I recently wrote about getting VCs excited about Marketplace start-ups. SaaS founders became envious!

Understanding how people wire tens of millions is the only Series A hack I recommend.

Few people understand the intellectual process behind investing.

VC is risk management.

Series A-focused VCs must cover two risks.

1. Market risk

You need a large market to cross a threshold beyond which you can build defensibilities. Series A VCs underwrite market risk.

They must see you have reached product-market fit (PMF) in a large total addressable market (TAM).

2. Execution risk

When evaluating your growth engine's blitzscaling ability, execution risk arises.

When investors remove operational uncertainty, they profit.

Series A VCs like businesses with derisked revenue streams. Don't raise unless you have a predictable model, pipeline, and growth.

Please beat these 3 metrics before Series A:

Achieve $1.5m ARR in 12-24 months (Market risk)

Above 100% Net Dollar Retention. (Market danger)

Lead Velocity Rate supporting $10m ARR in 2–4 years (Execution risk)

Hit the 3 and you'll raise $10M in 4 months. Discussing 2/3 may take 6–7 months.

If none, don't bother raising and focus on becoming a capital-efficient business (Topics for other posts).

Let's examine these 3 metrics for the brave ones.

1. Lead Velocity Rate supporting €$10m ARR in 2 to 4 years

Last because it's the least discussed. LVR is the most reliable data when evaluating a growth engine, in my opinion.

SaaS allows you to see the future.

Monthly Sales and Sales Pipelines, two predictive KPIs, have poor data quality. Both are lagging indicators, and minor changes can cause huge modeling differences.

Analysts and Associates will trash your forecasts if they're based only on Monthly Sales and Sales Pipeline.

LVR, defined as month-over-month growth in qualified leads, is rock-solid. There's no lag. You can See The Future if you use Qualified Leads and a consistent formula and process to qualify them.

With this metric in your hand, scaling your company turns into an execution play on which VCs are able to perform calculations risk.

2. Above-100% Net Dollar Retention.

Net Dollar Retention is a better-known SaaS health metric than LVR.

Net Dollar Retention measures a SaaS company's ability to retain and upsell customers. Ask what $1 of net new customer spend will be worth in years n+1, n+2, etc.

Depending on the business model, SaaS businesses can increase their share of customers' wallets by increasing users, selling them more products in SaaS-enabled marketplaces, other add-ons, and renewing them at higher price tiers.

If a SaaS company's annualized Net Dollar Retention is less than 75%, there's a problem with the business.

Slack's ARR chart (below) shows how powerful Net Retention is. Layer chart shows how existing customer revenue grows. Slack's S1 shows 171% Net Dollar Retention for 2017–2019.

Slack S-1

3. $1.5m ARR in the last 12-24 months.

According to Point 9, $0.5m-4m in ARR is needed to raise a $5–12m Series A round.

Target at least what you raised in Pre-Seed/Seed. If you've raised $1.5m since launch, don't raise before $1.5m ARR.

Capital efficiency has returned since Covid19. After raising $2m since inception, it's harder to raise $1m in ARR.

P9's 2016-2021 SaaS Funding Napkin

In summary, less than 1% of companies VCs meet get funded. These metrics can help you win.

If there’s demand for it, I’ll do one on direct-to-consumer.

Cheers!

The Top 8 Growth Hacking Techniques for Startups

These startups, and how they used growth-hack marketing to flourish, are some of the more ethical ones, while others are less so.

Before the 1970 World Cup began, Puma paid footballer Pele $120,000 to tie his shoes. The cameras naturally focused on Pele and his Pumas, causing people to realize that Puma was the top football brand in the world.

Early workers of Uber canceled over 5,000 taxi orders made on competing applications in an effort to financially hurt any of their rivals.

PayPal developed a bot that advertised cheap goods on eBay, purchased them, and paid for them with PayPal, fooling eBay into believing that customers preferred this payment option. Naturally, Paypal became eBay's primary method of payment.

Anyone renting a space on Craigslist had their emails collected by AirBnB, who then urged them to use their service instead. A one-click interface was also created to list immediately on AirBnB from Craigslist.

To entice potential single people looking for love, Tinder developed hundreds of bogus accounts of attractive people. Additionally, for at least a year, users were "accidentally" linked.

Reddit initially created a huge number of phony accounts and forced them all to communicate with one another. It eventually attracted actual users—the real meaning of "fake it 'til you make it"! Additionally, this gave Reddit control over the tone of voice they wanted for their site, which is still present today.

To disrupt the conferences of their main rival, Salesforce recruited fictitious protestors. The founder then took over all of the event's taxis and gave a 45-minute pitch for his startup. No place to hide!

When a wholesaler required a minimum purchase of 10, Amazon CEO Jeff Bezos wanted a way to purchase only one book from them. A wholesaler would deliver the one book he ordered along with an apology for the other eight books after he discovered a loophole and bought the one book before ordering nine books about lichens. On Amazon, he increased this across all of the users.

Original post available here

Higher startup valuations are often favorable for all parties. High valuations show a business's potential. New customers and talent are attracted. They earn respect.

Everyone benefits if a company's valuation rises.

Founders and investors have always been incentivized to overestimate a company's value.

Post-money valuations were inflated by 2021 market expectations and the valuation model's mechanisms.

Founders must understand both levers to handle a normalizing market.

2021, the year of miracles

2021 must've seemed miraculous to entrepreneurs, employees, and VCs. Valuations rose, and funding resumed after the first Covid-19 epidemic caution.

In 2021, VC investments increased from $335B to $643B. 518 new worldwide unicorns vs. 134 in 2020; 951 US IPOs vs. 431.

Things can change quickly, as 2020-21 showed.

Rising interest rates, geopolitical developments, and normalizing technology conditions drive down share prices and tech company market caps in 2022. Zoom, the poster-child of early lockdown success, is down 37% since 1st Jan.

Once-inflated valuations can become a problem in a normalizing market, especially for founders, employees, and early investors.

the reason why startups are always overvalued

To see why inflated valuations are a problem, consider one of its causes.

Private company values only fluctuate following a new investment round, unlike publicly-traded corporations. The startup's new value is calculated simply:

(Latest round share price) x (total number of company shares)

This is the industry standard Post-Money Valuation model.

Let’s illustrate how it works with an example. If a VC invests $10M for 1M shares (at $10/share), and the company has 10M shares after the round, its Post-Money Valuation is $100M (10/share x 10M shares).

This approach might seem like the most natural way to assess a business, but the model often unintentionally overstates the underlying value of the company even if the share price paid by the investor is fair. All shares aren't equal.

New investors in a corporation will always try to minimize their downside risk, or the amount they lose if things go wrong. New investors will try to negotiate better terms and pay a premium.

How the value of a struggling SpaceX increased

SpaceX's 2008 Series D is an example. Despite the financial crisis and unsuccessful rocket launches, the company's Post-Money Valuation was 36% higher after the investment round. Why?

Series D SpaceX shares were protected. In case of liquidation, Series D investors were guaranteed a 2x return before other shareholders.

Due to downside protection, investors were willing to pay a higher price for this new share class.

The Post-Money Valuation model overpriced SpaceX because it viewed all the shares as equal (they weren't).

Why entrepreneurs, workers, and early investors stand to lose the most

Post-Money Valuation is an effective and sufficient method for assessing a startup's valuation, despite not taking share class disparities into consideration.

In a robust market, where the firm valuation will certainly expand with the next fundraising round or exit, the inflated value is of little significance.

Fairness endures. If a corporation leaves at a greater valuation, each stakeholder will receive a proportional distribution. (i.e., 5% of a $100M corporation yields $5M).

SpaceX's inherent overvaluation was never a problem. Had it been sold for less than its Post-Money Valuation, some shareholders, including founders, staff, and early investors, would have seen their ownership drop.

The unforgiving world of 2022

In 2022, founders, employees, and investors who benefited from inflated values will face below-valuation exits and down-rounds.

For them, 2021 will be a curse, not a blessing.

Some tech giants are worried. Klarna's valuation fell from $45B (Oct 21) to $30B (Jun 22), Canvas from $40B to $27B, and GoPuffs from $17B to $8.3B.

Shazam and Blue Apron have to exit or IPO at a cheaper price. Premium share classes are protected, while others receive less. The same goes for bankrupts.

Those who continue at lower valuations will lose reputation and talent. When their value declines by half, generous employee stock options become less enticing, and their ability to return anything is questioned.

What can we infer about the present situation?

Such techniques to enhance your company's value or stop a normalizing market are fiction.

The current situation is a painful reminder for entrepreneurs and a crucial lesson for future firms.

The devastating market fall of the previous six months has taught us one thing:

1. Keep in mind that any valuation is speculative. Money Post A startup's valuation is a highly simplified approximation of its true value, particularly in the early phases when it lacks significant income or a cutting-edge product. It is merely a projection of the future and a hypothetical meter. Until it is achieved by an exit, a valuation is nothing more than a number on paper.
   

2. Assume the value of your company is lower than it was in the past. Your previous valuation might not be accurate now due to substantial changes in the startup financing markets. There is little reason to think that your company's value will remain the same given the 50%+ decline in many newly listed IT companies. Recognize how the market situation is changing and use caution.
   

3. Recognize the importance of the stake you hold. Each share class has a unique value that varies. Know the sort of share class you own and how additional contractual provisions affect the market value of your security. Frameworks have been provided by Metrick and Yasuda (Yale & UC) and Gornall and Strebulaev (Stanford) for comprehending the terms that affect investors' cash-flow rights upon withdrawal. As a result, you will be able to more accurately evaluate your firm and determine the worth of each share class.
   

4. Be wary of approving excessively protective share terms.
   The trade-offs should be considered while negotiating subsequent rounds. Accepting punitive contractual terms could first seem like a smart option in order to uphold your inflated worth, but you should proceed with caution. Such provisions ALWAYS result in misaligned shareholders, with common shareholders (such as you and your staff) at the bottom of the list.

Learn these subtle cues to gain influence.

Hate being ignored?

As a 24-year-old, I struggled at work. Attention-getting tips How to avoid being judged by my size, gender, and lack of wrinkles or gray hair?

I've learned seniority hacks. Influence. Within two years as a product manager, I led a team. I'm a Stanford MBA student.

These communication hacks can make you look senior and influential.

1. Slowly speak

We speak quickly because we're afraid of being interrupted.

When I doubt my ideas, I speak quickly. How can we slow down? Jamie Chapman says speaking slowly saps our energy.

Chapman suggests emphasizing certain words and pausing.

2. Interrupted? Stop the stopper

Someone interrupt your speech?

Don't wait. "May I finish?" No pause needed. Stop interrupting. I first tried this in Leadership Laboratory at Stanford. How quickly I gained influence amazed me.

Next time, try “May I finish?” If that’s not enough, try these other tips from Wendy R.S. O’Connor.

3. Context

Others don't always see what's obvious to you.

Through explanation, you help others see the big picture. If a senior knows it, you help them see where your work fits.

4. Don't ask questions in statements

“Your statement lost its effect when you ended it on a high pitch,” a group member told me. Upspeak, it’s called. I do it when I feel uncertain.

Upspeak loses influence and credibility. Unneeded. When unsure, we can say "I think." We can even ask a proper question.

Someone else's boasting is no reason to be dismissive. As leaders and colleagues, we should listen to our colleagues even if they use this speech pattern.

Give your words impact.

5. Signpost structure

Signposts improve clarity by providing structure and transitions.

Communication coach Alexander Lyon explains how to use "first," "second," and "third" He explains classic and summary transitions to help the listener switch topics.

Signs clarify. Clarity matters.

6. Eliminate email fluff

“Fine. When will the report be ready? — Jeff.”

Notice how senior leaders write short, direct emails? I often use formalities like "dear," "hope you're well," and "kind regards"

Formality is (usually) unnecessary.

7. Replace exclamation marks with periods

See how junior an exclamation-filled email looks:

Hi, all!
Hope you’re as excited as I am for tomorrow! We’re celebrating our accomplishments with cake! Join us tomorrow at 2 pm!
See you soon!

Why the exclamation points? Why not just one?

Hi, all.
Hope you’re as excited as I am for tomorrow. We’re celebrating our accomplishments with cake. Join us tomorrow at 2 pm!
See you soon.

8. Take space

"Playing high" means having an open, relaxed body, says Stanford professor and author Deborah Gruenfield.

Crossed legs or looking small? Relax. Get bigger.

Overview

I'm happy to provide this important update. We've worked on this for a year and a half, so I'm glad to finally write it. We named the application AESIR because we’ve love Norse Mythology. AESIR automates and runs trading strategies.

• Volatility, technical analysis, oscillators, and other signals are currently supported by AESIR.

• Additionally, we enhanced AESIR's ability to create distinctive bespoke signals by allowing it to analyze many indicators and produce a single signal.

• AESIR has a significant social component that allows you to copy the best-performing public setups and use them right away.

Enter your email here to be notified when AEISR launches.

Views on algorithmic trading

First, let me clarify. Anyone who claims algorithmic trading platforms are money-printing plug-and-play devices is a liar. Algorithmic trading platforms are a collection of tools.

A trading algorithm won't make you a competent trader if you lack a trading strategy and yolo your funds without testing. It may hurt your trade. Test and alter your plans to account for market swings, but comprehend market signals and trends.

Status Report

Throughout closed beta testing, we've communicated closely with users to design a platform they want to use.

To celebrate, we're giving you free Aesir Viking NFTs and we cover gas fees.

Why use a trading Algorithm?

• Automating a successful manual approach

• experimenting with and developing solutions that are impossible to execute manually

One AESIR strategy lets you buy any cryptocurrency that rose by more than x% in y seconds.

AESIR can scan an exchange for coins that have gained more than 3% in 5 minutes. It's impossible to manually analyze over 1000 trading pairings every 5 minutes. Auto buy dips or DCA around a Dip

Sneak Preview

Here's the Leaderboard, where you can clone the best public settings.

As a tiny, self-funded team, we're excited to unveil our product. It's a beta release, so there's still more to accomplish, but we know where we stand.

If this sounds like a project that you might want to learn more about, you can sign up to our newsletter and be notified when AESIR launches.

Useful Links:

Join the Discord | Join our subreddit | Newsletter | Mint Free NFT

His story will inspire you.

“Google search went down for a few hours in 2002; Jeff Dean handled all the queries by hand and checked quality doubled.”- Jeff Dean Facts.

One of many Jeff Dean jokes, but you get the idea.

Google's top six engineers met in a war room in mid-2000. Google's crawling system, which indexed the Web, stopped working. Users could still enter queries, but results were five months old.

Google just signed a deal with Yahoo to power a ten-times-larger search engine. Tension rose. It was crucial. If they failed, the Yahoo agreement would likely fall through, risking bankruptcy for the firm. Their efforts could be lost.

A rangy, tall, energetic thirty-one-year-old man named Jeff dean was among those six brilliant engineers in the makeshift room. He had just left D. E. C. a couple of months ago and started his career in a relatively new firm Google, which was about to change the world. He rolled his chair over his colleague Sanjay and sat right next to him, cajoling his code like a movie director. The history started from there.

When you think of people who shaped the World Wide Web, you probably picture founders and CEOs like Larry Page and Sergey Brin, Marc Andreesen, Tim Berners-Lee, Bill Gates, and Mark Zuckerberg. They’re undoubtedly the brightest people on earth.

Under these giants, legions of anonymous coders work at keyboards to create the systems and products we use. These computer workers are irreplaceable.

Let's get to know him better.

It's possible you've never heard of Jeff Dean. He's American. Dean created many behind-the-scenes Google products. Jeff, co-founder and head of Google's deep learning research engineering team, is a popular technology, innovation, and AI keynote speaker.

While earning an MS and Ph.D. in computer science at the University of Washington, he was a teaching assistant, instructor, and research assistant. Dean joined the Compaq Computer Corporation Western Research Laboratory research team after graduating.

Jeff co-created ProfileMe and the Continuous Profiling Infrastructure for Digital at Compaq. He co-designed and implemented Swift, one of the fastest Java implementations. He was a senior technical staff member at mySimon Inc., retrieving and caching electronic commerce content.

Dean, a top young computer scientist, joined Google in mid-1999. He was always trying to maximize a computer's potential as a child.

An expert

His high school program for processing massive epidemiological data was 26 times faster than professionals'. Epi Info, in 13 languages, is used by the CDC. He worked on compilers as a computer science Ph.D. These apps make source code computer-readable.

Dean never wanted to work on compilers forever. He left Academia for Google, which had less than 20 employees. Dean helped found Google News and AdSense, which transformed the internet economy. He then addressed Google's biggest issue, scaling.

Growing Google faced a huge computing challenge. They developed PageRank in the late 1990s to return the most relevant search results. Google's popularity slowed machine deployment.

Dean solved problems, his specialty. He and fellow great programmer Sanjay Ghemawat created the Google File System, which distributed large data over thousands of cheap machines.

These two also created MapReduce, which let programmers handle massive data quantities on parallel machines. They could also add calculations to the search algorithm. A 2004 research article explained MapReduce, which became an industry sensation.

Several revolutionary inventions

Dean's other initiatives were also game-changers. BigTable, a petabyte-capable distributed data storage system, was based on Google File. The first global database, Spanner, stores data on millions of servers in dozens of data centers worldwide.

It underpins Gmail and AdWords. Google Translate co-founder Jeff Dean is surprising. He contributes heavily to Google News. Dean is Senior Fellow of Google Research and Health and leads Google AI.

Recognitions

The National Academy of Engineering elected Dean in 2009. He received the 2009 Association for Computing Machinery fellowship and the 2016 American Academy of Arts and Science fellowship. He received the 2007 ACM-SIGOPS Mark Weiser Award and the 2012 ACM-Infosys Foundation Award. Lists could continue.

A sneaky question may arrive in your mind: How much does this big brain earn? Well, most believe he is one of the highest-paid employees at Google. According to a survey, he is paid $3 million a year.

He makes espresso and chats with a small group of Googlers most mornings. Dean steams milk, another grinds, and another brews espresso. They discuss families and technology while making coffee. He thinks this little collaboration and idea-sharing keeps Google going.

“Some of us have been working together for more than 15 years,” Dean said. “We estimate that we’ve collectively made more than 20,000 cappuccinos together.”

We all know great developers and software engineers. It may inspire many.