In today’s digital age, hype is a powerful marketing tool on social media platforms. The social media sphere is often caught up in different waves of hype. Hype takes shape in the form of seemingly unending buzz around a particular new product, event, venue opening and so on.
As with many other marketing tactics, hype
leverages on consumer behaviour. It feeds on consumers’ need to remain updated
with the latest trends for fear of missing out. Hyped products are essentially
portrayed as extremely desirable. This lays a self-imposed, societal pressure
on users to be part of the action, resulting into a perpetuating cycle that
feeds such hype.
IS IT POSSIBLE TO CREATE SUSTAINABLE HYPE?
Yes. Some definitions of hype attach the time element to it – hype will ultimately die off over time. This is true to a certain extent, but hype can be sustainable if executed strategically.
HOW TO CREATE SUSTAINABLE HYPE?
1. MAKE YOUR MARKETING ACTIVITY PERIODICAL
Marketing campaigns that have proven to be successful can be brought back periodically. For instance, Ben & Jerry’s Free Cone Day takes place annually in April. This has been a tradition since 1979. Due to repeated editions of this event, Ben & Jerry’s has successfully crafted a mental note in the minds of its consumers. As a result, the Free Cone Day has since become an annual sustainable hype that Ben & Jerry’s fans participate in. What marketers can learn from Ben & Jerry’s is to leverage on successful marketing campaigns, making it a periodic event that consumers can look forward to.
2. HOLISTIC PORTRAYAL
Hype does not necessarily have to be of a particular campaign. Instead, hype can be tied to a brand name. If consumers conclude that the hype created by a certain brand is not substantial, they will tend to switch off when it comes to future hype generated from that brand. This stems from the lack of trust in a brand’s marketing tactics and reduces the desired impact of marketing activities.
Hence, it is essential for brands to paint a holistic portrayal of the product or event that they are advertising. This might seem like an arduous task as marketers tend to showcase the best aspects of the subject in hand. That might seem strategic. However, if the audience are often left feeling disappointed due to the inflated expectations, they might grow to be skeptical of future marketing hype. Hence, brands have to find the balance between unrealistic portrayals and enticing marketing.
3. THE USE OF TRIGGERS
Triggers are cues that lead to certain
behavior, which in turn reward the behavior. This is called the habit loop (Triggers -> Behavior
-> Reward). Triggers can be internal
or external. Internal triggers lie inside the consumers’ minds and emotions.
For instance, people often find themselves opening the Instagram application
when they are bored. Boredom is the internal trigger that cues them to scroll through
Instagram. On the other hand, external triggers are cues in the environment. It
can come in different forms, such as paid advertisements and mobile
notifications.
Marketers often take advantage of this habit
loop by positioning its product or service in the loop. Some restaurants have
special promotions on a specific day of the week. If Restaurant A has special
promotions on every Wednesday that will be announced on their Facebook page,
fans of the restaurant will tend to check out the Facebook page on Wednesdays. The
day (Wednesday) is the trigger which leads to the behavior of checking out the
restaurant’s Facebook page. In turn, consumers will be rewarded with the
knowledge of the promotion and ultimately the actual promotion itself if they decide
to dine at the restaurant.
Hence, triggers help to generate hype around
long-running promotions to sustain it (though the volume of hype might not be
phenomenal).
TO USE HYPE AS A MARKETING TOOL, BRANDS MUST BE ABLE TO LIVE UP TO THE HEIGHTENED EXPECTATIONS
Hype is clearly a useful tool in brand marketing – but caution must be taken when generating hype as it can play out as a double-edged sword. With all the buzz and attention, can the product live up to heightened expectations? The consumer’s experience must specifically be taken into account as that would set the tone for other prospective consumers, image of the brand, and the relationship the brand has with its customers.
All in all, the consumer’s experiences must
have a positive output in order to reap benefits from social media hype. Should
reality fall short from expectations, brand image may suffer and overwhelming
hype may backfire upon the product and the brand itself.
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Would you trust a brand more if an AI model recommended it? For many, the answer is yes – and it’s changing the very nature of PR & Comms.
Our latest report digs into the changing nature of trust, as audiences turn to AI models for quick answers instead of going to organisations or media outlets directly, with AI fast becoming the final stop in the comms cycle.
This report unpacks:
Why trust has shifted, and where audiences are having these conversations
Why AI has become the last stop in the comms cycle
Methods for staying on top of your brand trust and reputation
To access the full report, fill in the form below:
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.
