I can't believe they’d even think it works!

Developers are usually interviewed before being hired, right? Every organization wants candidates who meet their needs. But they also want to avoid fraud.

There are cheaters in every field. Only two come to mind for the hiring process:

• Lying on a resume.

• Cheating on an online test.

Recently, I observed another one. One of my coworkers invited me to replace another developer during an online interview! I was astonished, but it’s not new.

The specifics

My ex-colleague recently texted me. No one from your former office will ever approach you after a year unless they need something.

Which was the case. My coworker said his wife needed help as a programmer. I was glad someone asked for my help, but I'm still a junior programmer.

Then he informed me his wife was selected for a fantastic job interview. He said he could help her with the online test, but he needed someone to help with the online interview.

Okay, I guess. Preparing for an online interview is beneficial. But then he said she didn't need to be ready. She needed someone to take her place.

I told him it wouldn't work. Every remote online interview I've ever seen required an open camera.

What followed surprised me. She'd ask to turn off the camera, he said.

I asked why.

He told me if an applicant is unwell, the interviewer may consider an off-camera interview. His wife will say she's sick and prefers no camera.

The plan left me speechless. I declined politely. He insisted and promised $2k if she got the job.

I felt insulted and told him if he persisted, I'd inform his office. I was furious. Later, I apologized and told him to stop.

I'm not sure what they did after that

I'm not sure if they found someone or listened to me. They probably didn't. How would she do the job if she even got it?

It's an internship, he said. With great pay, though. What should an intern do?

I suggested she do the interview alone. Even if she failed, she'd gain confidence and valuable experience.

Conclusion

Many interviewees cheat. My profession is vital to me, thus I'd rather improve my abilities and apply honestly. It's part of my identity.

Am I truthful? Most professionals are not. They fabricate their CVs. Often.

When you support interview cheating, you encourage more cheating! When someone cheats, another qualified candidate may not obtain the job.

One day, that could be you or me.

4 Pricey Tools That Are Valuable

I pay based on ROI (return on investment).

If a $20/month tool or $500 online course doubles my return, I'm in.

Investing helps me build wealth.

Canva Pro

I initially refused to pay.

My course content needed updating a few months ago. My Google Docs text looked cleaner and more professional in Canva.

I've used it to:

• product cover pages

• eBook covers

• Product page infographics

See my Google Sheets vs. Canva product page graph.

Google Sheets vs Canva

Yesterday, I used it to make a LinkedIn video thumbnail. It took less than 5 minutes and improved my video.

In 30 hours, the video had 39,000 views.

Here's more.

HypeFury

Hypefury rocks!

It builds my brand as I sleep. What else?

Because I'm traveling this weekend, I planned tweets for 10 days. It took me 80 minutes.

So while I travel or am absent, my content mill keeps producing.

Also I like:

• I can reach hundreds of people thanks to auto-DMs. I utilize it to advertise freebies; for instance, leave an emoji remark to receive my checklist. And they automatically receive a message in their DM.

• Scheduled Retweets: By appearing in a different time zone, they give my tweet a second chance.

It helps me save time and expand my following, so that's my favorite part.

It’s also super neat:

Zoom Pro

My course involves weekly and monthly calls for alumni.

Google Meet isn't great for group calls. The interface isn't great.

Zoom Pro is expensive, and the monthly payments suck, but it's necessary.

It gives my students a smooth experience.

Previously, we'd do 40-minute meetings and then reconvene.

Zoom's free edition limits group calls to 40 minutes.

This wouldn't be a good online course if I paid hundreds of dollars.

So I felt obligated to help.

YouTube Premium

My laptop has an ad blocker.

I bought an iPad recently.

When you're self-employed and work from home, the line between the two blurs. My bed is only 5 steps away!

When I read or watched videos on my laptop, I'd slide into work mode. Only option was to view on phone, which is awkward.

YouTube premium handles it. No more advertisements and I can listen on the move.

3 Expensive Tools That Aren't Valuable

Marketing strategies are sometimes aimed to make you feel you need 38474 cool features when you don’t.

Certain tools are useless.

I found it useless.

Depending on your needs. As a writer and creator, I get no return.

They could for other jobs.

Shield Analytics

It tracks LinkedIn stats, like:

• follower growth

• trend chart for impressions

• Engagement, views, and comment stats for posts

• and much more.

Middle-tier creator costs $12/month.

I got a 25% off coupon but canceled my free trial before writing this. It's not worth the discount.

Why?

LinkedIn provides free analytics. See:

Not thorough and won't show top posts.

I don't need to see my top posts because I love experimenting with writing.

Slack Premium

Slack was my classroom. Slack provided me a premium trial during the prior cohort.

I skipped it.

Sure, voice notes are better than a big paragraph. I didn't require pro features.

Marketing methods sometimes make you think you need 38474 amazing features. Don’t fall for it.

Calendly Pro

This may be worth it if you get many calls.

I avoid calls. During my 9-5, I had too many pointless calls.

I don't need:

• ability to schedule calls for 15, 30, or 60 minutes: I just distribute each link separately.

• I have a Gumroad consultation page with a payment option.

• follow-up emails: I hardly ever make calls, so

• I just use one calendar, therefore I link to various calendars.

I'll admit, the integrations are cool. Not for me.

If you're a coach or consultant, the features may be helpful. Or book meetings.

Conclusion

Investing is spending to make money.

Use my technique — put money in tools that help you make money. This separates it from being an investment instead of an expense.

Try free versions of these tools before buying them since everyone else is.

I've spent the last 10 years of my career mastering time management. I've tried different approaches and followed multiple people and sources. My knowledge is summarized.

Great people, including entrepreneurs, master time management. I learned time management in college. I was studying Computer Science and Finance and leading Tanzanian students in Bangalore, India. I had 24 hours per day to do this and enjoy campus. I graduated and received several awards. I've learned to maximize my time. These tips and tools help me finish quickly.

Eisenhower-Box

I don't remember when I read the article. James Clear, one of my favorite bloggers, introduced me to the Eisenhower Box, which I've used for years. Eliminate waste to master time management. By grouping your activities by importance and urgency, the tool helps you prioritize what matters and drop what doesn't. If it's urgent, do it. Delegate if it's urgent but not necessary. If it's important but not urgent, reschedule it; otherwise, drop it. I integrated the tool with Trello to manage my daily tasks. Since 2007, I've done this.

James Clear's article mentions Eisenhower Box.

Essentialism rules

Greg McKeown's book Essentialism introduced me to disciplined pursuit of less. I once wrote about this. I wasn't sure what my career's real opportunities and distractions were. A non-essentialist thinks everything is essential; you want to be everything to everyone, and your life lacks satisfaction. Poor time management starts it all. Reading and applying this book will change your life.

Essential vs non-essential

Life Calendar

Most of us make corporate calendars. Peter Njonjo, founder of Twiga Foods, said he manages time by putting life activities in his core calendars. It includes family retreats, weddings, and other events. He joked that his wife always complained to him to avoid becoming a calendar item. It's key. "Time Masters" manages life's four burners, not just work and corporate life. There's no "work-life balance"; it's life.

Health, Family, Work, and Friends.

The Brutal No

In a culture where people want to look good, saying "NO" to a favor request seems rude. In reality, the crime is breaking a promise. "Time Masters" have mastered "NO".  More "YES" means less time, and more "NO" means more time for tasks and priorities. Brutal No doesn't mean being mean to your coworkers; it means explaining kindly and professionally that you have other priorities.

To-Do vs. MITs

Most people are productive with a routine to-do list. You can't be effective by just checking boxes on a To-do list. When was the last time you completed all of your daily tasks? Never. You must replace the to-do list with Most Important Tasks (MITs). MITs allow you to focus on the most important tasks on your list. You feel progress and accomplishment when you finish these tasks. MITs don't include ad-hoc emails, meetings, etc.

Journal Mapped

Most people don't journal or plan their day in the developing South. I've learned to plan my day in my journal over time. I have multiple sections on one page: MITs (things I want to accomplish that day), Other Activities (stuff I can postpone), Life (health, faith, and family issues), and Pop-Ups (things that just pop up). I leave the next page blank for notes. I reflected on the blocks to identify areas to improve the next day. You will have bad days, but at least you'll realize it was due to poor time management.

Buy time/delegate

Time or money? When you make enough money, you lose time to make more. The smart buy "Time." I resisted buying other people's time for years. I regret not hiring an assistant sooner. Learn to buy time from others and pay for time-consuming tasks. Sometimes you think you're saving money by doing things yourself, but you're actually losing money.

This post is a summary. See the full post here.

Python Volatility-Based Catapult Indicator

As a catapult, this technical indicator uses three systems: Volatility (the fulcrum), Momentum (the propeller), and a Directional Filter (Acting as the support). The goal is to get a signal that predicts volatility acceleration and direction based on historical patterns. We want to know when the market will move. and where. This indicator outperforms standard indicators.

Knowledge must be accessible to everyone. This is why my new publications Contrarian Trading Strategies in Python and Trend Following Strategies in Python now include free PDF copies of my first three books (Therefore, purchasing one of the new books gets you 4 books in total). GitHub-hosted advanced indications and techniques are in the two new books above.

The Foundation: Volatility

The Catapult predicts significant changes with the 21-period Relative Volatility Index.

The Average True Range, Mean Absolute Deviation, and Standard Deviation all assess volatility. Standard Deviation will construct the Relative Volatility Index.

Standard Deviation is the most basic volatility. It underpins descriptive statistics and technical indicators like Bollinger Bands. Before calculating Standard Deviation, let's define Variance.

Variance is the squared deviations from the mean (a dispersion measure). We take the square deviations to compel the distance from the mean to be non-negative, then we take the square root to make the measure have the same units as the mean, comparing apples to apples (mean to standard deviation standard deviation). Variance formula:

As stated, standard deviation is:

# The function to add a number of columns inside an array
def adder(Data, times):
    
    for i in range(1, times + 1):
    
        new_col = np.zeros((len(Data), 1), dtype = float)
        Data = np.append(Data, new_col, axis = 1)
        
    return Data

# The function to delete a number of columns starting from an index
def deleter(Data, index, times):
    
    for i in range(1, times + 1):
    
        Data = np.delete(Data, index, axis = 1)
        
    return Data
    
# The function to delete a number of rows from the beginning
def jump(Data, jump):
    
    Data = Data[jump:, ]
    
    return Data

# Example of adding 3 empty columns to an array
my_ohlc_array = adder(my_ohlc_array, 3)

# Example of deleting the 2 columns after the column indexed at 3
my_ohlc_array = deleter(my_ohlc_array, 3, 2)

# Example of deleting the first 20 rows
my_ohlc_array = jump(my_ohlc_array, 20)

# Remember, OHLC is an abbreviation of Open, High, Low, and Close and it refers to the standard historical data file

def volatility(Data, lookback, what, where):
    
  for i in range(len(Data)):

     try:

        Data[i, where] = (Data[i - lookback + 1:i + 1, what].std())
     except IndexError:
        pass
        
  return Data

The RSI is the most popular momentum indicator, and for good reason—it excels in range markets. Its 0–100 range simplifies interpretation. Fame boosts its potential.

The more traders and portfolio managers look at the RSI, the more people will react to its signals, pushing market prices. Technical Analysis is self-fulfilling, therefore this theory is obvious yet unproven.

RSI is determined simply. Start with one-period pricing discrepancies. We must remove each closing price from the previous one. We then divide the smoothed average of positive differences by the smoothed average of negative differences. The RSI algorithm converts the Relative Strength from the last calculation into a value between 0 and 100.

def ma(Data, lookback, close, where): 
    
    Data = adder(Data, 1)
    
    for i in range(len(Data)):
           
            try:
                Data[i, where] = (Data[i - lookback + 1:i + 1, close].mean())
            
            except IndexError:
                pass
            
    # Cleaning
    Data = jump(Data, lookback)
    
    return Data
def ema(Data, alpha, lookback, what, where):
    
    alpha = alpha / (lookback + 1.0)
    beta  = 1 - alpha
    
    # First value is a simple SMA
    Data = ma(Data, lookback, what, where)
    
    # Calculating first EMA
    Data[lookback + 1, where] = (Data[lookback + 1, what] * alpha) + (Data[lookback, where] * beta)    
 
    # Calculating the rest of EMA
    for i in range(lookback + 2, len(Data)):
            try:
                Data[i, where] = (Data[i, what] * alpha) + (Data[i - 1, where] * beta)
        
            except IndexError:
                pass
            
    return Datadef rsi(Data, lookback, close, where, width = 1, genre = 'Smoothed'):
    
    # Adding a few columns
    Data = adder(Data, 7)
    
    # Calculating Differences
    for i in range(len(Data)):
        
        Data[i, where] = Data[i, close] - Data[i - width, close]
     
    # Calculating the Up and Down absolute values
    for i in range(len(Data)):
        
        if Data[i, where] > 0:
            
            Data[i, where + 1] = Data[i, where]
            
        elif Data[i, where] < 0:
            
            Data[i, where + 2] = abs(Data[i, where])
            
    # Calculating the Smoothed Moving Average on Up and Down
    absolute values        
                             
    lookback = (lookback * 2) - 1 # From exponential to smoothed
    Data = ema(Data, 2, lookback, where + 1, where + 3)
    Data = ema(Data, 2, lookback, where + 2, where + 4)
    
    # Calculating the Relative Strength
    Data[:, where + 5] = Data[:, where + 3] / Data[:, where + 4]
    
    # Calculate the Relative Strength Index
    Data[:, where + 6] = (100 - (100 / (1 + Data[:, where + 5])))  
    
    # Cleaning
    Data = deleter(Data, where, 6)
    Data = jump(Data, lookback)

    return Data

def relative_volatility_index(Data, lookback, close, where):

    # Calculating Volatility
    Data = volatility(Data, lookback, close, where)
    
    # Calculating the RSI on Volatility
    Data = rsi(Data, lookback, where, where + 1) 
    
    # Cleaning
    Data = deleter(Data, where, 1)
    
    return Data

The Arm Section: Speed

The Catapult predicts momentum direction using the 14-period Relative Strength Index.

As a reminder, the RSI ranges from 0 to 100. Two levels give contrarian signals:

• A positive response is anticipated when the market is deemed to have gone too far down at the oversold level 30, which is 30.

• When the market is deemed to have gone up too much, at overbought level 70, a bearish reaction is to be expected.

Comparing the RSI to 50 is another intriguing use. RSI above 50 indicates bullish momentum, while below 50 indicates negative momentum.

The direction-finding filter in the frame

The Catapult's directional filter uses the 200-period simple moving average to keep us trending. This keeps us sane and increases our odds.

Moving averages confirm and ride trends. Its simplicity and track record of delivering value to analysis make them the most popular technical indicator. They help us locate support and resistance, stops and targets, and the trend. Its versatility makes them essential trading tools.

This is the plain mean, employed in statistics and everywhere else in life. Simply divide the number of observations by their total values. Mathematically, it's:

We defined the moving average function above. Create the Catapult indication now.

Indicator of the Catapult

The indicator is a healthy mix of the three indicators:

• The first trigger will be provided by the 21-period Relative Volatility Index, which indicates that there will now be above average volatility and, as a result, it is possible for a directional shift.

• If the reading is above 50, the move is likely bullish, and if it is below 50, the move is likely bearish, according to the 14-period Relative Strength Index, which indicates the likelihood of the direction of the move.

• The likelihood of the move's direction will be strengthened by the 200-period simple moving average. When the market is above the 200-period moving average, we can infer that bullish pressure is there and that the upward trend will likely continue. Similar to this, if the market falls below the 200-period moving average, we recognize that there is negative pressure and that the downside is quite likely to continue.

lookback_rvi = 21
lookback_rsi = 14
lookback_ma  = 200
my_data = ma(my_data, lookback_ma, 3, 4)
my_data = rsi(my_data, lookback_rsi, 3, 5)
my_data = relative_volatility_index(my_data, lookback_rvi, 3, 6)

Two-handled overlay indicator Catapult. The first exhibits blue and green arrows for a buy signal, and the second shows blue and red for a sell signal.

The chart below shows recent EURUSD hourly values.

def signal(Data, rvi_col, signal):
    
    Data = adder(Data, 10)
        
    for i in range(len(Data)):
            
        if Data[i,     rvi_col] < 30 and \
           Data[i - 1, rvi_col] > 30 and \
           Data[i - 2, rvi_col] > 30 and \
           Data[i - 3, rvi_col] > 30 and \
           Data[i - 4, rvi_col] > 30 and \
           Data[i - 5, rvi_col] > 30:
               
               Data[i, signal] = 1
                           
    return Data

Signals are straightforward. The indicator can be utilized with other methods.

my_data = signal(my_data, 6, 7)

Lumiwealth shows how to develop all kinds of algorithms. I recommend their hands-on courses in algorithmic trading, blockchain, and machine learning.

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.

After you find a trading method or approach, follow these steps:

• Put emotions aside and adopt an analytical perspective.

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

• Try improving it and performing a forward test if you notice any possibility.

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

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

After checking the aforementioned, monitor the plan because market dynamics may change and render it unprofitable.

900K impressions, 8K clicks, and $$$ orders…

I recently started dropshipping. Now that I own my business and can charge it as a business expense, it feels less like money wasted if it doesn't work. I also made t-shirts to sell. I intended to open a t-shirt store and had many designs on a hard drive. I read that Tiktok advertising had a high conversion rate and low cost because they were new. According to many, the advertising' cost/efficiency ratio would plummet and become as bad as Google or Facebook Ads. Now felt like the moment to try Tiktok marketing and dropshipping. I work in marketing for a SaaS firm and have seen how poorly ads perform. I wanted to try it alone.

I set up $250 and ran advertising for a week. Before that, I made my own products, store, and marketing. In this post, I'll show you my process and results.

Setting up the store

Dropshipping is a sort of retail business in which the manufacturer ships the product directly to the client through an online platform maintained by a seller. The seller takes orders but has no stock. The manufacturer handles all orders. This no-stock concept increases profitability and flexibility.

In my situation, I used previous t-shirt designs to make my own product. I didn't want to handle order fulfillment logistics, so I looked for a way to print my designs on demand, ship them, and handle order tracking/returns automatically. So I found Printful.

I needed to connect my backend and supplier to a storefront so visitors could buy. 99% of dropshippers use Shopify, but I didn't want to master the difficult application. I wanted a one-day project. I'd previously worked with Big Cartel, so I chose them.

Big Cartel doesn't collect commissions on sales, simply a monthly flat price ($9.99 to $19.99 depending on your plan).

After opening a Big Cartel account, I uploaded 21 designs and product shots, then synced each product with Printful.

Developing the ads

I mocked up my designs on cool people photographs from placeit.net, a great tool for creating product visuals when you don't have a studio, camera gear, or models to wear your t-shirts.

I opened an account on the website and had advertising visuals within 2 hours.

Because my designs are simple (black design on white t-shirt), I chose happy, stylish people on plain-colored backdrops. After that, I had to develop an animated slideshow.

Because I'm a graphic designer, I chose to use Adobe Premiere to create animated Tiktok advertising.

Premiere is a fancy video editing application used for more than advertisements. Premiere is used to edit movies, not social media marketing. I wanted this experiment to be quick, so I got 3 social media ad templates from motionarray.com and threw my visuals in. All the transitions and animations were pre-made in the files, so it only took a few hours to compile. The result:

I downloaded 3 different soundtracks for the videos to determine which would convert best.

After that, I opened a Tiktok business account, uploaded my films, and inserted ad info. They went live within one hour.

The (poor) outcomes

As a European company, I couldn't deliver ads in the US. All of my advertisements' material (title, description, and call to action) was in English, hence they continued getting rejected in Europe for countries that didn't speak English. There are a lot of them:

I lost a lot of quality traffic, but I felt that if the images were engaging, people would check out the store and buy my t-shirts. I was wrong.

• 51,071 impressions on Day 1. 0 orders after 411 clicks

• 114,053 impressions on Day 2. 1.004 clicks and no orders

• Day 3: 987 clicks, 103,685 impressions, and 0 orders

• 101,437 impressions on Day 4. 0 orders after 963 clicks

• 115,053 impressions on Day 5. 1,050 clicks and no purchases

• 125,799 impressions on day 6. 1,184 clicks, no purchases

• 115,547 impressions on Day 7. 1,050 clicks and no purchases

• 121,456 impressions on day 8. 1,083 clicks, no purchases

• 47,586 impressions on Day 9. 419 Clicks. No orders

My overall conversion rate for video advertisements was 0.9%. TikTok's paid ad formats all result in strong engagement rates (ads average 3% to 12% CTR to site), therefore a 1 to 2% CTR should have been doable.

My one-week experiment yielded 8,151 ad clicks but no sales. Even if 0.1% of those clicks converted, I should have made 8 sales. Even companies with horrible web marketing would get one download or trial sign-up for every 8,151 clicks. I knew that because my advertising were in English, I had no impressions in the main EU markets (France, Spain, Italy, Germany), and that this impacted my conversion potential. I still couldn't believe my numbers.

I dug into the statistics and found that Tiktok's stats didn't match my store traffic data.

Looking more closely at the numbers

My ads were approved on April 26 but didn't appear until April 27. My store dashboard showed 440 visitors but 1,004 clicks on Tiktok. This happens often while tracking campaign results since different platforms handle comparable user activities (click, view) differently. In online marketing, residual data won't always match across tools.

My data gap was too large. Even if half of the 1,004 persons who clicked closed their browser or left before the store site loaded, I would have gained 502 visitors. The significant difference between Tiktok clicks and Big Cartel store visits made me suspicious. It happened all week:

• Day 1: 440 store visits and 1004 ad clicks

• Day 2: 482 store visits, 987 ad clicks

• 3rd day: 963 hits on ads, 452 store visits

• 443 store visits and 1,050 ad clicks on day 4.

• Day 5: 459 store visits and 1,184 ad clicks

• Day 6: 430 store visits and 1,050 ad clicks

• Day 7: 409 store visits and 1,031 ad clicks

• Day 8: 166 store visits and 418 ad clicks

The disparity wasn't related to residual data or data processing. The disparity between visits and clicks looked regular, but I couldn't explain it.

After the campaign concluded, I discovered all my creative assets (the videos) had a 0% CTR and a $0 expenditure in a separate dashboard. Whether it's a dashboard reporting issue or a budget allocation bug, online marketers shouldn't see this.

Tiktok can present any stats they want on their dashboard, just like any other platform that runs advertisements to promote content to its users. I can't verify that 895,687 individuals saw and clicked on my ad. I invested $200 for what appears to be around 900K impressions, which is an excellent ROI. No one bought a t-shirt, even an unattractive one, out of 900K people?

Would I do it again?

Nope. Whether I didn't make sales because Tiktok inflated the dashboard numbers or because I'm horrible at producing advertising and items that sell, I’ll stick to writing content and making videos. If setting up a business and ads in a few days was all it took to make money online, everyone would do it.

Video advertisements and dropshipping aren't dead. As long as the internet exists, people will click ads and buy stuff. Converting ads and selling stuff takes a lot of work, and I want to focus on other things.

I had always wanted to try dropshipping and I’m happy I did, I just won’t stick to it because that’s not something I’m interested in getting better at.

If I want to sell t-shirts again, I'll avoid Tiktok advertisements and find another route.