## More on Marketing

Jon Brosio

9 months ago

## This Landing Page is a (Legal) Money-Printing Machine

and it’s easy to build.

A landing page with good copy is a money-maker.

Let's be honest, page-builder templates are garbage.

They can help you create a nice-looking landing page, but not persuasive writing.

Over the previous 90 days, I've examined 200+ landing pages.

What's crazy?

Top digital entrepreneurs use a 7-part strategy to bring in email subscribers, generate prospects, and (passively) sell their digital courses.

Steal this 7-part landing page architecture to maximize digital product sales.

# The offer

Landing pages require offers.

Newsletter, cohort, or course offer.

Your reader should see this offer first. Includind:

Headline

Imagery

Call-to-action

Clear, persuasive, and simplicity are key. Example: the **Linkedin OS** course home page of digital entrepreneur Justin Welsh offers:

# A distinctly defined problem

Everyone needs an enemy.

You need an opponent on your landing page. Problematic.

Next, employ psychology to create a struggle in your visitor's thoughts.

Don't be clever here; label your customer's problem. The more particular you are, the bigger the situation will seem.

When you build a clear monster, you invite defeat. I appreciate Theo Ohene's Growth Roadmaps landing page.

# Exacerbation of the effects

Problem identification doesn't motivate action.

What would an unresolved problem mean?

This is landing page copy. When you describe the unsolved problem's repercussions, you accomplish several things:

You write a narrative (and stories are remembered better than stats)

You cause the reader to feel something.

You help the reader relate to the issue

Important!

My favorite script is:

"Sure, you can let [problem] go untreated. But what will happen if you do? Soon, you'll begin to notice [new problem 1] will start to arise. That might bring up [problem 2], etc."

Take the copywriting course, digital writer and entrepreneur Dickie Bush illustrates below when he labels the problem (see: "poor habit") and then illustrates the repercussions.

# The tale of transformation

Every landing page needs that "ah-ha!" moment.

Transformation stories do this.

Did you find a solution? Someone else made the discovery? Have you tested your theory?

Next, describe your (or your subject's) metamorphosis.

Kieran Drew nails his narrative (and revelation) here. Right before the disclosure, he introduces his "ah-ha!" moment:

# Testimonials

Social proof completes any landing page.

Social proof tells the reader, "If others do it, it must be worthwhile."

This is your argument.

Positive social proof helps (obviously).

Offer "free" training in exchange for a testimonial if you need social evidence. This builds social proof.

Most social proof is testimonies (recommended). Kurtis Hanni's creative take on social proof (using a screenshot of his colleague) is entertaining.

Bravo.

# Reveal your offer

Now's the moment to act.

Describe the "bundle" that provides the transformation.

Here's:

Course

Cohort

Ebook

Whatever you're selling.

Include a product or service image, what the consumer is getting ("how it works"), the price, any "free" bonuses (preferred), and a CTA ("buy now").

Clarity is key. Don't make a cunning offer. Make sure your presentation emphasizes customer change (benefits). Dan Koe's Modern Mastery landing page makes an offer. Consider:

# An ultimatum

Offering isn't enough.

You must give your prospect an ultimatum.

They can buy your merchandise from you.

They may exit the webpage.

That’s it.

It's crucial to show what happens if the reader does either. Stress the consequences of not buying (again, a little consequence amplification). Remind them of the benefits of buying.

I appreciate Charles Miller's product offer ending:

# The top online creators use a 7-part landing page structure:

Offer the service

Describe the problem

Amplify the consequences

Tell the transformational story

Include testimonials and social proof.

Reveal the offer (with any bonuses if applicable)

Finally, give the reader a deadline to encourage them to take action.

Sequence these sections to develop a landing page that (essentially) prints money.

Jano le Roux

10 months ago

## Here's What I Learned After 30 Days Analyzing Apple's Microcopy

*Move people with tiny words.*

Apple fanboy here.

Macs are awesome.

Their iPhones rock.

$19 cloths are great.

$999 stands are amazing.

I love Apple's microcopy even more.

It's like the marketing goddess bit into the Apple logo and blessed the world with microcopy.

I took on a 30-day micro-stalking mission.

Every time I caught myself wasting time on YouTube, I had to visit Apple’s website to learn the secrets of the marketing goddess herself.

We've learned. Golden apples are calling.

**Cut the friction**

Benefit-first, not commitment-first.

Brands lose customers through friction.

Most brands don't think like customers.

Brands want sales.

Brands want newsletter signups.

Here's their microcopy:

“Buy it now.”

“Sign up for our newsletter.”

Both are difficult. They ask for big commitments.

People are simple creatures. Want pleasure without commitment.

Apple nails this.

So, instead of highlighting the commitment, they highlight the benefit of the commitment.

Saving on the latest iPhone sounds easier than buying it. Everyone saves, but not everyone buys.

A subtle change in framing reduces friction.

Apple eliminates customer objections to reduce friction.

Less customer friction means simpler processes.

Apple's copy expertly reassures customers about shipping fees and not being home. Apple assures customers that returning faulty products is easy.

Apple knows that talking to a real person is the best way to reduce friction and improve their copy.

# Always rhyme

*Learn about fine rhyme.*

Poets make things beautiful with rhyme.

Copywriters use rhyme to stand out.

Apple’s copywriters have mastered the art of corporate rhyme.

Two techniques are used.

## 1. Perfect rhyme

Here, rhymes are identical.

## 2. Imperfect rhyme

Here, rhyming sounds vary.

Apple prioritizes meaning over rhyme.

Apple never forces rhymes that don't fit.

It fits so well that the copy seems accidental.

# Add alliteration

*Alliteration always entertains.*

Alliteration repeats initial sounds in nearby words.

Apple's copy uses alliteration like no other brand I've seen to create a rhyming effect or make the text more fun to read.

For example, in the sentence "Sam saw seven swans swimming," the initial "s" sound is repeated five times. This creates a pleasing rhythm.

Microcopy overuse is like pouring ketchup on a Michelin-star meal.

Alliteration creates a memorable phrase in copywriting. It's subtler than rhyme, and most people wouldn't notice; it simply resonates.

I love how Apple uses alliteration and contrast between "wonders" and "ease".

Assonance, or repeating vowels, isn't Apple's thing.

# You ≠ Hero, Customer = Hero

*Your brand shouldn't be the hero.*

Because they'll be using your product or service, your customer should be the hero of your copywriting. With your help, they should feel like they can achieve their goals.

I love how Apple emphasizes what you can do with the machine in this microcopy.

It's divine how they position their tools as sidekicks to help below.

This one takes the cake:

# Dialogue-style writing

*Conversational copy engages.*

Excellent copy Like sharing gum with a friend.

This helps build audience trust.

Apple does this by using natural connecting words like "so" and phrases like "But that's not all."

# Snowclone-proof

*The mother of all microcopy techniques.*

A snowclone uses an existing phrase or sentence to create a new one. The new phrase or sentence uses the same structure but different words.

It’s usually a well know saying like:

To be or not to be.

This becomes a formula:

To _ or not to _.

Copywriters fill in the blanks with cause-related words. Example:

To click or not to click.

Apple turns "survival of the fittest" into "arrival of the fittest."

It's unexpected and surprises the reader.

So this was fun.

But my fun has just begun.

Microcopy is 21st-century poetry.

I came as an Apple fanboy.

I leave as an Apple fanatic.

Now I’m off to find an apple tree.

Cause you know how it goes.

(Apples, trees, etc.)

*This post is a summary. Original post available **here**.*

Saskia Ketz

2 months ago

## I hate marketing for my business, but here's how I push myself to keep going

Start now.

When it comes to building my business, I’m passionate about a lot of things. I love creating user experiences that simplify branding essentials. I love creating new typefaces and color combinations to inspire logo designers. I love fixing problems to improve my product.

Business marketing isn't my thing.

This is shared by many. Many solopreneurs, like me, struggle to advertise their business and drive themselves to work on it.

Without a lot of promotion, no company will succeed. Marketing is 80% of developing a firm, and when you're starting out, it's even more. Some believe that you shouldn't build anything until you've begun marketing your idea and found enough buyers.

Marketing your business without marketing experience is difficult. There are various outlets and techniques to learn. Instead of figuring out where to start, it's easier to return to your area of expertise, whether that's writing, designing product features, or improving your site's back end. Right?

First, realize that your role as a founder is to market your firm. Being a founder focused on product, I rarely work on it.

Secondly, use these basic methods that have helped me dedicate adequate time and focus to marketing. They're all simple to apply, and they've increased my business's visibility and success.

# 1. Establish buckets for every task.

You've probably heard to schedule tasks you don't like. As simple as it sounds, blocking a substantial piece of my workday for marketing duties like LinkedIn or Twitter outreach, AppSumo customer support, or SEO has forced me to spend time on them.

Giving me lots of room to focus on product development has helped even more. Sure, this means scheduling time to work on product enhancements after my four-hour marketing sprint.

It also involves making space to store product inspiration and ideas throughout the day so I don't get distracted. This is like the advice to keep a notebook beside your bed to write down your insomniac ideas. I keep fonts, color palettes, and product ideas in folders on my desktop. Knowing these concepts won't be lost lets me focus on marketing in the moment. When I have limited time to work on something, I don't have to conduct the research I've been collecting, so I can get more done faster.

# 2. Look for various accountability systems

Accountability is essential for self-discipline. To keep focused on my marketing tasks, I've needed various streams of accountability, big and little.

Accountability groups are great for bigger things. SaaS Camp, a sales outreach coaching program, is mine. We discuss marketing duties and results every week. This motivates me to do enough each week to be proud of my accomplishments. Yet hearing what works (or doesn't) for others gives me benchmarks for my own marketing outcomes and plenty of fresh techniques to attempt.

… say, I want to DM 50 people on Twitter about my product — I get that many Q-tips and place them in one pen holder on my desk.

The best accountability group can't watch you 24/7. I use a friend's simple method that shouldn't work (but it does). When I have a lot of marketing chores, like DMing 50 Twitter users about my product, That many Q-tips go in my desk pen holder. After each task, I relocate one Q-tip to an empty pen holder. When you have a lot of minor jobs to perform, it helps to see your progress. You might use toothpicks, M&Ms, or anything else you have a lot of.

# 3. Continue to monitor your feedback loops

Knowing which marketing methods work best requires monitoring results. As an entrepreneur with little go-to-market expertise, every tactic I pursue is an experiment. I need to know how each trial is doing to maximize my time.

I placed Google and Facebook advertisements on hold since they took too much time and money to obtain Return. LinkedIn outreach has been invaluable to me. I feel that talking to potential consumers one-on-one is the fastest method to grasp their problem areas, figure out my messaging, and find product market fit.

Data proximity offers another benefit. Seeing positive results makes it simpler to maintain doing a work you don't like. Why every fitness program tracks progress.

Marketing's goal is to increase customers and revenues, therefore I've found it helpful to track those metrics and celebrate monthly advances. I provide these updates for extra accountability.

Finding faster feedback loops is also motivating. Marketing brings more clients and feedback, in my opinion. Product-focused founders love that feedback. Positive reviews make me proud that my product is benefitting others, while negative ones provide me with suggestions for product changes that can improve my business.

The best advice I can give a lone creator who's afraid of marketing is to just start. Start early to learn by doing and reduce marketing stress. Start early to develop habits and successes that will keep you going. The sooner you start, the sooner you'll have enough consumers to return to your favorite work.

## You might also like

Zuzanna Sieja

9 months ago

## In 2022, each data scientist needs to read these 11 books.

Non-technical talents can benefit data scientists in addition to statistics and programming.

As our article 5 Most In-Demand Skills for Data Scientists shows, being business-minded is useful. How can you get such a diverse skill set? We've compiled a list of helpful resources.

Data science, data analysis, programming, and business are covered. Even a few of these books will make you a better data scientist.

Ready? Let’s dive in.

# Best books for data scientists

# 1. The Black Swan

**Author:** Nassim Taleb

First, a less obvious title. Nassim Nicholas Taleb's seminal series examines uncertainty, probability, risk, and decision-making.

Three characteristics define a black swan event:

It is erratic.

It has a significant impact.

Many times, people try to come up with an explanation that makes it seem more predictable than it actually was.

People formerly believed all swans were white because they'd never seen otherwise. A black swan in Australia shattered their belief.

Taleb uses this incident to illustrate how human thinking mistakes affect decision-making. The book teaches readers to be aware of unpredictability in the ever-changing IT business.

Try multiple tactics and models because you may find the answer.

# 2. High Output Management

**Author:** Andrew Grove

Intel's former chairman and CEO provides his insights on developing a global firm in this business book. We think Grove would choose “management” to describe the talent needed to start and run a business.

That's a skill for CEOs, techies, and data scientists. Grove writes on developing productive teams, motivation, real-life business scenarios, and revolutionizing work.

Five lessons:

Every action is a procedure.

Meetings are a medium of work

Manage short-term goals in accordance with long-term strategies.

Mission-oriented teams accelerate while functional teams increase leverage.

Utilize performance evaluations to enhance output.

So — if the above captures your imagination, it’s well worth getting stuck in.

# 3. The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers

**Author:** Ben Horowitz

Few realize how difficult it is to run a business, even though many see it as a tremendous opportunity.

Business schools don't teach managers how to handle the toughest difficulties; they're usually on their own. So Ben Horowitz wrote this book.

It gives tips on creating and maintaining a new firm and analyzes the hurdles CEOs face.

Find suggestions on:

create software

Run a business.

Promote a product

Obtain resources

Smart investment

oversee daily operations

This book will help you cope with tough times.

# 4. Obviously Awesome: How to Nail Product Positioning

**Author: **April Dunford

Your job as a data scientist is a product. You should be able to sell what you do to clients. Even if your product is great, you must convince them.

How to? April Dunford's advice: Her book explains how to connect with customers by making your offering seem like a secret sauce.

You'll learn:

Select the ideal market for your products.

Connect an audience to the value of your goods right away.

Take use of three positioning philosophies.

Utilize market trends to aid purchasers

# 5. The Mom test

**Author: **Rob Fitzpatrick

The Mom Test improves communication. Client conversations are rarely predictable. The book emphasizes one of the most important communication rules: enquire about specific prior behaviors.

Both ways work. If a client has suggestions or demands, listen carefully and ensure everyone understands. The book is packed with client-speaking tips.

# 6. Introduction to Machine Learning with Python: A Guide for Data Scientists

**Authors:** Andreas C. Müller, Sarah Guido

Now, technical documents.

This book is for Python-savvy data scientists who wish to learn machine learning. Authors explain how to use algorithms instead of math theory.

Their technique is ideal for developers who wish to study machine learning basics and use cases. Sci-kit-learn, NumPy, SciPy, pandas, and Jupyter Notebook are covered beyond Python.

If you know machine learning or artificial neural networks, skip this.

# 7. Python Data Science Handbook: Essential Tools for Working with Data

**Author:** Jake VanderPlas

Data work isn't easy. Data manipulation, transformation, cleansing, and visualization must be exact.

Python is a popular tool. The Python Data Science Handbook explains everything. The book describes how to utilize Pandas, Numpy, Matplotlib, Scikit-Learn, and Jupyter for beginners.

The only thing missing is a way to apply your learnings.

# 8. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython

**Author:** Wes McKinney

The author leads you through manipulating, processing, cleaning, and analyzing Python datasets using NumPy, Pandas, and IPython.

The book's realistic case studies make it a great resource for Python or scientific computing beginners. Once accomplished, you'll uncover online analytics, finance, social science, and economics solutions.

# 9. Data Science from Scratch

**Author:** Joel Grus

Here's a title for data scientists with Python, stats, maths, and algebra skills (alongside a grasp of algorithms and machine learning). You'll learn data science's essential libraries, frameworks, modules, and toolkits.

The author works through all the key principles, providing you with the practical abilities to develop simple code. The book is appropriate for intermediate programmers interested in data science and machine learning.

Not that prior knowledge is required. The writing style matches all experience levels, but understanding will help you absorb more.

# 10. Machine Learning Yearning

**Author:** Andrew Ng

Andrew Ng is a machine learning expert. Co-founded and teaches at Stanford. This free book shows you how to structure an ML project, including recognizing mistakes and building in complex contexts.

The book delivers knowledge and teaches how to apply it, so you'll know how to:

Determine the optimal course of action for your ML project.

Create software that is more effective than people.

Recognize when to use end-to-end, transfer, and multi-task learning, and how to do so.

Identifying machine learning system flaws

Ng writes easy-to-read books. No rigorous math theory; just a terrific approach to understanding how to make technical machine learning decisions.

# 11. Deep Learning with PyTorch Step-by-Step

**Author:** Daniel Voigt Godoy

The last title is also the most recent. The book was revised on 23 January 2022 to discuss Deep Learning and PyTorch, a Python coding tool.

It comprises four parts:

Fundamentals (gradient descent, training linear and logistic regressions in PyTorch)

Machine Learning (deeper models and activation functions, convolutions, transfer learning, initialization schemes)

Sequences (RNN, GRU, LSTM, seq2seq models, attention, self-attention, transformers)

Automatic Language Recognition (tokenization, embeddings, contextual word embeddings, ELMo, BERT, GPT-2)

We admire the book's readability. The author avoids difficult mathematical concepts, making the material feel like a conversation.

# Is every data scientist a humanist?

Even as a technological professional, you can't escape human interaction, especially with clients.

We hope these books will help you develop interpersonal skills.

Vitalik

1 year ago

## An approximate introduction to how zk-SNARKs are possible (part 2)

If tasked with the problem of coming up with a zk-SNARK protocol, many people would make their way to this point and then get stuck and give up. How can a verifier possibly check every single piece of the computation, without looking at each piece of the computation individually? But it turns out that there is a clever solution.

## Polynomials

Polynomials are a special class of algebraic expressions of the form:

- x+5
- x^4
- x^3+3x^2+3x+1
- 628x^{271}+318x^{270}+530x^{269}+…+69x+381

i.e. they are a sum of any (finite!) number of terms of the form cx^k

There are many things that are fascinating about polynomials. But here we are going to zoom in on a particular one: **polynomials are a single mathematical object that can contain an unbounded amount of information** (think of them as a list of integers and this is obvious). The fourth example above contained 816 digits of tau, and one can easily imagine a polynomial that contains far more.

Furthermore, **a single equation between polynomials can represent an unbounded number of equations between numbers**. For example, consider the equation A(x)+ B(x) = C(x). If this equation is true, then it's also true that:

- A(0)+B(0)=C(0)
- A(1)+B(1)=C(1)
- A(2)+B(2)=C(2)
- A(3)+B(3)=C(3)

And so on for every possible coordinate. You can even construct polynomials to deliberately represent sets of numbers so you can check many equations all at once. For example, suppose that you wanted to check:

- 12+1=13
- 10+8=18
- 15+8=23
- 15+13=28

You can use a procedure called Lagrange interpolation to construct polynomials A(x) that give (12,10,15,15) as outputs at some specific set of coordinates (eg. (0,1,2,3)), B(x) the outputs (1,8,8,13) on thos same coordinates, and so forth. In fact, here are the polynomials:

- A(x)=-2x^3+\frac{19}{2}x^2-\frac{19}{2}x+12
- B(x)=2x^3-\frac{19}{2}x^2+\frac{29}{2}x+1
- C(x)=5x+13

Checking the equation A(x)+B(x)=C(x) with these polynomials checks all four above equations at the same time.

## Comparing a polynomial to itself

You can even check relationships between a large number of adjacent evaluations of the same polynomial using a simple polynomial equation. This is slightly more advanced. Suppose that you want to check that, for a given polynomial F, F(x+2)=F(x)+F(x+1) with the integer range {0,1…89} (so if you *also* check F(0)=F(1)=1, then F(100) would be the 100th Fibonacci number)

As polynomials, F(x+2)-F(x+1)-F(x) would not be exactly zero, as it could give arbitrary answers outside the range x={0,1…98}. But we can do something clever. In general, there is a rule that if a polynomial P is zero across some set S=\{x_1,x_2…x_n\} then it can be expressed as P(x)=Z(x)*H(x), where Z(x)=(x-x_1)*(x-x_2)*…*(x-x_n) and H(x) is also a polynomial. In other words, **any polynomial that equals zero across some set is a (polynomial) multiple of the simplest (lowest-degree) polynomial that equals zero across that same set.**

Why is this the case? It is a nice corollary of polynomial long division: the factor theorem. We know that, when dividing P(x) by Z(x), we will get a quotient Q(x) and a remainder R(x) is strictly less than that of Z(x). Since we know that P is zero on all of S, it means that R has to be zero on all of S as well. So we can simply compute R(x) via polynomial interpolation, since it's a polynomial of degree at most n-1 and we know n values (the zeros at S). Interpolating a polynomial with all zeroes gives the zero polynomial, thus R(x)=0 and H(x)=Q(x).

Going back to our example, if we have a polynomial F that encodes Fibonacci numbers (so F(x+2)=F(x)+F(x+1) across x=\{0,1…98\}), then I can convince you that F *actually satisfies this condition* by proving that the polynomial P(x)=F(x+2)-F(x+1)-F(x) is zero over that range, by giving you the quotient:

H(x)=\frac{F(x+2)-F(x+1)-F(x)}{Z(x)}

Where Z(x) = (x-0)*(x-1)*…*(x-98).

You can calculate Z(x) yourself (ideally you would have it precomputed), check the equation, and if the check passes then F(x) satisfies the condition!

Now, step back and notice what we did here. We converted a 100-step-long computation into a single equation with polynomials. Of course, proving the N'th Fibonacci number is not an especially useful task, especially since Fibonacci numbers have a closed form. But you can use exactly the same basic technique, just with some extra polynomials and some more complicated equations, to encode arbitrary computations with an arbitrarily large number of steps.

see part 3

Chritiaan Hetzner

9 months ago

## Mystery of the $1 billion'meme stock' that went to $400 billion in days

Who is AMTD Digital?

An unknown Hong Kong corporation joined the global megacaps worth over $500 billion on Tuesday.

The American Depository Share (ADS) with the ticker code HKD gapped at the open, soaring 25% over the previous closing price as trading began, before hitting an intraday high of $2,555.

At its peak, its market cap was almost $450 billion, more than Facebook parent Meta or Alibaba.

Yahoo Finance reported a daily volume of 350,500 shares, the lowest since the ADS began trading and much below the average of 1.2 million.

Despite losing a fifth of its value on Wednesday, it's still worth more than Toyota, Nike, McDonald's, or Walt Disney.

The company sold 16 million shares at $7.80 each in mid-July, giving it a $1 billion market valuation.

# Why the boom?

That market cap seems unjustified.

According to SEC reports, its income-generating assets barely topped $400 million in March. Fortune's emails and calls went unanswered.

Website discloses little about company model. Its one-minute business presentation film uses a Star Wars–like design to sell the company as a "one-stop digital solutions platform in Asia"

The SEC prospectus explains.

AMTD Digital sells a "SpiderNet Ecosystems Solutions" kind of club membership that connects enterprises. This is the bulk of its $25 million annual revenue in April 2021.

Pretax profits have been higher than top line over the past three years due to fair value accounting gains on Appier, DayDayCook, WeDoctor, and five Asian fintechs.

AMTD Group, the company's parent, specializes in investment banking, hotel services, luxury education, and media and entertainment. AMTD IDEA, a $14 billion subsidiary, is also traded on the NYSE.

# “Significant volatility”

Why AMTD Digital listed in the U.S. is unknown, as it informed investors in its share offering prospectus that could delist under SEC guidelines.

Beijing's red tape prevents the Sarbanes-Oxley Board from inspecting its Chinese auditor.

This frustrates Chinese stock investors. If the U.S. and China can't achieve a deal, 261 Chinese companies worth $1.3 trillion might be delisted.

Calvin Choi left UBS to become AMTD Group's CEO.

His capitalist background and status as a Young Global Leader with the World Economic Forum don't stop him from praising China's Communist party or celebrating the "glory and dream of the Great Rejuvenation of the Chinese nation" a century after its creation.

Despite having an executive vice chairman with a record of battling corruption and ties to Carrie Lam, Beijing's previous proconsul in Hong Kong, Choi is apparently being targeted for a two-year industry ban by the city's securities regulator after an investor accused Choi of malfeasance.

Some CMIG-funded initiatives produced money, but he didn't give us the proceeds, a corporate official told China's Caixin in October 2020. We don't know if he misappropriated or lost some money.

# A seismic anomaly

In fundamental analysis, where companies are valued based on future cash flows, AMTD Digital's mind-boggling market cap is a statistical aberration that should occur once every hundred years.

AMTD Digital doesn't know why it's so valuable. In a thank-you letter to new shareholders, it said it was confused by the stock's performance.

Since its IPO, the company has seen significant ADS price volatility and active trading volume, it said Tuesday. "To our knowledge, there have been no important circumstances, events, or other matters since the IPO date."

Permabears awoke after the jump. Jim Chanos asked if "we're all going to ignore the $400 billion meme stock in the room," while Nate Anderson called AMTD Group "sketchy."

It happened the same day SEC Chair Gary Gensler praised the 20th anniversary of the Sarbanes-Oxley Act, aimed to restore trust in America's financial markets after the Enron and WorldCom accounting fraud scandals.

The run-up revived unpleasant memories of Robinhood's decision to limit retail investors' ability to buy GameStop, regarded as a measure to protect hedge funds invested in the meme company.

Why wasn't HKD's buy button removed? Because retail wasn't behind it?" tweeted Gensler on Tuesday. "Real stock fraud. "You're worthless."