I shouldn't generalize, yet this is true.

Spending is simpler than earning.

Prove me wrong, but with home debt at $145k in 2020 and individual debt at $67k, people don't have their priorities straight.

Where does this loan originate?

Under-50 Americans owed $7.86 trillion in Q4 20T. That's more than the US's 3-trillion-dollar deficit.

Here’s a breakdown:
🏡 Mortgages/Home Equity Loans = $5.28 trillion (67%)
🎓 Student Loans = $1.20 trillion (15%)
🚗 Auto Loans = $0.80 trillion (10%)
💳 Credit Cards = $0.37 trillion (5%)
🏥 Other/Medical = $0.20 trillion (3%)

Images.google.com

At least the Fed and government can explain themselves with their debt balance which includes:

-Providing stimulus packages 2x for Covid relief

-Stabilizing the economy

-Reducing inflation and unemployment

-Providing for the military, education and farmers

No American should have this much debt.

Don’t get me wrong. Debt isn’t all the same. Yes, it’s a negative number but it carries different purposes which may not be all bad.

Good debt: Use those funds in hopes of them appreciating as an investment in the future

-Student loans
-Business loan
-Mortgage, home equity loan
-Experiences

Paying cash for a home is wasteful. Just if the home is exceptionally uncommon, only 1 in a million on the market, and has an incredible bargain with numerous bidders seeking higher prices should you do so.

To impress the vendor, pay cash so they can sell it quickly. Most people can't afford most properties outright. Only 15% of U.S. homebuyers can afford their home. Zillow reports that only 37% of homes are mortgage-free.

People have clearly overreached.

Ignore appearances.

5% down can buy a 10-bedroom mansion.

Not paying in cash isn't necessarily a negative thing given property prices have increased by 30% since 2008, and throughout the epidemic, we've seen work-from-homers resort to the midwest, avoiding pricey coastal cities like NYC and San Francisco.

By no means do I think NYC is dead, nothing will replace this beautiful city that never sleeps, and now is the perfect time to rent or buy when everything is below average value for people who always wanted to come but never could. Once social distance ends, cities will recover. 24/7 sardine-packed subways prove New York isn't designed for isolation.

When buying a home, pay 20% cash and the balance with a mortgage. A mortgage must be incorporated into other costs such as maintenance, brokerage fees, property taxes, etc. If you're stuck on why a home isn't right for you, read here. A mortgage must be paid until the term date. Whether its a 10 year or 30 year fixed mortgage, depending on interest rates, especially now as the 10-year yield is inching towards 1.25%, it's better to refinance in a lower interest rate environment and pay off your debt as well since the Fed will be inching interest rates up following the 10-year eventually to stabilize the economy, but I believe that won't be until after Covid and when businesses like luxury, air travel, and tourism will get bashed.

Bad debt: I guess the contrary must be true. There is no way to profit from the loan in the future, therefore it is just money down the drain.

-Luxury goods
-Credit card debt
-Fancy junk
-Vacations, weddings, parties, etc.

Credit cards and school loans are the two largest risks to the financial security of those under 50 since banks love to compound interest to affect your credit score and make it tougher to take out more loans, not that you should with that much debt anyhow. With a low credit score and heavy debt, banks take advantage of you because you need aid to pay more for their services. Paying back debt is the challenge for most.

Choose Not Chosen

As a financial literacy advocate and blogger, I prefer not to brag, but I will now. I know what to buy and what to avoid. My parents educated me to live a frugal, minimalist stealth wealth lifestyle by choice, not because we had to.

That's the lesson.

The poorest person who shows off with bling is trying to seem rich.

Rich people know garbage is a bad investment. Investing in education is one of the best long-term investments. With information, you can do anything.

Good with money shun some items out of respect and appreciation for what they have.

Less is more.

Instead of copying the Joneses, use what you have. They may look cheerful and stylish in their 20k ft home, yet they may be as broke as OJ Simpson in his 20-bedroom mansion.

Let's look at what appears good to follow and maintain your wealth.

#1: Quality comes before quantity

Being frugal doesn't entail being cheap and cruel. Rich individuals care about relationships and treating others correctly, not impressing them. You don't have to be rich to be good with money, although most are since they don't live the fantasy lifestyle.

Underspending is appreciating what you have.

Many people believe organic food is the same as washing chemical-laden produce. Hopefully. Organic, vegan, fresh vegetables from upstate may be more expensive in the short term, but they will help you live longer and save you money in the long run.

Consider. You'll save thousands a month eating McDonalds 3x a day instead of fresh seafood, veggies, and organic fruit, but your life will be shortened. If you want to save money and die early, go ahead, but I assume we all want to break the world record for longest person living and would rather spend less. Plus, elderly people get tax breaks, medicare, pensions, 401ks, etc. You're living for free, therefore eating fast food forever is a terrible decision.

With a few longer years, you may make hundreds or millions more in the stock market, spend more time with family, and just live.

Folks, health is wealth.

Consider the future benefit, not simply the cash sign. Cheapness is useless.

Same with stuff. Don't stock your closet with fast-fashion you can't wear for years. Buying inexpensive goods that will fail tomorrow is stupid.

Investing isn't only in stocks. You're living. Consume less.

#2: If you cannot afford it twice, you cannot afford it once

I learned this from my dad in 6th grade. I've been lucky to travel, experience things, go to a great university, and conduct many experiments that others without a stable, decent lifestyle can afford.

I didn't live this way because of my parents' paycheck or financial knowledge.

Saving and choosing caused it.

I always bring cash when I shop. I ditch Apple Pay and credit cards since I can spend all I want on even if my account bounces.

Banks are nasty. When you lose it, they profit.

Cash hinders banks' profits. Carrying a big, hefty wallet with cash is lame and annoying, but it's the best method to only spend what you need. Not for vacation, but for tiny daily expenses.

Physical currency lets you know how much you have for lunch or a taxi.

It's physical, thus losing it prevents debt.

If you can't afford it, it will harm more than help.

#3: You really can purchase happiness with money.

If used correctly, yes.

Happiness and satisfaction differ.

It won't bring you fulfillment because you must work hard on your own to help others, but you can travel and meet individuals you wouldn't otherwise meet.

You can meet your future co-worker or strike a deal while waiting an hour in first class for takeoff, or you can meet renowned people at a networking brunch.

Seen a pattern here?

Your time and money are best spent on connections. Not automobiles or firearms. That’s just stuff. It doesn’t make you a better person.

Be different if you've earned less. Instead of trying to win the lotto or become an NFL star for your first big salary, network online for free.

Be resourceful. Sign up for LinkedIn, post regularly, and leave unengaged posts up because that shows power.

Consistency is beneficial.

I did that for a few months and met amazing people who helped me get jobs. Money doesn't create jobs, it creates opportunities.

Resist social media and scammers that peddle false hopes.

Choose wisely.

#4: Avoid gushing over titles and purchasing trash.

As Insider’s Hillary Hoffower reports, “Showing off wealth is no longer the way to signify having wealth. In the US particularly, the top 1% have been spending less on material goods since 2007.”

I checked my closet. No brand comes to mind. I've never worn a brand's logo and rotate 6 white shirts daily. I have my priorities and don't waste money or effort on clothing that won't fit me in a year.

Unless it's your full-time work, clothing shouldn't be part of our mornings.

Lifestyle of stealth wealth. You're so fulfilled that seeming homeless won't hurt your self-esteem.

That's self-assurance.

Extroverts aren't required.

That's irrelevant.

Showing off won't win you friends.

They'll like your personality.

#5: Time is the most valuable commodity.

Being rich doesn't entail working 24/7 M-F.

They work when they are ready to work.

Waking up at 5 a.m. won't make you a millionaire, but it will inculcate diligence and tenacity in you.

You have a busy day yet want to exercise. You can skip the workout or wake up at 4am instead of 6am to do it.

Emotion-driven lazy bums stay in bed.

Those that are accountable keep their promises because they know breaking one will destroy their week.

Since 7th grade, I've worked out at 5am for myself, not to impress others. It gives me greater energy to contribute to others, especially on weekends and holidays.

It's a habit that I have in my life.

Find something that you take seriously and makes you a better person.

As someone who is close to becoming a millionaire and has encountered them throughout my life, I can share with you a few important differences that have shaped who we are as a society based on the weekends:

-Read

-Sleep

-Best time to work with no distractions

-Eat together

-Take walks and be in nature

-Gratitude

-Major family time

-Plan out weeks

-Go grocery shopping because health = wealth

#6. Perspective is Important

Timing the markets will slow down your career. Professors preach scarcity, not abundance. Why should school teach success? They give us bad advice.

If you trust in abundance and luck by attempting and experimenting, growth will come effortlessly. Passion isn't a term that just appears. Mistakes and fresh people help. You can get money. If you don't think it's worth it, you won't.

You don’t have to be wealthy to be good at money, but most are for these reasons.  Rich is a mindset, wealth is power. Prioritize your resources. Invest in yourself, knowing the toughest part is starting.

Thanks for reading!

A reading list for successful people

Elon Musk reads and talks. So, one learns. Many brilliant individuals & amazing literature.

This article recommends 3 Elon Musk novels. All of them helped me succeed. Hope they'll help you.

Douglas Adams's The Hitchhiker's Guide to the Galaxy

Page Count: 193
Rating on Goodreads: 4.23

Arthur Dent is pulled off Earth by a buddy seconds before it's razed for a cosmic motorway. The trio hitchhikes through space and gets into problems.

I initially read Hitchhiker's as a child. To evade my mum, I'd read with a flashlight under the covers. She'd scold at me for not sleeping on school nights when she found out. Oops.

The Hitchhiker's Guide to the Galaxy is lighthearted science fiction.

My favorite book quotes are:

• “Space is big. You won’t believe how vastly, hugely, mind-bogglingly big it is. I mean, you may think it’s a long way down the road to the chemist’s, but that’s just peanuts to space.”

• “Far out in the uncharted backwaters of the unfashionable end of the western spiral arm of the Galaxy lies a small unregarded yellow sun. Orbiting this at a distance of roughly ninety-two million miles is an utterly insignificant little blue-green planet whose ape-descended life forms are so amazingly primitive that they still think digital watches are a pretty neat idea.”

• “On planet Earth, man had always assumed that he was more intelligent than dolphins because he had achieved so much — the wheel, New York, wars, and so on — whilst all the dolphins had ever done was muck about in the water having a good time. But conversely, the dolphins had always believed that they were far more intelligent than man — for precisely the same reasons.”

the Sun Tzu book The Art Of War

Page Count: 273
Rating on Goodreads: 3.97

It's a classic. You may apply The Art of War's ideas to (nearly) every facet of life. Ex:

• Pick your fights.

• Keep in mind that timing is crucial.

• Create a backup plan in case something goes wrong.

• Obstacles provide us a chance to adapt and change.

This book was my first. Since then, I'm a more strategic entrepreneur. Excellent book. And read it ASAP!

My favorite book quotes are:

• “Victorious warriors win first and then go to war, while defeated warriors go to war first and then seek to win.”

• “Engage people with what they expect; it is what they are able to discern and confirms their projections. It settles them into predictable patterns of response, occupying their minds while you wait for the extraordinary moment — that which they cannot anticipate.”

• “If you know the enemy and know yourself, you need not fear the result of a hundred battles. If you know yourself but not the enemy, for every victory gained, you will also suffer a defeat. If you know neither the enemy nor yourself, you will succumb in every battle.”

Peter Thiel's book Zero to One

Page Count: 195
Rating on Goodreads: 4.18

Peter argues the best money-making strategies are typically unproven. Entrepreneurship should never have a defined path to success. Whoever says differently is lying.

Zero to One explores technology and society. Peter is a philosophy major and law school graduate, which informs the work.

Peters' ideas, depth, and intellect stood out in Zero to One. It's a top business book.

My favorite book quotes are:

• “The most valuable businesses of coming decades will be built by entrepreneurs who seek to empower people rather than try to make them obsolete.”

• “The next Bill Gates will not build an operating system. The next Larry Page or Sergey Brin won’t make a search engine. And the next Mark Zuckerberg won’t create a social network. If you are copying these guys, you aren’t learning from them.”

• “If your goal is to never make a mistake in your life, you shouldn’t look for secrets. The prospect of being lonely but right — dedicating your life to something that no one else believes in — is already hard. The prospect of being lonely and wrong can be unbearable.”

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:

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

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

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

4. 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.

Never design a product without explicit metrics and tracking tools.

Imagine driving cross-country without a dashboard. How do you know your school zone speed? Low gas? Without a dashboard, you can't monitor your car. You can't improve what you don't measure, as Peter Drucker said. Product managers must constantly enhance their understanding of their users, how they use their product, and how to improve it for optimum value. Customers will only pay if they consistently acquire value from your product.

I’m Solomon Ayanlakin. I’m a product manager at CredPal, a financial business that offers credit cards and Buy Now Pay Later services. Before falling into product management (like most PMs lol), I self-trained as a data analyst, using Alex the Analyst's YouTube playlists and DannyMas' virtual data internship. This article aims to help product managers, owners, and CXOs understand product metrics, give a methodology for creating them, and execute product experiments to enhance them.

☝🏽Introduction

Product metrics assist companies track product performance from the user's perspective. Metrics help firms decide what to construct (feature priority), how to build it, and the outcome's success or failure. To give the best value to new and existing users, track product metrics.

Why should a product manager monitor metrics?

• to assist your users in having a "aha" moment

• To inform you of which features are frequently used by users and which are not

• To assess the effectiveness of a product feature

• To aid in enhancing client onboarding and retention

• To assist you in identifying areas throughout the user journey where customers are satisfied or dissatisfied

• to determine the percentage of returning users and determine the reasons for their return

📈 What Metrics Ought a Product Manager to Monitor?

What indicators should a product manager watch to monitor product health? The metrics to follow change based on the industry, business stage (early, growth, late), consumer needs, and company goals. A startup should focus more on conversion, activation, and active user engagement than revenue growth and retention. The company hasn't found product-market fit or discovered what features drive customer value.

Depending on your use case, company goals, or business stage, here are some important product metric buckets:

All measurements shouldn't be used simultaneously. It depends on your business goals and what value means for your users, then selecting what metrics to track to see if they get it.

Some KPIs are more beneficial to track, independent of industry or customer type. To prevent recording vanity metrics, product managers must clearly specify the types of metrics they should track. Here's how to segment metrics:

1. The North Star Metric, also known as the Focus Metric, is the indicator and aid in keeping track of the top value you provide to users.

2. Primary/Level 1 Metrics: These metrics should either add to the north star metric or be used to determine whether it is moving in the appropriate direction. They are metrics that support the north star metric.

3. These measures serve as leading indications for your north star and Level 2 metrics. You ought to have been aware of certain problems with your L2 measurements prior to the North star metric modifications.

North Star Metric

This is the key metric. A good north star metric measures customer value. It emphasizes your product's longevity. Many organizations fail to grow because they confuse north star measures with other indicators. A good focus metric should touch all company teams and be tracked forever. If a company gives its customers outstanding value, growth and success are inevitable. How do we measure this value?

A north star metric has these benefits:

• Customer Obsession: It promotes a culture of customer value throughout the entire organization.

• Consensus: Everyone can quickly understand where the business is at and can promptly make improvements, according to consensus.

• Growth: It provides a tool to measure the company's long-term success. Do you think your company will last for a long time?

How can I pick a reliable North Star Metric?

Some fear a single metric. Ensure product leaders can objectively determine a north star metric. Your company's focus metric should meet certain conditions. Here are a few:

1. A good focus metric should reflect value and, as such, should be closely related to the point at which customers obtain the desired value from your product. For instance, the quick delivery to your home is a value proposition of UberEats. The value received from a delivery would be a suitable focal metric to use. While counting orders is alluring, the quantity of successfully completed positive review orders would make a superior north star statistic. This is due to the fact that a client who placed an order but received a defective or erratic delivery is not benefiting from Uber Eats. By tracking core value gain, which is the number of purchases that resulted in satisfied customers, we are able to track not only the total number of orders placed during a specific time period but also the core value proposition.
   

2. Focus metrics need to be quantifiable; they shouldn't only be feelings or states; they need to be actionable. A smart place to start is by counting how many times an activity has been completed.
   

3. A great focus metric is one that can be measured within predetermined time limits; otherwise, you are not measuring at all. The company can improve that measure more quickly by having time-bound focus metrics. Measuring and accounting for progress over set time periods is the only method to determine whether or not you are moving in the right path. You can then evaluate your metrics for today and yesterday. It's generally not a good idea to use a year as a time frame. Ideally, depending on the nature of your organization and the measure you are focusing on, you want to take into account on a daily, weekly, or monthly basis.
   

4. Everyone in the firm has the potential to affect it: A short glance at the well-known AAARRR funnel, also known as the Pirate Metrics, reveals that various teams inside the organization have an impact on the funnel. Ideally, the NSM should be impacted if changes are made to one portion of the funnel. Consider how the growth team in your firm is enhancing customer retention. This would have a good effect on the north star indicator because at this stage, a repeat client is probably being satisfied on a regular basis. Additionally, if the opposite were true and a client churned, it would have a negative effect on the focus metric.
   

5. It ought to be connected to the business's long-term success: The direction of sustainability would be indicated by a good north star metric. A company's lifeblood is product demand and revenue, so it's critical that your NSM points in the direction of sustainability. If UberEats can effectively increase the monthly total of happy client orders, it will remain in operation indefinitely.

Many product teams make the mistake of focusing on revenue. When the bottom line is emphasized, a company's goal moves from giving value to extracting money from customers. A happy consumer will stay and pay for your service. Customer lifetime value always exceeds initial daily, monthly, or weekly revenue.

Great North Star Metrics Examples

🥇 Basic/L1 Metrics:

The NSM is broad and focuses on providing value for users, while the primary metric is product/feature focused and utilized to drive the focus metric or signal its health. The primary statistic is team-specific, whereas the north star metric is company-wide. For UberEats' NSM, the marketing team may measure the amount of quality food vendors who sign up using email marketing. With quality vendors, more orders will be satisfied. Shorter feedback loops and unambiguous team assignments make L1 metrics more actionable and significant in the immediate term.

🥈 Supporting L2 metrics:

These are supporting metrics to the L1 and focus metrics. Location, demographics, or features are examples of L1 metrics. UberEats' supporting metrics might be the number of sales emails sent to food vendors, the number of opens, and the click-through rate. Secondary metrics are low-level and evident, and they relate into primary and north star measurements. UberEats needs a high email open rate to attract high-quality food vendors. L2 is a leading sign for L1.

Where can I find product metrics?

How can I measure in-app usage and activity now that I know what metrics to track? Enter product analytics. Product analytics tools evaluate and improve product management parameters that indicate a product's health from a user's perspective.

Various analytics tools on the market supply product insight. From page views and user flows through A/B testing, in-app walkthroughs, and surveys. Depending on your use case and necessity, you may combine tools to see how users engage with your product. Gainsight, MixPanel, Amplitude, Google Analytics, FullStory, Heap, and Pendo are product tools.

This article isn't sponsored and doesn't market product analytics tools. When choosing an analytics tool, consider the following:

• Tools for tracking your Focus, L1, and L2 measurements

• Pricing

• Adaptations to include external data sources and other products

• Usability and the interface

• Scalability

• Security

An investment in the appropriate tool pays off. To choose the correct metrics to track, you must first understand your business need and what value means to your users. Metrics and analytics are crucial for any tech product's growth. It shows how your business is doing and how to best serve users.

What quarterly bank earnings reveal

Big banks know the economy best. Unless we’re talking about a housing crisis in 2007…

Banks are crucial to the U.S. economy. The Fed, communities, and investments exchange money.

An economy depends on money flow. Banks' views on the economy can affect their decision-making.

Most large banks released quarterly earnings and forward guidance last week. Others were pessimistic about the future.

What Makes Banks Confident

Bank of America's profit decreased 30% year-over-year, but they're optimistic about the economy. Comparatively, they're bullish.

Who banks serve affects what they see. Bank of America supports customers.

They think consumers' future is bright. They believe this for many reasons.

The average customer has decent credit, unless the system is flawed. Bank of America's new credit card and mortgage borrowers averaged 771. New-car loan and home equity borrower averages were 791 and 797.

2008's housing crisis affected people with scores below 620.

Bank of America and the economy benefit from a robust consumer. Major problems can be avoided if individuals maintain spending.

Reasons Other Banks Are Less Confident

Spending requires income. Many companies, mostly in the computer industry, have announced they will slow or freeze hiring. Layoffs are frequently an indication of poor times ahead.

BOA is positive, but investment banks are bearish.

Jamie Dimon, CEO of JPMorgan, outlined various difficulties our economy could confront.

But geopolitical tension, high inflation, waning consumer confidence, the uncertainty about how high rates have to go and the never-before-seen quantitative tightening and their effects on global liquidity, combined with the war in Ukraine and its harmful effect on global energy and food prices are very likely to have negative consequences on the global economy sometime down the road.

That's more headwinds than tailwinds.

JPMorgan, which helps with mergers and IPOs, is less enthusiastic due to these concerns. Incoming headwinds signal drying liquidity, they say. Less business will be done.

Final Reflections

I don't think we're done. Yes, stocks are up 10% from a month ago. It's a long way from old highs.

I don't think the stock market is a strong economic indicator.

Many executives foresee a 2023 recession. According to the traditional definition, we may be in a recession when Q2 GDP statistics are released next week.

Regardless of criteria, I predict the economy will have a terrible year.

Weekly layoffs are announced. Inflation persists. Will prices return to 2020 levels if inflation cools? Perhaps. Still expensive energy. Ukraine's war has global repercussions.

I predict BOA's next quarter earnings won't be as bullish about the consumer's strength.

Old power paradigm blocks new planetary paradigm

The difference between our reality and the media's reality is like a tale of two worlds. The greatest and worst of times, really.

Expanding information demands complex skills and understanding to separate important information from ignorance and crap. And that's just the start of determining the source's aim.

Trust who? We see people trust liars in public and then be destroyed by their decisions. Mistakes may be devastating.

Many give up and don't trust anyone. Reality is a choice, though. Same risks.

We must separate our needs and wants from reality. Needs and wants have rules. Greed and selfishness create an unlivable planet.

Culturally, we know this, but we ignore it as foolish. Selfish and greedy people obtain what they want, while others suffer.

We invade, plunder, rape, and burn. We establish civilizations by institutionalizing an exploitable underclass and denying its existence. These cultural lies promote greed and selfishness despite their destructiveness.

Controlling parts of society institutionalize these lies as fact. Many of each age are willing to gamble on greed because they were taught to see greed and selfishness as principles justified by prosperity.

Our cultural understanding recognizes the long-term benefits of collaboration and sharing. This older understanding generates an increasing tension between greedy people and those who see its planetary effects.

Survival requires distinguishing between global and regional realities. Simple, yet many can't do it. This is the first time human greed has had a global impact.

In the past, conflict stories focused on regional winners and losers. Losers lose, winners win, etc. Powerful people see potential decades of nuclear devastation as local, overblown, and not personally dangerous.

Mutually Assured Destruction (MAD) was a human choice that required people to acquiesce to irrational devastation. This prevented nuclear destruction. Most would refuse.

A dangerous “solution” relies on nuclear trigger-pullers not acting irrationally. Since then, we've collected case studies of sane people performing crazy things in experiments. We've been lucky, but the climate apocalypse could be different.

Climate disaster requires only continuing current behavior. These actions already cause global harm, but that's not a threat. These activities must be viewed differently.

Once grasped, denying planetary facts is hard to accept. Deniers can't think beyond regional power. Seeing planet-scale is unusual.

Decades of indoctrination defining any planetary perspective as un-American implies communal planetary assets are for plundering. The old paradigm limits any other view.

In the same way, the new paradigm sees the old regional power paradigm as a threat to planetary civilization and lifeforms. Insane!

While MAD relied on leaders not acting stupidly to trigger a nuclear holocaust, the delayed climatic holocaust needs correcting centuries of lunacy. We must stop allowing craziness in global leadership.

Nothing in our acknowledged past provides a paradigm for such. Only primitive people have failed to reach our level of sophistication.

Before European colonization, certain North American cultures built sophisticated regional nations but abandoned them owing to authoritarian cruelty and destruction. They were overrun by societies that saw no wrong in perpetual exploitation. David Graeber's The Dawn of Everything is an example of historical rediscovery, which is now crucial.

From the new paradigm's perspective, the old paradigm is irrational, yet it's too easy to see those in it as ignorant or malicious, if not both. These people are both, but the collapsing paradigm they promote is older or more ingrained than we think.

We can't shift that paradigm's view of a dead world. We must eliminate this mindset from our nations' leadership. No other way will preserve the earth.

Change is occurring. As always with tremendous transition, younger people are building the new paradigm.

The old paradigm's disintegration is insane. The ability to detect errors and abandon their sources is more important than age. This is gaining recognition.

The breakdown of the previous paradigm is not due to senile leadership, but to systemic problems that the current, conservative leadership cannot recognize.

Stop following the old paradigm.