BEYOND STAR POWER: DO YOU REALLY NEED CELEBRITIES AND GLOBAL IP TO WIN CLICKS? A DATA-BACKED LOOK USING AD SPY INTELLIGENCE

We keep telling ourselves the same comforting story: if we could just get a big-name celebrity or a beloved global IP into our ads, everything else would fall into place. The algorithm would reward us. anstrex.com/blog/write-like-a-pro-10-copywriting-books-to-outshine-90-of-creators#entry:820194@1:url" target="_blank" rel="noreferrer noopener">Click-through rates would soar. Boards would stop asking awkward questions about efficiency.

But the data – and the market dynamics around it – tell a very different story.

Star power feels like a shortcut because it compresses years of trust-building into a single familiar face. Yet that “trust” is now one of the most volatile assets in modern advertising. As deepfake tools have become trivial to use, celebrities and creators have turned into prime targets. They leave behind exactly what generative models need: “hundreds of hours of footage and thousands of pictures” that make them unusually easy to impersonate, as researcher Alice Marwick points out in an investigation into how deepfakes are eroding influencers’ credibility.

The fallout is real. Deepfaked versions of Taylor Swift, Oprah Winfrey, Kim Kardashian and others have been used to promote dubious products. Mid-tier creators like Arielle Lorre and Jessi Caparella have discovered fabricated ads and altered images redirecting their likeness – and their audiences – to offers they never endorsed. According to Surfshark’s research, global consumers may have lost as much as $3.7 billion to deepfake scams in 2026, with social media impersonations accounting for about half of those losses, as the same reporting on influencer impersonation notes.

For brands, this isn’t just a cybersecurity curiosity. It strikes at the heart of why we chase star power in the first place. The whole point of borrowing a celebrity’s face is to rent their credibility. But if audiences are increasingly unsure whether what they’re seeing is real – and creators themselves say deepfakes are diluting their value and costing them followers’ trust – then the “credibility premium” behind that endorsement starts to evaporate. You’re paying top dollar for an asset whose signal is getting noisier by the month.

At the same time, the media environment is punishing anyone who overestimates the value of raw attention. In performance channels, click metrics are already decoupling from business impact. As one analysis of modern paid media explains, CTR has shifted “from a primary success metric to a diagnostic indicator,” more a reflection of algorithmic experimentation than genuine human resonance, and should be judged against post-click behavior and cost per acquisition instead of vanity spikes in traffic, as Search Engine Journal’s breakdown of CTR in 2026 makes clear.

In other words: a famous face can absolutely win auctions and generate clicks, but that no longer guarantees the campaign is working. High CTR on a celebrity-led ad might simply mean you’ve given the platform’s AI an easy, broad-interest creative to push – not that you’ve reached the right people or driven incremental revenue.

Meanwhile, the rest of the ecosystem is quietly re-optimizing around something much harder to procure than a global IP license: proprietary audience understanding and high-fidelity data. Competitive intelligence platforms are showing that the brands consistently outpacing their categories aren’t just outspending rivals; they’re “outbuying” them with systems built on audience precision and diversified placements, as a recent analysis of auction signals from Polaris AI’s social auction intelligence argues. Their edge doesn’t come from a celebrity spokesperson; it comes from the invisible architecture of how and where they buy.

The same logic is reshaping supposedly “star-driven” environments like out-of-home. Instead of paying a premium for the biggest, flashiest location — the Times Square of every media plan — smarter DOOH tools are shifting from location-first to audience-first planning. Platforms like JOLT’s Spark Intelligence start with behavioral, purchase and movement data to pinpoint where target audiences actually concentrate, then recommend the specific screens that deliver the highest-value exposures, often in less obvious environments that outperform mere footfall, as described in an overview of audience-informed DOOH planning.

When audience composition, context and proximity to moments of intent drive outcomes more than sheer impression volume, the idea that attaching a celebrity or global IP to the biggest possible canvas is the optimal move starts to look like a very expensive illusion. In a landscape defined by AI, signal loss and deepfake-fueled skepticism, the real star in your media plan isn’t the face on the creative – it’s the intelligence behind where, how and to whom that creative actually shows up.

If star power isn’t the real driver of performance, what is? When you look at accounts through an ad spy lens – scraping thousands of creatives, placements, and outcomes instead of a handful of “hero” case studies – a very different pattern emerges. The winners aren’t the brands with the most famous faces. They’re the brands that align three things ruthlessly well: the right audience, the right context, and the right post‑click experience.

First, audience. Modern ad platforms are no longer dumb pipes that simply spray impressions at whoever matches your demographic filters. They’re continuously re-optimizing toward people most likely to take a downstream action. As one performance strategist told Search Engine Journal, click‑through rate has shifted from a “primary success metric to a diagnostic indicator,” largely reflecting the algorithm’s own testing across audiences and placements. In other words, when you see a celebrity-led ad “crushing it” on CTR in your spy tools, you’re often just seeing the algorithm find people who love clicking on celebrity thumbnails – not necessarily people who buy.

Second, context. Ad spy intelligence makes it painfully clear that the same creative performs very differently depending on where and how it shows up. A slick, cinematic spot that looks great in a case study often underperforms as a skippable pre‑roll, yet a low‑fi expert talking to camera can quietly dominate in-feed placements. That aligns with what paid media leaders are seeing on platforms like LinkedIn, where founder-led and employee thought‑leader ads have driven clicks at a cost 68% lower than standard brand ads, with more than double the CTR, according to one campaign breakdown in the Content Marketing Institute. The “context” isn’t just the channel; it’s the expectation of the feed. In utility-driven, information-rich environments, audiences reward relevance and authority over spectacle.

The third – and most neglected – piece is what happens after the click. A spy screenshot will show you thumbnails and hooks, maybe even CTR, but it won’t show you whether that traffic became qualified pipeline or paying customers. Practitioners who tie ad platforms into CRM and revenue data are blunt about this. “A campaign can produce an efficient cost per lead and still have very little business impact,” one strategist told the Content Marketing Institute while describing dashboards that track progression from lead to opportunity and closed revenue. When those dashboards are layered against creative variations, a pattern shows up: the ads that win aren’t always the ones people are most eager to click – they’re the ones that attract people who stick around, explore cornerstone content, and move deeper into the funnel.

This is where the obsession with celebrities and global IP quietly breaks down. At scale, the algorithms are optimizing for signals like conversion rates, engagement depth, and cost per qualified opportunity. As Search Engine Journal points out, real success now sits “across a broader spectrum” of post‑click actions, not just click volume. Expensive talent may buy a spike in superficial engagement, but if those users bounce in seconds or never progress to SQLs, your CPMs and CPCs just went up for no incremental revenue.

Meanwhile, authority and relevance are compounding in quieter ways. Off‑site campaigns that repurpose substantial research into multiple formats – think expert video, on‑site explainers, PR angles, and social cuts – are built to perform across feeds, search, and even AI surfaces, as one strategist on The Moz Blog has argued. When you then put paid distribution behind the best‑performing slices of that ecosystem, you’re not paying for attention in a vacuum; you’re amplifying content that has already proven it can hold people’s interest and answer their questions. Those are exactly the kinds of journeys post‑click data rewards.

In other words, the data doesn’t care whether your spokesperson is a global celebrity or a subject‑matter expert with 8,000 followers. It cares whether the right person saw the right message in the right moment – and whether what came next was strong enough to turn a click into a customer.

Scroll through any ad spy dashboard and a strange pattern jumps out: some of the longest‑running, highest‑ROI creatives aren’t fronted by stars at all. They’re “nobodies” – stock-photo couples, faceless hands holding phones, low‑production talking heads recorded in a kitchen. And yet these unglamorous ads quietly outlive and outperform the glossy, talent-heavy campaigns.

What’s going on?

First, performance data doesn’t care about fame; it cares about fit. When you sort native, push, and instream ads by spend and duration, you repeatedly see inexpensive, low‑profile creatives beating out polished brand films because they nail three things simultaneously: a specific audience, a context that matches their mindset, and a post‑click journey that converts.

You can see this logic in other media, too. In digital out‑of‑home, the highest‑traffic screens are not the highest‑value ones; audience composition and proximity to “moments of intent” drive outcomes more than sheer exposure, as a recent look at smarter DOOH planning from Marketing Dive explains. Native and push work the same way. A no‑name nurse in a simple hospital corridor photo can beat a celebrity doctor if that placement is reaching “likely care seekers” reading an article about symptoms, at the exact moment they’re ready to click and act.

Second, algorithms have changed what “good” looks like. Click‑through rate used to be a clean proxy for interest; now, as Search Engine Journal points out, CTR is largely a diagnostic signal for how efficiently AI is testing audiences and creative. A celebrity face may spike curiosity clicks, but that doesn’t mean the traffic is qualified. When you use ad spy tools to filter not by CTR but by cost per acquisition, return on ad spend, and lead quality, the heroes are often boring, intent‑matched creatives that look like content, not like hype.

That has two big implications for “nobody” ads:

• Relatability beats aspiration. Users have developed antibodies to overpolished influencer content, and deepfake abuse is eroding trust even further. Coverage of AI‑generated scam ads impersonating famous creators on TikTok and Instagram notes how easily public figures can be cloned from “hundreds of hours of footage and thousands of pictures,” weakening the credibility of their likeness as an ad asset, according to reporting from the Guardian on deepfakes wrecking influencers’ credibility. In that environment, an unremarkable person in an unstaged setting can feel more believable than a famous face that might or might not be real.
• Clarity beats spectacle. Top‑performing native and instream ads in spy tools usually do one thing exceptionally well: they make the next step and the eventual value blindingly obvious. That lines up with guidance from the Content Marketing Institute, where practitioners stress that paid media has to be evaluated on what happens after the initial conversion – pipeline, qualified opportunities, and closed revenue – not just cheap leads or flashy engagement, as they outline in their piece on making paid media earn its place in the budget. Creatives that overindex on “wow” but under‑explain the offer tend to fall apart on those downstream metrics.

Third, “nobody” ads are easier to iterate into multi‑channel relevance. When your hero is a simple concept instead of a contracted celebrity – a pain point, a demo, a contrarian promise – you can spin that into dozens of variations across native, push, short‑form video, and even DOOH without clearing likeness rights every time. That kind of modular, cross‑format approach is exactly how modern campaigns build authority and visibility across search, social, and AI‑driven surfaces, as outlined in a recent Moz deep dive into multi‑channel relevance in the age of AI.

In practice, the highest‑ROI native, push, and instream ads you see in spy tools are rarely accidents. They’re the inevitable winners in an environment where:

• Audience targeting is sharper than ever.
• Algorithms reward post‑click quality over pre‑click glamour.
• User trust in polished, personality‑driven ads is eroding.
• And marketers are under pressure to prove that every paid impression contributes to actual business outcomes, not just “buzz.”

Celebrities and global IP can still have a role, but the data from ad spy intelligence makes one thing very clear: if you’re forced to choose between a famous face and a ruthlessly relevant “nobody” creative, bet on the nobody. The market already is.

Star power isn’t useless. It’s just far more situational – and fragile – than the glossy case studies suggest. When you look at celebrity and franchise‑driven ads through an ad spy lens, the rare breakout wins tend to cluster in a few tight scenarios where fame is doing a very specific job the algorithm or the copy simply can’t.

The first narrow case is credibility transfer in high‑friction categories. In verticals where consumers are fearful (insurance, finance, health), a famous face can function as a trust “accelerant” – if the rest of the system is dialed in. Competitive intelligence platforms like Polaris AI highlight that the real efficiency gaps in categories such as insurance come from audience precision and placement diversification, not just budget or message vanity. In its analysis of the insurance space, Polaris AI found that Progressive’s advantage showed up as a consistent media efficiency signal, which their team interpreted as a strategy grounded in smarter media mix, not louder spend or bolder creative alone, as AdExchanger explained. When a celebrity appears in the best‑performing insurance ads you see inside an ad spy tool, they’re usually layered onto an already tight performance engine: advanced audience models, ruthless testing of hooks and angles, and aggressive optimization to downstream metrics like cost per quote or policy, not just cheaper CPMs. The face is a multiplier, not the foundation.

The second case is launching or re‑positioning premium products to a defined, psychographic niche, where the talent has real overlap with the target. In your ad intelligence dashboard, these look like sequences, not one‑off hero spots: short‑form native placements, cut‑down instream edits, and creator‑style clips all repurposing the same shoot. This is where “clipping” suddenly becomes a performance tool instead of a vanity tactic. When brands build a library of moments from a celebrity shoot and then distribute those as highly tailored, modular assets – a 6‑second punchline for Reels, a 20‑second demo for YouTube, a testimonial‑style cut for TikTok – you see certain ads sustain strong engagement and efficient CPAs far longer than polished, one‑size‑fits‑all edits. Marketers have been quietly using this approach for years; Taco Bell, for instance, shot fan‑featured comedy content for its quesalupa launch and then sliced the footage into a series of short clips that ran across social and even fed into TV, a tactic that a social strategist described as simply “the latest version of the blooper reel,” as AdExchanger noted. When you apply that same mindset to a celebrity or global IP, the few standout winners in your spy data almost always share one trait: the star is being continuously re‑contextualized into dozens of creative tests, not locked into a single big‑bet spot.

The third narrow case is algorithmic leverage in attention‑rich but low‑intent environments. On feeds where people are mostly scrolling for entertainment (TikTok, YouTube Shorts, Reels), a known face can dramatically improve the first second: thumb‑stop rate, view‑through of the hook, and the platform’s willingness to give you cheap initial distribution. But under modern auction systems, front‑end engagement is only step one. As performance practitioners have been warning, metrics like click‑through rate or view rate are now more diagnostic than definitive: they tell you that your creative can win the auction and cut through, but not that it’s actually driving revenue. In performance channels, CTR has shifted from a pure measure of human interest to a proxy for how efficiently the AI is testing new audiences and formats, as one recent analysis in Search Engine Journal argued. The few celebrity‑fronted ads that keep showing up as “evergreen” in spy tools are those where the campaign architecture is built to exploit that dynamic: the star grabs attention cheaply, but the flow, offer, and measurement stack are optimized ruthlessly to post‑click quality – deeper engagement, higher conversion rates, and lower acquisition costs.

The fourth and riskiest case is borrowing identity in categories where identity is the product – think beauty, lifestyle, or creator‑economy tools. Here, an influencer or celebrity can be the difference between static CPMs and sudden scale. But this is also where the asset is most fragile. As deepfake scams proliferate, public figures’ likenesses are being repurposed without consent to promote dubious products, quietly scraped into synthetic endorsements, and used in outright fraud. Researchers and creators interviewed about the rise of AI impersonation warned that influencers now face a new kind of competition: not just other creators, but weaponized versions of their own faces, a trend that has already cost global consumers billions in scam losses, according to reporting from The Guardian’s coverage of TikTok deepfakes. When you license a celebrity’s image in this environment, you’re buying into a brand whose credibility can be diluted overnight by a single viral fake. That reality shows up in ad spy data as well: sharp bursts of performance followed by rapid fatigue or abrupt pull‑backs in spend once a talent‑related controversy, fake or real, starts to circulate.

In all of these narrow cases, fame earns its fee only when three conditions are met simultaneously in the data: the audience truly cares who the person is, the media system is optimized beyond vanity metrics, and the creative strategy treats the celebrity as one variable in a long‑horizon testing program, not a silver bullet. Strip away any of those, and your expensive face collapses back into what most star‑driven ads really are in the auction: just another high‑CPM experiment trying to prove it deserves to keep running.

If you’re a smaller advertiser staring at those IP-stuffed ads in your ad spy tool, the reflex is: “We could never afford that.” The good news is you don’t need to. You just need to steal the structure that makes those campaigns work and rebuild it with assets you already own.

Think of every winning celebrity or franchise ad you see in your spy feed as a template with four repeatable layers:

1. Audience and moment selection
2. Hook and framing device (what fame is doing)
3. Proof and payoff
4. Distribution and measurement

Star power mostly lives in layer two. Everything else is replicable with smart data and creative ops.

1. Start where the winners start: the audience, not the asset

Big brands don’t succeed with IP because they have famous faces; they succeed because they aim those faces at the right people, in the right moment. In digital out-of-home, for example, smarter campaigns now begin with audience intelligence, not just “busiest billboard.” Tools like JOLT’s Spark Intelligence identify where a target audience is actually concentrated and show that the highest‑traffic screen isn’t always the highest‑value one, since composition and context beat raw impressions for performance, as Marketing Dive’s analysis shows.

Apply that same principle to your meta ads, TikToks, YouTube pre-roll, or native placements:

• Use your CRM, pixel, and platform insights to find the pockets where your best customers over‑index.
• Prioritize creatives tailored to those pockets instead of chasing generic reach.
• In your ad spy tool, filter for placements (feeds, Stories, Shorts, DOOH, etc.) where lookalike brands are getting outsized longevity on non‑celebrity creatives. That’s where relevance is doing the heavy lifting.

You’re not competing with Nike’s global reach; you’re competing for hyper-relevant impressions where your specificity beats their star.

2. Replace the “famous face” with a recognizable pattern

Celebrity and IP often function as a fast pattern match: “Oh, I know that person/character, so I’ll stop scrolling.” You can get a similar interrupt without paying for likeness rights by building your own repeatable, recognizable creative patterns.

Leverage:

• Recurring visual formats – A consistent framing (over‑the‑shoulder screen recordings, the same kitchen background, the same “text on screen” animation) trains your audience to recognize you the way they’d recognize a familiar influencer.
• Repeatable hooks – If you notice in your spy feed that celeb-led spots lean on a certain angle (“I wish I’d known this sooner,” “My controversial opinion about X”), port the hook formula into your own talking-head or UGC-style videos.
• Mini‑characters and motifs – A support rep, a customer archetype, a simple mascot doodle, or even a recurring prop can become your low-budget IP.

This strategy also sidesteps a growing risk: the more famous and overexposed a face is online, the easier it is to deepfake. Widespread impersonation scams are already eroding follower trust, with fake endorsements from figures like Taylor Swift and Tom Hanks undermining creator credibility and costing consumers billions, as reporting on deepfake ad scams makes clear. By anchoring your creative in flexible patterns instead of rented faces, you’re less exposed to that credibility fallout.

3. Anchor the structure in proof, not personality

When you strip away the famous face, the strongest IP-led ads still rely on the same backbone: a clear claim, social proof, and a tangible outcome. That’s the backbone you can steal wholesale.

Break apart the best-performing celeb or franchise ads in your spy tool:

• What specific problem is stated in the first three seconds?
• What type of proof is used—numbers, screenshots, testimonials, product demos?
• How quickly do they transition from “look who’s talking” to “look what this did for me”?

Then swap in your own assets:

• Replace a celebrity anecdote with a real customer micro‑case (“It cut my prep time from 3 hours to 45 minutes”).
• Replace cinematic B‑roll with concrete product usage, dashboards, or side‑by‑side before/after comparisons.
• Replace expensive sets with “authentic environments” your best customers actually live or work in.

You also don’t need to finance a new concept every quarter. A single strong research finding or expert video can be atomized into multiple creative angles. Paid media doesn’t have to fund endless fresh assets; it can amplify your best-performing proof pieces across formats, from short video to social cuts and webinars, as practitioners interviewed by the Content Marketing Institute emphasize. That principle maps perfectly to performance ads: build one proof-rich spine and spin dozens of variants that copy its structure.

4. Distribute like a big brand—measure like a ruthless small one

The last layer big advertisers get right isn’t just media budget; it’s multi‑channel intent. Leading off‑site campaigns aren’t built as one‑off stunts. They’re designed to surface in social feeds, journalist coverage, and now AI‑driven surfaces, not just a single placement. Modern off‑site strategies deliberately create multiple content formats (short‑form video, carousels, articles) and seed them across creators, journalists, and communities so they show up in feeds, in media, and inside conversational search experiences, as a recent Moz breakdown of multi‑channel relevance explains.

You can follow the same logic at your own scale:

• Build one structural concept (problem → proof → payoff) and adapt it into: a 15-second UGC clip, a 30-second explainer, a static social ad, and a short landing page.
• Run lightweight tests across two or three channels instead of putting all your faith in a single platform where the algorithm might arbitrarily bury you.
• Measure outcomes that map to your real funnel, not just cheap clicks: cost per qualified lead, depth of engagement on your core explainer, or branded search lift—metrics B2B teams increasingly favor over vanity CPL, as detailed in the.

Your advantage as a smaller advertiser is not spectacle but speed. A global IP campaign might take months to clear contracts and approvals. You can watch it in your ad spy feed today, reverse‑engineer its bones this week, and launch five structurally similar—but founder- or customer-fronted—variants next week. Let the giants pay for the pattern; you profit from the remix.