My ego is so huge it won't fit through the door.

I don't know how I feel about it. I should be excited. Many of you have this exact dream to publish a book with a well-known book publisher and get a juicy advance.

Let me dissect how I'm thinking about it to help you.

How it happened

An email comes in. A generic "can we put a backlink on your website and get a freebie" email.

Almost deleted it.

Then I noticed the logo. It seemed shady. I found the URL. Check. I searched the employee's LinkedIn. Legit. I avoided middlemen. Check.

Mixed feelings. LinkedIn hasn't valued my writing for years. I'm just a guy in an unironed t-shirt whose content they sell advertising against.

They get big dollars. I get $0 and a few likes, plus some email subscribers.

Still, I felt adrenaline for hours.

I texted a few friends to see how they felt. I wrapped them.

Messages like "No shocker. You're entertaining online." I didn't like praises, so I blushed.

The thrill faded after hours. Who knows?

Most authors desire this chance.

"You entitled piece of crap, Denning!"

You may think so. Okay. My job is to stand on the internet and get bananas thrown at me.

I approached writing backwards. More important than a book deal was a social media audience converted to an email list.

Romantic authors think backward. They hope a fantastic book will land them a deal and an audience.

Rarely occurs. So I never pursued it. It's like permission-seeking or the lottery.

Not being a professional writer, I've never written a good book. I post online for fun and to express my opinions.

Writing is therapeutic. I overcome mental illness and rebuilt my life this way. Without blogging, I'd be dead.

I've always dreamed of staying alive and doing something I love, not getting a book contract. Writing is my passion. I'm a winner without a book deal.

Why I was given a book deal

You may assume I received a book contract because of my views or follows. Nope.

They gave me a deal because they like my writing style. I've heard this for eight years.

Several authors agree. One asked me to improve their writer's voice.

Takeaway: highlight your writer's voice.

What if they discover I'm writing incompetently?

An edited book is published. It's edited.

I need to master writing mechanics, thus this concerns me. I need help with commas and sentence construction.

I must learn verb, noun, and adjective. Seriously.

Writing a book may reveal my imposter status to a famous publisher. Imagine the email

"It happened again. He doesn't even know how to spell. He thinks 'less' is the correct word, not 'fewer.' Are you sure we should publish his book?"

Fears stink.

I'm capable of blogging. Even listicles. So what?

Writing for a major publisher feels advanced.

I only blog. I'm good at listicles. Digital media executives have criticized me for this.

• It is allegedly clickbait.

• Or it is following trends.

• Alternately, growth hacking.

Never. I learned copywriting to improve my writing.

Apple, Amazon, and Tesla utilize copywriting to woo customers. Whoever thinks otherwise is the wisest person in the room.

Old-schoolers loathe copywriters.

Their novels sell nothing.

They assume their elitist version of writing is better and that the TikTok generation will invest time in random writing with no subheadings and massive walls of text they can't read on their phones.

I'm terrified of book proposals.

My friend's book proposal suggestion was contradictory and made no sense.

They told him to compose another genre. This book got three Amazon reviews. Is that a good model?

The process disappointed him. I've heard other book proposal horror stories. Tim Ferriss' book "The 4-Hour Workweek" was criticized.

Because he has thick skin, his book came out. He wouldn't be known without that.

I hate book proposals.

An ongoing commitment

Writing a book is time-consuming.

I appreciate time most. I want to focus on my daughter for the next few years. I can't recreate her childhood because of a book.

No idea how parents balance kids' goals.

My silly face in a bookstore. Really?

Genuine thought.

I don't want my face in bookstores. I fear fame. I prefer anonymity.

I want to purchase a property in a bad Australian area, then piss off and play drums. Is bookselling worth it?

Are there even bookstores anymore?

(Except for Ryan Holiday's legendary Painted Porch Bookshop in Texas.)

What's most important about books

Many were duped.

Tweets and TikTok hopscotch vids are their future. Short-form content creates devoted audiences that buy newsletter subscriptions.

Books=depth.

Depth wins (if you can get people to buy your book). Creating a book will strengthen my reader relationships.

It's cheaper than my classes, so more people can benefit from my life lessons.

A deeper justification for writing a book

Mind wandered.

If I write this book, my daughter will follow it. "Look what you can do, love, when you ignore critics."

That's my favorite.

I'll be her best leader and teacher. If her dad can accomplish this, she can too.

My kid can read my book when I'm gone to remember her loving father.

Last paragraph made me cry.

The positive

This book thing might make me sound like Karen.

The upside is... Building in public, like I have with online writing, attracts the right people.

Proof-of-work over proposals, beautiful words, or huge aspirations. If you want a book deal, try writing online instead of the old manner.

Next steps

No idea.

I'm a rural Aussie. Writing a book in the big city is intimidating. Will I do it? Lots to think about. Right now, some level of reflection and gratitude feels most appropriate.

Sometimes when you don't feel worthy, it gives you the greatest lessons. That's how I feel about getting offered this book deal.

Perhaps you can relate.

Software can change any company.

Software is becoming essential. Everyone should consider how software affects their lives and others'.

Software on your phone, tablet, or computer offers many new options. We're experts in enough ways now.

Software Business Ideas will be popular by 2023.

ERP Programs

ERP software meets rising demand.

ERP solutions automate and monitor tasks that large organizations, businesses, and even schools would struggle to do manually.

ERP software could reach $49 billion by 2024.

CRM Program

CRM software is a must-have for any customer-focused business.

Having an open mind about your business services and products allows you to change platforms.

Another company may only want your CRM service.

Medical software

Healthcare facilities need reliable, easy-to-use software.

EHRs, MDDBs, E-Prescribing, and more are software options.

The global medical software market could reach $11 billion by 2025, and mobile medical apps may follow.

Presentation Software in the Cloud

SaaS presentation tools are great.

They're easy to use, comprehensive, and full of traditional Software features.

In today's cloud-based world, these solutions make life easier for people. We don't know about you, but we like it.

Software for Project Management

People began working remotely without signs or warnings before the 2020 COVID-19 pandemic.

Many organizations found it difficult to track projects and set deadlines.

With PMP software tools, teams can manage remote units and collaborate effectively.

App for Blockchain-Based Invoicing

This advanced billing and invoicing solution is for businesses and freelancers.

These blockchain-based apps can calculate taxes, manage debts, and manage transactions.

Intelligent contracts help blockchain track transactions more efficiently. It speeds up and improves invoice generation.

Software for Business Communications

Internal business messaging is tricky.

Top business software tools for communication can share files, collaborate on documents, host video conferences, and more.

Payroll Automation System

Software development also includes developing an automated payroll system.

These software systems reduce manual tasks for timely employee payments.

These tools help enterprise clients calculate total wages quickly, simplify tax calculations, improve record-keeping, and support better financial planning.

System for Detecting Data Leaks

Both businesses and individuals value data highly. Yahoo's data breach is dangerous because of this.

This area of software development can help people protect their data.

You can design an advanced data loss prevention system.

AI-based Retail System

AI-powered shopping systems are popular. The systems analyze customers' search and purchase patterns and store history and are equipped with a keyword database.

These systems offer many customers pre-loaded products.

AI-based shopping algorithms also help users make purchases.

Software for Detecting Plagiarism

Software can help ensure your projects are original and not plagiarized.

These tools detect plagiarized content that Google, media, and educational institutions don't like.

Software for Converting Audio to Text

Machine Learning converts speech to text automatically.

These programs can quickly transcribe cloud-based files.

Software for daily horoscopes

Daily and monthly horoscopes will continue to be popular.

Software platforms that can predict forecasts, calculate birth charts, and other astrology resources are good business ideas.

E-learning Programs

Traditional study methods are losing popularity as virtual schools proliferate and physical space shrinks.

Khan Academy online courses are the best way to keep learning.

Online education portals can boost your learning. If you want to start a tech startup, consider creating an e-learning program.

Conclusion

Software is booming. There's never been a better time to start a software development business, with so many people using computers and smartphones. This article lists eight business ideas for 2023. Consider these ideas if you're just starting out or looking to expand.

Niches are rich, as the adage goes.

Micro SaaS requires a great micro-niche; otherwise, it's merely plain old SaaS with a large audience.

Instead of targeting broad markets with few identifying qualities, specialise down to a micro-niche. How would you target these users?

Better go tiny. You'll locate and engage new consumers more readily and serve them better with a customized solution.

Imagine you're a real estate lawyer looking for a case management solution. Because it's so specific to you, you'd be lured to this link:

instead of below:

Next, locate mini SaaS niches that could work for you. You're not yet looking at the problems/solutions in these areas, merely shortlisting them.

The market should be growing, not shrinking

We shouldn't design apps for a declining niche. We intend to target stable or growing niches for the next 5 to 10 years.

If it's a developing market, you may be able to claim a stake early. You must balance this strategy with safer, longer-established niches (accountancy, law, health, etc).

First Micro SaaS apps I designed were for Merch By Amazon creators, a burgeoning niche. I found this niche when searching for passive income.

Graphic designers and entrepreneurs post their art to Amazon to sell on clothes. When Amazon sells their design, they get a royalty. Since 2015, this platform and specialty have grown dramatically.

Amazon doesn't publicize the amount of creators on the platform, but it's possible to approximate by looking at Facebook groups, Reddit channels, etc.

I could see the community growing week by week, with new members joining. Merch was an up-and-coming niche, and designers made money when their designs sold. All I had to do was create tools that let designers focus on making bestselling designs.

Look at the Google Trends graph below to see how this niche has evolved and when I released my apps and resigned my job.

Are the users able to afford the tools?

Who's your average user? Consumer or business? Is your solution budgeted?

If they're students, you'll struggle to convince them to subscribe to your study-system app (ahead of video games and beer).

Let's imagine you designed a Shopify plugin that emails customers when a product is restocked. If your plugin just needs 5 product sales a month to justify its cost, everyone wins (just be mindful that one day Shopify could potentially re-create your plugins functionality within its core offering making your app redundant ).

Do specialized users buy tools? If so, that's comforting. If not, you'd better have a compelling value proposition for your end customer if you're the first.

This should include how much time or money your program can save or make the user.

Are you able to understand the Micro SaaS market?

Ideally, you're already familiar about the industry/niche. Maybe you're fixing a challenge from your day job or freelance work.

If not, evaluate how long it would take to learn the niche's users. Health & Fitness is easier to relate to and understand than hedge fund derivatives trading.

Competing in these complex (and profitable) fields might offer you an edge.

B2C, B2M, or B2B?

Consider your user base's demographics. Will you target businesses, consumers, or both? Let's examine the different consumer types:

• B2B refers to business-to-business transactions where customers are other businesses. UpVoty, Plutio, Slingshot, Salesforce, Atlassian, and Hubspot are a few examples of SaaS, ranging from Micro SaaS to SaaS.

• Business to Consumer (B2C), in which your clients are people who buy things. For instance, Duolingo, Canva, and Nomad List.

• For instance, my tool KDP Wizard has a mixed user base of publishing enterprises and also entrepreneurial consumers selling low-content books on Amazon. This is a case of business to many (B2M), where your users are a mixture of businesses and consumers. There is a large SaaS called Dropbox that offers both personal and business plans.

Targeting a B2B vs. B2C niche is very different. The sales cycle differs.

• A B2B sales staff must make cold calls to potential clients' companies. Long sales, legal, and contractual conversations are typically required for each business to get the go-ahead. The cost of obtaining a new customer is substantially more than it is for B2C, despite the fact that the recurring fees are significantly higher.

• Since there is typically only one individual making the purchasing decision, B2C signups are virtually always self-service with reduced recurring fees. Since there is typically no outbound sales staff in B2C, acquisition costs are significantly lower than in B2B.

User Characteristics for B2B vs. B2C

Consider where your niche's users congregate if you don't already have a presence there.

B2B users frequent LinkedIn and Twitter. B2C users are on Facebook/Instagram/Reddit/Twitter, etc.

Churn is higher in B2C because consumers haven't gone through all the hoops of a B2B sale. Consumers are more unpredictable than businesses since they let their bank cards exceed limitations or don't update them when they expire.

With a B2B solution, there's a contractual arrangement and the firm will pay the subscription as long as they need it.

Depending on how you feel about the above (sales team vs. income vs. churn vs. targeting), you'll know which niches to pursue.

You ought to respect potential customers.

Would you hang out with customers?

You'll connect with users at conferences (in-person or virtual), webinars, seminars, screenshares, Facebook groups, emails, support calls, support tickets, etc.

If talking to a niche's user base makes you shudder, you're in for a tough road. Whether they're demanding or dull, avoid them if possible.

Merch users are mostly graphic designers, side hustlers, and entrepreneurs. These laid-back users embrace technologies that assist develop their Merch business.

I discovered there was only one annual conference for this specialty, held in Seattle, USA. I decided to organize a conference for UK/European Merch designers, despite never having done so before.

Hosting a conference for over 80 people was stressful, and it turned out to be much bigger than expected, with attendees from the US, Europe, and the UK.

I met many specialized users, built relationships, gained trust, and picked their brains in person. Many of the attendees were already Merch Wizard users, so hearing their feedback and ideas for future features was invaluable.

focused and specific

Instead of building for a generic, hard-to-reach market, target a specific group.

I liken it to fishing in a little, hidden pond. This small pond has only one species of fish, so you learn what bait it likes. Contrast that with trawling for hours to catch as many fish as possible, even if some aren't what you want.

In the case management scenario, it's difficult to target leads because several niches could use the app. Where do your potential customers hang out? Your generic solution: No.

It's easier to join a community of Real Estate Lawyers and see if your software can answer their pain points.

My Success with Micro SaaS

In my case, my Micro SaaS apps have been my chrome extensions. Since I launched them, they've earned me an average $10k MRR, allowing me to quit my lousy full-time job years ago.

I sold my apps after scaling them for a life-changing lump amount. Since then, I've helped unfulfilled software developers escape the 9-5 through Micro SaaS.

Whether it's a profitable side hustle or a liferaft to quit their job and become their own Micro SaaS boss.

Having built my apps to the point where I could quit my job, then scaled and sold them, I feel I can share my skills with software developers worldwide.

Read my free guide on self-funded SaaS to discover more about Micro SaaS, or download your own copy. 12 chapters cover everything from Idea to Exit.

Watch my YouTube video to learn how to construct a Micro SaaS app in 10 steps.

Python Heatmap Technical Indicator

Heatmaps provide an instant overview. They can be used with correlations or to predict reactions or confirm the trend in trading. This article covers RSI heatmap creation.

The Market System

Market regime:

• Bullish trend: The market tends to make higher highs, which indicates that the overall trend is upward.

• Sideways: The market tends to fluctuate while staying within predetermined zones.

• Bearish trend: The market has the propensity to make lower lows, indicating that the overall trend is downward.

Most tools detect the trend, but we cannot predict the next state. The best way to solve this problem is to assume the current state will continue and trade any reactions, preferably in the trend.

If the EURUSD is above its moving average and making higher highs, a trend-following strategy would be to wait for dips before buying and assuming the bullish trend will continue.

Indicator of Relative Strength

J. Welles Wilder Jr. introduced the RSI, a popular and versatile technical indicator. Used as a contrarian indicator to exploit extreme reactions. Calculating the default RSI usually involves these steps:

• Determine the difference between the closing prices from the prior ones.

• Distinguish between the positive and negative net changes.

• Create a smoothed moving average for both the absolute values of the positive net changes and the negative net changes.

• Take the difference between the smoothed positive and negative changes. The Relative Strength RS will be the name we use to describe this calculation.

• To obtain the RSI, use the normalization formula shown below for each time step.

The 13-period RSI and black GBPUSD hourly values are shown above. RSI bounces near 25 and pauses around 75. Python requires a four-column OHLC array for RSI coding.

import numpy as np
def add_column(data, times):
    
    for i in range(1, times + 1):
    
        new = np.zeros((len(data), 1), dtype = float)
        
        data = np.append(data, new, axis = 1)
    return data
def delete_column(data, index, times):
    
    for i in range(1, times + 1):
    
        data = np.delete(data, index, axis = 1)
    return data
def delete_row(data, number):
    
    data = data[number:, ]
    
    return data
def ma(data, lookback, close, position): 
    
    data = add_column(data, 1)
    
    for i in range(len(data)):
           
            try:
                
                data[i, position] = (data[i - lookback + 1:i + 1, close].mean())
            
            except IndexError:
                
                pass
            
    data = delete_row(data, lookback)
    
    return data
def smoothed_ma(data, alpha, lookback, close, position):
    
    lookback = (2 * lookback) - 1
    
    alpha = alpha / (lookback + 1.0)
    
    beta  = 1 - alpha
    
    data = ma(data, lookback, close, position)
    data[lookback + 1, position] = (data[lookback + 1, close] * alpha) + (data[lookback, position] * beta)
    for i in range(lookback + 2, len(data)):
        
            try:
                
                data[i, position] = (data[i, close] * alpha) + (data[i - 1, position] * beta)
        
            except IndexError:
                
                pass
            
    return data
def rsi(data, lookback, close, position):
    
    data = add_column(data, 5)
    
    for i in range(len(data)):
        
        data[i, position] = data[i, close] - data[i - 1, close]
     
    for i in range(len(data)):
        
        if data[i, position] > 0:
            
            data[i, position + 1] = data[i, position]
            
        elif data[i, position] < 0:
            
            data[i, position + 2] = abs(data[i, position])
            
    data = smoothed_ma(data, 2, lookback, position + 1, position + 3)
    data = smoothed_ma(data, 2, lookback, position + 2, position + 4)
    data[:, position + 5] = data[:, position + 3] / data[:, position + 4]
    
    data[:, position + 6] = (100 - (100 / (1 + data[:, position + 5])))
    data = delete_column(data, position, 6)
    data = delete_row(data, lookback)
    return data

Make sure to focus on the concepts and not the code. You can find the codes of most of my strategies in my books. The most important thing is to comprehend the techniques and strategies.

My weekly market sentiment report uses complex and simple models to understand the current positioning and predict the future direction of several major markets. Check out the report here:

Using the Heatmap to Find the Trend

RSI trend detection is easy but useless. Bullish and bearish regimes are in effect when the RSI is above or below 50, respectively. Tracing a vertical colored line creates the conditions below. How:

• When the RSI is higher than 50, a green vertical line is drawn.

• When the RSI is lower than 50, a red vertical line is drawn.

Zooming out yields a basic heatmap, as shown below.

Plot code:

def indicator_plot(data, second_panel, window = 250):
    fig, ax = plt.subplots(2, figsize = (10, 5))
    sample = data[-window:, ]
    for i in range(len(sample)):
        ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)  
        if sample[i, 3] > sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)  
        if sample[i, 3] < sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
        if sample[i, 3] == sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
    ax[0].grid() 
    for i in range(len(sample)):
        if sample[i, second_panel] > 50:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)  
        if sample[i, second_panel] < 50:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)  
    ax[1].grid()
indicator_plot(my_data, 4, window = 500)

Call RSI on your OHLC array's fifth column. 4. Adjusting lookback parameters reduces lag and false signals. Other indicators and conditions are possible.

Another suggestion is to develop an RSI Heatmap for Extreme Conditions.

Contrarian indicator RSI. The following rules apply:

• Whenever the RSI is approaching the upper values, the color approaches red.

• The color tends toward green whenever the RSI is getting close to the lower values.

Zooming out yields a basic heatmap, as shown below.

Plot code:

import matplotlib.pyplot as plt
def indicator_plot(data, second_panel, window = 250):
    fig, ax = plt.subplots(2, figsize = (10, 5))
    sample = data[-window:, ]
    for i in range(len(sample)):
        ax[0].vlines(x = i, ymin = sample[i, 2], ymax = sample[i, 1], color = 'black', linewidth = 1)  
        if sample[i, 3] > sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 0], ymax = sample[i, 3], color = 'black', linewidth = 1.5)  
        if sample[i, 3] < sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
        if sample[i, 3] == sample[i, 0]:
            ax[0].vlines(x = i, ymin = sample[i, 3], ymax = sample[i, 0], color = 'black', linewidth = 1.5)  
    ax[0].grid() 
    for i in range(len(sample)):
        if sample[i, second_panel] > 90:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'red', linewidth = 1.5)  
        if sample[i, second_panel] > 80 and sample[i, second_panel] < 90:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'darkred', linewidth = 1.5)  
        if sample[i, second_panel] > 70 and sample[i, second_panel] < 80:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'maroon', linewidth = 1.5)  
        if sample[i, second_panel] > 60 and sample[i, second_panel] < 70:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'firebrick', linewidth = 1.5) 
        if sample[i, second_panel] > 50 and sample[i, second_panel] < 60:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5) 
        if sample[i, second_panel] > 40 and sample[i, second_panel] < 50:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'grey', linewidth = 1.5) 
        if sample[i, second_panel] > 30 and sample[i, second_panel] < 40:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'lightgreen', linewidth = 1.5)
        if sample[i, second_panel] > 20 and sample[i, second_panel] < 30:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'limegreen', linewidth = 1.5) 
        if sample[i, second_panel] > 10 and sample[i, second_panel] < 20:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'seagreen', linewidth = 1.5)  
        if sample[i, second_panel] > 0 and sample[i, second_panel] < 10:
            ax[1].vlines(x = i, ymin = 0, ymax = 100, color = 'green', linewidth = 1.5)
    ax[1].grid()
indicator_plot(my_data, 4, window = 500)

Dark green and red areas indicate imminent bullish and bearish reactions, respectively. RSI around 50 is grey.

Summary

To conclude, my goal is to contribute to objective technical analysis, which promotes more transparent methods and strategies that must be back-tested before implementation.

Technical analysis will lose its reputation as subjective and unscientific.

When you find a trading strategy or technique, follow these steps:

• Put emotions aside and adopt a critical mindset.

• Test it in the past under conditions and simulations taken from real life.

• Try optimizing it and performing a forward test if you find any potential.

• Transaction costs and any slippage simulation should always be included in your tests.

• Risk management and position sizing should always be considered in your tests.

After checking the above, monitor the strategy because market dynamics may change and make it unprofitable.