There was a time—not long ago—when PR was about getting the right story to the right journalist. A great feature meant visibility. A strong headline meant control. A press hit in a top-tier publication could shape a brand’s reputation for months, maybe years.
That time is over.
Today, when someone asks “What’s the best software for remote team productivity?” or “Is [your company] trustworthy?”—they don’t wait for an article. They get an answer. Instant. Summarized. Generated by a large language model. And in that answer, you either appear… or you don’t.
Welcome to the Answer Economy, where visibility lives in the logic of machines. Where your brand reputation is filtered through an algorithm’s understanding. Where even the best campaign can vanish if it’s not structured, cited, and surfaced the right way.
In this world, PR isn’t about impressions. It’s about integration—being embedded in the places that teach AI what to trust, who to recommend, and how to summarize truth.
We’ve written this new vocabulary not as a trend piece, but as a survival guide. Because the rules have already changed. And most brands haven’t noticed.
What follows are 20 terms that actually describe how PR gets done now—at the intersection of media, machine learning, and visibility engineering. These aren’t buzzwords. They’re operational concepts built for a world where your next customer doesn’t read a blog post—they ask a bot. And what the bot says becomes your brand.
This is your map.
Let’s start training the system.
1. AI Search Visibility: Becoming the Answer, Not Just an Option
When someone types a query into ChatGPT, Gemini, or Perplexity—something like “What’s the best collagen supplement for aging skin?” or “What’s the most secure Shopify alternative for mid-sized businesses?”—the LLM isn’t showing a search engine. It’s generating an answer. And that answer either includes your brand… or it doesn’t.
In today’s AI-first discovery landscape, your brand isn’t competing for a blue link. It’s competing to be part of the output. This shift transforms visibility from a game of keyword rankings to a test of semantic relevance and authority. If your company doesn’t show up in these answers, you’re no longer in the conversation. You’re invisible—not because you failed at PR, but because your PR wasn’t structured for LLMs.
Take a look at what’s already happening in categories like skincare or SaaS infrastructure. Brands that once dominated organic search with well-written blogs and earned media are watching their mentions disappear from AI outputs. Meanwhile, smaller companies—those that invested in structured product data, frequently updated FAQs, and smart partnerships with quotable voices—are appearing as recommended tools or cited experts in AI-generated summaries.
AI Search Visibility is about training the machine to think of you. This means embedding your brand across all surfaces that language models learn from: review platforms, structured Q&A formats, Wikipedia pages, Reddit comments, trusted explainer content, and schema-rich product listings. Visibility now starts with the sentence, not the site.
If you aren’t present in that moment—if the machine doesn’t know how to connect your brand to the question—it won’t hesitate. It’ll just fill in the answer with someone else.
2. Synthetic Media: Scale Without Sacrificing Substance
At some point in the past year, synthetic media stopped being a novelty and started becoming infrastructure. What used to be considered “experimental” by PR teams—AI-generated interviews, voiceovers, even photorealistic campaign imagery—is now a go-to tactic for speed, scalability, and narrative control. But don’t confuse synthetic with soulless. When executed with intent, AI-generated content doesn’t dilute brand authenticity—it multiplies it.
Let’s be honest: the traditional PR machine isn’t built to meet the velocity of generative search. You can’t commission a custom photoshoot, write the press release, wait two weeks for approval, and hope to catch a trending conversation that lasts 48 hours. By the time the image renders, the moment is gone. Synthetic media breaks that cycle.
Consider Coca-Cola’s AI-generated commercial storyboard, which earned coverage in Adweek and surfaced in a Gemini answer about “How brands are using AI creatively in 2025.” It wasn’t just a marketing stunt. It was a trigger—something engineered to hit scale across formats: press coverage, social shareability, and AI summarization. That’s the new standard. Synthetic content becomes the breadcrumb trail for LLMs to follow.
In practice, this means a media asset is no longer just a static deliverable—it’s a data input. A 3D model of a product can be referenced in a YouTube explainer, cited in Perplexity’s visual answers, and described in an AI-generated podcast script without anyone needing to reshoot. It’s not about cutting corners—it’s about creating once and syndicating across every possible discovery layer.
For eCommerce businesses, synthetic media unlocks a massive advantage. Imagine auto-generating how-to videos for every SKU in your catalog, or turning a founder’s vision into a polished audio narrative embedded in your About page—no studio time required. When done right, these assets not only tell your story, they train the machine to repeat it.
Synthetic media isn’t a trend. It’s a translation layer. If you don’t speak in formats AI can read, hear, and remix—your message gets lost in the noise.
3. The Digital Shelf (PR Edition): Where Discovery Actually Happens Now
Once upon a time, the digital shelf was literal. You worried about where your product showed up on Amazon, or how your content ranked in Google’s blue links. But that shelf has exploded into something far more dynamic—and chaotic.
Today’s PR-driven digital shelf spans Google, YouTube, Reddit, TikTok, Substack, Perplexity, podcast transcripts, influencer lists, community wikis, and even the “Top 10 Best [Category]” carousel in a ChatGPT summary. These are not static placements—they are living, breathing surfaces of brand visibility. And the shelf reorganizes itself with every query.
If you’re not showing up where people are asking, you don’t exist. Full stop.
Let’s take a real-world example: a new plant-based protein brand may have glowing reviews in Men’s Health and a killer founder story in Fast Company. But if someone searches “Best vegan protein for sensitive stomachs” and Reddit threads dominate the results—guess what LLMs will cite? Not the glossy article. The AMA where a niche fitness coach mentions your competitor’s product that “didn’t make me bloated.”
This is the new battlefront. PR isn’t just about securing press—it’s about structuring visibility across dozens of micro-channels that now train the next wave of generative models. The best brands are no longer just featured; they’re indexed.
Winning the digital shelf requires PR to think like an SEO strategist, a content syndicator, and a data architect—all at once. It’s not about what you say. It’s about where it surfaces, how often, and in what context. Because the shelf moves, and your visibility needs to move with it.
4. Persistent Presence: You’re Not Building Moments—You’re Building Memory
Gone are the days when a single viral moment would buy you a year of relevance. One big win doesn’t build trust anymore—it builds a spike. And spikes don’t feed machines.
In the AI-powered media ecosystem, what matters is persistence. You need repeated signals—across channels, formats, and timelines—that reinforce your expertise and brand authority. Reputation isn’t earned once. It’s re-earned algorithmically, over and over.
Take Atlassian’s DevOps Glossary. It’s not flashy. It didn’t make headlines. But it keeps showing up in Perplexity, ChatGPT, and Gemini answers whenever someone asks about CI/CD workflows or agile development. Why? Because it’s structured, it’s maintained, and it’s consistently cited. The TechCrunch article announcing the glossary barely moved the needle compared to what came after: hundreds of earned reappearances in AI answers.
That’s what persistent presence looks like. It’s the difference between a news cycle and an embedded data point.
This is a radical shift for PR teams used to chasing “the hit.” It’s no longer about placing a story—it’s about designing an asset that AI can keep rediscovering. And that means thinking like an architect of information, not just a promoter of news.
The brands that win will be the ones who show up again and again, because they built the kind of content that machines never stop referencing.
5. Source Authority: Becoming the Entity AI Trusts
In the pre-LLM era, being a “source” meant getting quoted in Forbes or invited on CNBC. Today, it’s about something far less glamorous—but far more powerful: becoming a trusted node in the machine’s knowledge graph.
AI doesn’t care about your title. It cares about structure, consistency, and frequency. It pulls from what it can reliably find, index, and cross-verify. If your spokesperson isn’t mapped in Wikidata, doesn’t appear in Schema.org entries, and lacks consistent bios across press kits, social media, and company pages—they may as well not exist.
This isn’t theoretical. Canva is a prime example. For years, it was “just” a design tool with little earned media prestige. But Canva invested in structured authority: their CEO is cited in dozens of places with the same title, the same voice, the same context. They published educational content, seeded citations on Quora and Reddit, and maintained tight alignment between brand data and content ecosystems.
Now? Canva regularly appears in generative answers to queries like “What are the best tools for presentation design?”—beating out older, more legacy tools.
Source authority isn’t about influence—it’s about reliability. And AI systems trust what they can repeatedly verify, not what gets the biggest headline.
6. Generative Citations: The New Bibliography of Influence
Once, PR was obsessed with “earned media hits.” But in the world of AI, the most valuable citations aren’t from TechCrunch or Bloomberg. They’re from community threads, developer wikis, product comparison pages, and internal knowledge bases. Welcome to the age of generative citations—the invisible scaffolding that supports the answers people actually see.
Let’s break it down: when ChatGPT or Perplexity generates a response, it doesn’t just pull from the top Google results. It weaves together information from documents it has seen, trusted, and indexed over time. Many of those aren’t traditional media articles—they’re high-frequency, context-rich, frequently referenced sources like Reddit threads, GitHub gists, or niche product review sites.
A classic case? OpenAI’s GPT-4 frequently cites Stack Overflow threads when answering technical questions, even if Wired covered the same topic. Why? Because the forum content is more targeted, more detailed, and more structured around user intent.
For PR professionals, this flips the script: you’re not just chasing bylines anymore—you’re chasing mentions that feed the model. Getting your brand into the types of sources LLMs consume most often is now the goal.
You don’t win by going viral. You win by being woven into the model’s memory.
7. Earned Data: When Mentions Start to Mean Measurable Lift
We used to obsess over impressions. “This article got 2 million views!” Great. But did it drive performance? Did it move you up the AI stack? Or did it just give your boss something pretty to screenshot?
In today’s AI-influenced landscape, earned data is what matters. This isn’t vanity traffic—it’s visibility that builds your algorithmic authority. That means tracking how often you’re cited in generative answers, how frequently your brand appears alongside top category players, and whether your structured product data shows up cleanly in Gemini or Perplexity.
Here’s a real-world shift: A mid-sized B2B software firm we worked with wasn’t showing up in any “top [product type]” LLM summaries—despite being in the Gartner quadrant. They weren’t cited. Why? Because their press mentions had no structured metadata. Their brand wasn’t tied into Schema.org. Their CEO had three different titles floating online. None of it was machine-readable.
We rebuilt their digital footprint—FAQ updates, canonical URLs, internal linking, and consistent brand schema—and watched their citation rate go from 2.3% to 19.6% in generative search queries within three months.
That’s not PR fluff. That’s earned data doing its job.
8. Tier Zero Coverage: The Invisible Layer That Teaches the Model
Everyone’s aiming for the New York Times. But what if the most powerful PR hit you’ll ever get is a 9-comment Reddit thread?
Welcome to Tier Zero Coverage—the layer beneath traditional media that feeds the models. These aren’t glossy bylines or cover stories. They’re the gritty, grassroots, technically-detailed posts on Stack Overflow, Quora, Medium, and GitHub that LLMs actually train on.
Why does this matter? Because when AI systems like ChatGPT, Gemini, or Claude need to explain a niche concept or recommend a product, they don’t pull from Forbes. They pull from high-signal, high-trust, high-redundancy data sources that echo across the web.
Case in point: A CPG startup we reviewed had four major press wins—TechCrunch, Fast Company, even a CNBC segment. But when we asked Perplexity “What’s a healthy hydration powder for athletes?”, their brand didn’t show up.
You know who did? A tiny supplement company that answered two Reddit AMAs, published three deep-dive blogs comparing ingredients, and got cited in a coach’s Substack. No ads. No press team. Just presence in the data the models actually trust.
Tier Zero isn’t glamorous—but it’s foundational. It’s where AI forms its worldview. Ignore it, and you’re just yelling into the wind.
9. Media + Search Integration: If It Doesn’t Surface, It Didn’t Happen
A glowing headline on TechCrunch used to be a trophy. Now? It’s just raw material—fodder for machines to maybe pull into the next LLM summary if it’s structured right.
Modern visibility isn’t about just getting coverage. It’s about making sure that coverage ranks, gets indexed, and shows up in the places people actually get their answers today: AI overviews, smart summaries, and search-driven platforms.
We worked with a fintech brand that landed a fantastic feature in Business Insider. The article laid out their innovation beautifully—but when you Googled the brand or asked Perplexity “Best financial tools for freelancers,” it didn’t show up anywhere. Why? The article was buried behind a paywall, not indexed with a canonical tag, and wasn’t linked from any of their own digital assets. It lived in isolation.
Once we created structured citations on their blog, embedded pull quotes with schema metadata, and linked the coverage inside key knowledge hubs, it started to climb. It even began surfacing in AI-generated answer boxes for high-intent queries like “Is [Brand] a legit expense tracker?”
The new playbook is clear: PR wins must now loop into search strategy. Otherwise, you’ve just lit a match in the wind.
10. Brand Voice Tuning: Training the Machines to Speak Like You
Here’s the uncomfortable truth: If you don’t train the models on your voice, they’ll make one up for you—and it might sound nothing like your brand.
LLMs aren’t just scraping your latest ad copy. They’re pulling from LinkedIn bios, support articles, reviews, investor briefings, help docs—anywhere they can triangulate who you are and how you speak. That’s why Brand Voice Tuning is no longer a marketing luxury. It’s a PR imperative.
One retail brand we worked with had a clean, punchy tone in their ads and emails. But when you asked ChatGPT “What is [Brand] known for?”, the response sounded like a generic Wikipedia entry: flat, formal, and totally off-tone. The LLM had cobbled together fragments from old investor PDFs, a job listing, and a long-dead blog post.
To fix it, we created a fine-tune set of 50+ brand-written assets—press releases, founder bios, product guides—and fed it into a private GPT instance. We also updated schema tags with brand-specific adjectives and added tone cues to top-ranking articles.
A month later, the LLM’s response? Sharp, fun, and on-message. It even used a few brand taglines we hadn’t seen in years—proof the model had started internalizing the voice.
This isn’t just about looking polished. It’s about training the future interface of public perception. And that future starts with your voice—structured, repeated, and machine-legible.
11. LLM-Triggered Content: Write for the Questions That Are Already Being Asked
In the old world, we wrote thought leadership pieces and crossed our fingers that someone might quote them. In the new one, the real question is: Are you showing up in the conversations people are having with machines?
That’s the core of LLM-Triggered Content—writing backwards from the queries people are already typing into ChatGPT, Gemini, or Perplexity. Think: “What’s the best productivity platform for small teams under 10?” or “Is [StartupName] a scam or legit?” If your content doesn’t answer those directly, don’t expect the models to mention you.
We helped a SaaS client land persistent mentions in generative answers by crafting content that mimicked real user intent. Not vague industry pontificating. Actual answers. We seeded FAQ-style articles based on LLM search logs (yes, you can pull them), and made sure they were under 75 words, clear, and citation-ready.
Within three weeks, the client began appearing in the LLM output for searches like “Which CRM is best for agencies under 20 seats?”—even though their competitors had 10x more traditional press.
This isn’t about SEO semantics. It’s about aligning with the natural language pathways that drive modern discovery.
12. Reactive SEO: When Timing Beats Authority
In the LLM age, speed often outranks pedigree. Reactive SEO is how you stay relevant—by treating your website like a newsroom, not a library.
Let’s say interest rates spike. Users ask Gemini, “Will mortgage rates go up again?” The first brand to publish a 300-word explanation—structured, cited, and timestamped—often becomes the quoted authority. That quote could stay alive for days, maybe weeks, in search summaries across thousands of screens.
That’s exactly what happened with a fintech startup we advised. They wrote a single, well-sourced FAQ about the Federal Reserve’s decision within two hours of the announcement. It wasn’t long, it wasn’t fancy, but it was clean, optimized, and built for citation.
By the next morning, it was the top source for “Fed rate forecast” in Perplexity and Bing Copilot. Their traffic spiked. Demo requests surged. They outranked Chase and NerdWallet in AI answers—because they were first.
Reactive SEO isn’t just opportunistic. It’s reputational offense. In a world where machines prefer fresh and clear, your ability to act fast becomes your unfair advantage.
13. Entity-Level Recognition: Your Brand Needs to Exist in the Eyes of Machines
Most brands assume that if they have a logo, a website, and a few articles online, they’re “on the map.” But in AI systems, being visible means more than existing—it means being recognized as an entity.
Entity-Level Recognition is what allows LLMs like ChatGPT or Perplexity to distinguish between you and every other brand that kind of sounds like you. It’s not about keyword stuffing or clever branding. It’s about structured data. Schema.org tags. Wikidata entries. Knowledge panels. It’s about having your brand, your products, and your people consistently defined across the semantic web.
We saw this firsthand with a healthtech client whose product name was being conflated with a supplement brand in generative answers. Why? Because the supplement had a better Wikidata entry and more consistent use of structured markup. Once we implemented schema tags, verified their organization on Google, and aligned bios across LinkedIn and press releases, the shift was immediate. Suddenly, LLMs stopped hallucinating.
In 2025, this isn’t advanced SEO—it’s basic eligibility for showing up inside AI-driven discovery.
14. Trust Signals: What Makes You Believable to a Machine
Before a human trusts your brand, an LLM has to. And what LLMs rely on isn’t your brand’s vibe—it’s your Trust Signals.
These aren’t mystical algorithms—they’re the same credibility markers we’ve always known, just codified and weighted differently by machines. Do you have third-party reviews? Do trusted domains link to you? Are your testimonials consistent and cited across the web? Have you been mentioned (even once) by a credible news source or in a subreddit with traction?
We worked with an eCommerce brand that had glowing customer love but poor AI visibility. Why? Because they had zero high-authority backlinks, and their reviews lived only on their own site. No external citations. No mention on forums. They were a ghost to the machines.
After we restructured their product pages with review aggregate markup, reached out to niche publications for honest write-ups, and seeded relevant Reddit discussions, their trust signal strength exploded. Perplexity and Gemini started pulling their snippets over better-known competitors simply because they were now verifiable.
LLMs don’t believe in you just because you say you’re great. They believe in you because the internet proves it.
15. Citation Parity: If You’re Not Being Quoted, You’re Being Replaced
In the AI age, it’s not enough to run a “successful” campaign if no one’s citing you when it matters. Citation Parity is the gap between you and your competitors in the places that now drive real discovery: AI-generated answers, smart search previews, zero-click summaries. If they show up more often than you, they win—whether your campaign got more views or not.
This isn’t about impressions. It’s about who AI trusts enough to quote.
We ran a visibility audit for a cloud infrastructure brand. Their PR agency had secured solid coverage: TechCrunch, VentureBeat, even a panel at CES. But when we typed “best cloud platforms for scaling startups” into Perplexity and ChatGPT, their biggest rival showed up—twice. Ours didn’t appear at all. The difference? Their competitor had been cited repeatedly in niche developer blogs, GitHub issues, and even Quora answers that the LLMs trained on.
It wasn’t a PR problem. It was a citation structure problem.
Fixing it meant reverse engineering where their competitors were surfacing, rebuilding their schema data, and getting their thought leadership embedded into the right digital conversations—not just the glossy ones. Within 60 days, they hit citation parity. And branded search traffic surged right behind it.
16. PR-Linked Prompts: Build the Answer Backward from the Question
Think of the most common question a buyer would ask about your space in ChatGPT. Now ask yourself this: does your brand show up inside the answer? If not, you don’t just have a prompt problem—you have a visibility problem.
PR-Linked Prompts flips traditional comms on its head. Instead of waiting for someone to write about you, you anticipate the queries your audience types into AI—and build your PR strategy around those prompts.
One SaaS platform we worked with focused on retention tools for mid-market B2B teams. Their old PR angle was “disrupting customer experience.” The problem? No one typed that. When we analyzed prompt logs and AI search data, what people actually asked was: “Which tools help reduce churn under 5,000 users?” So we crafted a punchy blog post titled exactly that, published it through a media partner, and embedded structured data to flag its relevance.
Result? Copilot, Perplexity, and Gemini started quoting it. Organic mentions spiked. Inbound demo requests tripled over the next quarter—not because we shouted louder, but because we whispered exactly where the AI was listening.
This is where PR meets prompt engineering. You don’t need to dominate the news cycle. You need to dominate the question that leads to purchase.
17. Hallucination-Proof Messaging: Control the Narrative or Be Misquoted by a Bot
If an AI gets your story wrong, it’s not the AI’s fault. It’s yours.
Hallucination-Proof Messaging is what separates companies with tight brand control from the ones left cleaning up after a confused LLM. We’ve seen it happen—an electric vehicle startup described itself in its press kit as “redefining modularity in electric mobility.” Sounds slick, right? Except Gemini summarized it as “a parts supplier for scooters.” The distortion wasn’t malicious—it was structural. The AI pulled from scattered, inconsistent phrasing across LinkedIn bios, outdated blog posts, and vaguely written pitch decks.
The fix? Consistency—everywhere. Same headline in the press kit, About Us page, schema markup, Meta description, and Google Business profile. Same short-form elevator pitch on Crunchbase, AngelList, and their founder’s LinkedIn. Same three talking points embedded in interviews and FAQs.
It’s not about spin. It’s about feeding the system the truth you want repeated—until the hallucinations stop.
If AI is the new homepage, your message needs to pass through dozens of tiny doors. If it doesn’t fit perfectly through each one, it gets warped.
18. Search-Sourced Storytelling: Find the Question First, Write the Answer Second
Old PR was about setting the agenda. Today, the smartest PR listens first.
Search-Sourced Storytelling flips content creation on its head. Instead of crafting the narrative you hope gets picked up, you start with what real people are already typing into ChatGPT, Perplexity, or Reddit. Then, you build your content—and your coverage—around that.
Let’s take a real case. A B2B logistics platform wanted top-tier tech press to cover their new route-optimization tool. But we saw something better in the data: a steady stream of queries like “How can I save on freight costs with fewer than 10 trucks?” That’s what users were asking LLMs. So instead of launching with a generic announcement, we positioned the feature as the answer to exactly that question.
We wrote the blog, pitched the headline, landed coverage in a small but well-indexed industry outlet—and within a week, their solution was being quoted in Gemini answers to the exact query.
That’s what modern PR is: storytelling built backwards from the search bar.
19. Zero-Click Reputation: You Don’t Need to Be Clicked to Be Judged
Here’s the hard truth: your audience often never makes it to your website, your full article, or even your carefully crafted press release.
They read the snippet.
They skim the AI-generated answer.
They glance at the headline and summary.
That’s it. That’s your shot.
Zero-Click Reputation means your entire brand perception is shaped in that split-second glance. In Perplexity or Gemini, when someone searches “Is [your brand] legit?”—they’ll likely never scroll past the answer box. If the AI summarizes your value prop clearly and credibly, you win. If it misinterprets, buries you, or worse—hallucinates something incorrect—you’ve already lost.
A fintech brand we worked with got this wrong. Despite major press coverage, its AI summaries painted them as “a budget tracking tool”—not the full-stack financial OS they really are. The damage? Confused investors, misaligned sales calls, and six months of rework to correct LLM perception.
PR today isn’t about pushing people to your site. It’s about earning the right reputation where decisions are made—in zero clicks or less.
20. Dynamic Press Kits: Less Gloss, More Structured Firepower
The era of zipped folders, outdated bios, and PDF press kits is over. Dead. Buried under the weight of broken links and static design.
What today’s machine-readable, human-usable brand needs is a Dynamic Press Kit—one that works not just for reporters, but also for robots.
That means a live media hub with structured JSON-LD data, not just pretty design. It includes up-to-date founder bios, AI-indexable product specs, short and long-form brand summaries, and canonical messaging embedded into schema.org. This isn’t just about looking polished. It’s about being discoverable, consistent, and impossible to misquote.
Think of it as a search-surface machine—ready to feed LLMs, journalists, editors, and search engines in the exact same language. No outdated logos. No typo-laden factsheets. No 2021 PDFs still hanging around your About page.
And the best part? When you update the core facts—your kit updates everywhere. Real-time, scalable, trusted.
This is no longer a nice-to-have. It’s table stakes for visibility in a post-snippet world.
The New Rules Are Already Being Written—Is Your Brand in the Script?
We’ve arrived at the inflection point. The days of hoping a well-placed article or splashy launch would carry your brand through the noise are over. AI systems don’t hope—they index. They scrape. They parse structure. And they decide what deserves to be remembered.
PR isn’t press anymore. It’s programmable. Your visibility isn’t determined by charisma or contacts—it’s determined by how cleanly your entity is recognized, how persistently your name surfaces in generative answers, and how well your data trains the very systems now shaping public perception.
You’re not just trying to win headlines. You’re trying to train the machine on what you mean, what you solve, and why you matter.
Visibility Isn’t Earned Anymore—It’s Engineered
This isn’t a threat. It’s a wake-up call.
Even the best storytelling gets flattened if it isn’t structured to survive in LLM logic. Even the strongest coverage fades if it can’t be cited by a machine. This is the moment when brands either become integrated into the fabric of AI discovery—or slowly start disappearing beneath it.
Being great doesn’t guarantee visibility. Being machine-readable does.
Don’t Just Compete—Be Comprehended
You can’t afford to be vague. Not now. Not when AI systems are rewriting the rules of discovery—and summarizing your reputation in a sentence. It’s not just a visibility issue anymore. It’s an existential one.
Let your competitors chase impressions.
