is due to a combination of clear promise (‘10 steps’, etc.) and the scannable nature of the post, where you can easily work out which bits you want to read.

4. Emotion is good but beware the bait

While strong emotional headlines and those provoking curiosity may get you results, you need to rein in any urge to overstate.

In May 2017, Facebook announced it would demote “headlines that exaggerate the details of a story with sensational language” and those that aim “to make the story seem like a bigger deal than it really is.”

There may be some debate about what is and isn't clickbait, but there are two key points to consider. In the first place, the reader needs to feel encouraged to read. And in the second, they need to not be disappointed when they have finished reading.

5. Research, tailor and test

There are no hard and fast rules. You always need to research what works for your audience, your topics and your social platforms, and to test your headlines. Different audiences will require different content and will be accessing it on different platforms. For example, Outbrain works for an editorial-led audience more than a business-specific audience.

In the interests of transparency, this headline isn't the first that came to mind. It's the result of trawling through this research.

Maybe we all need to take the advice of Ann Handley, chief content officer at MarketingProfs: "Spend as much time writing the headline as you do an entire blog post or social post."

Belinda Henwood, Strategy & Content

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5 reasons why a headline goes viral

A headline might be a reader’s first – and only – contact with a brand, and many will keep skimming until they land on something that takes their interest.

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Is content marketing an art or a science?

It’s not a new debate but an increasingly relevant one. As technology continues to improve, the C-Suite is demanding a clearer measurement into impact. Marketing and communications professionals responsible for curating content are no longer governed by ‘gut feeling’ and instead, are increasingly driven by engagement metrics to demonstrate ROI.

These professionals are well aware how their role requires a mix of art and science thinking. They both draw from the left brain and the right brain, using data and reason to guide the creativity that fuels it.

But this relationship is less rigorously applied to content marketing – an emerging discipline that straddles both marketing and communications objectives.

Marketers and communications professionals have varying levels of social media sophistication – particularly with LinkedIn, which is often a core channel for content. With LinkedIn estimating more than 130, 000 posts are made on its newsfeed every week, organisations are increasingly turning to it as a distribution channel for thought leadership.

Far fewer, however, understand how to draw insight from the platform to ensure their content connects with their target audience.

Marketers and communications practitioners will often speak to me with this challenge solely in mind. Most are able to gauge the success of content on Facebook and Instagram to some level. Plenty of tools exist which measure various social aspects of content marketing, such as ‘likes’ or ‘shares’. But real engagement isn’t buzz. Determining whether content is connecting with a target audience is a key challenge.

Content marketers are struggling to understand whether their current LinkedIn strategy is working – whether it’s reaching the right audience and whether a piece of content is being actively engaged on the platform.

Other times, they will want to target a particular demographic; millennials for example. But they don’t have the understanding of what this group is looking for when they log onto this social networking site.

In short, what content marketers want to do is debunk the myths surrounding their own activity and drill down into strategy to make their dollars work harder.

How can data help?

Data is pivotal. Armed with information, marketers and communications professionals have a window into the opinions, passions and motivations of their audience.

At Isentia we’ve seen this in our own business. The Research & Insights stream has grown by 25 per cent in the last year, as this market recognises the importance of data. I’m often told by clients that they’re just at the start of their measurement journey, but still desperately rely on data to convince the C-Suite to spend money on content marketing.

Research & Insights can be used to help inform content marketing strategy by highlighting what brand-relevant topics an organisation’s audience is engaging with. It can also help content marketers understand where their brand sits against those their competitors, by measuring their share of voice on a particular topic.

But most importantly, data can help marketing and communications practitioners build out content itself. By understanding what type of content receives the most engagement on the platform, they can tailor their content strategies and measure their success at the same time.

Data is the key to debunking the myths of what does or doesn’t work in a content marketing strategy. It gives marketers and communications professionals the opportunity to ensure they understand their audience first and foremost, in order to communicate in a way that connects.

This is where science can help inform the art in content marketing.

Asha Oberoi
Head of Insights, Australia 

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Blog
Is your content connecting?

Is content marketing an art or a science?

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Video content represents 80% of all internet traffic in 2019

Video content continues to rise in popularity. We have explored how marketers can connect with their video audience and drive strong engagements.

Download our whitepaper to learn more.

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Whitepaper
A marketer’s guide to connect with a video audience

Find out the importance of video content in 2019 and how you can connect with your video audience

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Ngaire Crawford, Director of Insights, ANZ

In leadership meetings across the industry, a single question has become unavoidable: "What is our AI strategy?" Behind this question is often the unspoken hope for an "AI Easy Button": a mythical, one-click solution to our most complex measurement challenges. As someone who spends a large portion of my time designing these new frameworks, I'm infinitely more excited about the blueprints and the foundations than what colour the house is painted.

For the first time in my career, we have the tools to stop using proxies and start building what we've always wanted: true, at-scale, sophisticated measurement. The real opportunity isn't in automation, which lets the AI decide;  it's in the architecture and design of systems for the AI to follow. For decades, I’ve been frustrated by proxies. I’ve watched organisations use metrics like Impressions and Share of Voice as proxies for impact and influence. Too many people have been measuring the loudness of their voice, not whether anyone was actually listening.

Much of the history of communications measurement has been a story of 'good enough' data. And in some cases, data that wasn't even good at all (*cough* AVEs). 

Why a blueprint still needs an architect

But before we can harness the potential of AI, we have to be honest about the technology and tools we're working with. As anyone who's ever used a "smart" tool knows, they can be... well, confidently wrong.

The new challenge isn't just "Garbage In, Garbage Out." The new challenge is that the AI has become a high-speed, frighteningly convincing echo chamber. When a machine delivers a flawed insight, it does so with the resolute certainty of a supercomputer, laundering that flaw into a "fact."As architects, our job is to audit the blueprints and stress-test the materials before we build the house. When my team and I test these models, we're not just looking for what they do right. We're methodically hunting for where they go wrong.

Where we continue to see a critical need for human intervention and expertise:

  • Context Blindness: AI is a brilliant pattern-matcher, but it has limited real-world context and struggles to identify the intent of what’s being analysed. It can miss the nuance of language, the authority of a source, or whether something is fact or speculation.
  • Language Bias: This is my personal favourite and takes a few forms. AI is trained on text, but it isn't (yet) trained on human subtext. This can look like missed nuance for slang used by younger audiences or emerging shifts in the meaning of language. Models are ultimately impacted and biased by their training data, so this can also mean larger systemic biases are amplified and not appropriately interrogated.
  • Viewpoint Collapse: While AI can sometimes get locked into a perspective based on its training, it can also collapse multiple, distinct viewpoints (like a speaker's sarcastic intent vs. the literal text) into a single, flat monolith. This drastically changes the outcomes of your analysis and ultimately the understanding of your audience.

This is the methodical, behind-the-scenes work that often goes unseen, and it is the crucial due diligence needed. It’s not as flashy as writing a press release faster, but it’s the only way to build a tool you can actually trust to make a strategic decision.

New tools, same bedrock principles

This testing isn't just about finding technical bugs or funny hallucinations. We’re testing these new AI models against the foundational, hard-won principles of communications measurement that our industry has spent years formalising.

AI is an incredibly powerful new tool, but it doesn't get a free pass. It still has to follow the rules of good measurement.

  • Measure outcomes, not just outputs: This has always been our goal. An AI-driven approach that only counts outputs (like mentions or sentiment) 1,000 times faster is still just a faster measure of noise. It doesn't tell you if a single mind was changed or a single action was taken.
  • Demand transparency: A metric is useless if you can't explain how it's calculated. This is my biggest critique of the current "plug-and-play" approach to AI. If a vendor provides a proprietary 'Reputation Score' of 7.2, and they can't (or won't) tell you the formula, it's not a metric. It's marketing.
  • Link activity to business objectives: This is the most important rule of all. The only reason to measure is to inform a strategic decision that ladders up to a business goal. A tool that just produces data, but no clear insight linked to your specific objectives, has failed.

When we stop seeing AI as a magic box and start seeing it as a powerful, scalable engine, one that we must build and steer based on these principles, then it becomes truly transformative.

The payoff: the tools are finally catching up to our ambition

A new frontier of opportunity is here. Such as the capability to move from being reactive to being predictive, and it takes careful design to get this right. Our traditional analysis has been brilliant at explaining what has just happened. Now, as architects of these new systems, we are building and testing AI models that can scan the horizon for the faint signals that precede a major narrative shift.

We can empower movement from broadcasting and the old spray and pray approach; to precision, deliberate engagement of stakeholders and audiences. This is another area where the craft of measurement design is essential. AI gives us the power to see the micro-communities and specific, high-authority voices that actually shape opinion. The work is in designing the models that can identify them accurately.

Finally, we can (at last!) move from quantifying to qualifying at scale. For me, this is the most exciting and complex challenge. For 20 years, I’ve had to choose: a large-scale quantitative study (which missed nuance) or a small-scale qualitative review (which couldn't be scaled). As architects, we can now design frameworks that don't just give a "positive" score but confirm that a specific strategic message landed, with the right audiences, and in the intended context.

That is the opportunity. It's not magic. It's the methodical, patient engineering we've been waiting for. It’s the difference between a "plug-and-play" gimmick and a truly strategic asset. The real payoff isn't just faster reporting, it’s about fundamentally upgrading behaviours and expectations of measurement. This isn't an overnight shift. As any research leader will tell you, a new methodology takes time, testing and refinement to get right.

The future we've been waiting for

For my entire career, we’ve been strategic thinkers working with tools that could only show us the past. We were forced to be historians, meticulously analysing what had already happened to predict future behaviour. The key to using this new, complex technology effectively is; strong communication, articulation and critical human thinking. The power of any AI is unlocked by the quality of the question you ask it. It's a system that rewards clear, precise, and strategic language.

This is a massive homefield advantage for communicators, who have spent their entire careers honing the exact skills required to be the architects of this new era. The AI we are using today is the worst it will ever be. It will only get better, faster, and more capable from here. This is what's so thrilling, and it's just the beginning. This new generation of AI driven approaches doesn't replace our intuition, it amplifies it. As communicators (and researchers!) this is the moment to level up. We get to be the explorers and the strategists who connect communications directly to business, policy and societal outcomes. 

We're not just building better measurement and deeper insights; we're leading a more intelligent, more responsive and more impactful profession. What an incredibly exciting time to be in this industry.

Ready to be the architect of your own measurement strategy?

To learn how to build the right KPIs and tell a compelling story with your data, register for our live webinar:

  • Topic: Making Communications Count: Build your KPI confidence and storytelling"
  • Date & time: 12 November, 11am AEDT/ 2pm NZT
  • Hosted by: Ngaire Crawford, Director of Insights for ANZ, Isentia.
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Beyond the “Easy Button”: architecting a new, smarter era of comms measurement

Explore how crucial human oversight is over AI models when it comes to the future of smart measurement in communications.

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