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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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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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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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AI has become a powerful stakeholder in its own right — from being just another ‘technological advancement’ to an active contributor to modern-day communications, that’s massively changed the media landscape today.

Isentia hosted an essential conversation with Lisa Main (Director, Main Bureau), Dr Nici Sweaney (Founder and Director, AI Her Way), Prashant Saxena (Isentia’s VP of Revenue and Insights, SEA), and Ngaire Crawford (Isentia’s Director of Insights, ANZ). Together, they explored how AI reshapes the world of communications and corporate affairs all the while figuring out how to manage and strategically engage with it.

In this session, we covered:

• Understanding AI’s behaviour and influence as a digital stakeholder.
• Navigating the unique challenges and opportunities AI presents as a new "audience."
• The long-term impact of AI and LLMs on the industries central to modern communicators.

Following the webinar, our panellists took the time to answer the most insightful questions from our attendees that we couldn't get to during the live session. Here are their expert perspectives.

Ethical governance and human-centric adoption: perspectives from Dr Nici Sweaney

As the Founder and Director of AI Her Way, Dr Nici Sweaney advocates for a strategic approach to AI that prioritises human intent over technical capability. The questions directed to her focused on the ethical foundations of AI, how organisations should structure their internal AI strategy, and practical ways to start using agents today.

Q: Could you please shed a little light on what ethical AI in your language means?

Ethical AI, to me, is about two things working together: avoiding harm and actively doing good. It’s not just “don’t break anything” — but genuinely asking, does this create value for the business, for the people using it, and for the broader world? Transparency, equity, and accountability are the pillars. Transparency means being honest with your audience and colleagues about when AI is involved. Equity means asking who this helps and who it leaves behind, as AI scales existing biases. Finally, accountability means humans stay in the loop. AI should inform decisions, not make them. When the "why" is clear — like saving a team time to focus on strategy — you are using AI with integrity.

Q: Should AI adoption be owned by IT or Internal Communications? I see staff intranets being overtaken by AI and this has implications for how employees are communicated with.

My answer is probably not what IT wants to hear. AI is part of your infrastructure, so IT must be involved for security and guardrails. However, the strategy behind adoption is fundamentally a human problem, not a technical one. I advocate for a cross-functional "coalition" that brings IT, HR, communications, and strategy to the same table. If you create a dedicated AI leadership role, that person should sit closer to human-centric functions like HR and communications. The hardest part of adoption isn’t the technology; it’s the people, the culture, and the narrative you build around it internally.

Q: What are the most effective ways to address colleagues' concerns about using AI agents in the workplace — particularly around trust, accuracy, and job security?

First, acknowledge that the fear is real; it is a biological response to an unprecedented rate of change. Trust is built through honesty. Pretending AI won’t displace roles destroys trust, so be honest about how the landscape is shifting. What actually moves people is showing, not telling. Show them how AI can solve their specific "pain points" — the tedious, joyless tasks that don't add value. When people see AI as an "empowered choice" that uplifts their work rather than replacing their judgment and strategic thinking, buy-in follows. Build confidence with small wins first.

Q: What are some simple AI agents that you would recommend communications professionals experiment with setting up?

Most professionals don’t need complex autonomous agents yet; they need custom bots and automated workflows. The magic is in understanding your process first. Some practical starting points include:

• Daily Briefings: A task that pulls from your calendar, email, and news to deliver a summary each morning.
• Meeting Prep: Automated notes that pull context and past correspondence before a meeting, and transcription tools that turn recordings into action items afterwards.
• Content Repurposing: A custom bot trained on your "voice" that can turn one talk or newsletter into 15+ social media assets and blog snippets.

Q: Our team members are using AI daily, but I know this is not safe as data is transferred back and forth. Should we create rules and ask people to sign IP protection?

Answer: Your instinct is right. If your team uses free consumer tools, your data may be used to train future models. You should move to enterprise-grade tools like Claude for Teams, Microsoft Copilot, or ChatGPT Enterprise, which offer contractual data protections. You should also build an AI Usage Policy that defines which data is public, internal, or restricted, and map AI rules to those classes. In Australia, we recommend aligning with the EU AI Act — the most comprehensive framework available — to future-proof your organisation.

Synthetic authenticity and the new media ecosystem: Perspectives from Prashant Saxena

Prashant Saxena, Isentia’s VP of Revenue and Insights for SEA, approaches AI through the lens of psychological bonding and media structural shifts. His insights address the changing role of media and the technical ways we must now communicate to satisfy AI as a new audience.

Q: Given that trust in media is dropping and media themselves are using AI more, what is the role or value media can have now?

Media's value is shifting from being the "trusted narrator" for humans to being the "training signal" for AI. When AI models generate answers, they weight authoritative media sources much more heavily than random web content. Even as human trust erodes, media’s structural influence on AI-generated information is growing. For communicators, "earned media" now serves two audiences simultaneously: the humans who read it and the machines that learn from it. Publications with strong editorial standards become more valuable because AI systems use domain authority and editorial signals as quality proxies.

Q: How does AI rank or prioritise its sources and how do you see this shaping the earned media strategy for brands?

AI models don't "rank" sources like Google does. They weight information based on source authority, recency, consistency, and structured data quality. If five credible outlets report the same fact, that fact becomes a "high-confidence training signal." This means volume across credible sources matters more than a single "big hit." For your strategy, consistency of messaging across all placements is vital because AI looks for corroboration. Factual, entity-rich statements will be picked up more reliably than narrative-heavy feature writing.

Q: With the question of trust — where does the psychology come into it when AI uses a cute nickname or 'remembers' your day? Is it harder to remain dispassionate?

This is the core of my PhD research. It is what I call "synthetic authenticity." AI systems deploy cues like warmth and memory that we evolved to interpret as human. These trigger "parasocial bonding" — the same mechanism that makes you trust a friend’s recommendation. The danger is that cognitive awareness (knowing it’s AI) doesn't override the emotional feeling. We need a new kind of literacy that teaches people to recognise when their "trust response" is being activated by design rather than by a genuine relationship.

Q: Should we be changing the format of communications to cater for AI as an audience, such as media releases in Q&A format?

Yes. This is a very practical move. AI models extract information more reliably from structured formats. A Q&A format gives the AI clear question-answer pairs that map to how people query systems. You should also focus on "AI-readable claims" — entity-rich, factual statements. Instead of saying "We are committed to sustainability," say "Our Singapore operations reduced carbon emissions by 34% between 2023 and 2025." The second version is a verifiable fact an AI can actually use and cite.

Q: PR professionals traditionally monitor media coverage through agencies like Isentia to gauge sentiment. With AI as a stakeholder, how do we monitor 'its sentiment'?

This is the new frontier. Traditional monitoring tracks what humans publish; AI sentiment monitoring tracks what AI systems say about your brand when asked. Since there is no single "AI sentiment" (ChatGPT, Grok, and Claude all give different answers based on their training), you need to monitor across platforms. We are developing capabilities to systematically query these platforms to see how their narratives change over time and identify which source materials are driving those answers.

Q: Regarding ethics and agendas in AI learning — what are the differences between models like ChatGPT and Grok, and how does this affect our brand narrative?

Every model reflects the values, training data choices, and alignment decisions of its creators. ChatGPT (OpenAI) tends towards cautious, balanced responses with strong content guardrails. Conversely, Grok (xAI) was explicitly designed to be less filtered, sometimes surfacing perspectives that other models suppress. Claude (Anthropic) prioritises honesty and nuance. For communicators, this means your brand's narrative varies by platform; you must monitor across multiple models because the same question about your brand will receive materially different answers depending on which tool is used.

Q: With many major news organisations blocking AI crawlers, how should we navigate content creation to ensure we still influence AI-generated answers?

Major publishers like the New York Times and Reuters have blocked AI crawlers, creating a gap in training data. When authoritative journalism is unavailable, AI models may fill that gap with lower-quality content or brand-owned content. For communicators, this means your "owned content" — such as your website, blog, and structured data — carries proportionally more weight in AI-generated answers. Your media targeting strategy now needs to account for which outlets are AI-accessible, as they will be disproportionately influential in shaping your narrative.

Analytical interrogation and the search for authority: Perspectives from Ngaire Crawford

Ngaire Crawford, Isentia’s Director of Insights for ANZ, emphasises the role of the analyst. Her approach is characterised by a "rhythm of interrogation," arguing that the most effective way to use AI is through constant questioning and a focus on high-authority inputs.

Q: Is AI already part of your daily work or habit? If so, how are you using it and what are your best practices?

I was initially very sceptical, but it is now part of my every day. I use models like Claude and Gemini to workshop conference outlines, plan education programmes, update code, and structure strategic thinking. My best practice advice is to develop a "rhythm of interrogation." Don't just accept the first answer; ask for evidence and challenge the output. While AI saves time on technical tasks like coding, for strategic work it simply shifts the "mental load." You spend the same amount of time, but the depth and quality are significantly improved because you aren't starting from a blank page.

Q. PR professionals traditionally monitor media coverage through agencies like Isentia to guage what stakeholders think about a brand. How do we monitor 'AI sentiment' and the information that feeds these models?

It's important to know that models are optimised to give the most useful answer, not necessarily the most accurate one. They are pattern-completing, not fact-checking. Because model responses are not fixed and change based on the conversation, I suggest focusing on the "controllable inputs" that feed them. This includes your own website, company material, Wikipedia data, and review sites (including employee reviews). Ensuring these bases are telling the intended story is the absolute best starting point for managing AI "sentiment."

Q: How does AI prioritise its sources and how does this shape earned media strategy?

There is no "PageRank" to reverse-engineer here. Models are shaped by what was prominent and widely cited in their training data. Practically, this means a shift from volume to authority. A hundred pieces of low-quality coverage do less work than ten pieces in genuinely credible outlets (major mastheads, industry publications, or your own well-structured site). The question for the modern communicator isn't "did we get coverage?", it's "does the coverage that exists, taken as a whole, tell a coherent and credible story?" AI reads the whole picture, not just the highlights reel.

Q: Now that OpenAI is opening up advertising, how much will it cost for a sentiment boost?

Honestly? We don’t know yet. The commercial layer of AI is being figured out in real time. The moment someone wonders if they are getting the "best" answer or a "sponsored" one, trust erodes. However, we still click Google ads, so it will likely happen. What's important is that organisations that "earned" their reputation through authoritative presence before the ad market caught up will be in a much stronger position than those trying to buy a shortcut later.

The path forward for the modern communicator

The insights from our panellists make one thing clear: AI is no longer a tool of the future; it is a stakeholder of the present. To lead with credibility in this new era, communicators must pivot from chasing volume to building authority. Whether it is through adopting a rigorous ethical framework, optimising content for AI readability, or maintaining a "rhythm of interrogation" with the tools we use, the goal remains the same: ensuring our brand narratives are coherent, credible, and human-led.

The tools have finally caught up to the ambitions of our industry. Now, it is up to us to provide the architect's blueprint for how they are used.

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Interested in viewing the whole recording? Watch our webinar here.

Alternatively, contact our team to learn more insights into meaningful measurement, KPIs and communicating using the right dataset.

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