How a misplaced item may change your outlook

Losing your wallet means life stops. Money vanishes. No credit. Your identity is unverifiable. As you check your pockets for the missing object, you can't drive. You can't borrow a library book.

Last seen? intuitively. Every kid asks this, including yours. However, you know where you lost it: On the Providence River cycling trail. While pedaling vigorously, the wallet dropped out of your back pocket and onto the pavement.

A woman you know—your son's art teacher—says it will be returned. Faith.

You want that faith. Losing a wallet is all-consuming. You must presume it has been stolen and is being used to buy every diamond and non-fungible token on the market. Your identity may have been used to open bank accounts and fake passports. Because he used your license address, a ski mask-wearing man may be driving slowly past your house.

As you delete yourself by canceling cards, these images run through your head. You wait in limbo for replacements. Digital text on the DMV website promises your new license will come within 60 days and be approved by local and state law enforcement. In the following two months, your only defense is a screenshot.

Your wallet was ordinary. A worn, overstuffed leather rectangle. You understand how tenuous your existence has always been since you've never lost a wallet. You barely breathe without your documents.

Ironically, you wore a wallet-belt chain. You adored being a 1993 slacker for 15 years. Your wife just convinced you last year that your office job wasn't professional. You nodded and hid the chain.

Never lost your wallet. Until now.

Angry. Feeling stupid. How could you drop something vital? Why? Is the world cruel? No more dumb luck. You're always one pedal-stroke from death.

Then you get a call: We have your wallet.

Local post office, not cops.

The clerk said someone returned it. Due to trying to identify you, it's a chaos. It has your cards but no cash.

Your automobile screeches down the highway. You yell at the windshield, amazed. Submitted. Art teacher was right. Have some trust.

You thank the postmaster. You ramble through the story. The clerk doesn't know the customer, simply a neighborhood Good Samaritan. You wish you could thank that person for lifting your spirits.

You get home, beaming with gratitude. You thumb through your wallet, amazed that it’s all intact. Then you dig out your chain and reattach it.

Because even faith could use a little help.

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.

I placed a link on HackerNews and got 300 signups in a week. This post explains what happened.

Product Concept

The product is DbSchemaLibrary. A library of Database Schema.

I'm not sure where this idea originated from. Very fast. Build fast, fail fast, test many ideas, and one will be a hit. I tried it. Let's try it anyway, even though it'll probably fail. I finished The Lean Startup book and wanted to use it.

Database job bores me. Important! I get drowsy working on it. Someone must do it. I remember this happening once. I needed examples at the time. Something similar to Recall (my other project) that I can copy — or at least use as a reference.

Frequently googled. Many tabs open. The results were useless. I raised my hand and agreed to construct the database myself.

It resurfaced. I decided to do something.

Due Diligence

Lean Startup emphasizes validated learning. Everything the startup does should result in learning. I may build something nobody wants otherwise. That's what happened to Recall.

So, I wrote a business plan document. This happens before I code. What am I solving? What is my proposed solution? What is the leap of faith between the problem and solution? Who would be my target audience?

My note:

In my previous project, I did the opposite!

I wrote my expectations after reading the book's advice.

“Failure is a prerequisite to learning. The problem with the notion of shipping a product and then seeing what happens is that you are guaranteed to succeed — at seeing what happens.” — The Lean Startup book

These are successful metrics. If I don't reach them, I'll drop the idea and try another. I didn't understand numbers then. Below are guesses. But it’s a start!

I then wrote the project's What and Why. I'll use this everywhere. Before, I wrote a different pitch each time. I thought certain words would be better. I felt the audience might want something unusual.

Occasionally, this works. I'm unsure if it's a good idea. No stats, just my writing-time opinion. Writing every time is time-consuming and sometimes hazardous. Having a copy saved me duplication.

I can measure and learn from performance.

Last, I identified communities that might demand the product. This became an exercise in creativity.

The MVP

So now it’s time to build.

A MVP can test my assumptions. Business may learn from it. Not low-quality. We should learn from the tiniest thing.

I like the example of how Dropbox did theirs. They assumed that if the product works, people will utilize it. How can this be tested without a quality product? They made a movie demonstrating the software's functionality. Who knows how much functionality existed?

So I tested my biggest assumption. Users want schema references. How can I test if users want to reference another schema? I'd love this. Recall taught me that wanting something doesn't mean others do.

I made an email-collection landing page. Describe it briefly. Reference library. Each email sender wants a reference. They're interested in the product. Few other reasons exist.

Header and footer were skipped. No name or logo. DbSchemaLibrary is a name I thought of after the fact. 5-minute logo. I expected a flop. Recall has no users after months of labor. What could happen to a 2-day project?

I didn't compromise learning validation. How many visitors sign up? To draw a conclusion, I must track these results.

Posting Time

Now that the job is done, gauge interest. The next morning, I posted on all my channels. I didn't want to be spammy, therefore it required more time.

I made sure each channel had at least one fan of this product. I also answer people's inquiries in the channel.

My list stinks. Several channels wouldn't work. The product's target market isn't there. Posting there would waste our time. This taught me to create marketing channels depending on my persona.

Statistics! What actually happened

My favorite part! 23 channels received the link.

I stopped posting to Discord despite its high conversion rate. I eliminated some channels because they didn't fit. According to the numbers, some users like it. Most users think it's spam.

I was skeptical. And 12 people viewed it.

I didn't expect much attention on a startup subreddit. I'll likely examine Reddit further in the future. As I have enough info, I didn't post much. Time for the next validated learning

No comment. The post had few views, therefore the numbers are low.

The targeted people come next.

I'm a Toptal freelancer. There's a member-only Slack channel. Most people can't use this marketing channel, but you should! It's not as spectacular as discord's 27% conversion rate. But I think the users here are better.

I don’t really have a following anywhere so this isn’t something I can leverage.

The best yet. 10% is converted. With more data, I expect to attain a 10% conversion rate from other channels. Stable number.

This number required some work. Did you know that people use many different clients to read HN?

Unknowns

Untrackable views and signups abound. 1136 views and 135 signups are untraceable. It's 11%. I bet much of that came from Hackernews.

Overall Statistics

The 7-day signup-to-visit ratio was 17%. (Hourly data points)

First-day percentages were lower, which is noteworthy. Initially, it was little above 10%. The HN post started getting views then.

When traffic drops, the number reaches just around 20%. More individuals are interested in the connection. hn.algolia.com sent 2 visitors. This means people are searching and finding my post.

Interesting discoveries

1. HN post struggled till the US woke up.

11am UTC. After an hour, it lost popularity. It seemed over. 7 signups converted 13%. Not amazing, but I would've thought ahead.

After 4pm UTC, traffic grew again. 4pm UTC is 9am PDT. US awakened. 10am PDT saw 512 views.

2. The product was highlighted in a newsletter.

I found Revue references when gathering data. Newsletter platform. Someone posted the newsletter link. 37 views and 3 registrations.

3. HN numbers are extremely reliable

I don't have a time-lapse graph (yet). The statistics were constant all day.

• 2717 views later 272 new users, or 10.1%

• With 293 signups at 2856 views, 10.25%

• At 306 signups at 2965 views, 10.32%

Learnings

1. My initial estimations were wildly inaccurate

I wrote 30% conversion. Reading some articles, looks like 10% is a good number to aim for.

2. Paying attention to what matters rather than vain metrics

The Lean Startup discourages vanity metrics. Feel-good metrics that don't measure growth or traction. Considering the proportion instead of the total visitors made me realize there was something here.

What’s next?

There are lots of work to do. Data aggregation, display, website development, marketing, legal issues. Fun! It's satisfying to solve an issue rather than investigate its cause.

In the meantime, I’ve already written the first project update in another post. Continue reading it if you’d like to know more about the project itself! Shifting from Quantity to Quality — DbSchemaLibrary

Price Intelligently put out amazing content on pricing your SaaS product. This blog's link to the whole report is worth reading. Our key takeaways are below.

Don't base prices on the competition. Competitor-based pricing has clear drawbacks. Their pricing approach is yours. Your company offers customers something unique. Otherwise, you wouldn't create it. This strategy is static, therefore you can't add value by raising prices without outpricing competitors. Look, but don't touch is the competitor-based moral. You want to know your competitors' prices so you're in the same ballpark, but they shouldn't guide your selections. Competitor-based pricing also drives down prices.

Value-based pricing wins. This is customer-based pricing. Value-based pricing looks outward, not inward or laterally at competitors. Your clients are the best source of pricing information. By valuing customer comments, you're focusing on buyers. They'll decide if your pricing and packaging are right. In addition to asking consumers about cost savings or revenue increases, look at data like number of users, usage per user, etc.

Value-based pricing increases prices. As you learn more about the client and your worth, you'll know when and how much to boost rates. Every 6 months, examine pricing.

Cloning top customers. You clone your consumers by learning as much as you can about them and then reaching out to comparable people or organizations. You can't accomplish this without knowing your customers. Segmenting and reproducing them requires as much detail as feasible. Offer pricing plans and feature packages for 4 personas. The top plan should state Contact Us. Your highest-value customers want more advice and support.

Question your 4 personas. What's the one item you can't live without? Which integrations matter most? Do you do analytics? Is support important or does your company self-solve? What's too cheap? What's too expensive?

Not everyone likes per-user pricing. SaaS organizations often default to per-user analytics. About 80% of companies utilizing per-user pricing should use an alternative value metric because their goods don't give more value with more users, so charging for them doesn't make sense.

At least 3:1 LTV/CAC. Break even on the customer within 2 years, and LTV to CAC is greater than 3:1. Because customer acquisition costs are paid upfront but SaaS revenues accrue over time, SaaS companies face an early financial shortfall while paying back the CAC.

ROI should be >20:1. Indeed. Ensure the customer's ROI is 20x the product's cost. Microsoft Office costs $80 a year, but consumers would pay much more to maintain it.

A/B Testing. A/B testing is guessing. When your pricing page varies based on assumptions, you'll upset customers. You don't have enough customers anyway. A/B testing optimizes landing pages, design decisions, and other site features when you know the problem but not pricing.

Don't discount. It cheapens the product, makes it permanent, and increases churn. By discounting, you're ruining your pricing analysis.

Decentralized perpetual may be the next crypto market boom; with tons of perpetual popping up, let's look at two protocols that offer organic, non-inflationary yields.

Decentralized derivatives exchanges' market share has increased tenfold in a year, but it's still 2% of CEXs'. DEXs have a long way to go before they can compete with centralized exchanges in speed, liquidity, user experience, and composability.

I'll cover gains.trade and GMX protocol in Polygon, Avalanche, and Arbitrum. Both protocols support leveraged perpetual crypto, stock, and Forex trading.

Why these protocols?

Decentralized GMX Gains protocol

Organic yield: path to sustainability

I've never trusted Defi's non-organic yields. Example: XYZ protocol. 20–75% of tokens may be set aside as farming rewards to provide liquidity, according to tokenomics.

Say you provide ETH-USDC liquidity. They advertise a 50% APR reward for this pair, 10% from trading fees and 40% from farming rewards. Only 10% is real, the rest is "Ponzi." The "real" reward is in protocol tokens.

Why keep this token? Governance voting or staking rewards are promoted services.

Most liquidity providers expect compensation for unused tokens. Basic psychological principles then? — Profit.

Nobody wants governance tokens. How many out of 100 care about the protocol's direction and will vote?

Staking increases your token's value. Currently, they're mostly non-liquid. If the protocol is compromised, you can't withdraw funds. Most people are sceptical of staking because of this.

"Free tokens," lack of use cases, and skepticism lead to tokens moving south. No farming reward protocols have lasted.

It may have shown strength in a bull market, but what about a bear market?

What is decentralized perpetual?

A perpetual contract is a type of futures contract that doesn't expire. So one can hold a position forever.

You can buy/sell any leveraged instruments (Long-Short) without expiration.

In centralized exchanges like Binance and coinbase, fees and revenue (liquidation) go to the exchanges, not users.

Users can provide liquidity that traders can use to leverage trade, and the revenue goes to liquidity providers.

Gains.trade and GMX protocol are perpetual trading platforms with a non-inflationary organic yield for liquidity providers.

GMX protocol

GMX is an Arbitrum and Avax protocol that rewards in ETH and Avax. GLP uses a fast oracle to borrow the "true price" from other trading venues, unlike a traditional AMM.

GLP and GMX are protocol tokens. GLP is used for leveraged trading, swapping, etc.

GLP is a basket of tokens, including ETH, BTC, AVAX, stablecoins, and UNI, LINK, and Stablecoins.

GLP composition on arbitrum

GLP composition on Avalanche

GLP token rebalances based on usage, providing liquidity without loss.

Protocol "runs" on Staking GLP. Depending on their chain, the protocol will reward users with ETH or AVAX. Current rewards are 22 percent (15.71 percent in ETH and the rest in escrowed GMX) and 21 percent (15.72 percent in AVAX and the rest in escrowed GMX). escGMX and ETH/AVAX percentages fluctuate.

Where is the yield coming from?

Swap fees, perpetual interest, and liquidations generate yield. 70% of fees go to GLP stakers, 30% to GMX. Organic yields aren't paid in inflationary farm tokens.

Escrowed GMX is vested GMX that unlocks in 365 days. To fully unlock GMX, you must farm the Escrowed GMX token for 365 days. That means less selling pressure for the GMX token.

GMX's status

These are the fees in Arbitrum in the past 11 months by GMX.

GMX works like a casino, which increases fees. Most fees come from Margin trading, which means most traders lose money; this money goes to the casino, or GLP stakers.

Strategies

My personal strategy is to DCA into GLP when markets hit bottom and stake it; GLP will be less volatile with extra staking rewards.

GLP YoY return vs. naked buying

Let's say I invested $10,000 in BTC, AVAX, and ETH in January.

• BTC price: 47665$

• ETH price: 3760$

• AVAX price: $145

Current prices

• BTC $21,000 (Down 56 percent )

• ETH $1233 (Down 67.2 percent )

• AVAX $20.36 (Down 85.95 percent )

Your $10,000 investment is now worth around $3,000.

How about GLP? My initial investment is 50% stables and 50% other assets ( Assuming the coverage ratio for stables is 50 percent at that time)

Without GLP staking yield, your value is $6500.

Let's assume the average APR for GLP staking is 23%, or $1500. So 8000$ total. It's 50% safer than holding naked assets in a bear market.

In a bull market, naked assets are preferable to GLP.

Short farming using GLP

Simple GLP short farming.

You use a stable asset as collateral to borrow AVAX. Sell it and buy GLP. Even if GLP rises, it won't rise as fast as AVAX, so we can get yields.

Let's do the maths

You deposit $10,000 USDT in Aave and borrow Avax. Say you borrow $8,000; you sell it, buy GLP, and risk 20%.

After a year, ETH, AVAX, and BTC rise 20%. GLP is $8800. $800 vanishes. 20% yields $1600. You're profitable. Shorting Avax costs $1600. (Assumptions-ETH, AVAX, BTC move the same, GLP yield is 20%. GLP has a 50:50 stablecoin/others ratio. Aave won't liquidate

In naked Avax shorting, Avax falls 20% in a year. You'll make $1600. If you buy GLP and stake it using the sold Avax and BTC, ETH and Avax go down by 20% - your profit is 20%, but with the yield, your total gain is $2400.

Issues with GMX

GMX's historical funding rates are always net positive, so long always pays short. This makes long-term shorts less appealing.

Oracle price discovery isn't enough. This limitation doesn't affect Bitcoin and ETH, but it affects less liquid assets. Traders can buy and sell less liquid assets at a lower price than their actual cost as long as GMX exists.

As users must provide GLP liquidity, adding more assets to GMX will be difficult. Next iteration will have synthetic assets.

Gains Protocol

Best leveraged trading platform. Smart contract-based decentralized protocol. 46 crypto pairs can be leveraged 5–150x and 10 Forex pairs 5–1000x. $10 DAI @ 150x (min collateral x leverage pos size is $1500 DAI). No funding fees, no KYC, trade DAI from your wallet, keep funds.

DAI single-sided staking and the GNS-DAI pool are important parts of Gains trading. GNS-DAI stakers get 90% of trading fees and 100% swap fees. 10 percent of trading fees go to DAI stakers, which is currently 14 percent!

Trade volume

When a trader opens a trade, the leverage and profit are pulled from the DAI pool. If he loses, the protocol yield goes to the stakers.

If the trader's win rate is high and the DAI pool slowly depletes, the GNS token is minted and sold to refill DAI. Trader losses are used to burn GNS tokens. 25%+ of GNS is burned, making it deflationary.

Due to high leverage and volatility of crypto assets, most traders lose money and the protocol always wins, keeping GNS deflationary.

Gains uses a unique decentralized oracle for price feeds, which is better for leverage trading platforms. Let me explain.

Gains uses chainlink price oracles, not its own price feeds. Chainlink oracles only query centralized exchanges for price feeds every minute, which is unsuitable for high-precision trading.

Gains created a custom oracle that queries the eight chainlink nodes for the current price and, on average, for trade confirmation. This model eliminates every-second inquiries, which waste gas but are more efficient than chainlink's per-minute price.

This price oracle helps Gains open and close trades instantly, eliminate scam wicks, etc.

Other benefits include:

• Stop-loss guarantee (open positions updated)

• No scam wicks

• Spot-pricing

• Highest possible leverage

• Fixed-spreads. During high volatility, a broker can increase the spread, which can hit your stop loss without the price moving.

• Trade directly from your wallet and keep your funds.

• >90% loss before liquidation (Some platforms liquidate as little as -50 percent)

• KYC-free

• Directly trade from wallet; keep funds safe

Further improvements

GNS-DAI liquidity providers fear the impermanent loss, so the protocol is migrating to its own liquidity and single staking GNS vaults. This allows users to stake GNS without permanent loss and obtain 90% DAI trading fees by staking. This starts in August.

Their upcoming improvements can be found here.

Gains constantly add new features and change pairs. It's an interesting protocol.

Conclusion

Next bull run, watch decentralized perpetual protocols. Effective tokenomics and non-inflationary yields may attract traders and liquidity providers. But still, there is a long way for them to develop, and I don't see them tackling the centralized exchanges any time soon until they fix their inherent problems and improve fast enough.

Read the full post here.