While it seems there’s no singular “song of the summer” this year, there’s certainly been a sound of the summer. That sound is the certified-viral “Nothing beats a Jet2 holiday” audio clipped from the ads and in-flight videos of the budget British airline/travel company Jet2.

The hashtag #Jet2holidays has been used on 456,000 TikToks, and the audio has been used in 2.8M videos, most of which show vacation fails: pulling open hotel curtains to reveal the world’s smallest window, watersports disasters, wipeouts in the bowling lane, etc.

The “joke” is that Jet2’s relentlessly sunny earworm, Hold My Hand by Jess Glynne, creates a lighthearted mismatch when paired with epic vacation fails. As a budget-friendly airline and travel package provider, Jet2 experiences aren’t always known for being high-end or picture-perfect.

Instead of trying to swim upstream and “fix” the narrative around this onslaught of negative yet hilarious videos, Jet2 leaned in. They created a lipsyncing contest for the audio, offering £1,000 for the winning submission. Their video has 34M+ views and comments like “This is actually so iconic” and “Jet2 has entered the chat.”

The Lesson: If you can’t beat ‘em, join ‘em.

You can’t fight a wildfire with a press release or cold corporate messaging. When a good-natured social media trend has taken on a life of its own, you have no choice but to cheekily hitch your wagon to it and play along.

By winking at the joke, Jet2 showed they were in on the fun without directly admitting they sell lackluster experiences. It was a smart way to ride the wave without sinking brand equity.

Domino’s Pizza Turnaround

Back in 2009, Domino’s had a mess on their hands. In addition to viral videos of real employees doing heinous things to customers’ pizza, their product quality was slipping amidst franchise expansion. The fallout made Domino’s a lightning rod for criticism, and they needed to gain control of the narrative.

Enter Domino’s Pizza Turnaround, featuring one of my favorite off-kilter taglines ever: “Oh Yes We Did.” Domino’s tapped red-hot ad agency Crispin Porter + Bogusky for a come-to-Jesus ad campaign, featuring cutdowns from their wonderful four-minute marquee video where they faced the harsh truth.

The ads showed focus groups calling out their cardboard-like crust and their ketchup-esque sauce. It showed the corporate team cringing and shaking their heads in shame. Then it showed the team rallying wholeheartedly to make better pizza.

“You can either use negative comments to get you down, or you can use them to excite you and energize your process and make a better pizza. We did the latter.” – Patrick Doyle, President, Domino’s Pizza

The numbers following the refreshingly candid campaign didn’t lie. By the end of the next quarter (Q1 2010) Domino’s posted a 14.3% sales increase QOQ, one of the highest-ever revenue jumps for a fast food chain. (Source: UCLA Economics). By the end of 2010, the company’s stock had soared 130% from where it was at the end of 2009.

Domino’s stock continued to go on a remarkable run for the next twelve years, with gains dwarfing the S&P 500, Invesco QQQ, and Papa John’s for good measure.

Their stock went from $8.38 a share at the end of 2009 to $564.33 by the end of 2021. An absolutely legendary run. I, for one, don’t believe this would have happened with cardboard crust and ad campaigns acting like everything was hunky-dory.

The Lesson: Honesty is the fastest way to reset trust.

Instead of slightly tweaking the recipe, Domino’s tore everything down to the studs. That radical transparency showed customers the company was serious about fixing the problem, thus creating a clean break from the old baggage and opening the door to growth.

The Anti-Luxury Amsterdam Hostel

Back in 2013, my two friends and I needed a cheap hostel for a one-night stay in Amsterdam. After poking around online, one option stood out like a sore thumb: The Hans Brinker.​

In some of the boldest pieces of advertising I’ve ever seen, their site featured atypical “Before” and “After” photos of guests looking nice at check-in and awful at check-out, implying the Hans Brinker was a wild, chaotic, sleepless adventure.

So we did what 21-year-old guys do and immediately booked a night there. After being paired up in a room with a group of six Aussie guys on a bachelor party (who didn’t really sleep, and snored like locomotives for the hour or two they did) we got the full Hans Brinker Budget Hostel experience, as advertised.

Checking back in on the Hans Brinker today, they’re still living into their promise, albeit in a more tasteful way. Absolutely hilarious, daring lines like “Just don’t say we didn’t warn you” and “You probably won’t sleep much anyway” are paired with photos of llamas in dorm-style rooms.

This is a classic case of knowing what you are and what you aren’t. It’s also proof you don’t need a viral trend or a multimillion dollar ad campaign to own your “thing.” You just need to be intentional about your brand differentiation, especially above-the-fold, then put your shoulder behind it across your marketing efforts.

If the Hans Brinker website had featured their central location, history, team, or their (admittedly scant) amenities in 2013, we would have glossed over it and booked a place with better reviews. But they played (and still play) to the adventurous, younger crowd who’s looking for a story, not sleepy time.

The Lesson: Specificity beats general appeal every time.

Instead of getting lost in the noise with other listings, the Hans Brinker plays up their truth (cheap rates and unbridled chaos) in a way that speaks to a specific slice of customers. In a huge tourist destination, they don’t need to be everything to everyone.

In other words, nobody craves buffet food. So choose the food you serve best (steak, tacos, or in this case late-night pizza) and make it even more specific (dry-aged steak, al pastor tacos, or the biggest slice in town).

The Takeaway: Truth Is Your Trojan Horse

The truth, especially when it’s wrapped up in wit or self-awareness, is disarming. It can sneak past natural skepticism like a Trojan horse rolling through the gates.

Whether it makes people laugh, feel seen, or nod along, leaning into your brand’s truth shows your audience you’re willing to meet them where they are.

Specificity and honesty are also self-filtering. They pull in the right customers and build loyalty in a way that “We’ve got something for everybody” never will.

​Gil Templeton​
Demand Curve Staff Writer

When MidJourney launched via Discord 2+ years ago, the UX was tricky, at least for me. For those not intimately familiar with Discord (and a little intimidated by their first foray into image-gen) the experience left plenty to be desired.

You had to create and link a couple accounts, you were directed to use public channels filled with other users’ images, it wasn’t clear where your saves went (or how your credits worked), and you started every prompt by manually typing “/imagine”.

It constantly had me wondering, “Am I even using this right?” and the murky UX almost made me walk away.

Fast-forward to Midjourney today, and it’s as user-friendly as anything: a familiar “search bar” at the top for your prompt, upvoted eye-candy, a simple side panel for navigation, and no two-stepping through another platform (i.e., Discord).

This transformation epitomizes the stupid-simple standard that’s become the template for today’s AI platforms, where the inner-workings are increasingly mind-bending, but the outward-facing wrapper is instantly enticing.

Let’s take a closer look at this standard that’s coalescing around today’s AI darlings.

A New Standard for Chatbots and Visual Tools

The main interfaces of platforms like Lovable, ChatGPT, Gemini, Veo, etc. are shockingly stark, stripped-down, and simple. Even if you have no idea what you’re doing or if you really need this thing, you immediately know how you’re supposed to use it. Then your quick and easy outputs prove why you need it.

They throw you straight into the experience with virtually zero friction. “Just type something here and have your mind blown, we’ll figure out the details later,” seems to be the new norm. When they do ask you to sign up, it’s free and takes a click or two.

They strip out any potential rub and make the first interaction feel like a win, hooking you with your “Aha!” moment before you can even think about leaving.

My dear grandmother doesn’t know what “vibe” or “coding” mean, but could she vibe code on Lovable in a minute or two? Yeah, she could. It would probably be very bad (sorry, Nana) but she could type a few sentences and get something for her troubles.

Here are some themes and tactics helping these sites turn viewers into users:

• Frictionless or deferred sign-ups: These platforms tend to hook you with output before asking for a credit card. By the time you’re prompted to pay, the platform already has its hooks in you.
• Zero-education interfaces: They remove intimidation for first-timers by skipping the jargon and onboarding tours. There’s usually a single input field in a familiar search bar format, accompanied by easy-to-digest, human-sounding copy.
• Guided “first wins”: These platforms lower the cognitive load by showing suggestions, templates, or sample outputs from others, so users don’t have to think about how to take that first big step.
• Instant feedback: Rapid output delivers an instant dopamine hit that we’re well-documented suckers for. And with highly visual platforms like Sora, Midjourney, or Veo, the outputs are eye-catching and shareworthy.
• Dead-simple CTAs: “Type here” or “Upload a file” or “Paste your text” puts an easy-to-follow breadcrumb right in front of users without overwhelming them.
• Freemium plans: They’ll give you a taste of the real thing without making you pay a dime. Only when you want to cross a certain threshold of credits, time, or quality do they put a price tag on it.
• Lightning-fast Time To First Value (TTFV): By providing value (or the “Aha moment” below) so rapidly, these sites create instant momentum, making it far more likely you’ll engage and convert.

Some Other Interesting Examples

Plenty of other AI-forward or AI-enabled businesses are leaning into instant interactivity and quick wins to remove roadblocks and boost retention. Below are two creative examples:

​Replit uses a Mad Libs-esque approach for app creation, where the homepage asks first-timers to fill in the blanks on three input fields: type of project, who it’s for, and what it does. This works because it collapses the intimidating “Where do I start?” moment into a playful, low-effort interaction that personalizes the output and gets users involved before asking for an email.

​Creati conveys their value in a modular, highly interactive flowchart that begs for you to click on it. You can choose your model, featured object/product, and scene. Within seconds, the output updates to reflect your choices, showing you the exact value they bring.

Psychology of the Free Sample

The more I thought about this approach, the more I realized it’s essentially the digital cousin of the Costco free sample, on steroids. Free samples are a notoriously effective tactic at retail, as one industry study of grocery stores showed samples driving product purchases by 2000%.

The chart below shows just how effective free samples can prove to be across product categories (in real life, at least). Even a “laggard” like beer still sees a staggering 71% sales increase after engaging in free sampling.

Free samples work in supermarkets for similar reasons why they work on homepages:

• Instant gratification: Quick, rewarding outputs deliver that same hit of “I got something” like you get from a sugary chocolate chip cookie quadrant.
• Lowered sense of risk: Once you taste it, you know whether you like it or not. So when a site/experience gives you something you like, it’s easier to justify further engagement or payment.
• Reciprocity drives action: While this is likely stronger in an in-person situation, a no-questions-asked free trial/freemium subscription comes across to me as more endearing than the pay-first option.
• Higher awareness: Once you’re exposed to a brand or business, they’re more likely, on average, to be in your consideration set. Of course a positive, hands-on experience can make it even more familiar and memorable.

When I said “...on steroids.” earlier, I was hinting at the attribute that makes this “sampling” even more powerful: bespoke outputs. Because a free sample of baklava is great. No complaints.

But a free sample of exactly what you’re craving (a Philly cheesesteak for me right now) cooked in seconds and served hot? One nibble of that, and I’m 100% reaching for my wallet to buy the footlong. Being able to generate these unique, personal outputs at scale is now possible through AI.

Takeaway: Be Interactive and Instant

Today’s best homepages and landing pages grease users up, so they can glide through progress and achieve gratification (or “first value”) before they can blink.

Sure, yours might not be as simple as a prompt field, but when you aim to make a user’s first steps just as inviting, obvious, and rewarding as these masterful AI juggernauts, your conversion rate will act accordingly. (P.S. if you want deeper guidance on your CRO and landing page optimization, the Growth Program 2.0 will cover that in spades).

If your site’s first impression doesn’t have an interesting “hook” above the fold (more on that here), or it asks people to work too hard (decoding jargon, stumbling through sign-up, guessing the action they should take, etc.) you’re turning people off. And this gap is only getting more pronounced with frictionless AI tools becoming so ubiquitous.

While user behavior has always echoed the sentiment of “Don’t make me think,” it might be heading toward a place of, “Make me something.”

​Gil Templeton​
Demand Curve Staff Writer

We’ll start with three homepage best practices that give your page a rock-solid foundation.

Convert More With Your Homepage

Insight from Demand Curve​

Buyer journeys aren’t nearly as clean as we like to imagine. Most people won’t see your ad → visit your landing page → buy immediately.

It’s more likely to go like this:

1. They see your ad while doom-scrolling Instagram. They click.
2. Something distracts them away from their phone.
3. They remember later in the evening (or 3 weeks later) thanks to a Trigger Event.
4. They Google your company name.
5. They visit your homepage, not the conversion-focused landing page you intended them to hit.

(At least, that’s how I tend to buy things online.)

Is your homepage optimized for conversion? If not, you may be leaving growth on the table.

Yes, your homepage has many jobs (too many). One is to orient people to your brand and everything you do. But don’t forget high-intent visitors often visit your homepage late in the funnel.

Design it with conversion in mind.

Here are some quick ways to make sure your homepage converts:

1. Start by nailing the above-the-fold

Your above-the-fold (ATF) is the portion of your website that’s immediately visible to visitors: your hero header, subheaders, imagery, and calls to action (CTA).

Header and subheaders: Keep your copy short. Concisely convey what your product is and why they should care. Visitors shouldn’t have to scroll to understand what you offer and how they’ll get value from you.

Imagery: Whether static images, slides or video, keep your product(s) at the forefront. Photos with people are optional, but they have a proven track record of increasing conversion.

Call to action (CTA): Your ATF is the most important part of your most important page, and your CTA here might be the most important part of your entire site. This is what drives action. CTAs for ecommerce tend to be “shop now.” For services, “get started” and “try now” work well. Make sure your CTA is high-contrast and unignorable.

Here’s an example of an above-the-fold done well.

• Concise, punchy header and subheader explaining what Mosaic is and why you should care
• Attractive visuals of the product
• Clear, high-contrast call to action (although they should depart from their monochrome design and make the CTA a contrasting color to make it pop)

We wrote an entire playbook on ATF alone. When you’re ready to create your ATF, you can follow our step-by-step process.

2. Handle objections in your below-the-fold.

Below the fold, you briefly address any objections visitors might have.

Some elements you might include here:

Social proof: Share reviews, press, user-generated content, testimonials, endorsements, ratings, customer logos, and customer stats.

• Include social proof near your CTAs to handle their objections at the key moment where they’re deciding to click or not. Trust leads to action.
• There’s basically no such thing as too much social proof.

Product features: Highlight unique product features that address common concerns.

• Worried about quality? Here’s why we’re the best you can get.
• Worried it’ll take too long? We’ll have you onboarded in five minutes or less.
• Worried about not liking the product? If you don’t like it, we’ll give you a full refund.

FAQ: Take it a step further and add an FAQ section.

• Start with the most common or highest-friction questions.
• Assume they didn’t read the whole page and repeat all the key points.

Bestsellers: If you have several products, highlight your flagship and most popular items. Or highlight a “starter pack” or samples.

Footer: Include pages in the footer that you want to give visitors access to but aren’t critical to the conversion journey, like your exchanges and returns policy.

See how MUD\WTR uses their FAQ section to address common questions (objections):

Include CTAs throughout your homepage so visitors don’t have to scroll back to the ATF to take the next step in their buyer journey: the product, pricing, or sign-up pages. CTAs in a sticky nav work well, too.

3. Run an A/B test.

It’s easy to make changes and assume they’re better. Time to test that:

Filter for people who have already visited your ad landing pages. These are the warm visitors we’re experimenting with. Send half to your current homepage and the other half to your new, conversion-focused homepage. See which performs better.

Put a little love into your homepage, you might see a big bump in conversion.

For more, dive into our Above the Fold playbook and Landing Page guide.

Now it’s time to dig a little deeper into the layout of the “perfect” landing page. While homepages and landing pages share a lot of the same DNA, let’s expand on landing page-specific nuances below.

The Perfect Landing Page Checklist

Insight from Tuff Growth and Demand Curve.

Your marketing efforts are wasted if the landing page sucks.

That’s why it's a good idea to use a proven template rather than get too creative.

Wait, don’t we constantly tell you to be creative?

Yes, 100%, your marketing needs to be creative to stand out.

But creative layouts confuse people.

So, be creative with marketing (ads/content/email) and practical with conversion.

Here's a checklist for nailing the perfect landing page (high-res version):

Thanks to our friends at Tuff Growth for creating this A+ infographic, particularly Sean Tremaine, the genius writer and designer behind it. Let’s dive into each of these sections some more.

Hero Section:

​The hook is everything:

• Header: Clearly state what you do and why it matters.
• Subheader: Expand your headline. How do you do it?
• Image/Video: Visually communicate your product.
• Call-to-Action (CTA): Place an OBVIOUS button that guides the user to the next step.
• Navbar: Key conversion pages/sections only (Pricing, FAQ, Features) and make it sticky.

Social Proof #1

Social proof is one of the biggest motivators:

• Display usage numbers or logos of well-known customers to build credibility and trust.

Benefits/Features Sections:

Features = talking about yourself. Benefits = talking about your customer.

• Benefit Headers: Clearly state your product or service's main benefits.
• Feature Subheaders: Explain how they get that benefit with your product’s features.
• Image: Use visuals to reinforce the benefits and show your product in action.
• Use bullet points and icons for easy reading.
• Repeat your CTA button for each section.

Social Proof #2

There’s no such thing as too much social proof.

Go deeper with testimonials/case studies/reviews.

• Testimonials: Include quotes from satisfied customers, ideally with names and photos, to add authenticity.
• Case Studies: Highlight the results your customers have had.

You can see a deeper dive into the science of using reviews here.

FAQ Section:

• Don’t assume they read the page. Repeat key details.
• Handle the most common objections.
• Don't lay on the marketing speak, just give the facts.

Tip: Ask support and sales for common customer questions and objections.

Final CTA Section:

Make it glaringly obvious how you can help and how they can take action:

• Hammer in the top value prop.
• Make the CTA clear and persuasive.
• If it’s a form, use as few form fields as possible.

Footer Section:

• Only link to key conversion pages.
• Make it painfully obvious how to contact you.
• Privacy and Cookies Policies and Terms are mandatory.

Note: Of course, you can layer additional sections as appropriate for your startup. You can add pricing sections. Problem agitation. How it works. Product gallery. Your mission. And so on. This is a purely skeleton to build on top of.

Quick Tips

• 90% of the work is done by the hero. Make it hooky.
• Your CTA Button should be the most glaringly obvious thing on the page.
• Be short and clear. Optimize for scannability.
• Mobile-friendly is mandatory.
• If you have the traffic volume, A/B test regularly to find the copy and images that convert best. If not, get a lot of feedback from people.

Check this off next time you build a landing page, and you'll be ahead of 90+% of folks.

Want to get ahead of the rest?

Get our extremely detailed guide walking you through how to perfect each section.​ And if you want more detailed guides on every aspect of growth, sign up for the Demand Curve Growth Program 2.0 waitlist. Launching soon!
​
— The Demand Curve Team

A friend and I were dissecting a LinkedIn post from someone we both know, and it reeked of pure, unadulterated AI slop.

She asked a simple but important question: “Do you keep reading once you know it’s just pasted from AI?”

My response was a hard “No.” And I’ll be less likely to read another post from that person in the future, just because they’ve shown their hand. Their six-fingered hand, that is.

This anecdote speaks to the ways people (and platforms) have quickly learned to spot what’s genuine versus generated (what a CUNY professor describes as an “incredibly banal, realistic style.”) It also encapsulates how these types of posts and people are being categorically dismissed.

Since LLMs are so accessible and widespread, let’s start there, so you can be sure your brand’s associated text outputs (captions, ad copy, scripts, post on LinkedIn or X, web copy, emails, etc.) are boosting your credibility and reach.

Eight Ways To Nuke Your Copy Cred

To prove just how predictable AI writing can be, we threw a simple prompt into ChatGPT 4o to see how many instances of AI tells show up. While there are always exceptions, let’s look at some of the common (and lesser-known) AI text transgressions that can register as robot authorship:

• “It’s not just _____. It’s ______.” Similar formulaic, context-based comparisons such as these have been a darling of LLMs. While these can make a strong point or pivot in just a couple words, strive to find another format or approach to convey the idea.

• The much-maligned em dash: This well-documented “tell” has been a major blow to the infinitely versatile punctuation mark that writers notoriously overuse (guilty). In a strange reversal, real human writers are ditching it altogether to signal “Hey, I really put time and attention into this,” as much as it might pain them to do so.

• Excessive hedging or overly formal transitions: Spotting phrases like, “It may be prudent…” or “It might appear that…” show the lack of a clear and compelling human POV. Also formal transitions like "As a result" , "In parallel" , "Ultimately" feel mechanical and overused.

• Tripping over triplets: Using a sequence of threes is a historically strong tactic for storytelling. The number three scratches some itch in our human brains, and AI knows that. So if you see a “build, launch, and scale” or a “simple, smart, seamless” you’re likely staring down the barrel of a bot.

• Grandiose descriptors and verbs: These sensationalist adjectives, adverbs, and verbs try to drum up the emotion and persuasive flair, but they usually feel like a reach. I’m talking adjectives like revolutionary, groundbreaking, jaw-dropping, next-level etc. Adverbs like radically, seamlessly, shockingly, infinitely, etc. And verbs like delve, harness, illuminate, unleash, underscore, facilitate, streamline, bolster, embark, leverage, unlock, elevate, foster, map out, etc.

• Rhetorical Questions: These faux-conversational devices pop up when AI tries to sound engaging and interactive. Instead of naturally transitioning between ideas, AI drops in questions like "What's changed?" or "Sound familiar?" to create artificial dialogue.

• Nebulous quotes & sources: If you’re using a quote from someone, triple check that it exists in a credible source outside of your LLM. Sometimes you’ll get quotes that never existed, along with cloudy takes like “Studies show…” or “Experts agree…” when there’s not hard evidence backing it up. A real study showed AI failed to produce accurate citations about 60% of the time, so proceed with extreme caution.
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• “Tapestry.” Just the word “Tapestry.” From personal experience (and the experiences of those on a Reddit thread and Grammarly blog too), it seems like AI can’t get enough of this one. Try to resist the urge to use it, unless your content relates to an actual tapestry (not a metaphorical one).
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The examples above will be hard to avoid completely in all of your writing. Lots of the callouts are fairly common, and some are particularly effective (especially before they became a little suspicious). If you list a series of three things or use an em dash, nobody is going to write you off. But if you copy and paste a first-draft 300-word output from your LLM, you’ll probably sound some alarm bells.

Our Recommendation: If you're going to use AI to help draft content, use Claude over ChatGPT. In our experience, it's better at writing human-sounding prose. Use a reasoning model (like Opus 4 or Sonnet 4). These models can loop through instructions to avoid AI tells and make sure they don't show up. Create a "Claude Project" with plenty of examples of your actual writing, in your tone. Use this Project to draft your content. Finally, dictate your perspective (and loads of context) into the LLM before you simply prompt it to "write me a blog post." Your unique POV is a huge component of what makes your content human.

Worth Thousands of Words, Audiovisual No-No’s

When you’re going for realism, the same sloppy shortcuts that give your AI-generated copy away can taint your visual and audio assets. If you’re going for something so outlandish, unrealistic, or very clearly made with AI, people don’t judge the same way. As long as they know you’re not trying to fake them out.

But the moment you try to pass AI content off as an actual photograph, something human-made, or a real interview, it can be interpreted as deceptive and unethical. The backlash can be even stronger in certain industries like fashion, where models and photography are sacred. Last week’s public response to the AI model featured in a Guess ad in Vogue Magazine had people upset to say the least.

Product photography affected by AI can also pose an ethical dilemma. Let’s say you include a reference image of your brand’s purse in your Midjourney or Sora prompt, but the output looks more upscale.

The image looks glossy, immaculate, velvety, detailed, even though it doesn’t quite look like that in real life. Is it still honest to use that image in your ad, knowing AI dolled it up? Or have you crossed the line to misrepresentation?

We're not attorneys, but we'd urge you to research FTC regulations surrounding false advertising and deceptive claims in your industry.

Below are some practices and approaches you should avoid to ensure your audio/visual outputs aren’t seen as deceptive or jarring, especially if you are conveying realism:

• Fake humans pretending to be real ones: Passing off synthetic models or avatars as real people (whether in customer testimonials, interviews, or photoshoots) erodes credibility. Even if you disclose your AI usage or use an outright fake influencer (like the fleeting Mia Zelu of Wimbledon fame), it’s no guarantee people will like it or see it as ethical.

• Uncanny glitches in video: An unnatural movement or jarring facial expression quickly tells viewers they’re looking at AI. If the point of your video hinges on looking real, don’t use AI unless you have total mastery of the output and you disclose your usage of AI. The “Uncanny Valley” theory supports this notion that people can’t stand to look at something almost human. Act accordingly.

• Fake news-style interviews: Creating realistic yet fake footage of someone saying something they never said crosses the line (whether it’s a deepfake of a real person or a made-up character that looks like an everyday person). Unless you’re 100% transparent, or if your account is clearly for comedy/satire purposes only, stay away. This format has proven to be easy to pull off with Google Veo 3.
  ​
• Synthetic voiceovers with no context: AI narration with unnatural or flat delivery can stand out as inauthentic to some listeners (or stylistic to others). Use it to prototype or time your edits, but if you want the best shot at a voiceover that conveys human emotion (especially in high-touch, produced pieces) use real voiceover talent. However, ElevenLabs raised $180M in January at a $3B valuation, so the gap might be bridged pretty quickly if progress stays the course. And of course there are cases where AI voiceover works well.
  ​
• ChatGPT Sepia Filter: That telltale yellow-beige tint that washes over AI-generated images. It's the visual equivalent of the AI em dash. Yellowish images can still get your point across and might be better than nothing, but make sure the visual message is worth the potential credibility hit. A quick "temperature" and "tint" adjustment can fix the issue.

Platforms Prioritizing Quality

Tech platforms are making their stance clear, use AI to elevate, not automate. They want creators and users who embrace this new technology to add value. They’ve been fine-tuning their policies and algorithms to sort for quality over sheer quantity.

YouTube made a change to their monetization policy where “faceless,” repetitive, or mass-produced content (often made possible with AI) will now be deemed inauthentic and ineligible for monetization. And while remixes and AI content are still allowed, creators must add clear value or commentary for it to qualify. The bar might not be particularly high, but at least the bar has been re-set.

Google has also clarified their stance of “Rewarding high-quality content, however it is produced.” Pay special attention to that phrase: “high-quality.” They’re much less concerned with how something was made, and much more concerned with the actual merits of the site or blog. In other words, you can definitely use AI to help write your SEO-boosting blogs, but the final draft better not read like unoriginal, regurgitated goop.

And if you’re like me, you’re probably scrolling through LinkedIn like you’re walking through a minefield, cautiously approaching each post to inspect for clear and present traces of AI before devoting time to reading it.

Bottom Line: Recalibrating Our Filter

Sure, the tools are faster than ever. The slop is sloppier than ever. But we humans are already doing what we’ve always done during these eras of newfound media overload, recalibrating our filters and redefining our threshold for what’s worthy of our time and attention.

So while you can now “write” a blog post by dictating a few sentences into AI and hitting a couple buttons, remember, so can everyone else. The barriers to entry are lower, and because of that, the bar for quality has never been higher.

​Gil Templeton​
Demand Curve Staff Writer

Stockholm-based Lovable turned a simple, powerful idea into a rocket ship: use AI to let anyone build apps or sites just by describing what they want. The approach, vibe coding, became popular this year as a tool for rapid prototyping, paired with software.

Within eight months of launching in late 2023, Lovable attracted 2.3M active users, saw over 10M projects built, and raised a $200M Series A, valuing the company at ≈ $1.8B. They minted a European AI unicorn at unprecedented speed.

By letting you speak your app into existence with vibes only, it basically turns moodboarding into shipping. A founder described it as holding a “magic key” that opens the door to software without developers.

This level of product-market alignment makes customers’ obsession with the product a natural growth lever. Every output becomes a showcase people want to show off. And each user becomes a signal-boosting evangelist.

It’s one of those rare cases where an innovation has so many use cases and so much visual intrigue, the product itself is the growth engine no matter what channel it’s on or who’s looking at it.

The 12-Channel Illusion

On the contrary, some growth gurus were quick to claim Lovable architected their growth through a complex omni-channel strategy:

1. GitHub - Launched as GPT Engineer, got 54K stars
2. Product Hunt - Multiple launches, starting January 2024
3. X/Twitter - Daily posts from CEO Anton Osika​
4. LinkedIn - Professional spin on the same X/Twitter content
5. Discord - 34K+ member community
6. YouTube - 20K+ subscribers, product demos
7. Google Ads - Paid search campaigns
8. Partnerships - Agency deals with commission structures
9. Podcasts - Hit every major tech show (20VC, Lenny's, etc.)
10. Events - Presented at Slush and other startup conferences
11. Reddit - Strategic threads showcasing the product
12. SEO - Blogged about their own growth to attract more growth

Impressive list, but this is more correlation than causation. It's what happens when your viral coefficient (the average number of new users that an existing user generates) is insanely high. Because starting a fire is a littleee easier when your product is a 50-gallon drum of jet fuel.

The Viral Coefficient Driving It All

During Lovable's early hypergrowth from over 20,000 users in late January 2025 to over 500,000 in February, they achieved ~25x user expansion in about a month, implying a peak weekly viral coefficient K ≈ 1.24.

When your viral coefficient is that high, channel selection becomes irrelevant. Post on Product Hunt? Viral. Tweet about it? Viral. Show up at an event? The crowd goes wild.

It's not that Lovable mastered these 12 channels in order to grow. It's that their product is so shareable, user-friendly, visually stunning, and so "holy sh*t look what I made in minutes" that any exposure becomes a growth loop.

Mo’ Money. No Problems.

And if you're still tempted to mimic their strategy, gut check whether you have as much cash on-hand to fuel your growth.

Unlike most startups, Lovable never had to worry about scraping together cash, due to a sizable $7.5M pre-seed followed by an explosion of early revenue traction. Lovable launched on November 21st 2024. By February 2025 (3 months after launch), they had:

• Acquired 30,000 paying customers
• Hit $17M ARR
• Raised a $15M pre-Series A
• Spent $2M to get there (mentioned in an X post from the CEO, Anton Osika)

While Osika doesn’t mention exactly how they spent the $2M, even if only 20% of that $2M went to marketing, that's still $133,000/mo in marketing spend out of the gate. Most startups are trying to stretch out $10k over three months of Meta ads. 🥲

When you have that kind of capital, you can afford to have a presence everywhere at once. You can hire Discord community managers, video content editors, SEO writers, and still have budget left for paid ads.

Why Your Bicycle Can't Handle a Jet Engine

Lovable rides a jet engine fueled by three things:

1. Insane product-market fit that creates outputs people compulsively share
2. Early revenue and venture funding that enables simultaneous channel execution
3. Perfect timing in the AI gold rush where "I built this with AI" still grabs eyeballs

There’s a good chance your startup doesn’t have all of these to the degree Lovable does. Which means copying their channel playbook isn’t particularly useful.

The Actual Takeaways Here

Strip away the hype and oversimplification, and here's what matters:

• Build virality into your product: To the extent your product/service supports it, ask yourself, "Is my product something people actually want to show others? Can we build in network effect dynamics?"
• Be realistic about resources: If you can’t spend $100K+/month on growth, you probably can’t fund a breakneck 12-channel growth strategy.
• Recognize survivorship bias: Remember, for every Lovable, there are 1,000 startups that tried to "be everywhere" and burned out.
• Learn from Lovables individual channel strategies: None of this is meant to knock Lovable. They are clearly very talented marketers and you can still learn from them. Building in public on X might be a great strategy for you.

The Channel Focus Reality Check

In the incredibly likely event your product doesn't have Lovable's inherent virality, here's your channel playbook:

1. Test 3-5 channels with small budgets ($3-5K each)
2. Identify the one with the best unit economics
3. Scale that channel until you hit diminishing returns
4. Only then consider adding channel #2

It’s not as sexy, but a steady, sustainable, scalable growth engine is how the majority of successful startups actually grow (it's also the key focus of the Demand Curve Growth Program).

Bottom Line: Product Over Everything

Lovable's story is seductive (and potentially dangerous) because it suggests you can brute force your way to product-market fit. “Just be everywhere all the time! Master ALL the channels! Growth will surely follow!”

That's bass-ackwards. Lovable earned the right to be everywhere, because their product was everywhere-worthy. They mastered all channels because every channel bowed down to it.

Your job isn't to copy Lovable's channel tactics. It's to build something users love and share as much as Lovable. Until then, a focused channel strategy likely beats cosplaying as a hypergrowth startup.

​Gil Templeton​
Demand Curve Staff Writer

​Kevin DePopas​
​Demand Curve Chief Growth Officer

Quiznos (2004): The Scary Sub Spongmonkeys

The Situation: Quiznos was getting their lunch eaten by Subway, which had a huge marketing budget and was building momentum through brand recognition, value messaging, and healthy offerings (yes, the Jared Fogle ads). Quiznos needed a breakout campaign to make them relevant and top-of-mind, especially with the younger crowd.

The Goal: Stand out in a crowded fast food market by being weird and irreverent, targeting younger, internet-savvy customers in the early viral video era.

The Rebrand: Quiznos launched the infamous national ad campaign featuring the “Spongmonkeys,” aka the bizarre, rodents with floating heads and screeching voices.

The Reception: The ads were plenty memorable, but deeply off-putting. The original Spongmonkeys were born from a viral Flash animation video, but their jump to mainstream TV was jarring for most Americans. Many were grossed out and/or creeped out, but most importantly, the campaign didn’t communicate anything meaningful.

Despite high ad spend, Quiznos lost market share and momentum as Subway doubled down on clear messaging around value and freshness. They emerged from Chapter 11 bankruptcy restructuring in 2014. Today, there are fewer than 200 Quiznos locations, compared to about 4,700 at their peak. Compare that to Subway’s 37,000 global locations. Of course, you can’t pin it all on one bad brand move, but the campaign might’ve taken Quiznos from “toasty” to “toast.”

The Takeaway: It’s okay to be weird, as long as you have a good reason for it. Being memorable doesn’t matter if people don’t remember what you’re selling (or when your food becomes associated with something kinda repulsive). Wackiness and silliness can’t carry your positioning if your core value prop isn’t clear.

Jaguar (2024): The Eclectic Electric U-Turn

The Situation: Jaguar had seen seven straight years of declining sales and was lagging behind luxury competitors in the EV arms race. With growing regulatory pressure on gas-guzzlers in Europe and a change in preference toward tech-forward EVs, Jaguar desperately hit the hardest of resets.

The Goal: Boldly recast Jaguar as a premium EV player and reposition the brand against Tesla and Porsche instead of leaning on heritage.

The Rebrand: A shocking repositioning of Jaguar into a minimalist EV-only brand with all-new type and colors, flattened logos, and a nebulous high-art ad that went viral for the wrong reasons.​

The Reception: Like a bad car wreck, this gave people major whiplash. Fans (and pretty much everyone else on the planet) reacted viscerally, noting how the classic allure of the heritage brand was completely gone. People were confused by the vague “Copy Nothing” slam-poetry and enraged that the ad didn’t even show a car.

While sales had been declining for years, only 49 Jaguars were purchased across Europe in April 2025 (yes, 49 cars across continental Europe). Compare that to 1,961 cars in April 2024, and that’s a 97.5% drop in YOY sales. Mind-boggling for a storied hundred-year-old company.

The Takeaway: Jaguar absolutely needed to make a bold change. But instead of ushering the brand into the EV age, they came across as confusing, vacant, and weird for weird’s sake. They’d likely be better off if they made a more focused shift that combined their glorious heritage with today’s EV tech (and still offered a fuel-burner or two as a safety net for now).

Tropicana (2009): Grasping at Straws

The Situation: Minimalism and clean design were becoming the dominant aesthetic in CPG, as brands like Honest Tea and Naked Juice gained market share. Classic orange juice was facing hipper, healthier competition, and the legacy brand felt like they needed to make a shift.

The Goal: Tropicana wanted to modernize its image to signal purity and healthiness, appealing to a younger group of health-conscious shoppers.

The Rebrand: A total packaging overhaul that replaced the iconic orange-with-a-straw for a minimalist glass of juice and sterile sans-serif type.

The Reception: Customers couldn’t find it. The new look removed about every distinctive brand asset that made Tropicana recognizable and iconic. Within 60 days, sales had dropped by 20% (a loss of over $30 million). Needless to say, the old packaging made a quick comeback.

Tropicana sales saw a sharp rebound after reverting to the previous look, but it still didn’t reach previous highs. It’s likely that sixty days was enough time for consumer habits to shift permanently, and the reversion could have also signaled a somewhat-stale step backward, when Tropicana had a chance to evolve more intentionally from the failed effort.

The Takeaway: Sometimes recognition is better than reinvention. Mega-distinctive assets (like the red and white spiral straw in the orange) are strong visual cues for consumers to quickly identify at-shelf. So sometimes it’s best to gently update them, not ditch them altogether. When a premium, legacy brand looks more like the everyday store brand, consumers will either have trouble finding it, or they’ll default to the cheaper option and move on.

HBO Max → Max (2023): Rewinding Brand Equity

The Situation: Warner Bros​. and Discovery had just merged, and they wanted to consolidate media assets under one roof to compete with Netflix and Disney+. There was internal pressure to streamline the brand and create a name that could stand for more than prestige TV.

The Goal: Create a platform that housed all content under one neutral umbrella. “Max” was supposed to be simple and expansive, allowing it to flex to select, new Discovery offerings.

The Rebrand: HBO Max (originally HBO GO) rebranded to “Max,” as part of the consolidation strategy.

The Reception: The name lost the strongest asset HBO had: its name. “HBO” stood for premium TV, while “Max” sounded like a budget broadband provider. Because of consumer confusion, the app tanked in App Store rankings, and HBO’s reputation got watered down by association with reality TV and clutter.

The Takeaway: Play to your strengths. If one part of your brand holds more equity than the rest of your offerings combined, build on that. HBO was the standard-bearer in award-winning, premium entertainment for decades, and they should have put their valuable name on a pedestal. After the confusion, HBO wised up and reverted back to HBO Max after several iterations of Max. A “full-circle” moment for the ages.

JCPenney (2011): The Anti-Sale Strategy

The Situation: JCPenney was struggling for relevance after the recession. Big-box and specialty retailers like Target, Kohl’s, and fast fashion brands were stealing market share, and JCPenny’s coupon-driven model suddenly felt outdated. Fresh off his success as the retail chief at Apple, the board brought in Ron Johnson as the new CEO to lead the reinvention.

The Goal: Reposition JCPenney as a modern, stylish department store that didn’t rely on gimmicky sales. The idea was to attract younger, higher-income shoppers and compete with trendy retailers.

The Rebrand: Ron Johnson led a full-scale rebrand from the top down. In addition to overhauling the brand’s look (including a square in the logo to match the new “fair and square” pricing approach, get it?) he eliminated sales, coupons, and markdowns in favor of an everyday pricing model.

The Reception: It turns out the traditional JCPenney shopper was a deal-hunter who loved coupons and doorbuster sales more than pricing transparency. The rebrand was seen as unearned and untrue to their crowd’s sensibilities.

In one year, JCPenney lost over $4 billion in revenue as foot traffic plummeted. Johnson was fired in 2013, and the brand walked back most of the changes. But they still experienced a slow, decade-long slide until filing for bankruptcy in 2020. Where’s JCPenny today? It looks like they just offloaded about 20% of their locations to a PE firm.

The Takeaway: Don’t rebrand for the customer you wish you had. Rebrand for the one you’ve earned, and reap the halo-effect along the way. Drastically changing your business strategy without accurate insights is a gamble to say the least. A rebrand should evolve your positioning without erasing what people were actually showing up for.

So When Should You Rebrand?

If your business is in one of the situations below, it might be time to consider making one. If not, you should probably fight the urge for now.

• Your positioning has shifted: You’ve evolved beyond your original product or audience, and your current brand doesn’t accurately reflect what you do best.
• You’re being mistaken for someone else: If customers confuse you with a competitor or unrelated brand, you need to stand out more clearly.
• You’re targeting a new audience segment: A new prospective target may require a fresh voice, look, or story to resonate. But make sure it doesn’t turn your loyalists off, RE: JCPenney.
• You’ve outgrown your humble beginnings: Maybe you didn’t have the time or budget to invest in quality branding when you started your business. If you’ve received a new round of funding or can otherwise afford a needed brand update, a fresh coat of paint might be the professional sheen you need.
• You’re entering a new stage of growth: Important opportunities like expanding to new markets or launching a flagship product can be the right moment to level up.

Find Clarity, Then Use Creativity

I hope these cautionary tales haven’t scared you away from making an important brand update if you need to.

The takeaway here isn’t “Rebrands are dangerous.”

The takeaway is: Rebrands can be multipliers, but they need to be executed thoughtfully.

There’s a reason just about every company undergoes a rebrand or two throughout the years. Offerings, audiences, opportunities…they can all change, and a brand needs to make strategic updates in order to keep its footing and keep climbing.

Have any good stories or lessons from your company’s rebrand? Reply with a message, we’d love to hear about it.

​Gil Templeton​
Demand Curve Staff Writer

The AI Productivity Paradox

This week, I analyzed feedback from 800+ companies explaining why they joined our Growth Program. One founder wrote:

"All our growth has come magically and almost nothing we did seems to work."

Another said they were running:

"Organic, App Store Search Ads, Google Ads, Facebook Ads, Affiliate Marketing, YouTube, Snapchat..." but still struggling to scale.

This is the pattern I see everywhere now, amplified by AI tools.

Look, I've been there. When you're just starting a company, you inherently don't know what works. To find out, you need to test. And generally speaking, testing more gives you more chances to unlock a winner.

But there's a difference between systematic experimentation and spraying and praying at 10x speed.

Companies using AI to run 20 tests per month when they used to run 3 end up with a lot of shallow data but very few real deep learnings that inform how they can adapt their strategy and double down on what's working.

Not to mention, even if you can run 20 tests per month:

• Are you adequately budgeting those tests?
• Are you letting them run long enough?
• Are you documenting what you learned?
• Are you building on previous insights?

The answer is almost always no.

​Your Foundation Is Your Multiplier

Think about it this way, if you just got your driver's license, getting a Ferrari won't make you a good driver. It'll just make you more dangerous on the road. And if you're heading in the wrong direction, you're going to end up 100 miles off course, when if you rode a bike, you'd only end up a mile off course.

How I think about it:

• Strong fundamentals × AI = Compound growth
• Weak fundamentals × AI = Compound confusion

Here's what strong fundamentals actually look like. Make sure to have these in place before amplifying your growth efforts with AI.

1. Know Your 5 Fits (Not Just Product-Market Fit)

After working with hundreds of startups at our agency and thousands of startups through our Growth Program, we've identified 5 critical fits. We wrote a whole newsletter about this in May, but it's worth revisiting.

• Market-Product Fit: Your product actually works. People are pulling it out of your hands. They use it and tell friends.
  ​
• Market-Model Fit: Your pricing aligns with how your market buys. (One company we worked with was trying to sell $50K enterprise contracts through self-serve.)
  ​
• Market-Brand Fit: Your brand resonates with your specific audience (e.g., Stripe's technical excellence appeals to developers).
  ​
• Market-Channel Fit: You're where your customers actually make purchasing decisions (e.g., B2B SaaS on LinkedIn, not TikTok).
  ​
• Model-Channel Fit: Your unit economics work in your chosen channels (e.g., $10/month products can't afford $100+ CACs).

Miss any of these, and AI will enable you to spin your wheels faster than ever, until you run out of cash.

2. Implement a Minimally Viable Experimentation Framework

One Growth Program student told us their biggest challenge was...

"Knowing what's working/not working...and consequently, knowing where to focus."

When you're running a startup, it seems so appealing to have all your tests cleanly organized and meticulously tracked.

But like wasting time on worthless AI-fueled tests, overbuilding your experimentation framework can pull valuable time from running the actual experiments.

I can't tell you how much time I've wasted in Notion, Clickup, Asana, etc...

Even a minimum level of organization helps. What matters is learning intentionally to inform your strategy.

This is the difference between testing loops and learning loops:

• Testing loops ask: "Which version won?"
• Learning loops ask: "What did this teach us about our customer?"

You don't need a complex system. Create a simple Google Doc with these questions:

Ideating tests:

• What metric are we trying to improve?
• What are all our hypotheses for improving it? (List them all, even wild ones)
• What evidence or customer insight supports each hypothesis?

Prioritizing tests:

• Which test has the highest conviction based on customer data?
• Do we have enough traffic/users for a meaningful result?
• What's the effort vs. potential impact?

Planning tests:

• What exactly are we changing?
• What does success look like? (Define win criteria upfront)
• What's our budget/time limit?

Learning from tests:

• What happened? (Just the facts)
• Why did it happen? (Your best explanation)
• What's our next test based on this learning?

Not that you need it, but I'm giving you permission to literally do this in a Google Doc. The best system is the one you'll actually use.

Three well-designed experiments that you track beat 20 random (un-tracked) tests, every time.

3. Max Out What Works

Most early-stage startups abandon their channels too early.

I worked with a DTC company spending $6,000/month on ads. They had barely scratched the surface of their serviceable addressable market.

Their CAC was $40, and their unit economics could support up to $80 CAC before they would be unprofitable on every sale.

As they pushed spend above $6,000, their CAC crept up to $50, then $60. They panicked and pulled back.

But here's what they missed. Even at $60 CAC, they were still profitable on each sale. The real questions they should have asked:

• What's our payback period at the higher CAC?
  This is how long it takes to recoup your customer acquisition cost. If you spend $60 to acquire a customer, when do you get that $60 back? For subscription businesses, it might be 3-6 months. For this DTC company, it was immediate on first purchase.
  ​
• Can our cash position handle the float?
  "Float" is the money you need upfront before customers pay you back. Even if you're profitable long-term, you need enough cash to cover acquisition costs while waiting for revenue. A startup with $50K can't float thousands in ad spend if payback takes months.
  ​
• Is our contribution margin still healthy?
  This is what's left after subtracting all variable costs (product, shipping, transaction fees) from revenue. As long as this margin exceeds your CAC, you're adding profit with every sale.

For this company, all three answers were favorable. In other words, they were leaving cash on the table by pulling back ad spend.

Rising CAC isn't always bad. Only start testing new channels when your marginal CAC in the current channel exceeds what you could realistically achieve elsewhere.

Most startups never get there. They see CAC increase 20% and immediately jump to the next shiny channel, spreading themselves thin instead of maximizing what's already working.

Have you actually pushed your best channel to its limits? Or did you just get scared when the numbers changed?

The Bottom Line

Before you add another AI tool to your stack, test another channel, or pull the plug on an existing test, ask yourself:

1. When's the last time you went through the 5 Fits framework with your co-founder or a trusted advisor?
2. Do you have a simple, systematic way to document learnings from tests?
3. Have you maxed out your best-performing channel?

Depending on your answers above, AI may actually be delaying your success.

Focus on your fundamentals first. Build real learning systems. Max out what's working.

Then, and only then, let AI amplify your efforts.

Kevin

​Kevin DePopas​
​Chief Growth Officer

This lesson focuses on lead marketing messages (your homepage, ad copy, pitch deck headlines, social content, etc.) Of course there are places where customers are seeking more technical or detailed info, but let’s focus on high-level copy today.

The “What” Trap shows up when your messaging answers questions such as:

• “What do we make?”
• “What industry are we disrupting?”
• “What features are we proud of?”
• “What’s our origin story?”

All fair questions internally. But externally, they produce messaging like:

• “We use clean, ethical ingredients.”
• “Scalable cloud infrastructure solutions”
• “Innovation is in our DNA.”
• “Meeting the highest industry standards.”

None of this is wrong per se, but it’s answering the wrong question. Because your customer isn’t asking “What do you do?” They’re asking “What’s in it for me?”

While this messaging might be technically accurate, it’s emotionally vacant.

Why Do So Many Make This Mistake?

Most founders and marketers don’t set out to write ineffective, self-centered copy. But when you’re so deep inside the business, it’s like trying to read your label from inside the jar. And it’s easy to default to what you know best: What you made. How you made it. Why it’s better.

That’s all valid stuff. But it’s not what gets strangers to stop scrolling or lean in.

You don’t win with more description or explanation. You win with more relevance.

The B.A.D. to B.E.S.T. Pivot

When messaging falls into The “What” Trap, it tends to be an ineffective mix of boastful, abstract, and dry. In other words, it’s just plain B.A.D.

In order to pivot to a more appealing message, we need to shift our point of view to create the B.E.S.T. message:

• Benefit-Led: Lead with what your customer gets, not what you made.
• Empathetic: Show how you understand their problem or aspiration.
• Story-Driven: Anchor the message in a moment or feeling they can relate to.
• Transformational: Focus on how their life can improve because of you.

As you can see, all of the B.E.S.T. lines on the right have flipped the focus to the customer. They use specificity, and they imply a transformation for the better.

For other useful exercises, check out the Copywriting Frameworks Cheatsheet featured in the Growth Program.

​

Tips for Making the Pivot

Speak to one person: You’re not shouting at a crowd through a megaphone, you’re showing one person what they stand to gain.

• Ex. “We provide 24/7 tech support.” → “You’ll never have to troubleshoot alone again.”

Speak like a real person: Use contractions, cut any fluff, and avoid incomplete sentences.

• Ex. “Innovating smarter workplace software solutions for you since 2005” → “You run the business. We’ll handle the boring stuff.”

Embrace directives/imperatives: The examples in the chart above use words like “feel,” “get,” and “wake up” to be actionable and paint a picture of what life could look like with the product or service.

• Ex. “A platform designed for fast-growing startups” → “Scale smarter. Sleep better.”

Start with your customer’s “after” state: Stop selling features and start selling transformation. What does your customer want to achieve or get rid of?

• Ex. “Designed with posture-correcting lumbar support” → “Work a twelve-hour day without a sore back.”

Give it the “So what?” test: Don’t expect a stranger to care unless it’s immediately clear what your product/service can do to improve their emotional state.

• Ex. “Delivered in 2–3 business days” → “Order today. Get it by the weekend.”

Putting It All Together: Three Unique Examples

Let's transform real messaging from B.A.D. to B.E.S.T. by working with three examples representing different businesses: a B2B software tool, a service marketplace, and a consumer product.

Example 1: B2B Software (Analytics Platform)

Step 1: Start with the bad example "Advanced AI-powered analytics with real-time dashboard capabilities"

Step 2: Identify the core benefit Marketers can finally understand which campaigns actually drive revenue.

Step 3: Try a version for each B.E.S.T. tenet

• Benefit: See which campaigns make money (not just clicks)
• Empathy: "I'm tired of explaining why our CTR is high but sales are flat"
• Story: Your CEO can finally stop questioning your ad spend
• Transformation: From guessing what works to knowing what pays

Step 4: Draft new lines from the above insights

• Stop guessing which ads actually make money.
• See your real ROI, minus all the WTF.
• Turn marketing data into a narrative your CEO actually understands.
• Go from ‘CTR is high’ to ‘Revenue is higher.’

Example 2: Service (Freelance Marketplace)

Step 1: Start with the bad example "Vetted network of 10,000+ professional freelancers"

Step 2: Identify the core benefit Hiring help doesn't have to eat up your whole week.

Step 3: Try a version for each B.E.S.T. tenet

• Benefit: Get help without the hiring time suck
• Empathy: "I need help NOW but don't have 3 weeks to find someone"
• Story: You posted at 9am and had three great options by lunch
• Transformation: From drowning in work to actually moving forward

Step 4: Draft new lines from the above insights

• Get unstuck without the 47-step hiring process.
• Find help faster than writing another job post.
• Post your project at breakfast. Review candidates by lunch.
• Leave the hiring circus behind for good.

Example 3: Consumer Product (Sleep App)

Step 1: Start with the bad example "Science-based sleep optimization technology"

Step 2: Identify the core benefit Selling the feeling of waking up well-rested.

Step 3: Try a version for each B.E.S.T. tenet

• Benefit: Wake up feeling like a functional human
• Empathy: "I'm so tired of being tired all the time"
• Story: You didn't need three alarms for the first time in weeks
• Transformation: From zombie mode to morning person

Step 4: Draft new lines from the above insights

• Wake up feeling human, not hungover.
• Sleep through the night without the 3am spiral.
• Stop pretending coffee is a personality trait.
• How to become an annoyingly cheerful morning person

Now it’s time to try this exercise for your business. Start with any lead marketing messages that don’t clearly answer “What’s in it for me?” for your customers, and walk through the steps above. After you’ve got a worthy replacement line, go live and test it to see how it improves your key metrics.

Keep Your Eye on the Ball

Now more than ever, it’s hard to stay focused. With so many channels to manage, AI outputs to choose from, content to create, and thought leaders zinging hot takes, it’s easy to lose the plot when it comes to creating consistent, compelling messaging.

But messaging clarity is still one of the biggest levers you can pull, especially if you can zoom out far enough to see your business through the eyes of your target audience.

If you run your copy through the “What’s in it for me?” lens, and resist the urge to simply describe what you do, you’ll be ahead of most competitors stuck in “me” mode.

The more you get into this habit, the more you’ll turn marketing goop into messaging that works hard.

​Gil Templeton​
Demand Curve Staff Writer

Step 1: Warm Up With Name Archetypes

To begin your naming project, let’s start by establishing some common categories of names. You’ll naturally gravitate toward some buckets over others, but keep your ideation broad at first. Buckets you don't initially gravitate towards might end up leading you somewhere.

• Descriptive: These names tell you exactly what the company does. Clear, literal, and SEO-friendly, but not too unique or aspirational. Ex. General Motors, The Weather Channel​
• Abstract: Made-up words that have virtually no meaning or connotation, but can come to mean something over time. Often catchy and distinct. Ex. Xerox, Hulu, Dasani​
• Evocative: Names that hint at a larger story, emotion, or cultural idea, inviting interpretation and storytelling. Ex. Robinhood, Patagonia​
• Functional-Fresh: Names that reference what the product does, with a playful or metaphorical twist. Fun and somewhat intuitive. Ex. Swiffer, Pinterest​
• Founder’s Name: Using the founder’s name or a variation to signal legacy, craft, or prestige. Common for food & bev, DTC, and fashion. Ex. Ben & Jerry’s, Chanel​
• Compound: Portmanteaus formed by two words smashed together to create something new and memorable, great at signaling multiple ideas. Ex. Facebook, YouTube​

Keep in mind, this list of categories isn't exhaustive, and there’s certainly no right or wrong place to begin. This is just a good way to ground ourselves and get the ideas flowing.

Exercise: Look at 8–10 brands you love, and see if you can put each of their names into one of the categories above. Some might fit into a couple categories, and some might fall into less common categories not listed here.

Step 2: Play the Numbers Game

Like most creative exercises, naming is a numbers game, where a higher quantity naturally leads to higher quality. Remember, Da Vinci had hundreds of projects that were unsuccessful, and only a couple that endured.

For example, a famed study (retold in Art & Fear) split a pottery class into two groups: one graded solely on sheer quantity of their pottery output, the other on creating a single perfect pot. Each time, the quantity group “accidentally” produced the best pots, simply by throwing more clay and learning from each attempt.

In this spirit, try to riff with a partner or two in this early phase. Create a fun and open space where there are no bad ideas (even though 95+% of them will certainly be bad ideas). Like improv comedy, it’s all about “Yes, and…” at this stage.

Write down anything that comes to mind and don’t linger. Keep going. And going. And going.

And if you don’t have a partner, keep your keyboard clicking, your pen moving (or your voice dictating into AI). Inertia is your friend. You should be aiming for a couple hundred names.

Exercise: Generate 50+ names for each archetype category, for a total of 300-500 names. Store these in a Google Sheet to review later. This process can go faster than you think, especially with AI.

Routes and Resources to Riff With

While you’re in the “quantity” phase, here are some tools or prompts that can help you iterate.

• Embrace Latin roots: Dig into relevant root words (e.g. port, aqua, vis, dict) then combine or augment them in different ways. These can be somewhat of a cheat code, clueing people in on what your product might do or solve (even if it’s a 100% made up word).
• Translate key words in other languages: Sometimes hearing a boring English word in another language can add some flair or help you unlock a new word altogether.
• Use word finder tools: I always have a Litscape tab open during a naming project. The “words containing sequence” tool helps you find all words that contain your chosen sequence of letters.
• Common idioms and sayings: Let’s say you’re naming a home improvement business. Look up any and all idioms having to do with houses, and you might find part of a phrase or saying that brings it all home.
• Portmanteaus via AI: ChatGPT is pretty good at understanding the assignment when it comes to two-part word mashups. Keep your prompt simple, instructing it to combine two relevant themes or motifs into non-existent words that retain typical phonetic structures.
• Tap into the senses: Think about what your product or service looks, feels, sounds, or even tastes like, then brainstorm around those qualities. Sensory words often carry implicit emotion, which helps your name do more with less.
• Map out your metaphors: Build a mind map of symbolic themes associated with your brand (e.g. growth = gardens, rocket ships, compounding interest). These detours can lead to surprising but resonant name ideas.

Step 3: Thin the Word Herd

Once you’ve spent enough time amassing a huge batch of names in your Google Sheet (hopefully a couple hundred), it’s time to trim the list down to the cream of the crop.

First, go back through your master list and highlight the names that feel like they have the most potential.

Maybe there were a couple you fell in love with when you wrote them down, or maybe fresh eyes give you a newfound appreciation for names that didn’t trip your trigger initially.

There’s no hard and fast rule here — or anywhere in this meandering process for that matter — but I’d aim for a batch of your best 30+ names at this point.

Exercise: Narrow down to your top 30 or so names. Look for ones that: (1) made you smile when you wrote them, (2) feel fresh with new eyes, (3) could work across multiple products, (4) you'd feel proud to tell your mom about.

Step 4: The Heartbreaker, Check Availability

Up until now, we’ve been living in a naming fantasy land, but it’s time to face reality. Get ready to say goodbye to the majority of the selected names you’ve fallen in love with, because most of them will be unavailable for you to use IRL (in real life). Here’s how you can check for viability.

• Give it a Google: The quickest way to see if a brand with a name like yours exists (especially within your category) is to Google it. If there’s a brand with the same name in an unrelated industry, you’re usually safe, as long as it wouldn’t be confusing to a consumer. This is why Delta Airlines and Delta Faucets can coexist peacefully.
• Do a trademark search: Ah, good ol’ government websites. Use the US Patent & Trademark Office TESS tool to check whether your name is trademarked by someone else already. You can often see who owns the trademark in case you wanted to do further research or reach out directly.
• Check for URL availability: I use GoDaddy.com to see if my name’s “.com” version is available, and if not, I see which other options might fit the bill. The closer you can get to “brandname.com” the better, usually. This is more of a consideration than a black-and-white decision — but if an established company is already using your name, owns the best URL, and has a high SEO ranking for your name, is that an uphill battle worth fighting?

If the .com URL is already taken for a name you love, try these prefixes: get-, hey-, try-, use-. Or try -app, -co, -hq as suffixes. The D2C healthcare brand Hims launched in 2017 under the domain Forhims.com before they could acquire the cleaner Hims.com domain in 2020.

• Salvaging favorites: You might have already listed some existing names with funky or off-kilter spelling (e.g. Lyft or Tumblr), but now can be a time to push words into more unique territory to make them distinct from competitors or established brands in other industries, especially if there may be some confusion.
  • Try dropping a letter (“Quick” becomes “Quik”)
  • Try swapping letters with similar sounds (“Light” becomes “Lyte”)
  • Try adding extra letters (“Drop” becomes “Dropp”)

Misspellings may have worked for Flickr in 2004, but proceed with caution. Every dropped vowel or swapped consonant adds friction, at least at first. People will generally type the 'correct' spelling first, potentially sending traffic to competitors. Only do this if your name is worth the education tax (and the obligatory investor eyeroll).

• Check Your Domain's History: Even if a domain is available, that doesn’t guarantee a clean history. A close friend of mine picked what seemed like the perfect URL with his his ideal ".com" address for a cheap price. Months later, he learned his emails were going to spam folders because the domain was an adult site years prior. It was still blacklisted, and he had to rebrand the whole company. Sigh.

While it's great to sound relevant and current, leaning into the major trends can sometimes leave you lost in the noise. Take a look below at the exponential boom of names ending in "-ify" and how they start to blend together after a while.

Step 5: End With the Gut-Checklist

After checking the availability of 30ish favorite names, you’ll likely end up with 5ish viable options that are legally safe and pass your initial vibe test.

If there’s a clear, legally viable winner in the group, great. Test that option against the following criteria below. If you have a couple contenders you feel good about, do the same to see if one rises above the rest.

If you need a sounding board or another set of eyes, ask a trusted partner or an expert in the space to test the name against the following questions. However, be cautious about opening this up to a group. It can be hard to achieve consensus or useful feedback through a larger audience.

Your Gut-Checklist:

• Can someone pronounce it correctly after reading it once?
• Can someone spell it correctly after hearing it once?
• Is it easy to remember?
• Does it feel like the future of your brand?
• Could it stretch to your future products or offerings?
• Would you be proud to wear it on a shirt?

The Bottom Line

Once you have the name that passes the test, sleep on it, say it out loud, imagine it in a headline or on packaging. A great brand name should make a strong first impression and leave a lasting one, too. So if yours can make customers smile, spark curiosity, or solve a problem for your business, don’t overthink it too hard.

Sleep on it, and if it still holds up tomorrow, congratulations. You might have just found a name that opens doors for your brand.

​Gil Templeton​
Demand Curve Staff Writer

Over the years, our newsletter sponsorship business has essentially run itself. Inbound inquiries flow through our website, occasional leads come from marketplace aggregators like Passionfroot and Paved, and revenue remains stable without much intervention.

With our heads down relaunching Growth Program 2.0, sponsorship revenue hadn't gotten much love from a growth standpoint.

During the second week of June, Justin (our CEO) and I mapped out Q3 priorities. We decided it was time for a quick 80/20 sprint to improve newsletter revenue and operations.

The goal: Double sponsorship revenue in 30 days (doing as little work as possible).

The challenge: We had contacts scattered across email threads, a basic Notion database acting as our "CRM," Sponsy (where we host our newsletter storefront), and no systematic approach to nurturing leads.

Here’s how we began to tackle the opportunity.

Understanding Our Options, Shrinking the Problem

I needed to understand what we were working with, so I mapped out the top ways to grow newsletter revenue:

After some thinking, we agreed that our fastest path to near-term revenue (without incurring too much operational overhead) was reconnecting with people who already know us…

• Previous Sponsors
• Warm Inquiries

The two categories comprised hundreds of potential deals just waiting for follow-up. Now that we had our priorities, we moved on to the next challenge, getting organized.

Getting Organized, Finding the Right Infrastructure

Before reaching out to these two buckets of prospects, I needed somewhere to house the data and manage the process.

After researching options, I landed on Attio. They'd sponsored our newsletter months back, and their AI-native CRM positioning and Notion-esque UI/UX intrigued me.

I reached out to see if they'd be comfortable with me documenting my experience using their tool.

They agreed and are sponsoring this issue, but everything you're about to read is my genuine experience using their tool. Attio has since become our main CRM.

The Implementation, Multiple Tools, One Workflow

Here's the workflow I built. It involves several tools working together, with Attio as the central hub.

Step 1: Data Extraction & Import

First, I pulled two lists:

• Previous sponsors from Sponsy (our sponsorship management tool).
• Inbound inquiries from Tally forms that pipe into Notion.

I uploaded these as CSVs into Attio, creating a unified deals “list”. While the CSVs only contained basic company info fields (company name, domain, and main contact email), Attio automatically enriched all the other data I needed (company descriptions, revenue estimates, employee counts, LinkedIn profile URLs, previous email conversations, etc.).

Step 2: Intelligent Filtering with AI Fields

Next, I didn't want to waste time nurturing prospects if they weren't a good fit to sponsor our newsletter. I decided all previous sponsors were worth reaching out to, but I needed to filter the larger list of inbound inquiries that never converted.

Attio lets you create “AI Attribute” fields that analyze structured and unstructured data using LLMs. I figured I could use a Research Agent attribute field to help me analyze and categorize inbound prospects based on fit.

So I created a "Sponsor Fit" field that evaluates each company based on two criteria:

1. Whether they target startups/marketers
2. Whether they have budget to support sponsorships

This cut my outreach list by 60%, focusing only on high-probability opportunities.

Note for builders: I was considering using a tool like Clay for filtering and data enrichment, but Attio handles similar enrichments internally without buying another tool or learning a new system. If Attio doesn't have an enrichment capability you need, you can fire workflows that integrate with Clay, n8n, or other tools. Simple enough for lightweight systems, but can scale if needed.

Step 3: Research for Personalization

Now that I had organized lists of previous sponsors and good-fit potential sponsors, it was time to plan the campaigns.

Data shows personalized emails can 2X+ response rates, so I wanted to tastefully incorporate personalization that proved we understand each company's product and how it relates to the Demand Curve audience.

To do this, I built another AI Research Agent Attribute field in Attio that:

• Visits each company's website
• Extracts their main product offering
• Summarizes key value props
• Formats it for email personalization

We’ll use this field later in our personalized email outreach, stick with me!

Step 4: Building Smart Campaigns

Time to put it all together. I built two campaigns in Attio:

• Campaign A (Previous Sponsors): Companies that have already sponsored our newsletter one or multiple times.
• Campaign B (Warm Inquiries): People who filled out our inbound form but didn't move forward AND met our “sponsor fit” threshold.

Step 5: Creating the Email Copy

Rather than crafting campaign copy from scratch, I wanted our emails to reflect how we actually talk about Demand Curve sponsorships.

I used ChatGPT o3 to build a scraper (via Google Apps Script) that pulled all my sales-related email conversations from the past two weeks into a Google Sheet. This captured how I handle objections, explain service offerings, answer questions, all the nuances of real conversations.

Vibe Coding Shoutout: I’m not a developer, so I had to vibe code this whole scraper. It took about 20 minutes.

I then exported the CSV of my sponsor sales conversations and fed it into a Claude 4.0 Opus Project, asking it to create simple 3-4 touch campaigns for each audience.

Pro tip: To improve your cold email quality, create a Claude Project and load it with training data from cold email experts. I loaded all of Lavender AI's cold emailing blog content into my project before feeding it my sales conversations.

Step 6: Personalizing with AI Content

Research from Lavender AI shows that including a personalized "P.S." at the end of emails can increase reply rates by 35%.

So I used Attio's AI Variable functionality within my email sequence to reference the “Product/Value Prop” field I created earlier, and use it to create personalized P.S. lines for each prospect:

"P.S. I think {Company Name}’s {AI Field: Product/Value Prop} would resonate with our audience."

Notice how I'm able to reference the AI Research Agent field I created earlier (Product/Value Prop) as a prompt input within Attio's AI email variable.

Results So Far

I ran the campaigns for 14 days and have continued any active sales conversations since. Here are the preliminary results (as of 7/15):

• 32% campaign reply rate (industry average is 8-10%)
• 24 active deals initiated from initial campaigns
• 4 package deals closed so far
• 9 deals active (still in conversation)

Want to join the mix for Q3/Q4 sponsorships? Email me. 😉

What's working well:

• AI enrichment saved hours of manual research.
• The AI variable within email templates (and it's ability to reference other AI fields as prompt inputs) is a powerful feature I haven’t seen in many other email tools.
• Everything lives in one place, Attio acts as my hub, consolidates sheets and Notion into a single source of truth.
• Attio’s Call Intelligence meeting assistant joins my calls and captures notes/follow-up items (I didn’t even realize this was a feature when I signed up, but I’m liking it).
• As an avid Notion user (and a sucker for good design), I appreciate the thoughtfulness of Attio's UI/UX.

Looking ahead: I'm excited to see how Attio continues developing agentic capabilities. Similar to how Attio removes the need for Clay for lightweight enrichment, with further development, it could eliminate the need for n8n for AI automation use cases.

I'd also love if Attio's AI fields allowed connecting custom LLMs for more flexibility in what models run on the backend, getting closer to Clay's customization options.

The Consolidation Potential

As I built the workflow above, it was hard to ignore that Attio could potentially replace multiple tools in our stack.

• CRM: If you're using Notion as a makeshift CRM (like we were), Attio can obviously replace that.
• Data Enrichment: If you're contemplating Clay for enrichment, I’d test out Attio first to save yourself another subscription.
• Meeting Recordings: Paying for meeting recording tools? Attio can likely replace these.
• Email Sequences: Attio's built-in email automation can potentially save you yet another SaaS subscription. (Attio also has a pretty seamless integration with Mixmax that I’m playing with).

We haven't consolidated everything yet, but the potential is there. And for smaller teams, this could mean significant simplification and cost savings.

If You're Thinking About Modernizing Your Sales Stack

Attio genuinely surprised me. The AI features aren't an afterthought, they're front and center throughout the application. The interface is clean enough that our team actually uses it. And the potential for tool consolidation is real.

If you're like I was (cobbling together spreadsheets, losing track of conversations, missing follow-ups) it's worth exploring.

​Try Attio free for 14 days →​

No credit card required.

High-production video is no longer just for giants with million-dollar media budgets. AI has collapsed the cost, time, and overall hassle of video creation, giving lean teams the power to punch way above their weight. What used to take a quarter can now happen over a weekend, and the results can be just as effective when done right.

• You can now iterate and test video ad creative (not just static) without waiting on agencies, shoots, or post-production delays.
• Brand storytelling is back on the table for teams who couldn’t previously afford the polish required to make it feel legit.
• It’s easier than ever to stand out in noisy channels like TikTok and YouTube with content that looks like it came from a studio, not an iPhone.

What does traditional video production (sans AI) look like?

Obviously video production can be done at any budget, from person-talking-to-iPhone all the way up to a feature film. But let’s look at what a brand might need for a somewhat-polished 30-second pre-roll video ad with human talent:

There’s a crazy amount of expense and effort that goes into this process — especially when results may vary. And while having a high-production brand video can perform well, it might not “outperform” assets produced on way scrappier budgets.

The new economics of AI video production

Case Study: How the Kalshi video was made

Let’s take a look at what went into making the Kalshi ad referenced earlier. Again, this aired during the 2025 NBA finals. Here’s a great quote from PJ Accetturo, the self-proclaimed “AI filmmaker” who was hired to make the ad:

“It was aired on TV, alongside $400K+ 2-month-long productions, and this took me 2 days, costing a lot less. But most importantly, I got to stay in my underwear for the entire shoot.”

In PJ’s blog post about making the ad, he casually reveals his process. Basically, he:

• Writes a rough script
• Uses Gemini to convert it into a shot list
• Runs the prompt through Google Veo 3 on Flow​
• Selects the outputs that meet his standard/vision
• Then edits the sequence using a common video-editing software.

A couple days. About $2,000 in AI video credits. One talented dude working from home. Compare that to the headaches of typical video production, and the case becomes compelling quickly. In the same blog, Accetturo makes a prediction about where things might be headed:

“The future is small teams making viral, brand-adjacent content weekly, getting 80 to 90 percent of the results for way less.”

While the ad is chaotic and imperfect, it’s proof that companies can make broadcast ads (and lower-stakes videos) with AI tools instead of traditional production studios. This is a massive opportunity for emerging and challenger brands looking to steal attention from more established category players.

You can debate the quality of the ad (and point out that it clearly looks AI-generated), but you can’t debate the earned media coverage and economic efficiency of the spot. Just search “Kalshi Ad” on Google and you’ll see the splash of earned media attention the ad generated.

AI Video Showdown: Sora vs. Midjourney vs. Veo

Let’s break down three common video-generation platforms so you can understand which might be best for your style of video. Depending on your subject matter (ex. beautiful light-motion product shot vs. introducing a talking mascot) your choice of platform can make all the difference.

OpenAI Sora

Strengths: Sora excels at generating realistic, physics-aware scenes with cinematic lighting and fluid motion, all inside longer-form (up to 60 seconds) clips. Its deep integration with ChatGPT makes it perfect for prompt-driven storytelling.

Best for:

• Captivating product shots in vivid settings
• Mood pieces for lifestyle or mission-driven brands
• Explainers using metaphor-heavy visuals
• Preserving real details of a product throughout shots
• Creating environmental stills that you can later add motion to

Midjourney Video (V6.0+)

Strengths: Midjourney’s video output leans hyper-stylized, with dreamlike textures, bold motion, and painterly effects. It’s lightweight and faster than the rest, ideal for bold creative that doesn’t rely on realism.

Best for:

• Social-first, scroll-stopping visuals
• Brand identity loops for video intros, banners, and reels
• Abstract, dreamy, or hyperreal visuals
• Product mood reels (ex. luxury perfume ad in abstract fog)

Google Veo 3

Strengths: Veo 3 delivers polished, photorealistic footage with cinematic camera moves, sharp details, and high resolution, making it the most production-ready tool of the bunch. Best for realistic shots with people, and its frame-to-frame capability adds a useful layer of control.

Best for:

• Polished ad spots that mimic agency-level work
• B-roll libraries to elevate decks, ads, or site content
• Quick-cut trailers or brand intros
• Funny or absurd character-based scenes

Note: We know, there are other video generation platforms out there…Kling, Runway ML, Higgsfield, (and countless AI UGC tools). Each has their benefits and tradeoffs. Here’s a more comprehensive list.

Where do things go from here?

For brands and businesses looking to embrace AI-generated video, here are some informed predictions about the trends and changes we’ll see in the near future.

“Close enough” becomes enough

While AI video opens up tons of possibilities that aren’t feasible on traditional production budgets, it’s still hard to get it just right. For companies who can handle their product looking a little distorted at times or an unnatural gesture from a character, AI will scratch the video itch. For those seeking perfection or complete control, traditional production has the upper hand, for now.

Not a believer yet? Don’t forget how far video AI can progress in a single year.

Niche comedy social accounts

Whether it’s an Instagram account like @alexlexobx1 that leans into the shared experiences and inside jokes of a community like the NC Outer Banks, or a slew of political-leaning TikTok handles spoofing the other party’s apparent hypocrisy, absurd comedy is an easily repeatable, occasionally viral formula for AI video (and AI image) generation.

A numbers game

It’s becoming less about creating perfect pieces of art and more about creating as many assets as possible with the chance one or two in the batch will gain traction. Entrepreneurs and Vtubers like Bloo (who has 2.5M Youtube subscribers) are leveraging AI to create low-effort clips, sometimes up to 80 per day. While critics will call it classic “AI slop,” view counts and occasional virality are showing the potential of a volume-based video approach.

The bottom line

AI video still has its quirks, but you'd be wise to start testing because six months from now (let alone a year from now) your control over consistency and realism in AI video will likely be 10x what it is now.

The tools are ready. The gap between big budgets and bootstrapped teams just disappeared. So what are you waiting for?

Time to start shipping.

​Gil Templeton​
​Creative Director @ BrandBossHQ​
Demand Curve Guest Writer

P.S. Check out my portfolio if you're interested.

Since TikTok exploded in 2020, every major platform has shifted from follower-based to interest-based algorithms. Instagram, YouTube Shorts, and even LinkedIn have all adopted similar mechanics for content distribution.

The algorithm shows your content to a small test group. If the test group engages (quantified via watch time, shares, saves, etc.), the algorithm keeps expanding reach. If not, reach slows, then stops.

This means your follower count matters much less than it used to. Your first post can literally reach millions of users if it captures attention.

Having a solid follower count can certainly help. It's why my favorite Youtube channel, Veritasium, seems to pull 5M+ views in 24 hours, every time. The algo knows their content is top-notch, so it pushes it hard.

Enter the "Generalist Principle"

I first heard of this concept from author, Brendan Kane, in his podcast interview with Chris Do on The Futur. Brendan and his team have built content strategies for everyone from Taylor Swift to small, hyper-niche craftspeople. After analyzing thousands of viral posts, he noticed something counterintuitive.

The most successful "niche" creators don't actually create niche content. They take their expertise and package it so anyone can understand and enjoy it, while still delivering value to their core audience.

Think of it like this. A tax accountant could post the same piece of content, framed two different ways:

• "New IRS Rule 462.B Affects S-Corp Distributions."
• "The IRS Just Changed A Single Rule That Could Save You $10,000."

Same topic, but one version has a chance of attracting viewers who would never follow a tax accountant.

Let's Look at the Numbers

Say you're a B2B SaaS consultant creating content about enterprise software implementation.

Niche approach:
​The primary goal of your content is to educate people on the nuances of enterprise software implementation.

• Total addressable audience: 100,000 people
• Viral reach: 10% see your content
• Views: 10,000
• Viewers who are potential clients: 50%
• Potential clients reached: 5,000

Generalist approach:
​The primary goal of your content is humor, entertainment, or novelty, while subtlety educating on enterprise software implementation.

• Total addressable audience: 1,000,000 people
• Viral reach: 10% see your content
• Views: 100,000
• Viewers who are potential clients: 10%
• Potential clients reached: 10,000

Despite an 80% drop in the proportion of viewers who are potential clients (50% → 10%) with general content, your potential customer base still doubles thanks to the broader audience.

Three Examples Worth Studying

In his free e-book, The Guide To Going Viral, Brendan uses the following examples to highlight the generalist principle.

​Tanner Leatherstein makes handmade leather goods. Instead of turning his Instagram grid into a wall of undifferentiated product shots targeted at affluent buyers, he buys $500+ designer bags and tears them apart on camera.

His 'Is It Worth It?' series taps into a question a lot of people have wondered, are luxury goods worth the price? While dissecting each bag, he not only entertains the masses, he also builds trust with a large number of people who may consider buying a bag from him instead of Hermès.

​Dr. Julie Smith is a clinical psychologist. Instead of posting academic lectures about cognitive behavioral therapy techniques that only fellow therapists would understand, she uses everyday objects to visualize complex mental health concepts.

In one video, she fills a trash can with crumpled papers to represent emotional overwhelm, then slowly removes and folds each paper to show what therapy feels like. Through this format, she entertains millions who will probably never book a session, while demonstrating her expertise to a select few who might.

​Graham Stephan teaches personal finance. His biggest video (8.6M views) isn't titled "Understanding Compound Interest." It's "How I Bought a Tesla for $78/Month." Far more people are curious to know his trick vs. learning about a subject they already think they understand. The finance principles he teaches along the way feel like a bonus, not the main point of the video.

Our Own Mixed Results

I've been testing this myself on the Demand Curve LinkedIn. Most of our videos get between 1,000 and 5,000 views. Decent for B2B content (Right guys? We're doing great, right? 😅)

But one video hit 390,000 views. The topic? Celsius energy drinks.

The hook was simple:

"In 2017, Celsius was essentially nonexistent, but now they have 11% market share and they're worth $9B. So I found myself asking, how did they get so big so quickly?"

Here are some of the generalist principles that may have come into play on the Celsius video.

1. Celsius is a brand regular people recognize and have opinions about.
2. The visual showed Celsius cans immediately (first 2 seconds), confirming this was about something familiar.
3. The question "how did they grow so quickly?" interests marketers, CPG founders, and Celsius fans alike, not just energy drink operators.

Compared to a hook like "How energy drink companies can grow through retail partnerships," the hook I chose had a shot at appealing to a much broader audience.

A Brute Force Approach

One brute force way to test the generalist principle is starting with a hook that has nothing to do with your business, then bridging to your actual topic.

This concept is similar to the idea of basing your content on "validated outlier" formats and hooks. We cover this topic in-depth in Growth Program 2.0. Hop on the waitlist here.

Here's an example. This creator's videos regularly saw 1,200 to 10,000 views until he posted the video below (which reached 1.3M views & 68k likes).

The video starts with a viral meme hook, then transitions to showing the creator's AI workflow for optimizing landing page messaging. Yes, this technique is a bit cheeky, but his account reached 45k followers within 10 weeks of launching. Can't knock the results.

Note: The brute force approach still needs to be executed thoughtfully. The video above worked because the viral meme humorously bridges into a much drier (but still intriguing and valuable) AI workflow. If the juxtaposition wasn't funny, or if the workflow wasn't valuable, the video probably would have flopped.

We'll Be The Guinea Pig

We're running our own experiment next Tuesday (July 8th), testing the generalist hook format from above. The formula:

1. Start with a validated generalist viral hook (similar to the one above)
2. Build a bridge to a curiosity-inducing workflow (that adds value)
3. Demonstrate expertise on our actual topic throughout the video

I'll report back on whether it works or whether I look like an idiot for trying. Seriously though, check our LinkedIn on Tuesday to see this technique in a business context.

How to Use This Today

First, look at your last 10 posts. Count how many require insider knowledge to understand. If it's more than two, you're probably being too niche. Also, consistently low (and not improving) view counts are a red flag.

Second, take your next planned post and rewrite the first 1-3 lines a couple times (or a couple hundred using AI). Each version should pique the interest of someone outside your industry. Then pick the one that would even make your mom curious.

Third, remember that broader reach doesn't mean dumbing down your content. It means being smarter about how you package it.

The goal isn't to trick people into watching your content. We're simply trying to earn the attention of a wider audience, which allows us to deliver value to more of the people who matter to your business.

Have fun testing!

Kevin

P.S. The video we're testing on Tuesday opens with a sweaty, shirtless tech-bro surrounded by liquor bottles. Professional reputation on the line. Wish us luck.

Let's start with the math that changed how we think about growth.

Growth Loops, not Growth Hacks

Insight from Reforge.

Which would you choose:

• Initiative A: Gives you 500 new users this week but nothing afterward.
• Initiative B: Gives you 20 new users in week one, 22 in week two, etc (growing 10% WoW) for every week going forward.

Initiative B will take 14 weeks to reach 500 new users.

But after 1 year, you’ll have 28,208 new users and grow by ~2600 per week. By the end of year 2, you have 4,035,039 new users (assuming a constant 10% growth rate).

This is the general principle behind compounding Growth Loops:

In short, the output of a marketing initiative feeds back into the input. Examples:

Another classic example is ads:

1. You spend money to run ads
2. You profitably acquire new customers
3. You use said profit to acquire more customers. If you need help running ads, we’ve built an ad agency specifically designed for startups.

In short, your primary marketing efforts should not be one-off tactics. Instead, they should be initiatives that can compound. Here are examples that do not compound:

• Launching on Product Hunt: You get an influx of users. You… can’t launch on Product Hunt again.
• Timed-limited Promos: You get a big influx of customers and revenue. You can’t just run another promo.
• Press coverage: You get featured in Forbes. You get a big spike in traffic. It disappears a couple of days later. You can’t be featured all the time.

Compound growth sounds great. But how do you know which loops to build? This is where strategy comes in.

Create a real strategy, not just a list of goals & tactics

Insight from Mark Pollard.

Most companies' "strategies" are either purely:

Goals:

• Become relevant with Gen Z
• Increase sales by 30%

Tactics:

• Post on LinkedIn 5 times per week
• Create lead magnets

Mark (aka Strategy Friend) defines a strategy as "an informed opinion about how to win."

Your strategy is supposed to tell you exactly what your team needs to do to grow. Yet, according to Mark, most strategies look like this:

They're missing the key insight to the real cause of the problem and a strategy to help solve the problem. Instead, they just jump straight into tactics with no clear vision.

"Tactics are simply the activities that make a strategy happen."

Here are two examples of what a good strategy looks like:

We've covered the power of compounding growth. We understand how strategy drives tactics. Now let's simplify growth to its essence.

This mental model will help you shrink the big wide world of growth opportunities into four logical buckets.

The 4 high-level ways to drive growth

Insight from a great article from MKT1.

Fundamentally, there are only four high-level ways to drive growth.

This image from MKT1 summarizes it perfectly:

A startup can do a million things to grow (we’ve covered over 455 of them here), but given extremely limited resources, you should find the highest leverage place to apply pressure to grow now.

Understanding these four primary levers helps you prioritize. Let’s dive into each:

1. Get more $$$ from your current slice of pie

• Charge more money from existing customers (make sure to increase perceived value too).
• Sell more products to existing customers (upsell/cross-sell)
• For SaaS, increase revenue per customer by adding new features and tiers, increase the number of seats they use, or increase product usage.
• Reduce churn so revenue can grow over time. The SaaS Quick Ratio is a handy metric for determining whether your growth and churn are healthy.

2. Capture the same pie more efficiently

You’re always getting new customers, but you can do it better. You can generate more revenue with the same or less cost and effort.

There are really only two fundamental ways to do this:

• Increase conversion rates with better funnels (copy, landing pages, lead magnets, sales, etc).
• Lower acquisition costs with better creatives, targeting, lead quality, (and conversion rates ;0)

Note: Check our Growth Vault for 84+ tactics to increase conversions

3. Capture more of the same pie

You’re growing within the same market segment but can get MORE leads:

• Double down on what’s working, but always experiment with creative ideas.
• Watch out for diminishing returns (increasing acquisition costs), especially on ads, if you’ve been going after the same market for a while and keep increasing budgets. That’s especially true if it’s a niche market.
• If you’re steadily growing, don’t wait until you cap out before expanding the pie because it takes longer than you think.
• Set up a different growth engine (content or sales instead of ads)

Note: No matter how good you are, you will never get the whole pie, sorry!

4. Expand the pie (or test new pies entirely)

• Go after new markets/segments (industries, company sizes, geos, verticals).
  • If you’re very early stage, this is just trying to find product-market fit.
• Depending on the new segment, you can either use the same growth engine (ads) or you need to set up another one (i.e., outbound or content).
• Create new content, messaging, and funnels tailored to the new “pie”.
• Always run small tests before going all in. Make sure to prioritize your tests using the RICE/DRICE frameworks.
• Double down if you have similar or higher conversion rates with this new market or segment.

How to use it

Every few months, pick one of these to prioritize and go hard on it. What matters most will depend on your current circumstances (and likely stage). For example:

• A very early-stage company is either focusing hard on one market/segment or testing several to find product-market fit.
• A startup with PMF will likely want to improve conversion rates with well-optimized funnels, great onboarding, and strong retention.
• Then they'll want to focus on capturing more of the same pie by ramping up their current growth engine (ads) or setting up a second (outbound).
• Then they might want to get more from their current customers by charging more and upselling and cross-selling.
• Then, they might want to expand markets/segments as they reach saturation in their current ones.

If you want some support...

​Growth Program 2.0 takes these frameworks deeper with personalized growth paths, AI-powered feedback, and human coaching to help you implement and iterate.

Knowing frameworks is step one. Executing and adapting is where the real work lives. We’re here to support you along the way.

​Join Growth Program 2.0 Waitlist →

— Kevin and the Demand Curve Team

A lot of marketers get distracted trying to impress other marketers, but what they should really be doing is converting strangers into customers.

When Nike runs an abstract, artistic campaign, it works because everyone already knows what Nike does.

And Apple can show artistic lifestyle shots because their products are already familiar. These brands have earned the right to be creative through decades of clear messaging. They’ve already established what they do and why it matters.

When you're an unknown startup trying the same approach, you're essentially asking people to solve a puzzle while doom scrolling. No thank you.

Your job here is to educate and excite your prospects, not confuse them with fancy, abstract messaging.

You have about 0.5 seconds to communicate value before they scroll past, and you can only afford to be creative once you've built clear brand association with your specific outcome.

But why is this so hard for unknown startups to accept? The answer lies in basic psychology.

The Cognitive Load Problem

Psychologist George Miller discovered that humans can only process 5-7 pieces of information at the same time. And in low-consideration span environments, like social media, that number drops even lower.

This means that every "creative" element like clever wordplay, abstract imagery, multiple messages all add cognitive load.

So the formula is simple: more mental effort = less conversions.

Example of High Cognitive Load (Low Converting):

• Headline: "Connect With Prospects In Powerful New Ways"
• Subtext: "Revolutionary AI-powered sales ecosystem"
• Visual: Abstract geometric shapes
• Mental effort required: What does this do? Who is it for? How does it help me?

Here’s how you should rewrite it:

Example of Low Cognitive Load (High Converting):

• Headline: "Get 2x More Sales Calls Booked"
• Subtext: "AI writes your cold emails in 30 seconds"
• Visual: Simple email screenshot
• Mental effort required: None. The value instantly clicks in your mind.

Now the value is super clear. You save time writing emails, and get 2 times the amount of calls booked.

But cognitive load is step one, now let’s talk about step two: context. We’ll figure out exactly what headspace your audience is in when your ad pops up.

Context Is Everything: Matching Creative to Mindset

Before writing a single word, visualize where your prospect is when they see your ad. The more descriptive, the better.

Instagram/TikTok: Entertainment Mode

• Mindset: Mindlessly scrolling, chilling on the couch, TV on, baby is crying, and your cat is trying to scale the screen door again. Distractions are everywhere.
• Consideration span: 0.5-3 seconds for initial hook
• Creative approach: Bold, simple, outcome-focused
• What could work: "47 calls booked in 30 days" with calendar screenshot and numbers in a big font.

LinkedIn: Professional Break Mode

• Mindset: Quick break between meetings, stress-eating a protein bar, while looking to learn something to improve at your job.
• Consideration span: 2-5 seconds, but higher intent
• Creative approach: Professional but direct, focus on business outcomes and tutorials
• What could work: "Here's exactly how I booked 47 calls this last month" with a loom video attached explaining your process.

Facebook: Social Connection Mode

• Mindset: Checking on high school friends you haven't talked to in 10 years, getting distracted by your uncle's political rants, seeing that your mom shared a video of a guy making tiny pancakes. Your ad should feel like content a friend would actually share.
• Consideration span: 1-2 seconds, very low tolerance for promotion
• Creative approach: Native, conversational, problem-first
• What could work: "Anyone else struggling to get clients on calls? Found this approach that actually works" with casual selfie-style video, feels like a friend sharing a genuine discovery.

YouTube: Content Consumption Mode

• Mindset: You’re trying to figure out how to “Fix a Squeaky Door in 2 Minutes” and now you’re getting an ad about tax software. You’re annoyed, about to click on the skip button, but you might give it 5 seconds if it’s actually interesting.
• Consideration span: 5 seconds before skip option, slightly more patient than Instagram/TikTok.
• Creative approach: Story-driven, can be longer, but hook still critical
• What works: "This changed how I book clients" with personal story

Now that we understand how context shapes attention, let's get tactical. Here are the four pillars that separate high-converting creative from expensive failures.

The 4 Pillars of Anti-Creative Creative

Pillar 1: Outcome-First Messaging

Stop talking about your company. Start talking about their results.

The Transformation:

• Before: "We're the world's leading email marketing platform"
• After: "Send emails that actually get opened"

Lead with the outcome they want, not the process you provide.

More Examples:

• Before: "Advanced CRM with AI-powered analytics"
• After: "Never lose a lead again"
• Before: "Revolutionary fitness technology"
• After: "Lose 10 pounds in 30 days"
• Before: "Comprehensive project management solution"
• After: "Finish projects 2 weeks faster"

Pillar 2: Ruthless Simplicity

Every word in your creative should earn its place. If it doesn't directly contribute to the value proposition, cut it.

Meaningless Phrases to Eliminate:

• "World-class" (says nothing specific)
• "Revolutionary" (overused, meaningless)
• "Cutting-edge" (what does this actually mean?)
• "Industry-leading" (according to who?)

The Edit Test: Read your headline out loud. If you can remove a word without losing meaning, remove it.

Example Edit Process:

• Original: "Our revolutionary AI-powered platform helps busy startups streamline their daily workflow processes"
• Edit 1: "AI-powered platform that helps startups streamline workflows"
• Edit 2: "AI platform that streamlines startup workflows"
• Final: "Automate your daily tasks with AI"

Pillar 3: Problem-Solution Clarity

Your prospect should instantly understand three things:

1. What problem you solve
2. How you solve it
3. What they get as a result

Here’s a high-converting formula: "Get [Specific Outcome] with [Simple Method] in [Time Frame]"

Examples:

• "Get 100 qualified leads with AI-powered prospecting in 7 days"
• "Build a profitable newsletter with our content templates in 30 minutes"
• "Book 5x more sales calls with personalized video outreach in 10 minutes"

Pillar 4: Context Optimization

Like we talked about before, design your creative for the specific platform and mindset, not your brand guidelines.

• Instagram Version: Bold text overlay, clear benefit, swipe-friendly format
• LinkedIn Version: Professional screenshot, business outcome, comment-worthy angles
• Facebook Version: Conversational tone, problem-first approach, native feel
• YouTube Version: Story setup, clear payoff, skip-resistant hook

Your Anti-Creative Audit Cheatsheet

Run every ad creative through these questions:

Clarity Check:

• Can a 12-year-old understand what I'm offering?
• Is the main benefit in the first 5 words?
• Does the visual support or distract from the message?

Simplicity Test:

• Can I remove any words without losing meaning?
• Am I using industry jargon or clear language?
• Is there only one main message?

Context Alignment:

• Does this work for someone scrolling mindlessly?
• Am I respecting their current mindset on this platform?
• Is the cognitive load minimal?

Outcome Focus:

• Do I lead with customer outcome, not company features?
• Is the benefit specific and measurable?
• Would my ideal customer instantly see the value?

The Bottom Line

The most effective creative isn't creative at all, it's clear, direct, and outcome-focused.

Save the artistic expression for when you're Nike. Until then, master the art of boring clarity that converts strangers into customers.

— Joey and the Demand Curve Team

Think of your startup as a puzzle with five interlocking pieces. Miss one, and growth becomes much more difficult:

• Market-Product Fit: Do people desperately want what you’re building?
• Market-Model Fit: Can your market actually afford what you’re selling?
• Market-Brand Fit: Does your brand resonate with your target audience?
• Market-Channel Fit: Can you reach your market where they hang out?
• Model-Channel Fit: Does your pricing align with your acquisition costs?

*Bonus* Product-Channel Fit: Can someone understand your product's value in the time/format your channel provides?

Each fit is a potential failure point. But get all five (ideally, six) right, and you can unlock scalable, sustainable growth.

Market-Product Fit

Most people call this "product-market fit" or PMF.

Definition: People want your product so badly they’d be upset if you took it away.

The test: When Brian Chesky asked early Airbnb users how they’d feel if Airbnb disappeared, they said “devastated.” That’s market-product fit.

Signs you have it:

• Customers pull your product from you (vs. you pushing it)
• Word-of-mouth becomes your biggest growth channel
• People use your product despite bugs and missing features
• Retention curves flatten (people stick around)

Red flags you don’t:

• You’re constantly convincing people why they need your product
• High churn after trials or POCs
• “It’s nice, but…” is the most common feedback

What founders miss: “Nice to have” and “must have” are very different. If your market can easily live without you, you might not have market-product fit (or you’re just in a crowded space with lots of alternatives).

For early-stage founders, market-product fit is your north star. Without this fit, optimizing anything else is premature. Check out our growth program if you need helping nailing market-product fit.

Market-Model Fit

Definition: Your pricing matches both your market’s ability/willingness to pay and your growth ambitions.

The math:

• 1,000 customers × $100/year = $100K business (lifestyle).
• 1,000 customers × $100K/year = $100M business (venture-scale).

It's hard to build a billion-dollar business selling $10/month to SMBs, the math simply doesn’t work at scale.

If you have a small market size AND low average annual revenue per customer, that's a market-model fit issue (especially if your goal is to build a large company).

This seems like an obvious concept, but it's something startups often get wrong. That's likely because they think their market is bigger than it really is, and/or they think they'll be able to charge more than they really can.

This diagram from founder and investor Christoph Janz demonstrates our point. There's a tradeoff between the number of customers you need to acquire and the price you're able to charge.

Market-Brand Fit

Definition: Your brand instantly connects with your market’s identity and aspirations.

Here’s an example:

​Stripe, the payments infrastructure company, had to build trust to scale. Businesses are understandably cautious about who handles their money and customer payment data.

They crafted a brand that emphasizes security, reliability, and technical excellence. Their documentation, website design, and even their API are all highly crafted, communicating trustworthiness without saying a word.

If their brand was cluttered, overly casual, or inconsistent, they’d likely struggle to win trust from developers and finance teams.

Most founders treat branding as an afterthought, but your brand is often your first (and sometimes only) chance to connect with your market.

Like Stripe, your brand should immediately communicate fit with your market.

Market-Channel Fit

Definition: Your ideal customers naturally congregate where you’re trying to reach them.

The test: Ask 10 ideal customers: “Where do you spend your time online or in-person?" Their answers will point towards potential channels.

Combinations that work:

• B2B SaaS → LinkedIn (decision-makers discussing business)
• Gen Z fashion → TikTok (young people seeking trends)
• Developer tools → GitHub/X/Reddit (engineers sharing solutions)
• Enterprise software → Outbound sales (complex deals need human touch)

Combinations that fail:

• Senior healthcare → Snapchat (wrong demographic)
• DevTools → FM radio ads (engineers don’t discover tools there)
• Luxury goods → Groupon (destroys premium positioning)

Choosing channels based on cost or comfort rather than where customers actually hang out can be a costly mistake.

Model-Channel Fit

Definition: Your business model's unit economics align with your customer acquisition channel costs.

This determines which channels you can actually afford to use profitably. The more you charge, the more you can spend to acquire each customer.

A few rules of thumb:

Your model-channel fit can also determine fundraising needs.

For example, if you're bringing an enterprise SaaS tool to market with $100K ACV, expect to spend 15-30% of ACV to acquire customers ($15K-$30K CAC).

If you only raise a $100K friends-and-family round, you'll run out of capital after acquiring 3-7 customers. This might signal you need to raise significantly more to effectively bring the product to market.

Product-Channel Fit: The Bonus Consideration

Definition: Your product's complexity matches your channel's ability to communicate value.

Some products are too complex to explain in low-attention channels. Others are too simple to justify high-touch channels.

The communication test: Can someone understand your product's value in the time/format your channel provides?

Examples that work:

• Simple meditation app + TikTok ads = ✓ (15-second video can show the entire value prop)
• Enterprise security software + direct sales = ✓ (complex product gets dedicated explanation time)

Examples that fail:

• Enterprise security software + Instagram ads (only) = ✗ (impossible to explain compliance features while users scroll)
• Simple task app + 3-hour sales calls = ✗ (wastes everyone's time explaining obvious features)

Smart teams choose an appropriate set of channels that allow them to naturally convey the value of their product (and address objections) rather than forcing complex products through low-touch channels.

Your Next Steps

Audit Your Fits: This doesn’t have to be an academic exercise. Just talk with your co-founders, your team, or yourself, and rate each fit from 1-10. Be intellectually honest, and brainstorm the changes you need to make to improve your score.

Your growth potential is bottlenecked by your weakest score, not your strongest.

The testing hierarchy:

1. Validate Market-Product Fit first (nothing else matters without this)
2. Confirm Market-Model Fit second (can they afford it?)
3. Develop the others in parallel (they’re interdependent)

You can fake fits temporarily with capital. Discounts simulate market-model fit. Ads mask poor channel fit. But eventually, reality wins.

If you could only fix one fit in the next 90 days, which would create the biggest breakthrough?

That’s where you start. Not with your strongest fit, with your weakest.

If you liked this content, check out our growth program. It contains hundreds of in-depth modules just like this.

Most GPT-generated image ads are mediocre at best.

Yet on social media, everyone says, “I whipped up these high-converting ads with ChatGPT in half a minute.”

What they’re hiding is all the 12+ iterations they had to make, the edits they did in Photoshop, and that they very thoroughly prompted GPT to get a decent output.

Meanwhile, on LinkedIn:

“Just tell GPT to clone this ad with your branding—and boom—a high-quality ad.”

So I tried that. I said, “Recreate this ad but with my product and branding.”

The results were disappointing to say the least:

• Layouts that didn’t make sense
• Copy that reads like it was written by my grandpa on hallucinogens
• Warped product renders
• Fonts and colors that didn’t match my brand
• And zero grasp of why the ad worked in the first place

Here’s the ad I asked it to clone:

I like this feature point-out ad from Oats Overnight. It tells me the cost, calories, protein amount, and that others love it. Perfect.

Since it’s an Ecomm ad, I selected one of my recent favorite Ecomm brands, IM8, to make an ad for (I'm not affiliated; I just like their packaging).

I asked GPT to clone the ad but with my branding and product. I gave it a list of some value props and let it rip.

Recreate this ad but with im8health.com’s branding. Attached is the image of my product, and here are some value props to use:​

- 95% felt a noticeable boost in daily energy levels.- 85% experienced less bloating and improved digestion.- Only $2 per serving- One scoop. Once a day.- All-in-one wellness.- Superfoods, Greens, Fruits, Herbs.- Heart Health Support.- Joint and Muscle Health Support.- Hydra Electrolytes.

Here’s what I got:

That’s not what I was expecting.
​
The visual hierarchy isn’t great. The padding is atrocious.
​
It changed the product image and decided that “technology” is actually spelled “technotogy.”
​
It also got rid of the elements that I felt made the reference a great ad.

Here’s what I’ve observed: GPT isn't your creative director (yet). It's your caffeinated but clueless intern.

It needs constraints, structure, and direction. Without them, you get, well.. this.

I spent the last few weeks building a repeatable system that turns GPT into a rough-draft engine, one that gets you 95% of the way to a usable ad in a fraction of the time and cost of starting from scratch.

Here’s how it works:

Step 1: Create a JSON file of your brand

Most people give vague instructions in GPT, such as “Use our brand colors and fonts.” But GPT works exponentially better with structured data.

Instead, feed it a JSON file like this:

json
{
"brandName": "IM-8",
"colors": ["#A40000", "#E3D8CD", "#FFFFFF"],
"fonts": ["Playfair Display", "Inter"],
"valueProps": [
"Supports gut health",
"All-in-one daily greens",
"Backed by nutrition science"
],
"tone": "Scientific but approachable",
"targetAudience": "Health-conscious professionals, 30-45",
"callToAction": "Try risk-free for 30 days"
}

This gives GPT constraints and direction, which leads to better creative output.

But the neat part is you don’t need to be technical or know how to create a JSON file. Just tell ChatGPT everything you want included in the file and it’ll create for you.

What I do is feed it everything I want it to know, like brand guidelines, tone of voice, font style, look and feel, etc. I also take a full-page screenshot of my landing page for ChatGPT to extract things I didn’t think of. (Link to the screenshot tool: gofullpage.com)

Here’s the exact prompt I used:

You’re going to create a master JSON file of my brand. You will structure the file in such a way that I can easily feed it to you to reference when making image ads – so that you can apply my branding to the ad references I give you. I want you to take my fonts, branding, colors, value props etc and turn it into the ultimate JSON file.

Here’s what the JSON must include:

• brand_name: e.g., “IM-8 Daily Essentials”
• tagline: One-line brand positioning or hero line
• fonts:
  • headline_font: name or description
  • body_font: name or fallback option
• colors:
  • primary: hex code
  • secondary: hex code
  • background: hex code
  • accent: hex code
• value_props: High-impact claims or stats (e.g., “95% felt more energy”)
• functional_benefits: Tangible outcomes of using the product
• trust_signals: Endorsements, social proof, certifications
• key_ingredients or core_features: If the product is ingredient- or feature-driven
• tone_voice: A few adjectives that describe how the brand speaks (e.g., “confident, clinical, warm”)
• visual_branding_notes: Description of packaging aesthetics, logo placement, typical imagery (but not ad layouts)

[Insert any other specific brand guidelines that ChatGPT might not be able to extract from the landing page screenshot alone]

Attached is a full-page screenshot of my product landing page. Analyze it thoroughly and extract all relevant branding cues, layout patterns, and copywriting angles — including testimonials, claims, imagery style, and benefits.

Now that I have a structured JSON file, I can go to the next step.

Step 2: Ask GPT how it would prompt itself

I don’t see enough people doing this.

Instead of trying to write the perfect prompt yourself, give GPT your brand JSON + a reference ad and ask:

“With this JSON and ad reference, how would you prompt yourself to recreate this ad, step-by-step, using your own best practices?”

GPT will return a specific, structured prompt. And it’s usually better than what I’d come up with anyways. Once I get the prompt I’ll read through it and modify it a bit to get exactly what I want.

You’ll get something like this:

Step 3: Feed it the right imagery

GPT image generation works best when you’re clear about what kind of image you want.

Use a reference ad and match its structure. For example:

• If the ad uses a product photo on a clean background, upload your product photo.
• If it uses lifestyle imagery, pull something from Unsplash or your own shoots.

The more visually aligned your input is, the better the output.

I used these images for my ad:

​

Step 4: Feed everything into ChatGPT to get a solid rough draft creative

Now I’ll give ChatGPT the prompt that it generated itself, my brand JSON file again, and the product images.

With a much better prompt and structured data for ChatGPT to use, I get a much better result:

Much better, but not perfect yet.

• There are still some misspellings.
• The fonts aren’t accurate.
• And some of the spacing could be improved.
• It also randomly decided to add “Total wellness. Simplified” to the bottle.

At this point you can continue to tweak it within GPT, but I wouldn’t recommend this. You tell it, “Change the headline to ‘Elite Daily Nutrition’” and it changes that but then also morphs your product or changes other copy.

Here’s what I would do instead:

Step 5: Polish the result with a junior designer

GPT gets you most of the way there. But the fine details still break as I pointed out above.

So I take the GPT draft and hand it off to a junior designer (Fiverr, GetAds, etc.) with a simple brief:

“Use this layout. Replace the fonts and imagery with the real assets. Keep everything else the same.”

By limiting the designer’s scope to just “make this look exactly like this, but with our real assets,” you avoid lengthy creative discussions, long briefs and feedback loops.

Here’s what the final output looks like:

Bonus step: Turn this into a project within ChatGPT

Create a ChatGPT project and give it the JSON file, your brand guidelines, and anything else you’d want it to know so you don’t have to do this every time. Then any time you want to create a new ad you can just do so within the project and it will already have all your brand details saved.

Final thoughts

AI isn’t replacing designers anytime soon. But it is changing the creative workflow from expensive exploration with long feedback loops to rapid iteration with focused human polish.

The teams winning with AI aren’t replacing their designers. They’re creating human-AI workflows that leverage the strengths of both.