My nameless, faceless channel case study

The Numbers

I anonymize this YouTube channel.

It's in a trendy, crowded niche. Sharing it publicly will likely enhance competition.

I'll still share my dashboard numbers:

A year ago, the video was released.

What I earned

I'll stop stalling. Here's a screenshot of my YouTube statistics page displaying Adsense profits.

YouTube Adsense made me ZERO dollars.

OMG!

How is this possible?

YouTube Adsense can't monetize my niche. This is typical in faceless niches like TikTok's rain videos. If they were started a while ago, I'm sure certain rain accounts are monetized, but not today.

I actually started a soothing sounds faceless YouTube channel. This was another account of mine.

I looped Pexels films for hours. No background music, just wind, rain, etc.

People could watch these videos to relax or get ready for bed. They're ideal for background noise and relaxation.

They're long-lasting, too. It's easy to make a lot from YouTube Adsense if you insert ads.

Anyway, I tried to monetize it and couldn’t. This was about a year ago. That’s why I doubt new accounts in this genre would be able to get approved for ads.

Back to my faceless channel with 68 million views.

I received nothing from YouTube Adsense, but I made money elsewhere.

Getting paid by the gods of affiliate marketing

Place links in the video and other videos on the channel to get money. Visitors that buy through your affiliate link earn you a commission.

This video earned many clicks on my affiliate links.

I linked to a couple of Amazon products, a YouTube creator tool, my kofi link, and my subscribe link.

Sponsorships

Brands pay you to include ads in your videos.

This video led to many sponsorships.

I've done dozens of sponsorship campaigns that paid $40 to $50 for an end screen to $450 for a preroll ad.

Last word

Overall, I made less than $3,000.

If I had time, I'd be more proactive with sponsorships. You can pitch brand sponsorships. This actually works.

I'd do that if I could rewind time.

I still can, but I think the reaction rate would be higher closer to the viral video's premiere date.

Are MVPs outdated and have no place in modern product culture?

Frank Robinson coined "MVP" in 2001. In the same year as the Agile Manifesto, the first Scrum experiment began. MVPs are old.

The concept was created to solve the waterfall problem at the time.

The market was still sour from the .com bubble. The tech industry needed a new approach. Product and Agile gained popularity because they weren't waterfall.

More than 20 years later, waterfall is dead as dead can be, but we are still talking about MVPs. Does that make sense?

What is an MVP?

Minimum viable product. You probably know that, so I'll be brief:

[…] The MVP fits your company and customer. It's big enough to cause adoption, satisfaction, and sales, but not bloated and risky. It's the product with the highest ROI/risk. […] — Frank Robinson, SyncDev

MVP is a complete product. It's not a prototype. It's your product's first iteration, which you'll improve. It must drive sales and be user-friendly.

At the MVP stage, you should know your product's core value, audience, and price. We are way deep into early adoption territory.

What about all the things that come before?

Modern product discovery

Eric Ries popularized the term with The Lean Startup in 2011. (Ries would work with the concept since 2008, but wide adoption came after the book was released).

Ries' definition of MVP was similar to Robinson's: "Test the market" before releasing anything. Ries never mentioned money, unlike Jobs. His MVP's goal was learning.

“Remove any feature, process, or effort that doesn't directly contribute to learning” — Eric Ries, The Lean Startup

Product has since become more about "what" to build than building it. What started as a learning tool is now a discovery discipline: fake doors, prototyping, lean inception, value proposition canvas, continuous interview, opportunity tree... These are cheap, effective learning tools.

Over time, companies realized that "maximum ROI divided by risk" started with discovery, not the MVP. MVPs are still considered discovery tools. What is the problem with that?

Time to Market vs Product Market Fit

Waterfall's Time to Market is its biggest flaw. Since projects are sliced horizontally rather than vertically, when there is nothing else to be done, it’s not because the product is ready, it’s because no one cares to buy it anymore.

MVPs were originally conceived as a way to cut corners and speed Time to Market by delivering more customer requests after they paid.

Original product development was waterfall-like.

Time to Market defines an optimal, specific window in which value should be delivered. It's impossible to predict how long or how often this window will be open.

Product Market Fit makes this window a "state." You don’t achieve Product Market Fit, you have it… and you may lose it.

Take, for example, Snapchat. They had a great time to market, but lost product-market fit later. They regained product-market fit in 2018 and have grown since.

An MVP couldn't handle this. What should Snapchat do? Launch Snapchat 2 and see what the market was expecting differently from the last time? MVPs are a snapshot in time that may be wrong in two weeks.

MVPs are mini-projects. Instead of spending a lot of time and money on waterfall, you spend less but are still unsure of the results.

MVPs aren't always wrong. When releasing your first product version, consider an MVP.

Minimum viable product became less of a thing on its own and more interchangeable with Alpha Release or V.1 release over time.

Modern discovery technics are more assertive and predictable than the MVP, but clarity comes only when you reach the market.

MVPs aren't the starting point, but they're the best way to validate your product concept.

This is for young entrepreneurs, especially in tech.

People give useless success advice on TikTok and Reddit. Early risers, bookworms, etc. Entrepreneurship courses. Work hard and hustle.

False. These aren't successful traits.

I mean, organization is good. As someone who founded several businesses and now works at a VC firm, I find these tips to be clichés.

Based on founding four successful businesses and working with other successful firms, here's my best actionable advice:

1. Choose a sector or a niche and become an expert in it.

This is more generic than my next tip, but it's a must-do that's often overlooked. Become an expert in the industry or niche you want to enter. Discover everything.

Buy (future) competitors' products. Understand consumers' pain points. Market-test. Target keyword combos. Learn technical details.

The most successful businesses I've worked with were all formed by 9-5 employees. They knew the industry's pain points. They started a business targeting these pain points.

2. Choose a niche or industry crossroads to target.

How do you choose an industry or niche? What if your industry is too competitive?

List your skills and hobbies. Randomness is fine. Find an intersection between two interests or skills.

Say you build websites well. You like cars.

Web design is a *very* competitive industry. Cars and web design?

Instead of web design, target car dealers and mechanics. Build a few fake demo auto mechanic websites, then cold call shops with poor websites. Verticalize.

I've noticed a pattern:

• Person works in a particular industry for a corporation.

• Person gains expertise in the relevant industry.

• Person quits their job and launches a small business to address a problem that their former employer was unwilling to address.

I originally posted this on Reddit and it seemed to have taken off so I decided to share it with you all.

Focus on the product. When someone buys from you, you convince them the product's value exceeds the price. It's not fair and favors the buyer.

Creating a superior product or service will win. Narrowing this helps you outcompete others.

You may be their only (lucky) option.

McMurtry Spéirling outperforms Tesla in speed and efficiency.

EVs were ridiculously slow for decades. However, the 2008 Tesla Roadster revealed that EVs might go extraordinarily fast. The Tesla Model S Plaid and Rimac Nevera are the fastest-accelerating road vehicles, despite combustion-engined road cars dominating the course. A little-known firm beat Tesla and Rimac in the 0-60 race, beat F1 vehicles on a circuit, and boasts a 350-mile driving range. The McMurtry Spéirling is completely insane.

Mat Watson of CarWow, a YouTube megastar, was recently handed a Spéirling and access to Silverstone Circuit (view video above). Mat ran a quarter-mile on Silverstone straight with former F1 driver Max Chilton. The little pocket-rocket automobile touched 100 mph in 2.7 seconds, completed the quarter mile in 7.97 seconds, and hit 0-60 in 1.4 seconds. When looking at autos quickly, 0-60 times can seem near. The Tesla Model S Plaid does 0-60 in 1.99 seconds, which is comparable to the Spéirling. Despite the meager statistics, the Spéirling is nearly 30% faster than Plaid!

My vintage VW Golf 1.4s has an 8.8-second 0-60 time, whereas a BMW Z4 3.0i is 30% faster (with a 0-60 time of 6 seconds). I tried to beat a Z4 off the lights in my Golf, but the Beamer flew away. If they challenge the Spéirling in a Model S Plaid, they'll feel as I did. Fast!

Insane quarter-mile drag time. Its road car record is 7.97 seconds. A Dodge Demon, meant to run extremely fast quarter miles, finishes so in 9.65 seconds, approximately 20% slower. The Rimac Nevera's 8.582-second quarter-mile record was miles behind drag racing. This run hampered the Spéirling. Because it was employing gearing that limited its top speed to 150 mph, it reached there in a little over 5 seconds without accelerating for most of the quarter mile! McMurtry can easily change the gearing, making the Spéirling run quicker.

McMurtry did this how? First, the Spéirling is a tiny single-seater EV with a 60 kWh battery pack, making it one of the lightest EVs ever. The 1,000-hp Spéirling has more than one horsepower per kg. The Nevera has 0.84 horsepower per kg and the Plaid 0.44.

However, you cannot simply construct a car light and power it. Instead of accelerating, it would spin. This makes the Spéirling a fan car. Its huge fans create massive downforce. These fans provide the Spéirling 2 tonnes of downforce while stationary, so you could park it on the ceiling. Its fast 0-60 time comes from its downforce, which lets it deliver all that power without wheel spin.

It also possesses complete downforce at all speeds, allowing it to tackle turns faster than even race vehicles. Spéirlings overcame VW IDRs and F1 cars to set the Goodwood Hill Climb record (read more here). The Spéirling is a dragstrip winner and track dominator, unlike the Plaid and Nevera.

The Spéirling is astonishing for a single-seater. Fan-generated downforce is more efficient than wings and splitters. It also means the vehicle has very minimal drag without the fan. The Spéirling can go 350 miles per charge (WLTP) or 20-30 minutes at full speed on a track despite its 60 kWh battery pack. The G-forces would hurt your neck before the battery died if you drove around a track for longer. The Spéirling can charge at over 200 kW in about 30 minutes. Thus, driving to track days, having fun, and returning is possible. Unlike other high-performance EVs.

Tesla, Rimac, or Lucid will struggle to defeat the Spéirling. They would need to build a fan automobile because adding power to their current vehicle would make it uncontrollable. The EV and automobile industries now have a new, untouchable performance king.

Why breakthrough technologies must be accessible

ChatGPT has exploded. Over 1 million people have used the app, and coding sites like Stack Overflow have banned its answers. It's huge.

I wouldn't have called that as an AI researcher. ChatGPT uses the same GPT-3 technology that's been around for over two years.

More than impressive technology, ChatGPT 3 shows how access makes breakthroughs usable. OpenAI has finally made people realize the power of AI by packaging GPT-3 for normal users.

We think of Thomas Edison as the inventor of the lightbulb, not because he invented it, but because he popularized it.

Going forward, AI companies that make using AI easy will thrive.

Use-case importance

Most modern AI systems use massive language models. These language models are trained on 6,000+ years of human text.

GPT-3 ate 8 billion pages, almost every book, and Wikipedia. It created an AI that can write sea shanties and solve coding problems.

Nothing new. I began beta testing GPT-3 in 2020, but the system's basics date back further.

Tools like GPT-3 are hidden in many apps. Many of the AI writing assistants on this platform are just wrappers around GPT-3.

Lots of online utilitarian text, like restaurant menu summaries or city guides, is written by AI systems like GPT-3. You've probably read GPT-3 without knowing it.

Accessibility

Why is ChatGPT so popular if the technology is old?

ChatGPT makes the technology accessible. Free to use, people can sign up and text with the chatbot daily. ChatGPT isn't revolutionary. It does it in a way normal people can access and be amazed by.

Accessibility isn't easy. OpenAI's Sam Altman tweeted that opening ChatGPT to the public increased computing costs.

Each chat costs "low-digit cents" to process. OpenAI probably spends several hundred thousand dollars a day to keep ChatGPT running, with no immediate business case.

Academic researchers and others who developed GPT-3 couldn't afford it. Without resources to make technology accessible, it can't be used.

Retrospective

This dynamic is old. In the history of science, a researcher with a breakthrough idea was often overshadowed by an entrepreneur or visionary who made it accessible to the public.

We think of Thomas Edison as the inventor of the lightbulb. But really, Vasilij Petrov, Thomas Wright, and Joseph Swan invented the lightbulb. Edison made technology visible and accessible by electrifying public buildings, building power plants, and wiring.

Edison probably lost a ton of money on stunts like building a power plant to light JP Morgan's home, the NYSE, and several newspaper headquarters.

People wanted electric lights once they saw their benefits. By making the technology accessible and visible, Edison unlocked a hugely profitable market.

Similar things are happening in AI. ChatGPT shows that developing breakthrough technology in the lab or on B2B servers won't change the culture.

AI must engage people's imaginations to become mainstream. Before the tech impacts the world, people must play with it and see its revolutionary power.

As the field evolves, companies that make the technology widely available, even at great cost, will succeed.

OpenAI's compute fees are eye-watering. Revolutions are costly.