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.
Loren is an experienced marketing professional who translates data and insights using Isentia solutions into trends and research, bringing clients closer to the benefits of audience intelligence. Loren thrives on introducing the groundbreaking ways in which data and insights can help a brand or organisation, enabling them to exceed their strategic objectives and goals.
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.
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:
X reasons why…
X things you…
This is what…
This is the…
This is how…
The top five phrases ending a B2C headline were:
…the world
…X years
…goes viral
…to know
…X days
Admittedly, the second-place holder might not rate as well in Australia, but the five top-performing first words were:
This…
Trump…
How…
10…
Why…
So, what doesn't work for B2C audiences? The five worst-performing frequently used phrases were:
control of your
your own business
work for you
the introduction of
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:
X ways to…
The future of…
X things you…
How to get…
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:
How to…
The X…
X things…
X ways…
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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Blog
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.
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.
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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
If you ask ChatGPT or Gemini about your organisation today, the answer won't come straight from your website. Instead, it uses sources the model already trusts, which are often months or years old. So if your last big mention was a crisis or a controversy from 2023, that's probably still how AI describes you.
This is the tough reality for anyone working in PR and communications today. More people are getting their first—and sometimes only—impression of your organisation from an AI-generated summary, not from search results or the homepage. And these summaries often rely on outdated information.
What does freshness actually mean?
Content freshness refers to how recent the sources are that an AI model uses when it talks about you. It might seem like a minor technical point, but it's actually very important.
Search engines have always valued fresh content, and they let you update information quickly. If you change a page, Google recrawls it, and rankings can shift in days. Large language models don't work like this. As Lisa Main, Director at Main Bureau, said on Isentia's "AI as a Stakeholder" panel, "large language models are not databases of verified facts." These models are trained on a snapshot of the internet, updated only from time to time, and they rely on sources that were already prominent when they were trained. This means a past crisis or a controversy that is already resolved can keep showing up in AI answers long after it's no longer relevant.
She shared the example of how a day and a half after a notorious terror attack, she asked ChatGPT if the area had ever experienced a tragedy of that type. It replied that it had not." The model wasn't being careless, but it just hadn't updated to include the latest news. This gap between what reality is and what AI still believes is true sums up the content freshness problem.
Dr Nici Sweaney, founder of AI Her Way, explained on the same panel why this gap matters. She calls AI "an accidental narrator" — it shapes what people believe about your organisation just by repeating the latest information it received. The system simply uses what's available and is not trying to be harmful, so it's important to make sure that information is up to date.
How does this change the way organisations show up?
For PR and communications teams, this changes what "reputation management" means. Put simply, messaging that an LLM cites will remain relevant, no matter when it dates from. Messaging that has not been factored into the LLM’s answers, meanwhile, will have no discernible impact on an increasingly vital - even central - channel, regardless of how many other metrics it might win out on.
This leads to two important things to consider:
First, the conditions that surround recent earned media, statements, and announcements determine whether an AI model updates its picture of the brand, or keeps running on an outdated one. Catherine Arrow of the PR Knowledge Hub made a related point on the "Inside the AI Shift" webinar: LLMs and the agents built on them are "often forbidden from going behind paywalls, from scraping particular sites," which she said creates a kind of "news vacuum." The same logic applies to the brand’s own newsroom or press page. If it isn't feeding the model something current, the model has nothing current to draw from.
Second, owned content—like blog posts, media releases, and website pages — are strategically important because they’re something the organisation in question can control , but only if they are updated. If a page hasn't changed in eighteen months, it's much more likely to disappear from AI results, making any reputation built on it unstable. If something is published once and not updated, the brand risks letting older, less positive stories take its place.
For public sector and government communicators, the stakes are more immediate again. When a government agency's guidance changes, whether that's eligibility criteria, compliance requirements, or a service update, and the fresh version doesn't make it into what AI models are citing, people will still get fed old information, with potentially devastating real-world implications.
The evidence is already there
This is not just in theory. It's playing out in global research and in the day-to-day data right now.
AI is quietly replacing the front door to your content
The Reuters Institute's Digital News Report Australia 2026 confirms that many PR teams have noticed that Google organic search traffic to news sites dropped by a third worldwide between November 2024 and November 2025, and by 38% in the US, as AI Overviews and AI Mode launched. Publishers expect this traffic to nearly halve again in the next three years. Some now call this trend a move towards "Google Zero." For communications teams, this means people are increasingly less likely to click through to your website to check if information is current. More often, they're trusting what the AI says: hence why it’s so important to monitor content freshness.
AI models are now web-enabled and they might not actually guarantee source accuracy
One challenge is that most major chatbots are now web-enabled. For example, ChatGPT can browse the internet, Gemini uses Google Search, and Perplexity has its own live index. This makes it easy to assume that AI always knows the latest information. However, this does not mean that they are always accurate when it comes to citations. A study from Columbia's Tow Center for Digital Journalism tested eight AI search tools with 1,600 queries. They found that these tools failed to correctly identify or cite the source article more than 60% of the time. Some tools were wrong on most tests and rarely showed any uncertainty. New information has not had time to be checked or confirmed like older stories have. This is the real risk of relying on the newest updates — a story that is fast moving and poorly sourced about your organisation might end up in an AI answer before it’s even verified or fact-checked.
People are turning to AI chatbots specifically for what's new
The same report found that 35% of people who use AI chatbots for news do so to get the latest media updates. Dr Sora Park from the University of Canberra's News and Media Research Centre explained on the "Digital News Report Australia 2026" webinar that the main reason people use AI chatbots for news is that "AI collates stories from different news sources into a single response." People expect these tools to provide current information. If your organisation's newest content isn't included (and you have something current or novel to communicate) you miss the chance to reach audiences when they're most interested.
Fresh content doesn’t always equate to ‘new’ content
A notable example of creating freshness that LLMs reward and prioritise comes from updating existing pages, rather from creating brand-new content. Republishing and refreshing current material is more effective than many communications teams realise, as long as one actually updates the content, not just the date.
Evergreen pages are the first casualties when AI overviews roll in
The DNR Australia 2026 report also notes that once someone is inside an AI chatbot conversation, they rarely leave it to check the source — only 4% of AI chatbot users say they always or often click through to the original article, compared with 19% for search and 17% for social media. The pages that used to earn traffic just by sitting there, permanent and useful, are now the ones most likely to lose visibility, because AI models favour what's recent over what's merely correct.
One fresh statement doesn't automatically undo a stale narrative
If an executive online, especially one who has a lot of weight to what they post online, says something controversial and it quickly spreads across media articles, social media and search — it will definitely be picked up by AI as well. There is a golden window of opportunity that they need to capitalise on to clarify what they said. If they don’t, the negative story that was already built into the data AI models use, will not be affected much by the executive’s clarification statement, which wasn’t that timely anyway. As Catherine Arrow of the PR Knowledge Hub said on the "Inside the AI Shift" webinar: "public relations and media relations are not the same thing," and relying on a single release misses the point. The real lesson is not to publish faster after a crisis, but to build a strong, up-to-date presence before you need it. In our latest report, “How can leaders communicate in an age of scrutiny”, we’ve outlined exactly how comms leaders can communicate by adapting their content to audiences exposed to the “AI way” of news dissemination.
What PR & Comms teams should actually do?
The challenge is that organisations can't make an AI model update its answers whenever they want. What they can do is track whether recent work is actually being noticed, which is what Lumina AI View can help with.
Lumina AI View monitors which sources AI models use when talking about your organisation, how strong and recent those sources are, and how you compare to competitors. Freshness is one of five key factors in the overall score. If your freshness score drops, it's an early warning that your latest campaign or announcement hasn't reached the AI ecosystem yet, and older stories are still dominating.
What’s important to note is that the tool provides a list of source citations, paired with reputation pillars like direction, integrity, performance and innovation — giving a comms professional a fully-rounded understanding of what they need to do. It’s not just the case of knowing source citations, but also of understanding your own AI perception and performance to make informed decisions — whether that’s for a brand,a government agency, a NFP or elsewhere.
This kind of tracking is even more important because it shifts by industry and by market, so "AI visibility" doesn't mean the same monitoring job for every organisation. AI answers for healthcare might draw from the smallest, highest-trust pool of sources (mostly clinical and government), but SaaS and fintech answers lean heavily on editorial reviews and comparison sites. Ngaire Crawford made a similar point regionally on the "AI as a Stakeholder" panel. For the APAC region specifically, she pushed back on the assumption that editorial media dominates AI citations — "there are a lot of really massive claims about the impact of editorial media... some as high as 85, 88%. That's not what we're seeing." Instead, she found "a fairly even split between (editorial media) and company content," alongside a real presence for review sites, forums, and academic sources. For a comms team, that means the freshness strategy that works for a media-heavy consumer brand might not work for a government agency whose AI visibility is really riding on review sites, .gov pages, or industry forums instead.
By tracking regularly — weekly or as a routine check— you turn the vague concern of "what is AI saying about us" into something that is super clear. You can see if recent coverage changed your list of citations, or if your owned content is still being found, or where there are gaps that need to be filled because old stories still exist and are causing problems.
The opportunity in staying current
There's a real advantage here too. If old content keeps you tied to an outdated story, fresh content is a direct way for PR and communications teams to influence how AI presents them. Publishing regularly, keeping your own pages updated, and getting recent, credible coverage is not just for human audiences. It's how PR professionals can make sure the systems shaping first impressions have the right information.
Teams that make it an ongoing habit of checking in regularly, watching for changes, and keeping fresh, credible content flowing, will have more control over how AI describes their organisation.
If you would like to know more about our Lumina suite, please reach out here and our team will get in touch with for you a quick demo.
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Blog
Why is content freshness the new currency for AI visibility?
AI summaries are replacing websites as your organisation’s first impression. Here’s why content freshness—and the sources feeding these models—matters more than ever.
