More on Web3 & Crypto
Ashraful Islam
4 years ago
Clean API Call With React Hooks
| Photo by Juanjo Jaramillo on Unsplash |
Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.
When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.
The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.
In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.
I’m using a code sandbox for this blog which you can get here.
import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";
export default function App() {
const [posts, setPosts] = useState(null);
const [error, setError] = useState("");
const [loading, setLoading] = useState(false);
useEffect(() => {
handlePosts();
}, []);
const handlePosts = async () => {
setLoading(true);
try {
const result = await axios.get(
"https://jsonplaceholder.typicode.com/posts"
);
setPosts(result.data);
} catch (err) {
setError(err.message || "Unexpected Error!");
} finally {
setLoading(false);
}
};
return (
<div className="App">
<div>
<h1>Posts</h1>
{loading && <p>Posts are loading!</p>}
{error && <p>{error}</p>}
<ul>
{posts?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
</div>
);
}
I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.
Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.
If we try to call another API from the same component then how that would gonna look? Let’s see.
500: Internal Server Error
Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.
Let’s refactor to make the code more reusable with fewer repetitions.
Step 1: Create a Hook for the Redundant API Request Codes
Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?
The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.
500: Internal Server Error
Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.
With hooks in action, let’s change our old codes in App component, like this:
500: Internal Server Error
How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?
Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…
Step 2: One Component Should Take Just One Responsibility
Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.
We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:
import axios from "axios";
const apiClient = axios.create({
// Later read this URL from an environment variable
baseURL: "https://jsonplaceholder.typicode.com"
});
export default apiClient;
All API calls for comments resource will be in the following file:
import client from "./client";
const getComments = () => client.get("/comments");
export default {
getComments
};
All API calls for posts resource are placed in the following file:
import client from "./client";
const getPosts = () => client.get("/posts");
export default {
getPosts
};
Finally, the App component looks like the following:
import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";
export default function App() {
const getPostsApi = useApi(postsApi.getPosts);
const getCommentsApi = useApi(commentsApi.getComments);
useEffect(() => {
getPostsApi.request();
getCommentsApi.request();
}, []);
return (
<div className="App">
{/* Post List */}
<div>
<h1>Posts</h1>
{getPostsApi.loading && <p>Posts are loading!</p>}
{getPostsApi.error && <p>{getPostsApi.error}</p>}
<ul>
{getPostsApi.data?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
{/* Comment List */}
<div>
<h1>Comments</h1>
{getCommentsApi.loading && <p>Comments are loading!</p>}
{getCommentsApi.error && <p>{getCommentsApi.error}</p>}
<ul>
{getCommentsApi.data?.map((comment) => (
<li key={comment.id}>{comment.name}</li>
))}
</ul>
</div>
</div>
);
}
Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.
Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.
So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.
Final Thoughts
The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.
Franz Schrepf
3 years ago
What I Wish I'd Known About Web3 Before Building
Cryptoland rollercoaster
I've lost money in crypto.
Unimportant.
The real issue: I didn’t understand how.
I'm surrounded with winners. To learn more, I created my own NFTs, currency, and DAO.
Web3 is a hilltop castle. Everything is valuable, decentralized, and on-chain.
The castle is Disneyland: beautiful in images, but chaotic with lengthy lines and kids spending too much money on dressed-up animals.
When the throng and businesses are gone, Disneyland still has enchantment.
The Real Story of Web3
NFTs
Scarcity. Scarce NFTs. That's their worth.
Skull. Rare-looking!
Nonsense.
Bored Ape Yacht Club vs. my NFTs?
Marketing.
BAYC is amazing, but not for the reasons people believe. Apecoin and Otherside's art, celebrity following, and innovation? Stunning.
No other endeavor captured the zeitgeist better. Yet how long did you think it took to actually mint the NFTs?
1 hour? Maybe a week for the website?
Minting NFTs is incredibly easy. Kid-friendly. Developers are rare. Think about that next time somebody posts “DevS dO SMt!?”
NFTs will remain popular. These projects are like our Van Goghs and Monets. Still, be wary. It still uses exclusivity and wash selling like the OG art market.
Not all NFTs are art-related.
Soulbound and anonymous NFTs could offer up new use cases. Property rights, privacy-focused ID, open-source project verification. Everything.
NFTs build online trust through ownership.
We just need to evolve from the apes first.
NFTs' superpower is marketing until then.
Crypto currency
What the hell is a token?
99% of people are clueless.
So I invested in both coins and tokens. Same same. Only that they are not.
Coins have their own blockchain and developer/validator community. It's hard.
Creating a token on top of a blockchain? Five minutes.
Most consumers don’t understand the difference, creating an arbitrage opportunity: pretend you’re a serious project without having developers on your payroll.
Few market sites help. Take a look. See any tokens?
There's a hint one click deeper.
Some tokens are legitimate. Some coins are bad investments.
Tokens are utilized for DAO governance and DApp payments. Still, know who's behind a token. They might be 12 years old.
Coins take time and money. The recent LUNA meltdown indicates that currency investing requires research.
DAOs
Decentralized Autonomous Organizations (DAOs) don't work as you assume.
Yes, members can vote.
A productive organization requires more.
I've observed two types of DAOs.
Total decentralization total dysfunction
Centralized just partially. Community-driven.
A core team executes the DAO's strategy and roadmap in successful DAOs. The community owns part of the organization, votes on decisions, and holds the team accountable.
DAOs are public companies.
Amazing.
A shareholder meeting's logistics are staggering. DAOs may hold anonymous, secure voting quickly. No need for intermediaries like banks to chase up every shareholder.
Successful DAOs aren't totally decentralized. Large-scale voting and collaboration have never been easier.
And that’s all that matters.
Scale, speed.
My Web3 learnings
Disneyland is enchanting. Web3 too.
In a few cycles, NFTs may be used to build trust, not clout. Not speculating with coins. DAOs run organizations, not themselves.
Finally, some final thoughts:
NFTs will be a very helpful tool for building trust online. NFTs are successful now because of excellent marketing.
Tokens are not the same as coins. Look into any project before making a purchase. Make sure it isn't run by three 9-year-olds piled on top of one another in a trench coat, at the very least.
Not entirely decentralized, DAOs. We shall see a future where community ownership becomes the rule rather than the exception once we acknowledge this fact.
Crypto Disneyland is a rollercoaster with loops that make you sick.
Always buckle up.
Have fun!
Stephen Moore
3 years ago
Web 2 + Web 3 = Web 5.
Monkey jpegs and shitcoins have tarnished Web3's reputation. Let’s move on.
Web3 was called "the internet's future."
Well, 'crypto bros' shouted about it loudly.
As quickly as it arrived to be the next internet, it appears to be dead. It's had scandals, turbulence, and crashes galore:
Web 3.0's cryptocurrencies have crashed. Bitcoin's all-time high was $66,935. This month, Ethereum fell from $2130 to $1117. Six months ago, the cryptocurrency market peaked at $3 trillion. Worst is likely ahead.
Gas fees make even the simplest Web3 blockchain transactions unsustainable.
Terra, Luna, and other dollar pegs collapsed, hurting crypto markets. Celsius, a crypto lender backed by VCs and Canada's second-largest pension fund, and Binance, a crypto marketplace, have withheld money and coins. They're near collapse.
NFT sales are falling rapidly and losing public interest.
Web3 has few real-world uses, like most crypto/blockchain technologies. Web3's image has been tarnished by monkey profile pictures and shitcoins while failing to become decentralized (the whole concept is controlled by VCs).
The damage seems irreparable, leaving Web3 in the gutter.
Step forward our new saviour — Web5
Fear not though, as hero awaits to drag us out of the Web3 hellscape. Jack Dorsey revealed his plan to save the internet quickly.
Dorsey has long criticized Web3, believing that VC capital and silicon valley insiders have created a centralized platform. In a tweet that upset believers and VCs (he was promptly blocked by Marc Andreessen), Dorsey argued, "You don't own "Web3." VCs and LPs do. Their incentives prevent it. It's a centralized organization with a new name.
Dorsey announced Web5 on June 10 in a very Elon-like manner. Block's TBD unit will work on the project (formerly Square).
Web5's pitch is that users will control their own data and identity. Bitcoin-based. Sound familiar? The presentation pack's official definition emphasizes decentralization. Web5 is a decentralized web platform that enables developers to write decentralized web apps using decentralized identifiers, verifiable credentials, and decentralized web nodes, returning ownership and control over identity and data to individuals.
Web5 would be permission-less, open, and token-less. What that means for Earth is anyone's guess. Identity. Ownership. Blockchains. Bitcoin. Different.
Web4 appears to have been skipped, forever destined to wish it could have shown the world what it could have been. (It was probably crap.) As this iteration combines Web2 and Web3, simple math and common sense add up to 5. Or something.
Dorsey and his team have had this idea simmering for a while. Daniel Buchner, a member of Block's Decentralized Identity team, said, "We're finishing up Web5's technical components."
Web5 could be the project that decentralizes the internet. It must be useful to users and convince everyone to drop the countless Web3 projects, products, services, coins, blockchains, and websites being developed as I write this.
Web5 may be too late for Dorsey and the incoming flood of creators.
Web6 is planned!
The next months and years will be hectic and less stable than the transition from Web 1.0 to Web 2.0.
Web1 was around 1991-2004.
Web2 ran from 2004 to 2021. (though the Web3 term was first used in 2014, it only really gained traction years later.)
Web3 lasted a year.
Web4 is dead.
Silicon Valley billionaires are turning it into a startup-style race, each disrupting the next iteration until they crack it. Or destroy it completely.
Web5 won't last either.
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Chris Moyse
3 years ago
Sony and LEGO raise $2 billion for Epic Games' metaverse
‘Kid-friendly’ project holds $32 billion valuation
Epic Games announced today that it has raised $2 billion USD from Sony Group Corporation and KIRKBI (holding company of The LEGO Group). Both companies contributed $1 billion to Epic Games' upcoming ‘metaverse' project.
“We need partners who share our vision as we reimagine entertainment and play. Our partnership with Sony and KIRKBI has found this,” said Epic Games CEO Tim Sweeney. A new metaverse will be built where players can have fun with friends and brands create creative and immersive experiences, as well as creators thrive.
Last week, LEGO and Epic Games announced their plans to create a family-friendly metaverse where kids can play, interact, and create in digital environments. The service's users' safety and security will be prioritized.
With this new round of funding, Epic Games' project is now valued at $32 billion.
“Epic Games is known for empowering creators large and small,” said KIRKBI CEO Sren Thorup Srensen. “We invest in trends that we believe will impact the world we and our children will live in. We are pleased to invest in Epic Games to support their continued growth journey, with a long-term focus on the future metaverse.”
Epic Games is expected to unveil its metaverse plans later this year, including its name, details, services, and release date.
Pen Magnet
3 years ago
Why Google Staff Doesn't Work
Sundar Pichai unveiled Simplicity Sprint at Google's latest all-hands conference.
To boost employee efficiency.
Not surprising. Few envisioned Google declaring a productivity drive.
Sunder Pichai's speech:
“There are real concerns that our productivity as a whole is not where it needs to be for the head count we have. Help me create a culture that is more mission-focused, more focused on our products, more customer focused. We should think about how we can minimize distractions and really raise the bar on both product excellence and productivity.”
The primary driver driving Google's efficiency push is:
Google's efficiency push follows 13% quarterly revenue increase. Last year in the same quarter, it was 62%.
Market newcomers may argue that the previous year's figure was fuelled by post-Covid reopening and growing consumer spending. Investors aren't convinced. A promising company like Google can't afford to drop so quickly.
Google’s quarterly revenue growth stood at 13%, against 62% in last year same quarter.
Google isn't alone. In my recent essay regarding 2025 programmers, I warned about the economic downturn's effects on FAAMG's workforce. Facebook had suspended hiring, and Microsoft had promised hefty bonuses for loyal staff.
In the same article, I predicted Google's troubles. Online advertising, especially the way Google and Facebook sell it using user data, is over.
FAAMG and 2nd rung IT companies could be the first to fall without Post-COVID revival and uncertain global geopolitics.
Google has hardly ever discussed effectiveness:
Apparently openly.
Amazon treats its employees like robots, even in software positions. It has significant turnover and a terrible reputation as a result. Because of this, it rarely loses money due to staff productivity.
Amazon trumps Google. In reality, it treats its employees poorly.
Google was the founding father of the modern-day open culture.
Larry and Sergey Google founded the IT industry's Open Culture. Silicon Valley called Google's internal democracy and transparency near anarchy. Management rarely slammed decisions on employees. Surveys and internal polls ensured everyone knew the company's direction and had a vote.
20% project allotment (weekly free time to build own project) was Google's open-secret innovation component.
After Larry and Sergey's exit in 2019, this is Google's first profitability hurdle. Only Google insiders can answer these questions.
Would Google's investors compel the company's management to adopt an Amazon-style culture where the developers are treated like circus performers?
If so, would Google follow suit?
If so, how does Google go about doing it?
Before discussing Google's likely plan, let's examine programming productivity.
What determines a programmer's productivity is simple:
How would we answer Google's questions?
As a programmer, I'm more concerned about Simplicity Sprint's aftermath than its economic catalysts.
Large organizations don't care much about quarterly and annual productivity metrics. They have 10-year product-launch plans. If something seems horrible today, it's likely due to someone's lousy judgment 5 years ago who is no longer in the blame game.
Deconstruct our main question.
How exactly do you change the culture of the firm so that productivity increases?
How can you accomplish that without affecting your capacity to profit? There are countless ways to increase output without decreasing profit.
How can you accomplish this with little to no effect on employee motivation? (While not all employers care about it, in this case we are discussing the father of the open company culture.)
How do you do it for a 10-developer IT firm that is losing money versus a 1,70,000-developer organization with a trillion-dollar valuation?
When implementing a large-scale organizational change, success must be carefully measured.
The fastest way to do something is to do it right, no matter how long it takes.
You require clearly-defined group/team/role segregation and solid pass/fail matrices to:
You can give performers rewards.
Ones that are average can be inspired to improve
Underachievers may receive assistance or, in the worst-case scenario, rehabilitation
As a 20-year programmer, I associate productivity with greatness.
Doing something well, no matter how long it takes, is the fastest way to do it.
Let's discuss a programmer's productivity.
Why productivity is a strange term in programming:
Productivity is work per unit of time.
Money=time This is an economic proverb. More hours worked, more pay. Longer projects cost more.
As a buyer, you desire a quick supply. As a business owner, you want employees who perform at full capacity, creating more products to transport and boosting your profits.
All economic matrices encourage production because of our obsession with it. Productivity is the only organic way a nation may increase its GDP.
Time is money — is not just a proverb, but an economical fact.
Applying the same productivity theory to programming gets problematic. An automating computer. Its capacity depends on the software its master writes.
Today, a sophisticated program can process a billion records in a few hours. Creating one takes a competent coder and the necessary infrastructure. Learning, designing, coding, testing, and iterations take time.
Programming productivity isn't linear, unlike manufacturing and maintenance.
Average programmers produce code every day yet miss deadlines. Expert programmers go days without coding. End of sprint, they often surprise themselves by delivering fully working solutions.
Reversing the programming duties has no effect. Experts aren't needed for productivity.
These patterns remind me of an XKCD comic.
Programming productivity depends on two factors:
The capacity of the programmer and his or her command of the principles of computer science
His or her productive bursts, how often they occur, and how long they last as they engineer the answer
At some point, productivity measurement becomes Schrödinger’s cat.
Product companies measure productivity using use cases, classes, functions, or LOCs (lines of code). In days of data-rich source control systems, programmers' merge requests and/or commits are the most preferred yardstick. Companies assess productivity by tickets closed.
Every organization eventually has trouble measuring productivity. Finer measurements create more chaos. Every measure compares apples to oranges (or worse, apples with aircraft.) On top of the measuring overhead, the endeavor causes tremendous and unnecessary stress on teams, lowering their productivity and defeating its purpose.
Macro productivity measurements make sense. Amazon's factory-era management has done it, but at great cost.
Google can pull it off if it wants to.
What Google meant in reality when it said that employee productivity has decreased:
When Google considers its employees unproductive, it doesn't mean they don't complete enough work in the allotted period.
They can't multiply their work's influence over time.
Programmers who produce excellent modules or products are unsure on how to use them.
The best data scientists are unable to add the proper parameters in their models.
Despite having a great product backlog, managers struggle to recruit resources with the necessary skills.
Product designers who frequently develop and A/B test newer designs are unaware of why measures are inaccurate or whether they have already reached the saturation point.
Most ignorant: All of the aforementioned positions are aware of what to do with their deliverables, but neither their supervisors nor Google itself have given them sufficient authority.
So, Google employees aren't productive.
How to fix it?
Business analysis: White suits introducing novel items can interact with customers from all regions. Track analytics events proactively, especially the infrequent ones.
SOLID, DRY, TEST, and AUTOMATION: Do less + reuse. Use boilerplate code creation. If something already exists, don't implement it yourself.
Build features-building capabilities: N features are created by average programmers in N hours. An endless number of features can be built by average programmers thanks to the fact that expert programmers can produce 1 capability in N hours.
Work on projects that will have a positive impact: Use the same algorithm to search for images on YouTube rather than the Mars surface.
Avoid tasks that can only be measured in terms of time linearity at all costs (if a task can be completed in N minutes, then M copies of the same task would cost M*N minutes).
In conclusion:
Software development isn't linear. Why should the makers be measured?
Notation for The Big O
I'm discussing a new way to quantify programmer productivity. (It applies to other professions, but that's another subject)
The Big O notation expresses the paradigm (the algorithmic performance concept programmers rot to ace their Google interview)
Google (or any large corporation) can do this.
Sort organizational roles into categories and specify their impact vs. time objectives. A CXO role's time vs. effect function, for instance, has a complexity of O(log N), meaning that if a CEO raises his or her work time by 8x, the result only increases by 3x.
Plot the influence of each employee over time using the X and Y axes, respectively.
Add a multiplier for Y-axis values to the productivity equation to make business objectives matter. (Example values: Support = 5, Utility = 7, and Innovation = 10).
Compare employee scores in comparable categories (developers vs. devs, CXOs vs. CXOs, etc.) and reward or help employees based on whether they are ahead of or behind the pack.
After measuring every employee's inventiveness, it's straightforward to help underachievers and praise achievers.
Example of a Big(O) Category:
If I ran Google (God forbid, its worst days are far off), here's how I'd classify it. You can categorize Google employees whichever you choose.
The Google interview truth:
O(1) < O(log n) < O(n) < O(n log n) < O(n^x) where all logarithmic bases are < n.
O(1): Customer service workers' hours have no impact on firm profitability or customer pleasure.
CXOs Most of their time is spent on travel, strategic meetings, parties, and/or meetings with minimal floor-level influence. They're good at launching new products but bad at pivoting without disaster. Their directions are being followed.
Devops, UX designers, testers Agile projects revolve around deployment. DevOps controls the levers. Their automation secures results in subsequent cycles.
UX/UI Designers must still prototype UI elements despite improved design tools.
All test cases are proportional to use cases/functional units, hence testers' work is O(N).
Architects Their effort improves code quality. Their right/wrong interference affects product quality and rollout decisions even after the design is set.
Core Developers Only core developers can write code and own requirements. When people understand and own their labor, the output improves dramatically. A single character error can spread undetected throughout the SDLC and cost millions.
Core devs introduce/eliminate 1000x bugs, refactoring attempts, and regression. Following our earlier hypothesis.
The fastest way to do something is to do it right, no matter how long it takes.
Conclusion:
Google is at the liberal extreme of the employee-handling spectrum
Microsoft faced an existential crisis after 2000. It didn't choose Amazon's data-driven people management to revitalize itself.
Instead, it entrusted developers. It welcomed emerging technologies and opened up to open source, something it previously opposed.
Google is too lax in its employee-handling practices. With that foundation, it can only follow Amazon, no matter how carefully.
Any attempt to redefine people's measurements will affect the organization emotionally.
The more Google compares apples to apples, the higher its chances for future rebirth.
Josef Cruz
3 years ago
My friend worked in a startup scam that preys on slothful individuals.
He explained everything.
A drinking buddy confessed. Alexander. He says he works at a startup based on a scam, which appears too clever to be a lie.
Alexander (assuming he developed the story) or the startup's creator must have been a genius.
This is the story of an Internet scam that targets older individuals and generates tens of millions of dollars annually.
The business sells authentic things at 10% of their market value. This firm cannot be lucrative, but the entrepreneur has a plan: monthly subscriptions to a worthless service.
The firm can then charge the customer's credit card to settle the gap. The buyer must subscribe without knowing it. What's their strategy?
How does the con operate?
Imagine a website with a split homepage. On one page, the site offers an attractive goods at a ridiculous price (from 1 euro to 10% of the product's market worth).
Same product, but with a stupid monthly subscription. Business is unsustainable. They buy overpriced products and resell them too cheaply, hoping customers will subscribe to a useless service.
No customer will want this service. So they create another illegal homepage that hides the monthly subscription offer. After an endless scroll, a box says Yes, I want to subscribe to a service that costs x dollars per month.
Unchecking the checkbox bugs. When a customer buys a product on this page, he's enrolled in a monthly subscription. Not everyone should see it because it's illegal. So what does the startup do?
A page that varies based on the sort of website visitor, a possible consumer or someone who might be watching the startup's business
Startup technicians make sure the legal page is displayed when the site is accessed normally. Typing the web address in the browser, using Google, etc. The page crashes when buying a goods, preventing the purchase.
This avoids the startup from selling a product at a loss because the buyer won't subscribe to the worthless service and charge their credit card each month.
The illegal page only appears if a customer clicks on a Google ad, indicating interest in the offer.
Alexander says that a banker, police officer, or anyone else who visits the site (maybe for control) will only see a valid and buggy site as purchases won't be possible.
The latter will go to the site in the regular method (by typing the address in the browser, using Google, etc.) and not via an online ad.
Those who visit from ads are likely already lured by the site's price. They'll be sent to an illegal page that requires a subscription.
Laziness is humanity's secret weapon. The ordinary person ignores tiny monthly credit card charges. The subscription lasts around a year before the customer sees an unexpected deduction.
After-sales service (ASS) is useful in this situation.
After-sales assistance begins when a customer notices slight changes on his credit card, usually a year later.
The customer will search Google for the direct debit reference. How he'll complain to after-sales service.
It's crucial that ASS appears in the top 4/5 Google search results. This site must be clear, and offer chat, phone, etc., he argues.
The pigeon must be comforted after waking up. The customer learns via after-sales service that he subscribed to a service while buying the product, which justifies the debits on his card.
The customer will then clarify that he didn't intend to make the direct debits. The after-sales care professional will pretend to listen to the customer's arguments and complaints, then offer to unsubscribe him for free because his predicament has affected him.
In 99% of cases, the consumer is satisfied since the after-sales support unsubscribed him for free, and he forgets the debited amounts.
The remaining 1% is split between 0.99% who are delighted to be reimbursed and 0.01%. We'll pay until they're done. The customer should be delighted, not object or complain, and keep us beneath the radar (their situation is resolved, the rest, they don’t care).
It works, so we expand our thinking.
Startup has considered industrialization. Since this fraud is working, try another. Automate! So they used a site generator (only for product modifications), underpaid phone operators for after-sales service, and interns for fresh product ideas.
The company employed a data scientist. This has allowed the startup to recognize that specific customer profiles can be re-registered in the database and that it will take X months before they realize they're subscribing to a worthless service. Customers are re-subscribed to another service, then unsubscribed before realizing it.
Alexander took months to realize the deception and leave. Lawyers and others apparently threatened him and former colleagues who tried to talk about it.
The startup would have earned prizes and competed in contests. He adds they can provide evidence to any consumer group, media, police/gendarmerie, or relevant body. When I submitted my information to the FBI, I was told, "We know, we can't do much.", he says.