New social media producers' biggest error

The Treadmill of Social Media Content

New creators focus on the wrong platforms.

They post to Instagram, Twitter, TikTok, etc.

They create daily material, but it's never enough for social media algorithms.

Creators recognize they're on a content creation treadmill.

They have to keep publishing content daily just to stay on the algorithm’s good side and avoid losing the audience they’ve built on the platform.

This is exhausting and unsustainable, causing creator burnout.

They focus on short-lived platforms, which is an issue.

Comparing low- and high-return social media platforms

Social media networks are great for reaching new audiences.

Their algorithm is meant to viralize material.

Social media can use you for their aims if you're not careful.

To master social media, focus on the right platforms.

To do this, we must differentiate low-ROI and high-ROI platforms:

Low ROI platforms are ones where content has a short lifespan. High ROI platforms are ones where content has a longer lifespan.

A tweet may be shown for 12 days. If you write an article or blog post, it could get visitors for 23 years.

ROI is drastically different.

New creators have limited time and high learning curves.

Nothing is possible.

First create content for high-return platforms.

ROI for social media platforms

Here are high-return platforms:

1. Your Blog - A single blog article can rank and attract a ton of targeted traffic for a very long time thanks to the power of SEO.

2. YouTube - YouTube has a reputation for showing search results or sidebar recommendations for videos uploaded 23 years ago. A superb video you make may receive views for a number of years.

3. Medium - A platform dedicated to excellent writing is called Medium. When you write an article about a subject that never goes out of style, you're building a digital asset that can drive visitors indefinitely.

These high ROI platforms let you generate content once and get visitors for years.

This contrasts with low ROI platforms:

1. Twitter

2. Instagram

3. TikTok

4. LinkedIn

5. Facebook

The posts you publish on these networks have a 23-day lifetime. Instagram Reels and TikToks are exceptions since viral content can last months.

If you want to make content creation sustainable and enjoyable, you must focus the majority of your efforts on creating high ROI content first. You can then use the magic of repurposing content to publish content to the lower ROI platforms to increase your reach and exposure.

How To Use Your Content Again

So, you’ve decided to focus on the high ROI platforms.

Great!

You've published an article or a YouTube video.

You worked hard on it.

Now you have fresh stuff.

What now?

If you are not repurposing each piece of content for multiple platforms, you are throwing away your time and efforts.

You've created fantastic material, so why not distribute it across platforms?

Repurposing Content Step-by-Step

For me, it's writing a blog article, but you might start with a video or podcast.

The premise is the same regardless of the medium.

Start by creating content for a high ROI platform (YouTube, Blog Post, Medium). Then, repurpose, edit, and repost it to the lower ROI platforms.

Here's how to repurpose pillar material for other platforms:

1. Post the article on your blog.

2. Put your piece on Medium (use the canonical link to point to your blog as the source for SEO)

3. Create a video and upload it to YouTube using the talking points from the article.

4. Rewrite the piece a little, then post it to LinkedIn.

5. Change the article's format to a Thread and share it on Twitter.

6. Find a few quick quotes throughout the article, then use them in tweets or Instagram quote posts.

7. Create a carousel for Instagram and LinkedIn using screenshots from the Twitter Thread.

8. Go through your film and select a few valuable 30-second segments. Share them on LinkedIn, Facebook, Twitter, TikTok, YouTube Shorts, and Instagram Reels.

9. Your video's audio can be taken out and uploaded as a podcast episode.

If you (or your team) achieve all this, you'll have 20-30 pieces of social media content.

If you're just starting, I wouldn't advocate doing all of this at once.

Instead, focus on a few platforms with this method.

You can outsource this as your company expands. (If you'd want to learn more about content repurposing, contact me.)

You may focus on relevant work while someone else grows your social media on autopilot.

You develop high-ROI pillar content, and it's automatically chopped up and posted on social media.

This lets you use social media algorithms without getting sucked in.

Thanks for reading!

No Paid Ads Required

I had an online store. After a year of running the company alongside my 9-to-5, I made enough to resign.

That day was amazing.

This Instagram marketing plan helped the store succeed.

How did I increase my sales to five figures a month without using any paid advertising?

I used customer event marketing.

I'm not sure this term exists. I invented it to describe what I was doing.

Instagram word-of-mouth, fan engagement, and interaction drove sales.

If a customer liked or disliked a product, the buzz would drive attention to the store.

I used customer-based events to increase engagement and store sales.

Success!

Here are the weekly Instagram customer events I coordinated while running my business:

• Be the Buyer Days

• Flash sales

• Mystery boxes

Be the Buyer Days: How do they work?

Be the Buyer Days are exactly that.

You choose a day to share stock selections with social media followers.

This is an easy approach to engaging customers and getting fans enthusiastic about new releases.

First, pick a handful of items you’re considering ordering. I’d usually pick around 3 for Be the Buyer Day.

Then I'd poll the crowd on Instagram to vote on their favorites.

This was before Instagram stories, polls, and all the other cool features Instagram offers today. I think using these tools now would make this event even better.

I'd ask customers their favorite back then.

The growing comments excited customers.

Then I'd declare the winner, acquire the products, and start selling it.

How do flash sales work?

I mostly ran flash sales.

You choose a limited number of itemsdd for a few-hour sale.

We wanted most sales to result in sold-out items.

When an item sells out, it contributes to the sensation of scarcity and can inspire customers to visit your store to buy a comparable product, join your email list, become a fan, etc.

We hoped they'd act quickly.

I'd hold flash deals twice a week, which generated scarcity and boosted sales.

The store had a few thousand Instagram followers when I started flash deals.

Each flash sale item would make $400 to $600.

$400 x 3= $1,200

That's $1,200 on social media!

Twice a week, you'll make roughly $10K a month from Instagram.

$1,200/day x 8 events/month=$9,600

Flash sales did great.

We held weekly flash deals and sent social media and email reminders. That’s about it!

How are mystery boxes put together?

All you do is package a box of store products and sell it as a mystery box on TikTok or retail websites.

A $100 mystery box would cost $30.

You're discounting high-value boxes.

This is a clever approach to get rid of excess inventory and makes customers happy.

It worked!

Be the Buyer Days, flash deals, and mystery boxes helped build my company without paid advertisements.

All companies can use customer event marketing. Involving customers and providing an engaging environment can boost sales.

Try it!

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

Blockchain validates transactions with consensus algorithms. Bitcoin and Ethereum use Proof-of-Work, while Polkadot and Cardano use Proof-of-Stake.

Other consensus protocols are used to verify transactions besides these two. This post focuses on Proof-of-Time (PoT), used by Analog, and Proof-of-History (PoH), used by Solana as a hybrid consensus protocol.

PoT and PoH may seem similar to users, but they are actually very different protocols.

Proof-of-Time (PoT)

Analog developed Proof-of-Time (PoT) based on Delegated Proof-of-Stake (DPoS). Users select "delegates" to validate the next block in DPoS. PoT uses a ranking system, and validators stake an equal amount of tokens. Validators also "self-select" themselves via a verifiable random function."

The ranking system gives network validators a performance score, with trustworthy validators with a long history getting higher scores. System also considers validator's fixed stake. PoT's ledger is called "Timechain."

Voting on delegates borrows from DPoS, but there are changes. PoT's first voting stage has validators (or "time electors" putting forward a block to be included in the ledger).

Validators are chosen randomly based on their ranking score and fixed stake. One validator is chosen at a time using a Verifiable Delay Function (VDF).

Validators use a verifiable delay function to determine if they'll propose a Timechain block. If chosen, they validate the transaction and generate a VDF proof before submitting both to other Timechain nodes.

This leads to the second process, where the transaction is passed through 1,000 validators selected using the same method. Each validator checks the transaction to ensure it's valid.

If the transaction passes, validators accept the block, and if over 2/3 accept it, it's added to the Timechain.

Proof-of-History (PoH)

Proof-of-History is a consensus algorithm that proves when a transaction occurred. PoH uses a VDF to verify transactions, like Proof-of-Time. Similar to Proof-of-Work, VDFs use a lot of computing power to calculate but little to verify transactions, similar to (PoW).

This shows users and validators how long a transaction took to verify.

PoH uses VDFs to verify event intervals. This process uses cryptography to prevent determining output from input.

The outputs of one transaction are used as inputs for the next. Timestamps record the inputs' order. This checks if data was created before an event.

PoT vs. PoH

PoT and PoH differ in that:

• PoT uses VDFs to select validators (or time electors), while PoH measures time between events.

• PoH uses a VDF to validate transactions, while PoT uses a ranking system.

• PoT's VDF-elected validators verify transactions proposed by a previous validator. PoH uses a VDF to validate transactions and data.

Conclusion

Both Proof-of-Time (PoT) and Proof-of-History (PoH) validate blockchain transactions differently. PoT uses a ranking system to randomly select validators to verify transactions.

PoH uses a Verifiable Delay Function to validate transactions, verify how much time has passed between two events, and allow validators to quickly verify a transaction without malicious actors knowing the input.

Bear markets don't last forever, but that's hard to remember. Jamie Cullen's illustration

A bear market is a 20% decline from peak to trough in stock prices.

The S&P 500 was down 24% from its January highs at its low point this year. Bear market.

The U.S. stock market has had 13 bear markets since WWII (including the current one). Previous 12 bear markets averaged –32.7% losses. From peak to trough, the stock market averaged 12 months. The average time from bottom to peak was 21 months.

In the past seven decades, a bear market roundtrip to breakeven has averaged less than three years.

Long-term averages can vary widely, as with all historical market data. Investors can learn from past market crashes.

Historical bear markets offer lessons.

Bear market duration

A bear market can cost investors money and time. Most of the pain comes from stock market declines, but bear markets can be long.

Here are the longest U.S. stock bear markets since World war 2:

Stock market crashes can make it difficult to break even. After the 2008 financial crisis, the stock market took 4.5 years to recover. After the dotcom bubble burst, it took seven years to break even.

The longer you're underwater in the market, the more suffering you'll experience, according to research. Suffering can lead to selling at the wrong time.

Bear markets require patience because stocks can take a long time to recover.

Stock crash recovery

Bear markets can end quickly. The Corona Crash in early 2020 is an example.

The S&P 500 fell 34% in 23 trading sessions, the fastest bear market from a high in 90 years. The entire crash lasted one month. Stocks broke even six months after bottoming. Stocks rose 100% from those lows in 15 months.

Seven bear markets have lasted two years or less since 1945.

The 2020 recovery was an outlier, but four other bear markets have made investors whole within 18 months.

During a bear market, you don't know if it will end quickly or feel like death by a thousand cuts.

Recessions vs. bear markets

Many people believe the U.S. economy is in or heading for a recession.

I agree. Four-decade high inflation. Since 1945, inflation has exceeded 5% nine times. Each inflationary spike caused a recession. Only slowing economic demand seems to stop price spikes.

This could happen again. Stocks seem to be pricing in a recession.

Recessions almost always cause a bear market, but a bear market doesn't always equal a recession. In 1946, the stock market fell 27% without a recession in sight. Without an economic slowdown, the stock market fell 22% in 1966. Black Monday in 1987 was the most famous stock market crash without a recession. Stocks fell 30% in less than a week. Many believed the stock market signaled a depression. The crash caused no slowdown.

Economic cycles are hard to predict. Even Wall Street makes mistakes.

Bears vs. bulls

Bear markets for U.S. stocks always end. Every stock market crash in U.S. history has been followed by new all-time highs.

How should investors view the recession? Investing risk is subjective.

You don't have as long to wait out a bear market if you're retired or nearing retirement. Diversification and liquidity help investors with limited time or income. Cash and short-term bonds drag down long-term returns but can ensure short-term spending.

Young people with years or decades ahead of them should view this bear market as an opportunity. Stock market crashes are good for net savers in the future. They let you buy cheap stocks with high dividend yields.

You need discipline, patience, and planning to buy stocks when it doesn't feel right.

Bear markets aren't fun because no one likes seeing their portfolio fall. But stock market downturns are a feature, not a bug. If stocks never crashed, they wouldn't offer such great long-term returns.